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Observability Pipelines allows you to collect and process logs within your own infrastructure, and then route them to downstream integrations.
Note: This endpoint is in Preview.
GET https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines
Retrieve a list of pipelines.
This endpoint requires the observability_pipelines_read permission.
이름
유형
설명
page[size]
integer
Size for a given page. The maximum allowed value is 100.
page[number]
integer
Specific page number to return.
OK
Represents the response payload containing a list of pipelines and associated metadata.
항목
유형
설명
data [required]
[object]
The schema data.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
id [required]
string
Unique identifier for the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
meta
object
Metadata about the response.
totalCount
int64
The total number of pipelines.
{
"data": [
{
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"group_id": "consumer-group-0",
"id": "kafka-source",
"librdkafka_options": [
{
"name": "fetch.message.max.bytes",
"value": "1048576"
}
],
"sasl": {
"mechanism": "string"
},
"tls": {
"ca_file": "string",
"crt_file": "/path/to/cert.crt",
"key_file": "string"
},
"topics": [
"topic1",
"topic2"
],
"type": "kafka"
}
]
},
"name": "Main Observability Pipeline"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
],
"meta": {
"totalCount": 42
}
}Bad Request
API error response.
{
"errors": [
"Bad Request"
]
}Not Authorized
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Curl command
curl -X GET "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines" \
-H "Accept: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
Note: This endpoint is in Preview.
POST https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelineshttps://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines
Create a new pipeline.
This endpoint requires the observability_pipelines_deploy permission.
항목
유형
설명
data [required]
object
Contains the the pipeline configuration.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Main Observability Pipeline"
},
"type": "pipelines"
}
}OK
Top-level schema representing a pipeline.
항목
유형
설명
data [required]
object
Contains the pipeline’s ID, type, and configuration attributes.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
id [required]
string
Unique identifier for the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"group_id": "consumer-group-0",
"id": "kafka-source",
"librdkafka_options": [
{
"name": "fetch.message.max.bytes",
"value": "1048576"
}
],
"sasl": {
"mechanism": "string"
},
"tls": {
"ca_file": "string",
"crt_file": "/path/to/cert.crt",
"key_file": "string"
},
"topics": [
"topic1",
"topic2"
],
"type": "kafka"
}
]
},
"name": "Main Observability Pipeline"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
}Bad Request
API error response.
{
"errors": [
"Bad Request"
]
}Not Authorized
API error response.
{
"errors": [
"Bad Request"
]
}Conflict
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \
-d @- << EOF
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Main Observability Pipeline"
},
"type": "pipelines"
}
}
EOF
// Create a new pipeline returns "OK" response
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)
func main() {
body := datadogV2.ObservabilityPipelineCreateRequest{
Data: datadogV2.ObservabilityPipelineCreateRequestData{
Attributes: datadogV2.ObservabilityPipelineDataAttributes{
Config: datadogV2.ObservabilityPipelineConfig{
Destinations: []datadogV2.ObservabilityPipelineConfigDestinationItem{
datadogV2.ObservabilityPipelineConfigDestinationItem{
ObservabilityPipelineDatadogLogsDestination: &datadogV2.ObservabilityPipelineDatadogLogsDestination{
Id: "datadog-logs-destination",
Inputs: []string{
"filter-processor",
},
Type: datadogV2.OBSERVABILITYPIPELINEDATADOGLOGSDESTINATIONTYPE_DATADOG_LOGS,
}},
},
Processors: []datadogV2.ObservabilityPipelineConfigProcessorItem{
datadogV2.ObservabilityPipelineConfigProcessorItem{
ObservabilityPipelineFilterProcessor: &datadogV2.ObservabilityPipelineFilterProcessor{
Id: "filter-processor",
Include: "service:my-service",
Inputs: []string{
"datadog-agent-source",
},
Type: datadogV2.OBSERVABILITYPIPELINEFILTERPROCESSORTYPE_FILTER,
}},
},
Sources: []datadogV2.ObservabilityPipelineConfigSourceItem{
datadogV2.ObservabilityPipelineConfigSourceItem{
ObservabilityPipelineDatadogAgentSource: &datadogV2.ObservabilityPipelineDatadogAgentSource{
Id: "datadog-agent-source",
Type: datadogV2.OBSERVABILITYPIPELINEDATADOGAGENTSOURCETYPE_DATADOG_AGENT,
}},
},
},
Name: "Main Observability Pipeline",
},
Type: "pipelines",
},
}
ctx := datadog.NewDefaultContext(context.Background())
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.CreatePipeline", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewObservabilityPipelinesApi(apiClient)
resp, r, err := api.CreatePipeline(ctx, body)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `ObservabilityPipelinesApi.CreatePipeline`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `ObservabilityPipelinesApi.CreatePipeline`:\n%s\n", responseContent)
}
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" go run "main.go"// Create a new pipeline returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ObservabilityPipelinesApi;
import com.datadog.api.client.v2.model.ObservabilityPipeline;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfig;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigDestinationItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigProcessorItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigSourceItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineCreateRequest;
import com.datadog.api.client.v2.model.ObservabilityPipelineCreateRequestData;
import com.datadog.api.client.v2.model.ObservabilityPipelineDataAttributes;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogAgentSource;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogAgentSourceType;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogLogsDestination;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogLogsDestinationType;
import com.datadog.api.client.v2.model.ObservabilityPipelineFilterProcessor;
import com.datadog.api.client.v2.model.ObservabilityPipelineFilterProcessorType;
import java.util.Collections;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setUnstableOperationEnabled("v2.createPipeline", true);
ObservabilityPipelinesApi apiInstance = new ObservabilityPipelinesApi(defaultClient);
ObservabilityPipelineCreateRequest body =
new ObservabilityPipelineCreateRequest()
.data(
new ObservabilityPipelineCreateRequestData()
.attributes(
new ObservabilityPipelineDataAttributes()
.config(
new ObservabilityPipelineConfig()
.destinations(
Collections.singletonList(
new ObservabilityPipelineConfigDestinationItem(
new ObservabilityPipelineDatadogLogsDestination()
.id("datadog-logs-destination")
.inputs(
Collections.singletonList(
"filter-processor"))
.type(
ObservabilityPipelineDatadogLogsDestinationType
.DATADOG_LOGS))))
.processors(
Collections.singletonList(
new ObservabilityPipelineConfigProcessorItem(
new ObservabilityPipelineFilterProcessor()
.id("filter-processor")
.include("service:my-service")
.inputs(
Collections.singletonList(
"datadog-agent-source"))
.type(
ObservabilityPipelineFilterProcessorType
.FILTER))))
.sources(
Collections.singletonList(
new ObservabilityPipelineConfigSourceItem(
new ObservabilityPipelineDatadogAgentSource()
.id("datadog-agent-source")
.type(
ObservabilityPipelineDatadogAgentSourceType
.DATADOG_AGENT)))))
.name("Main Observability Pipeline"))
.type("pipelines"));
try {
