Amazon RDS에서 SQL용 데이터베이스 모니터링 설정

문서 > 데이터베이스 모니터링 > SQL Server 설정 > Amazon RDS에서 SQL용 데이터베이스 모니터링 설정

데이터베이스 모니터링은 쿼리 메트릭, 쿼리 샘플, 실행 계획, 데이터베이스 상태, 장애 조치, 이벤트와 같은 정보를 수집해 Microsoft SQL Server 데이터베이스에 관한 상세한 정보를 가시화합니다.

데이터베이스에서 데이터베이스 모니터링을 활성화하려면 다음 단계를 따르세요.

AWS 통합 설정
데이터베이스에 에이전트 액세스 권한 부여
에이전트 설치
RDS 통합 설치

시작 전 참고 사항

지원되는 SQL 서버 버전: 2014, 2016, 2017, 2019, 2022
Supported Agent versions: 7.41.0+
Performance impact: The default Agent configuration for Database Monitoring is conservative, but you can adjust settings such as the collection interval and query sampling rate to better suit your needs. For most workloads, the Agent represents less than one percent of query execution time on the database and less than one percent of CPU.

Database Monitoring runs as an integration on top of the base Agent (see benchmarks).
Proxies, load balancers, and connection poolers: The Datadog Agent must connect directly to the host being monitored. The Agent should not connect to the database through a proxy, load balancer, or connection pooler. If the Agent connects to different hosts while it is running (as in the case of failover, load balancing, and so on), the Agent calculates the difference in statistics between two hosts, producing inaccurate metrics.
Data security considerations: Read about how Database Management handles sensitive information for information about what data the Agent collects from your databases and how to ensure it is secure.

AWS 통합 설정

Amazon Web Service 통합 타이틀에 있는 Resource Collection 섹션에서 Standard Collection을 활성화합니다.

에이전트 액세스 권한 부여

Datadog 에이전트가 통계와 쿼리를 수집하려면 데이터베이스에 읽기 전용 액세스가 필요합니다.

읽기 전용 로그인을 생성하여 서버에 연결하고 필요한 권한을 부여하세요.

USE [master];
CREATE LOGIN datadog WITH PASSWORD = '<PASSWORD>';
GO
--Set context to msdb database and create datadog user
USE [msdb];
CREATE USER datadog FOR LOGIN datadog;
GO
--Switch back to master and grant datadog user server permissions
USE [master];
GRANT VIEW SERVER STATE to datadog;
GRANT VIEW ANY DEFINITION to datadog;
GO

각 애플리케이션 추가 데이터베이스에 datadog 사용자를 생성합니다.

USE [database_name];
CREATE USER datadog FOR LOGIN datadog;

RDS에서는 CONNECT ANY DATABASE를 허용하지 않기 때문에 이 단계를 실행해야 합니다. Datadog 에이전트가 각 데이터베이스에 연결되어 있어야 해당 데이터베이스에 맞는 파일 I/O 통계를 수집할 수 있습니다.

에이전트 설치하기

AWS에서는 호스트에 바로 액세스하는