ObservabilityPipeline result = apiInstance.createPipeline(body);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling ObservabilityPipelinesApi#createPipeline");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" java "Example.java""""
Create a new pipeline returns "OK" response
"""
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.observability_pipelines_api import ObservabilityPipelinesApi
from datadog_api_client.v2.model.observability_pipeline_config import ObservabilityPipelineConfig
from datadog_api_client.v2.model.observability_pipeline_create_request import ObservabilityPipelineCreateRequest
from datadog_api_client.v2.model.observability_pipeline_create_request_data import (
ObservabilityPipelineCreateRequestData,
)
from datadog_api_client.v2.model.observability_pipeline_data_attributes import ObservabilityPipelineDataAttributes
from datadog_api_client.v2.model.observability_pipeline_datadog_agent_source import (
ObservabilityPipelineDatadogAgentSource,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_agent_source_type import (
ObservabilityPipelineDatadogAgentSourceType,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_logs_destination import (
ObservabilityPipelineDatadogLogsDestination,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_logs_destination_type import (
ObservabilityPipelineDatadogLogsDestinationType,
)
from datadog_api_client.v2.model.observability_pipeline_filter_processor import ObservabilityPipelineFilterProcessor
from datadog_api_client.v2.model.observability_pipeline_filter_processor_type import (
ObservabilityPipelineFilterProcessorType,
)
body = ObservabilityPipelineCreateRequest(
data=ObservabilityPipelineCreateRequestData(
attributes=ObservabilityPipelineDataAttributes(
config=ObservabilityPipelineConfig(
destinations=[
ObservabilityPipelineDatadogLogsDestination(
id="datadog-logs-destination",
inputs=[
"filter-processor",
],
type=ObservabilityPipelineDatadogLogsDestinationType.DATADOG_LOGS,
),
],
processors=[
ObservabilityPipelineFilterProcessor(
id="filter-processor",
include="service:my-service",
inputs=[
"datadog-agent-source",
],
type=ObservabilityPipelineFilterProcessorType.FILTER,
),
],
sources=[
ObservabilityPipelineDatadogAgentSource(
id="datadog-agent-source",
type=ObservabilityPipelineDatadogAgentSourceType.DATADOG_AGENT,
),
],
),
name="Main Observability Pipeline",
),
type="pipelines",
),
)
configuration = Configuration()
configuration.unstable_operations["create_pipeline"] = True
with ApiClient(configuration) as api_client:
api_instance = ObservabilityPipelinesApi(api_client)
response = api_instance.create_pipeline(body=body)
print(response)
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" python3 "example.py"# Create a new pipeline returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.unstable_operations["v2.create_pipeline".to_sym] = true
end
api_instance = DatadogAPIClient::V2::ObservabilityPipelinesAPI.new
body = DatadogAPIClient::V2::ObservabilityPipelineCreateRequest.new({
data: DatadogAPIClient::V2::ObservabilityPipelineCreateRequestData.new({
attributes: DatadogAPIClient::V2::ObservabilityPipelineDataAttributes.new({
config: DatadogAPIClient::V2::ObservabilityPipelineConfig.new({
destinations: [
DatadogAPIClient::V2::ObservabilityPipelineDatadogLogsDestination.new({
id: "datadog-logs-destination",
inputs: [
"filter-processor",
],
type: DatadogAPIClient::V2::ObservabilityPipelineDatadogLogsDestinationType::DATADOG_LOGS,
}),
],
processors: [
DatadogAPIClient::V2::ObservabilityPipelineFilterProcessor.new({
id: "filter-processor",
include: "service:my-service",
inputs: [
"datadog-agent-source",
],
type: DatadogAPIClient::V2::ObservabilityPipelineFilterProcessorType::FILTER,
}),
],
sources: [
DatadogAPIClient::V2::ObservabilityPipelineDatadogAgentSource.new({
id: "datadog-agent-source",
type: DatadogAPIClient::V2::ObservabilityPipelineDatadogAgentSourceType::DATADOG_AGENT,
}),
],
}),
name: "Main Observability Pipeline",
}),
type: "pipelines",
}),
})
p api_instance.create_pipeline(body)
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" rb "example.rb"// Create a new pipeline returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_observability_pipelines::ObservabilityPipelinesAPI;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfig;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigDestinationItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigProcessorItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigSourceItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineCreateRequest;
use datadog_api_client::datadogV2::model::ObservabilityPipelineCreateRequestData;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDataAttributes;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogAgentSource;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogAgentSourceType;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogLogsDestination;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogLogsDestinationType;
use datadog_api_client::datadogV2::model::ObservabilityPipelineFilterProcessor;
use datadog_api_client::datadogV2::model::ObservabilityPipelineFilterProcessorType;
#[tokio::main]
async fn main() {
let body =
ObservabilityPipelineCreateRequest::new(
ObservabilityPipelineCreateRequestData::new(
ObservabilityPipelineDataAttributes::new(
ObservabilityPipelineConfig::new(
vec![
ObservabilityPipelineConfigDestinationItem::ObservabilityPipelineDatadogLogsDestination(
Box::new(
ObservabilityPipelineDatadogLogsDestination::new(
"datadog-logs-destination".to_string(),
vec!["filter-processor".to_string()],
ObservabilityPipelineDatadogLogsDestinationType::DATADOG_LOGS,
),
),
)
],
vec![
ObservabilityPipelineConfigProcessorItem::ObservabilityPipelineFilterProcessor(
Box::new(
ObservabilityPipelineFilterProcessor::new(
"filter-processor".to_string(),
"service:my-service".to_string(),
vec!["datadog-agent-source".to_string()],
ObservabilityPipelineFilterProcessorType::FILTER,
),
),
)
],
vec![
ObservabilityPipelineConfigSourceItem::ObservabilityPipelineDatadogAgentSource(
Box::new(
ObservabilityPipelineDatadogAgentSource::new(
"datadog-agent-source".to_string(),
ObservabilityPipelineDatadogAgentSourceType::DATADOG_AGENT,
),
),
)
],
),
"Main Observability Pipeline".to_string(),
),
"pipelines".to_string(),
),
);
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.CreatePipeline", true);
let api = ObservabilityPipelinesAPI::with_config(configuration);
let resp = api.create_pipeline(body).await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run/**
* Create a new pipeline returns "OK" response
*/
import { client, v2 } from "@datadog/datadog-api-client";
const configuration = client.createConfiguration();
configuration.unstableOperations["v2.createPipeline"] = true;
const apiInstance = new v2.ObservabilityPipelinesApi(configuration);
const params: v2.ObservabilityPipelinesApiCreatePipelineRequest = {
body: {
data: {
attributes: {
config: {
destinations: [
{
id: "datadog-logs-destination",
inputs: ["filter-processor"],
type: "datadog_logs",
},
],
processors: [
{
id: "filter-processor",
include: "service:my-service",
inputs: ["datadog-agent-source"],
type: "filter",
},
],
sources: [
{
id: "datadog-agent-source",
type: "datadog_agent",
},
],
},
name: "Main Observability Pipeline",
},
type: "pipelines",
},
},
};
apiInstance
.createPipeline(params)
.then((data: v2.ObservabilityPipeline) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" tsc "example.ts"Note: This endpoint is in Preview.
GET https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}
Get a specific pipeline by its ID.
This endpoint requires the observability_pipelines_read permission.
이름
유형
설명
pipeline_id [required]
string
The ID of the pipeline to retrieve.
OK
Top-level schema representing a pipeline.
항목
유형
설명
data [required]
object
Contains the pipeline’s ID, type, and configuration attributes.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
id [required]
string
Unique identifier for the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"group_id": "consumer-group-0",
"id": "kafka-source",
"librdkafka_options": [
{
"name": "fetch.message.max.bytes",
"value": "1048576"
}
],
"sasl": {
"mechanism": "string"
},
"tls": {
"ca_file": "string",
"crt_file": "/path/to/cert.crt",
"key_file": "string"
},
"topics": [
"topic1",
"topic2"
],
"type": "kafka"
}
]
},
"name": "Main Observability Pipeline"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
}Forbidden
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Path parameters
export pipeline_id="CHANGE_ME"
# Curl command
curl -X GET "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/${pipeline_id}" \
-H "Accept: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
Get a specific pipeline returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.observability_pipelines_api import ObservabilityPipelinesApi
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = environ["PIPELINE_DATA_ID"]
configuration = Configuration()
configuration.unstable_operations["get_pipeline"] = True
with ApiClient(configuration) as api_client:
api_instance = ObservabilityPipelinesApi(api_client)
response = api_instance.get_pipeline(
pipeline_id=PIPELINE_DATA_ID,
)
print(response)
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" python3 "example.py"# Get a specific pipeline returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.unstable_operations["v2.get_pipeline".to_sym] = true
end
api_instance = DatadogAPIClient::V2::ObservabilityPipelinesAPI.new
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = ENV["PIPELINE_DATA_ID"]
p api_instance.get_pipeline(PIPELINE_DATA_ID)
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" rb "example.rb"// Get a specific pipeline returns "OK" response
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)
func main() {
// there is a valid "pipeline" in the system
PipelineDataID := os.Getenv("PIPELINE_DATA_ID")
ctx := datadog.NewDefaultContext(context.Background())
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.GetPipeline", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewObservabilityPipelinesApi(apiClient)
resp, r, err := api.GetPipeline(ctx, PipelineDataID)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `ObservabilityPipelinesApi.GetPipeline`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `ObservabilityPipelinesApi.GetPipeline`:\n%s\n", responseContent)
}
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" go run "main.go"// Get a specific pipeline returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ObservabilityPipelinesApi;
import com.datadog.api.client.v2.model.ObservabilityPipeline;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setUnstableOperationEnabled("v2.getPipeline", true);
ObservabilityPipelinesApi apiInstance = new ObservabilityPipelinesApi(defaultClient);
// there is a valid "pipeline" in the system
String PIPELINE_DATA_ID = System.getenv("PIPELINE_DATA_ID");
try {
ObservabilityPipeline result = apiInstance.getPipeline(PIPELINE_DATA_ID);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling ObservabilityPipelinesApi#getPipeline");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" java "Example.java"// Get a specific pipeline returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_observability_pipelines::ObservabilityPipelinesAPI;
#[tokio::main]
async fn main() {
// there is a valid "pipeline" in the system
let pipeline_data_id = std::env::var("PIPELINE_DATA_ID").unwrap();
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.GetPipeline", true);
let api = ObservabilityPipelinesAPI::with_config(configuration);
let resp = api.get_pipeline(pipeline_data_id.clone()).await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run/**
* Get a specific pipeline returns "OK" response
*/
import { client, v2 } from "@datadog/datadog-api-client";
const configuration = client.createConfiguration();
configuration.unstableOperations["v2.getPipeline"] = true;
const apiInstance = new v2.ObservabilityPipelinesApi(configuration);
// there is a valid "pipeline" in the system
const PIPELINE_DATA_ID = process.env.PIPELINE_DATA_ID as string;
const params: v2.ObservabilityPipelinesApiGetPipelineRequest = {
pipelineId: PIPELINE_DATA_ID,
};
apiInstance
.getPipeline(params)
.then((data: v2.ObservabilityPipeline) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" tsc "example.ts"Note: This endpoint is in Preview.
PUT https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}
Update a pipeline.
This endpoint requires the observability_pipelines_deploy permission.
이름
유형
설명
pipeline_id [required]
string
The ID of the pipeline to update.
항목
유형
설명
data [required]
object
Contains the pipeline’s ID, type, and configuration attributes.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
id [required]
string
Unique identifier for the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "updated-datadog-logs-destination-id",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Updated Pipeline Name"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
}OK
Top-level schema representing a pipeline.
항목
유형
설명
data [required]
object
Contains the pipeline’s ID, type, and configuration attributes.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
id [required]
string
Unique identifier for the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"group_id": "consumer-group-0",
"id": "kafka-source",
"librdkafka_options": [
{
"name": "fetch.message.max.bytes",
"value": "1048576"
}
],
"sasl": {
"mechanism": "string"
},
"tls": {
"ca_file": "string",
"crt_file": "/path/to/cert.crt",
"key_file": "string"
},
"topics": [
"topic1",
"topic2"
],
"type": "kafka"
}
]
},
"name": "Main Observability Pipeline"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
}Bad Request
API error response.
{
"errors": [
"Bad Request"
]
}Not Authorized
API error response.
{
"errors": [
"Bad Request"
]
}Not Found
API error response.
{
"errors": [
"Bad Request"
]
}Conflict
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Path parameters
export pipeline_id="CHANGE_ME"
# Curl command
curl -X PUT "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/${pipeline_id}" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \
-d @- << EOF
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "updated-datadog-logs-destination-id",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Updated Pipeline Name"
},
"id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"type": "pipelines"
}
}
EOF
// Update a pipeline returns "OK" response
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)
func main() {
// there is a valid "pipeline" in the system
PipelineDataID := os.Getenv("PIPELINE_DATA_ID")
body := datadogV2.ObservabilityPipeline{
Data: datadogV2.ObservabilityPipelineData{
Attributes: datadogV2.ObservabilityPipelineDataAttributes{
Config: datadogV2.ObservabilityPipelineConfig{
Destinations: []datadogV2.ObservabilityPipelineConfigDestinationItem{
datadogV2.ObservabilityPipelineConfigDestinationItem{
ObservabilityPipelineDatadogLogsDestination: &datadogV2.ObservabilityPipelineDatadogLogsDestination{
Id: "updated-datadog-logs-destination-id",
Inputs: []string{
"filter-processor",
},
Type: datadogV2.OBSERVABILITYPIPELINEDATADOGLOGSDESTINATIONTYPE_DATADOG_LOGS,
}},
},
Processors: []datadogV2.ObservabilityPipelineConfigProcessorItem{
datadogV2.ObservabilityPipelineConfigProcessorItem{
ObservabilityPipelineFilterProcessor: &datadogV2.ObservabilityPipelineFilterProcessor{
Id: "filter-processor",
Include: "service:my-service",
Inputs: []string{
"datadog-agent-source",
},
Type: datadogV2.OBSERVABILITYPIPELINEFILTERPROCESSORTYPE_FILTER,
}},
},
Sources: []datadogV2.ObservabilityPipelineConfigSourceItem{
datadogV2.ObservabilityPipelineConfigSourceItem{
ObservabilityPipelineDatadogAgentSource: &datadogV2.ObservabilityPipelineDatadogAgentSource{
Id: "datadog-agent-source",
Type: datadogV2.OBSERVABILITYPIPELINEDATADOGAGENTSOURCETYPE_DATADOG_AGENT,
}},
},
},
Name: "Updated Pipeline Name",
},
Id: PipelineDataID,
Type: "pipelines",
},
}
ctx := datadog.NewDefaultContext(context.Background())
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.UpdatePipeline", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewObservabilityPipelinesApi(apiClient)
resp, r, err := api.UpdatePipeline(ctx, PipelineDataID, body)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `ObservabilityPipelinesApi.UpdatePipeline`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `ObservabilityPipelinesApi.UpdatePipeline`:\n%s\n", responseContent)
}
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" go run "main.go"// Update a pipeline returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ObservabilityPipelinesApi;
import com.datadog.api.client.v2.model.ObservabilityPipeline;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfig;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigDestinationItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigProcessorItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineConfigSourceItem;
import com.datadog.api.client.v2.model.ObservabilityPipelineData;
import com.datadog.api.client.v2.model.ObservabilityPipelineDataAttributes;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogAgentSource;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogAgentSourceType;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogLogsDestination;
import com.datadog.api.client.v2.model.ObservabilityPipelineDatadogLogsDestinationType;
import com.datadog.api.client.v2.model.ObservabilityPipelineFilterProcessor;
import com.datadog.api.client.v2.model.ObservabilityPipelineFilterProcessorType;
import java.util.Collections;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setUnstableOperationEnabled("v2.updatePipeline", true);
ObservabilityPipelinesApi apiInstance = new ObservabilityPipelinesApi(defaultClient);
// there is a valid "pipeline" in the system
String PIPELINE_DATA_ID = System.getenv("PIPELINE_DATA_ID");
ObservabilityPipeline body =
new ObservabilityPipeline()
.data(
new ObservabilityPipelineData()
.attributes(
new ObservabilityPipelineDataAttributes()
.config(
new ObservabilityPipelineConfig()
.destinations(
Collections.singletonList(
new ObservabilityPipelineConfigDestinationItem(
new ObservabilityPipelineDatadogLogsDestination()
.id("updated-datadog-logs-destination-id")
.inputs(
Collections.singletonList(
"filter-processor"))
.type(
ObservabilityPipelineDatadogLogsDestinationType
.DATADOG_LOGS))))
.processors(
Collections.singletonList(
new ObservabilityPipelineConfigProcessorItem(
new ObservabilityPipelineFilterProcessor()
.id("filter-processor")
.include("service:my-service")
.inputs(
Collections.singletonList(
"datadog-agent-source"))
.type(
ObservabilityPipelineFilterProcessorType
.FILTER))))
.sources(
Collections.singletonList(
new ObservabilityPipelineConfigSourceItem(
new ObservabilityPipelineDatadogAgentSource()
.id("datadog-agent-source")
.type(
ObservabilityPipelineDatadogAgentSourceType
.DATADOG_AGENT)))))
.name("Updated Pipeline Name"))
.id(PIPELINE_DATA_ID)
.type("pipelines"));
try {
ObservabilityPipeline result = apiInstance.updatePipeline(PIPELINE_DATA_ID, body);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling ObservabilityPipelinesApi#updatePipeline");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" java "Example.java""""
Update a pipeline returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.observability_pipelines_api import ObservabilityPipelinesApi
from datadog_api_client.v2.model.observability_pipeline import ObservabilityPipeline
from datadog_api_client.v2.model.observability_pipeline_config import ObservabilityPipelineConfig
from datadog_api_client.v2.model.observability_pipeline_data import ObservabilityPipelineData
from datadog_api_client.v2.model.observability_pipeline_data_attributes import ObservabilityPipelineDataAttributes
from datadog_api_client.v2.model.observability_pipeline_datadog_agent_source import (
ObservabilityPipelineDatadogAgentSource,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_agent_source_type import (
ObservabilityPipelineDatadogAgentSourceType,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_logs_destination import (
ObservabilityPipelineDatadogLogsDestination,
)
from datadog_api_client.v2.model.observability_pipeline_datadog_logs_destination_type import (
ObservabilityPipelineDatadogLogsDestinationType,
)
from datadog_api_client.v2.model.observability_pipeline_filter_processor import ObservabilityPipelineFilterProcessor
from datadog_api_client.v2.model.observability_pipeline_filter_processor_type import (
ObservabilityPipelineFilterProcessorType,
)
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = environ["PIPELINE_DATA_ID"]
body = ObservabilityPipeline(
data=ObservabilityPipelineData(
attributes=ObservabilityPipelineDataAttributes(
config=ObservabilityPipelineConfig(
destinations=[
ObservabilityPipelineDatadogLogsDestination(
id="updated-datadog-logs-destination-id",
inputs=[
"filter-processor",
],
type=ObservabilityPipelineDatadogLogsDestinationType.DATADOG_LOGS,
),
],
processors=[
ObservabilityPipelineFilterProcessor(
id="filter-processor",
include="service:my-service",
inputs=[
"datadog-agent-source",
],
type=ObservabilityPipelineFilterProcessorType.FILTER,
),
],
sources=[
ObservabilityPipelineDatadogAgentSource(
id="datadog-agent-source",
type=ObservabilityPipelineDatadogAgentSourceType.DATADOG_AGENT,
),
],
),
name="Updated Pipeline Name",
),
id=PIPELINE_DATA_ID,
type="pipelines",
),
)
configuration = Configuration()
configuration.unstable_operations["update_pipeline"] = True
with ApiClient(configuration) as api_client:
api_instance = ObservabilityPipelinesApi(api_client)
response = api_instance.update_pipeline(pipeline_id=PIPELINE_DATA_ID, body=body)
print(response)
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" python3 "example.py"# Update a pipeline returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.unstable_operations["v2.update_pipeline".to_sym] = true
end
api_instance = DatadogAPIClient::V2::ObservabilityPipelinesAPI.new
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = ENV["PIPELINE_DATA_ID"]
body = DatadogAPIClient::V2::ObservabilityPipeline.new({
data: DatadogAPIClient::V2::ObservabilityPipelineData.new({
attributes: DatadogAPIClient::V2::ObservabilityPipelineDataAttributes.new({
config: DatadogAPIClient::V2::ObservabilityPipelineConfig.new({
destinations: [
DatadogAPIClient::V2::ObservabilityPipelineDatadogLogsDestination.new({
id: "updated-datadog-logs-destination-id",
inputs: [
"filter-processor",
],
type: DatadogAPIClient::V2::ObservabilityPipelineDatadogLogsDestinationType::DATADOG_LOGS,
}),
],
processors: [
DatadogAPIClient::V2::ObservabilityPipelineFilterProcessor.new({
id: "filter-processor",
include: "service:my-service",
inputs: [
"datadog-agent-source",
],
type: DatadogAPIClient::V2::ObservabilityPipelineFilterProcessorType::FILTER,
}),
],
sources: [
DatadogAPIClient::V2::ObservabilityPipelineDatadogAgentSource.new({
id: "datadog-agent-source",
type: DatadogAPIClient::V2::ObservabilityPipelineDatadogAgentSourceType::DATADOG_AGENT,
}),
],
}),
name: "Updated Pipeline Name",
}),
id: PIPELINE_DATA_ID,
type: "pipelines",
}),
})
p api_instance.update_pipeline(PIPELINE_DATA_ID, body)
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" rb "example.rb"// Update a pipeline returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_observability_pipelines::ObservabilityPipelinesAPI;
use datadog_api_client::datadogV2::model::ObservabilityPipeline;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfig;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigDestinationItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigProcessorItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineConfigSourceItem;
use datadog_api_client::datadogV2::model::ObservabilityPipelineData;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDataAttributes;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogAgentSource;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogAgentSourceType;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogLogsDestination;
use datadog_api_client::datadogV2::model::ObservabilityPipelineDatadogLogsDestinationType;
use datadog_api_client::datadogV2::model::ObservabilityPipelineFilterProcessor;
use datadog_api_client::datadogV2::model::ObservabilityPipelineFilterProcessorType;
#[tokio::main]
async fn main() {
// there is a valid "pipeline" in the system
let pipeline_data_id = std::env::var("PIPELINE_DATA_ID").unwrap();
let body =
ObservabilityPipeline::new(
ObservabilityPipelineData::new(
ObservabilityPipelineDataAttributes::new(
ObservabilityPipelineConfig::new(
vec![
ObservabilityPipelineConfigDestinationItem::ObservabilityPipelineDatadogLogsDestination(
Box::new(
ObservabilityPipelineDatadogLogsDestination::new(
"updated-datadog-logs-destination-id".to_string(),
vec!["filter-processor".to_string()],
ObservabilityPipelineDatadogLogsDestinationType::DATADOG_LOGS,
),
),
)
],
vec![
ObservabilityPipelineConfigProcessorItem::ObservabilityPipelineFilterProcessor(
Box::new(
ObservabilityPipelineFilterProcessor::new(
"filter-processor".to_string(),
"service:my-service".to_string(),
vec!["datadog-agent-source".to_string()],
ObservabilityPipelineFilterProcessorType::FILTER,
),
),
)
],
vec![
ObservabilityPipelineConfigSourceItem::ObservabilityPipelineDatadogAgentSource(
Box::new(
ObservabilityPipelineDatadogAgentSource::new(
"datadog-agent-source".to_string(),
ObservabilityPipelineDatadogAgentSourceType::DATADOG_AGENT,
),
),
)
],
),
"Updated Pipeline Name".to_string(),
),
pipeline_data_id.clone(),
"pipelines".to_string(),
),
);
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.UpdatePipeline", true);
let api = ObservabilityPipelinesAPI::with_config(configuration);
let resp = api.update_pipeline(pipeline_data_id.clone(), body).await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run/**
* Update a pipeline returns "OK" response
*/
import { client, v2 } from "@datadog/datadog-api-client";
const configuration = client.createConfiguration();
configuration.unstableOperations["v2.updatePipeline"] = true;
const apiInstance = new v2.ObservabilityPipelinesApi(configuration);
// there is a valid "pipeline" in the system
const PIPELINE_DATA_ID = process.env.PIPELINE_DATA_ID as string;
const params: v2.ObservabilityPipelinesApiUpdatePipelineRequest = {
body: {
data: {
attributes: {
config: {
destinations: [
{
id: "updated-datadog-logs-destination-id",
inputs: ["filter-processor"],
type: "datadog_logs",
},
],
processors: [
{
id: "filter-processor",
include: "service:my-service",
inputs: ["datadog-agent-source"],
type: "filter",
},
],
sources: [
{
id: "datadog-agent-source",
type: "datadog_agent",
},
],
},
name: "Updated Pipeline Name",
},
id: PIPELINE_DATA_ID,
type: "pipelines",
},
},
pipelineId: PIPELINE_DATA_ID,
};
apiInstance
.updatePipeline(params)
.then((data: v2.ObservabilityPipeline) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" tsc "example.ts"Note: This endpoint is in Preview.
DELETE https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/{pipeline_id}
Delete a pipeline.
This endpoint requires the observability_pipelines_delete permission.
이름
유형
설명
pipeline_id [required]
string
The ID of the pipeline to delete.
OK
Forbidden
API error response.
{
"errors": [
"Bad Request"
]
}Not Found
API error response.
{
"errors": [
"Bad Request"
]
}Conflict
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Path parameters
export pipeline_id="CHANGE_ME"
# Curl command
curl -X DELETE "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/${pipeline_id}" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}"
"""
Delete a pipeline returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.observability_pipelines_api import ObservabilityPipelinesApi
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = environ["PIPELINE_DATA_ID"]
configuration = Configuration()
configuration.unstable_operations["delete_pipeline"] = True
with ApiClient(configuration) as api_client:
api_instance = ObservabilityPipelinesApi(api_client)
api_instance.delete_pipeline(
pipeline_id=PIPELINE_DATA_ID,
)
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" python3 "example.py"# Delete a pipeline returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.unstable_operations["v2.delete_pipeline".to_sym] = true
end
api_instance = DatadogAPIClient::V2::ObservabilityPipelinesAPI.new
# there is a valid "pipeline" in the system
PIPELINE_DATA_ID = ENV["PIPELINE_DATA_ID"]
api_instance.delete_pipeline(PIPELINE_DATA_ID)
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" rb "example.rb"// Delete a pipeline returns "OK" response
package main
import (
"context"
"fmt"
"os"
"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)
func main() {
// there is a valid "pipeline" in the system
PipelineDataID := os.Getenv("PIPELINE_DATA_ID")
ctx := datadog.NewDefaultContext(context.Background())
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.DeletePipeline", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewObservabilityPipelinesApi(apiClient)
r, err := api.DeletePipeline(ctx, PipelineDataID)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `ObservabilityPipelinesApi.DeletePipeline`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
}
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" go run "main.go"// Delete a pipeline returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ObservabilityPipelinesApi;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setUnstableOperationEnabled("v2.deletePipeline", true);
ObservabilityPipelinesApi apiInstance = new ObservabilityPipelinesApi(defaultClient);
// there is a valid "pipeline" in the system
String PIPELINE_DATA_ID = System.getenv("PIPELINE_DATA_ID");
try {
apiInstance.deletePipeline(PIPELINE_DATA_ID);
} catch (ApiException e) {
System.err.println("Exception when calling ObservabilityPipelinesApi#deletePipeline");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" java "Example.java"// Delete a pipeline returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_observability_pipelines::ObservabilityPipelinesAPI;
#[tokio::main]
async fn main() {
// there is a valid "pipeline" in the system
let pipeline_data_id = std::env::var("PIPELINE_DATA_ID").unwrap();
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.DeletePipeline", true);
let api = ObservabilityPipelinesAPI::with_config(configuration);
let resp = api.delete_pipeline(pipeline_data_id.clone()).await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run/**
* Delete a pipeline returns "OK" response
*/
import { client, v2 } from "@datadog/datadog-api-client";
const configuration = client.createConfiguration();
configuration.unstableOperations["v2.deletePipeline"] = true;
const apiInstance = new v2.ObservabilityPipelinesApi(configuration);
// there is a valid "pipeline" in the system
const PIPELINE_DATA_ID = process.env.PIPELINE_DATA_ID as string;
const params: v2.ObservabilityPipelinesApiDeletePipelineRequest = {
pipelineId: PIPELINE_DATA_ID,
};
apiInstance
.deletePipeline(params)
.then((data: any) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.comus3.datadoghq.comus5.datadoghq.comdatadoghq.euap1.datadoghq.comddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" tsc "example.ts"Note: This endpoint is in Preview.
POST https://api.ap1.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/validatehttps://api.datadoghq.eu/api/v2/remote_config/products/obs_pipelines/pipelines/validatehttps://api.ddog-gov.com/api/v2/remote_config/products/obs_pipelines/pipelines/validatehttps://api.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/validatehttps://api.us3.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/validatehttps://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/validate
Validates a pipeline configuration without creating or updating any resources.
Returns a list of validation errors, if any.
This endpoint requires the observability_pipelines_read permission.
항목
유형
설명
data [required]
object
Contains the the pipeline configuration.
attributes [required]
object
Defines the pipeline’s name and its components (sources, processors, and destinations).
config [required]
object
Specifies the pipeline's configuration, including its sources, processors, and destinations.
destinations [required]
[ <oneOf>]
A list of destination components where processed logs are sent.
Option 1
object
The datadog_logs destination forwards logs to Datadog Log Management.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be datadog_logs.
Allowed enum values: datadog_logs
default: datadog_logs
Option 2
object
The amazon_s3 destination sends your logs in Datadog-rehydratable format to an Amazon S3 bucket for archiving.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
bucket [required]
string
S3 bucket name.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys.
region [required]
string
AWS region of the S3 bucket.
storage_class [required]
enum
S3 storage class.
Allowed enum values: STANDARD,REDUCED_REDUNDANCY,INTELLIGENT_TIERING,STANDARD_IA,EXPRESS_ONEZONE,ONEZONE_IA,GLACIER,GLACIER_IR,DEEP_ARCHIVE
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 3
object
The google_cloud_storage destination stores logs in a Google Cloud Storage (GCS) bucket.
It requires a bucket name, GCP authentication, and metadata fields.
acl [required]
enum
Access control list setting for objects written to the bucket.
Allowed enum values: private,project-private,public-read,authenticated-read,bucket-owner-read,bucket-owner-full-control
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
bucket [required]
string
Name of the GCS bucket.
id [required]
string
Unique identifier for the destination component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
key_prefix
string
Optional prefix for object keys within the GCS bucket.
metadata [required]
[object]
Custom metadata key-value pairs added to each object.
name [required]
string
The metadata key.
value [required]
string
The metadata value.
storage_class [required]
enum
Storage class used for objects stored in GCS.
Allowed enum values: STANDARD,NEARLINE,COLDLINE,ARCHIVE
type [required]
enum
The destination type. Always google_cloud_storage.
Allowed enum values: google_cloud_storage
default: google_cloud_storage
Option 4
object
The splunk_hec destination forwards logs to Splunk using the HTTP Event Collector (HEC).
auto_extract_timestamp
boolean
If true, Splunk tries to extract timestamps from incoming log events.
If false, Splunk assigns the time the event was received.
encoding
enum
Encoding format for log events.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
index
string
Optional name of the Splunk index where logs are written.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
sourcetype
string
The Splunk sourcetype to assign to log events.
type [required]
enum
The destination type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The sumo_logic destination forwards logs to Sumo Logic.
encoding
enum
The output encoding format.
Allowed enum values: json,raw_message,logfmt
header_custom_fields
[object]
A list of custom headers to include in the request to Sumo Logic.
name [required]
string
The header field name.
value [required]
string
The header field value.
header_host_name
string
Optional override for the host name header.
header_source_category
string
Optional override for the source category header.
header_source_name
string
Optional override for the source name header.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 6
object
The elasticsearch destination writes logs to an Elasticsearch cluster.
api_version
enum
The Elasticsearch API version to use. Set to auto to auto-detect.
Allowed enum values: auto,v6,v7,v8
bulk_index
string
The index to write logs to in Elasticsearch.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be elasticsearch.
Allowed enum values: elasticsearch
default: elasticsearch
Option 7
object
The rsyslog destination forwards logs to an external rsyslog server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 8
object
The syslog_ng destination forwards logs to an external syslog-ng server over TCP or UDP using the syslog protocol.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
keepalive
int64
Optional socket keepalive duration in milliseconds.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The destination type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 9
object
The azure_storage destination forwards logs to an Azure Blob Storage container.
blob_prefix
string
Optional prefix for blobs written to the container.
container_name [required]
string
The name of the Azure Blob Storage container to store logs in.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be azure_storage.
Allowed enum values: azure_storage
default: azure_storage
Option 10
object
The microsoft_sentinel destination forwards logs to Microsoft Sentinel.
client_id [required]
string
Azure AD client ID used for authentication.
dcr_immutable_id [required]
string
The immutable ID of the Data Collection Rule (DCR).
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
table [required]
string
The name of the Log Analytics table where logs are sent.
tenant_id [required]
string
Azure AD tenant ID.
type [required]
enum
The destination type. The value should always be microsoft_sentinel.
Allowed enum values: microsoft_sentinel
default: microsoft_sentinel
Option 11
object
The google_chronicle destination sends logs to Google Chronicle.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
customer_id [required]
string
The Google Chronicle customer ID.
encoding
enum
The encoding format for the logs sent to Chronicle.
Allowed enum values: json,raw_message
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
log_type
string
The log type metadata associated with the Chronicle destination.
type [required]
enum
The destination type. The value should always be google_chronicle.
Allowed enum values: google_chronicle
default: google_chronicle
Option 12
object
The new_relic destination sends logs to the New Relic platform.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The New Relic region.
Allowed enum values: us,eu
type [required]
enum
The destination type. The value should always be new_relic.
Allowed enum values: new_relic
default: new_relic
Option 13
object
The sentinel_one destination sends logs to SentinelOne.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
region [required]
enum
The SentinelOne region to send logs to.
Allowed enum values: us,eu,ca,data_set_us
type [required]
enum
The destination type. The value should always be sentinel_one.
Allowed enum values: sentinel_one
default: sentinel_one
Option 14
object
The opensearch destination writes logs to an OpenSearch cluster.
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be opensearch.
Allowed enum values: opensearch
default: opensearch
Option 15
object
The amazon_opensearch destination writes logs to Amazon OpenSearch.
auth [required]
object
Authentication settings for the Amazon OpenSearch destination.
The strategy field determines whether basic or AWS-based authentication is used.
assume_role
string
The ARN of the role to assume (used with aws strategy).
aws_region
string
AWS region
external_id
string
External ID for the assumed role (used with aws strategy).
session_name
string
Session name for the assumed role (used with aws strategy).
strategy [required]
enum
The authentication strategy to use.
Allowed enum values: basic,aws
bulk_index
string
The index to write logs to.
id [required]
string
The unique identifier for this component.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The destination type. The value should always be amazon_opensearch.
Allowed enum values: amazon_opensearch
default: amazon_opensearch
processors
[ <oneOf>]
A list of processors that transform or enrich log data.
Option 1
object
The filter processor allows conditional processing of logs based on a Datadog search query. Logs that match the include query are passed through; others are discarded.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs should pass through the filter. Logs that match this query continue to downstream components; others are dropped.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be filter.
Allowed enum values: filter
default: filter
Option 2
object
The parse_json processor extracts JSON from a specified field and flattens it into the event. This is useful when logs contain embedded JSON as a string.
field [required]
string
The name of the log field that contains a JSON string.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be parse_json.
Allowed enum values: parse_json
default: parse_json
Option 3
object
The Quota Processor measures logging traffic for logs that match a specified filter. When the configured daily quota is met, the processor can drop or alert.
drop_events [required]
boolean
If set to true, logs that matched the quota filter and sent after the quota has been met are dropped; only logs that did not match the filter query continue through the pipeline.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
ignore_when_missing_partitions
boolean
If true, the processor skips quota checks when partition fields are missing from the logs.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
name [required]
string
Name of the quota.
overflow_action
enum
The action to take when the quota is exceeded. Options:
drop: Drop the event.
no_action: Let the event pass through.
overflow_routing: Route to an overflow destination.
Allowed enum values: drop,no_action,overflow_routing
overrides
[object]
A list of alternate quota rules that apply to specific sets of events, identified by matching field values. Each override can define a custom limit.
fields [required]
[object]
A list of field matchers used to apply a specific override. If an event matches all listed key-value pairs, the corresponding override limit is enforced.
name [required]
string
The field name.
value [required]
string
The field value.
limit [required]
object
The maximum amount of data or number of events allowed before the quota is enforced. Can be specified in bytes or events.
enforce [required]
enum
Unit for quota enforcement in bytes for data size or events for count.
Allowed enum values: bytes,events
limit [required]
int64
The limit for quota enforcement.
partition_fields
[string]
A list of fields used to segment log traffic for quota enforcement. Quotas are tracked independently by unique combinations of these field values.
type [required]
enum
The processor type. The value should always be quota.
Allowed enum values: quota
default: quota
Option 4
object
The add_fields processor adds static key-value fields to logs.
fields [required]
[object]
A list of static fields (key-value pairs) that is added to each log event processed by this component.
name [required]
string
The field name.
value [required]
string
The field value.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be add_fields.
Allowed enum values: add_fields
default: add_fields
Option 5
object
The remove_fields processor deletes specified fields from logs.
fields [required]
[string]
A list of field names to be removed from each log event.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
The PipelineRemoveFieldsProcessor inputs.
type [required]
enum
The processor type. The value should always be remove_fields.
Allowed enum values: remove_fields
default: remove_fields
Option 6
object
The rename_fields processor changes field names.
fields [required]
[object]
A list of rename rules specifying which fields to rename in the event, what to rename them to, and whether to preserve the original fields.
destination [required]
string
The field name to assign the renamed value to.
preserve_source [required]
boolean
Indicates whether the original field, that is received from the source, should be kept (true) or removed (false) after renaming.
source [required]
string
The original field name in the log event that should be renamed.
id [required]
string
A unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
type [required]
enum
The processor type. The value should always be rename_fields.
Allowed enum values: rename_fields
default: rename_fields
Option 7
object
The generate_datadog_metrics processor creates custom metrics from logs and sends them to Datadog.
Metrics can be counters, gauges, or distributions and optionally grouped by log fields.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
metrics [required]
[object]
Configuration for generating individual metrics.
group_by
[string]
Optional fields used to group the metric series.
include [required]
string
Datadog filter query to match logs for metric generation.
metric_type [required]
enum
Type of metric to create.
Allowed enum values: count,gauge,distribution
name [required]
string
Name of the custom metric to be created.
value [required]
<oneOf>
Specifies how the value of the generated metric is computed.
Option 1
object
Strategy that increments a generated metric by one for each matching event.
strategy [required]
enum
Increments the metric by 1 for each matching event.
Allowed enum values: increment_by_one
Option 2
object
Strategy that increments a generated metric based on the value of a log field.
field [required]
string
Name of the log field containing the numeric value to increment the metric by.
strategy [required]
enum
Uses a numeric field in the log event as the metric increment.
Allowed enum values: increment_by_field
type [required]
enum
The processor type. Always generate_datadog_metrics.
Allowed enum values: generate_datadog_metrics
default: generate_datadog_metrics
Option 8
object
The sample processor allows probabilistic sampling of logs at a fixed rate.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
percentage
double
The percentage of logs to sample.
rate
int64
Number of events to sample (1 in N).
type [required]
enum
The processor type. The value should always be sample.
Allowed enum values: sample
default: sample
Option 9
object
The parse_grok processor extracts structured fields from unstructured log messages using Grok patterns.
disable_library_rules
boolean
If set to true, disables the default Grok rules provided by Datadog.
id [required]
string
A unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
The list of Grok parsing rules. If multiple matching rules are provided, they are evaluated in order. The first successful match is applied.
match_rules [required]
[object]
A list of Grok parsing rules that define how to extract fields from the source field. Each rule must contain a name and a valid Grok pattern.
name [required]
string
The name of the rule.
rule [required]
string
The definition of the Grok rule.
source [required]
string
The name of the field in the log event to apply the Grok rules to.
support_rules [required]
[object]
A list of Grok helper rules that can be referenced by the parsing rules.
name [required]
string
The name of the Grok helper rule.
rule [required]
string
The definition of the Grok helper rule.
type [required]
enum
The processor type. The value should always be parse_grok.
Allowed enum values: parse_grok
default: parse_grok
Option 10
object
The sensitive_data_scanner processor detects and optionally redacts sensitive data in log events.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this component.
rules [required]
[object]
A list of rules for identifying and acting on sensitive data patterns.
keyword_options
object
Configuration for keywords used to reinforce sensitive data pattern detection.
keywords [required]
[string]
A list of keywords to match near the sensitive pattern.
proximity [required]
int64
Maximum number of tokens between a keyword and a sensitive value match.
name [required]
string
A name identifying the rule.
on_match [required]
<oneOf>
Defines what action to take when sensitive data is matched.
Option 1
object
Configuration for completely redacting matched sensitive data.
action [required]
enum
Action type that completely replaces the matched sensitive data with a fixed replacement string to remove all visibility.
Allowed enum values: redact
options [required]
object
Configuration for fully redacting sensitive data.
replace [required]
string
The ObservabilityPipelineSensitiveDataScannerProcessorActionRedactOptions replace.
Option 2
object
Configuration for hashing matched sensitive values.
action [required]
enum
Action type that replaces the matched sensitive data with a hashed representation, preserving structure while securing content.
Allowed enum values: hash
options
object
The ObservabilityPipelineSensitiveDataScannerProcessorActionHash options.
Option 3
object
Configuration for partially redacting matched sensitive data.
action [required]
enum
Action type that redacts part of the sensitive data while preserving a configurable number of characters, typically used for masking purposes (e.g., show last 4 digits of a credit card).
Allowed enum values: partial_redact
options [required]
object
Controls how partial redaction is applied, including character count and direction.
characters [required]
int64
The ObservabilityPipelineSensitiveDataScannerProcessorActionPartialRedactOptions characters.
direction [required]
enum
Indicates whether to redact characters from the first or last part of the matched value.
Allowed enum values: first,last
pattern [required]
<oneOf>
Pattern detection configuration for identifying sensitive data using either a custom regex or a library reference.
Option 1
object
Defines a custom regex-based pattern for identifying sensitive data in logs.
options [required]
object
Options for defining a custom regex pattern.
rule [required]
string
A regular expression used to detect sensitive values. Must be a valid regex.
type [required]
enum
Indicates a custom regular expression is used for matching.
Allowed enum values: custom
Option 2
object
Specifies a pattern from Datadog’s sensitive data detection library to match known sensitive data types.
options [required]
object
Options for selecting a predefined library pattern and enabling keyword support.
id [required]
string
Identifier for a predefined pattern from the sensitive data scanner pattern library.
use_recommended_keywords
boolean
Whether to augment the pattern with recommended keywords (optional).
type [required]
enum
Indicates that a predefined library pattern is used.
Allowed enum values: library
scope [required]
<oneOf>
Determines which parts of the log the pattern-matching rule should be applied to.
Option 1
object
Includes only specific fields for sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Applies the rule only to included fields.
Allowed enum values: include
Option 2
object
Excludes specific fields from sensitive data scanning.
options [required]
object
Fields to which the scope rule applies.
fields [required]
[string]
The ObservabilityPipelineSensitiveDataScannerProcessorScopeOptions fields.
target [required]
enum
Excludes specific fields from processing.
Allowed enum values: exclude
Option 3
object
Applies scanning across all available fields.
target [required]
enum
Applies the rule to all fields.
Allowed enum values: all
tags [required]
[string]
Tags assigned to this rule for filtering and classification.
type [required]
enum
The processor type. The value should always be sensitive_data_scanner.
Allowed enum values: sensitive_data_scanner
default: sensitive_data_scanner
Option 11
object
The ocsf_mapper processor transforms logs into the OCSF schema using a predefined mapping configuration.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mappings [required]
[object]
A list of mapping rules to convert events to the OCSF format.
include [required]
string
A Datadog search query used to select the logs that this mapping should apply to.
mapping [required]
<oneOf>
Defines a single mapping rule for transforming logs into the OCSF schema.
Option 1
enum
Predefined library mappings for common log formats.
Allowed enum values: CloudTrail Account Change,GCP Cloud Audit CreateBucket,GCP Cloud Audit CreateSink,GCP Cloud Audit SetIamPolicy,GCP Cloud Audit UpdateSink,Github Audit Log API Activity,Google Workspace Admin Audit addPrivilege,Microsoft 365 Defender Incident,Microsoft 365 Defender UserLoggedIn,Okta System Log Authentication,Palo Alto Networks Firewall Traffic
type [required]
enum
The processor type. The value should always be ocsf_mapper.
Allowed enum values: ocsf_mapper
default: ocsf_mapper
Option 12
object
The add_env_vars processor adds environment variable values to log events.
id [required]
string
The unique identifier for this component. Used to reference this processor in the pipeline.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
type [required]
enum
The processor type. The value should always be add_env_vars.
Allowed enum values: add_env_vars
default: add_env_vars
variables [required]
[object]
A list of environment variable mappings to apply to log fields.
field [required]
string
The target field in the log event.
name [required]
string
The name of the environment variable to read.
Option 13
object
The dedupe processor removes duplicate fields in log events.
fields [required]
[string]
A list of log field paths to check for duplicates.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
mode [required]
enum
The deduplication mode to apply to the fields.
Allowed enum values: match,ignore
type [required]
enum
The processor type. The value should always be dedupe.
Allowed enum values: dedupe
default: dedupe
Option 14
object
The enrichment_table processor enriches logs using a static CSV file or GeoIP database.
file
object
Defines a static enrichment table loaded from a CSV file.
encoding [required]
object
File encoding format.
delimiter [required]
string
The encoding delimiter.
includes_headers [required]
boolean
The encoding includes_headers.
type [required]
enum
Specifies the encoding format (e.g., CSV) used for enrichment tables.
Allowed enum values: csv
key [required]
[object]
Key fields used to look up enrichment values.
column [required]
string
The items column.
comparison [required]
enum
Defines how to compare key fields for enrichment table lookups.
Allowed enum values: equals
field [required]
string
The items field.
path [required]
string
Path to the CSV file.
schema [required]
[object]
Schema defining column names and their types.
column [required]
string
The items column.
type [required]
enum
Declares allowed data types for enrichment table columns.
Allowed enum values: string,boolean,integer,float,date,timestamp
geoip
object
Uses a GeoIP database to enrich logs based on an IP field.
key_field [required]
string
Path to the IP field in the log.
locale [required]
string
Locale used to resolve geographical names.
path [required]
string
Path to the GeoIP database file.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
target [required]
string
Path where enrichment results should be stored in the log.
type [required]
enum
The processor type. The value should always be enrichment_table.
Allowed enum values: enrichment_table
default: enrichment_table
Option 15
object
The reduce processor aggregates and merges logs based on matching keys and merge strategies.
group_by [required]
[string]
A list of fields used to group log events for merging.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
merge_strategies [required]
[object]
List of merge strategies defining how values from grouped events should be combined.
path [required]
string
The field path in the log event.
strategy [required]
enum
The merge strategy to apply.
Allowed enum values: discard,retain,sum,max,min,array,concat,concat_newline,concat_raw,shortest_array,longest_array,flat_unique
type [required]
enum
The processor type. The value should always be reduce.
Allowed enum values: reduce
default: reduce
Option 16
object
The throttle processor limits the number of events that pass through over a given time window.
group_by
[string]
Optional list of fields used to group events before the threshold has been reached.
id [required]
string
The unique identifier for this processor.
include [required]
string
A Datadog search query used to determine which logs this processor targets.
inputs [required]
[string]
A list of component IDs whose output is used as the input for this processor.
threshold [required]
int64
the number of events allowed in a given time window. Events sent after the threshold has been reached, are dropped.
type [required]
enum
The processor type. The value should always be throttle.
Allowed enum values: throttle
default: throttle
window [required]
double
The time window in seconds over which the threshold applies.
sources [required]
[ <oneOf>]
A list of configured data sources for the pipeline.
Option 1
object
The kafka source ingests data from Apache Kafka topics.
group_id [required]
string
Consumer group ID used by the Kafka client.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
librdkafka_options
[object]
Optional list of advanced Kafka client configuration options, defined as key-value pairs.
name [required]
string
The name of the librdkafka configuration option to set.
value [required]
string
The value assigned to the specified librdkafka configuration option.
sasl
object
Specifies the SASL mechanism for authenticating with a Kafka cluster.
mechanism
enum
SASL mechanism used for Kafka authentication.
Allowed enum values: PLAIN,SCRAM-SHA-256,SCRAM-SHA-512
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
topics [required]
[string]
A list of Kafka topic names to subscribe to. The source ingests messages from each topic specified.
type [required]
enum
The source type. The value should always be kafka.
Allowed enum values: kafka
default: kafka
Option 2
object
The datadog_agent source collects logs from the Datadog Agent.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be datadog_agent.
Allowed enum values: datadog_agent
default: datadog_agent
Option 3
object
The splunk_tcp source receives logs from a Splunk Universal Forwarder over TCP.
TLS is supported for secure transmission.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_tcp.
Allowed enum values: splunk_tcp
default: splunk_tcp
Option 4
object
The splunk_hec source implements the Splunk HTTP Event Collector (HEC) API.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always splunk_hec.
Allowed enum values: splunk_hec
default: splunk_hec
Option 5
object
The amazon_s3 source ingests logs from an Amazon S3 bucket.
It supports AWS authentication and TLS encryption.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
region [required]
string
AWS region where the S3 bucket resides.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. Always amazon_s3.
Allowed enum values: amazon_s3
default: amazon_s3
Option 6
object
The fluentd source ingests logs from a Fluentd-compatible service.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be `fluentd.
Allowed enum values: fluentd
default: fluentd
Option 7
object
The fluent_bit source ingests logs from Fluent Bit.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (for example, as the input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be fluent_bit.
Allowed enum values: fluent_bit
default: fluent_bit
Option 8
object
The http_server source collects logs over HTTP POST from external services.
auth_strategy [required]
enum
HTTP authentication method.
Allowed enum values: none,plain
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
Unique ID for the HTTP server source.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_server.
Allowed enum values: http_server
default: http_server
Option 9
object
The sumo_logic source receives logs from Sumo Logic collectors.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
type [required]
enum
The source type. The value should always be sumo_logic.
Allowed enum values: sumo_logic
default: sumo_logic
Option 10
object
The rsyslog source listens for logs over TCP or UDP from an rsyslog server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be rsyslog.
Allowed enum values: rsyslog
default: rsyslog
Option 11
object
The syslog_ng source listens for logs over TCP or UDP from a syslog-ng server using the syslog protocol.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
mode [required]
enum
Protocol used by the syslog source to receive messages.
Allowed enum values: tcp,udp
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be syslog_ng.
Allowed enum values: syslog_ng
default: syslog_ng
Option 12
object
The amazon_data_firehose source ingests logs from AWS Data Firehose.
auth
object
AWS authentication credentials used for accessing AWS services such as S3. If omitted, the system’s default credentials are used (for example, the IAM role and environment variables).
assume_role
string
The Amazon Resource Name (ARN) of the role to assume.
external_id
string
A unique identifier for cross-account role assumption.
session_name
string
A session identifier used for logging and tracing the assumed role session.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be amazon_data_firehose.
Allowed enum values: amazon_data_firehose
default: amazon_data_firehose
Option 13
object
The google_pubsub source ingests logs from a Google Cloud Pub/Sub subscription.
auth [required]
object
GCP credentials used to authenticate with Google Cloud Storage.
credentials_file [required]
string
Path to the GCP service account key file.
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
project [required]
string
The GCP project ID that owns the Pub/Sub subscription.
subscription [required]
string
The Pub/Sub subscription name from which messages are consumed.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be google_pubsub.
Allowed enum values: google_pubsub
default: google_pubsub
Option 14
object
The http_client source scrapes logs from HTTP endpoints at regular intervals.
auth_strategy
enum
Optional authentication strategy for HTTP requests.
Allowed enum values: basic,bearer
decoding [required]
enum
The decoding format used to interpret incoming logs.
Allowed enum values: bytes,gelf,json,syslog
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
scrape_interval_secs
int64
The interval (in seconds) between HTTP scrape requests.
scrape_timeout_secs
int64
The timeout (in seconds) for each scrape request.
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be http_client.
Allowed enum values: http_client
default: http_client
Option 15
object
The logstash source ingests logs from a Logstash forwarder.
id [required]
string
The unique identifier for this component. Used to reference this component in other parts of the pipeline (e.g., as input to downstream components).
tls
object
Configuration for enabling TLS encryption between the pipeline component and external services.
ca_file
string
Path to the Certificate Authority (CA) file used to validate the server’s TLS certificate.
crt_file [required]
string
Path to the TLS client certificate file used to authenticate the pipeline component with upstream or downstream services.
key_file
string
Path to the private key file associated with the TLS client certificate. Used for mutual TLS authentication.
type [required]
enum
The source type. The value should always be logstash.
Allowed enum values: logstash
default: logstash
name [required]
string
Name of the pipeline.
type [required]
string
The resource type identifier. For pipeline resources, this should always be set to pipelines.
default: pipelines
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Main Observability Pipeline"
},
"type": "pipelines"
}
}OK
Response containing validation errors.
항목
유형
설명
errors
[object]
The ValidationResponse errors.
meta [required]
object
Describes additional metadata for validation errors, including field names and error messages.
field
string
The field name that caused the error.
id
string
The ID of the component in which the error occurred.
message [required]
string
The detailed error message.
title [required]
string
A short, human-readable summary of the error.
{
"errors": [
{
"meta": {
"field": "region",
"id": "datadog-agent-source",
"message": "Field 'region' is required"
},
"title": "Field 'region' is required"
}
]
}Bad Request
API error response.
{
"errors": [
"Bad Request"
]
}Not Authorized
API error response.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
{
"errors": [
"Bad Request"
]
}
# Curl command
curl -X POST "https://api.ap1.datadoghq.com"https://api.datadoghq.eu"https://api.ddog-gov.com"https://api.datadoghq.com"https://api.us3.datadoghq.com"https://api.us5.datadoghq.com/api/v2/remote_config/products/obs_pipelines/pipelines/validate" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \
-d @- << EOF
{
"data": {
"attributes": {
"config": {
"destinations": [
{
"id": "datadog-logs-destination",
"inputs": [
"filter-processor"
],
"type": "datadog_logs"
}
],
"processors": [
{
"id": "filter-processor",
"include": "service:my-service",
"inputs": [
"datadog-agent-source"
],
"type": "filter"
}
],
"sources": [
{
"id": "datadog-agent-source",
"type": "datadog_agent"
}
]
},
"name": "Main Observability Pipeline"
},
"type": "pipelines"
}
}
EOF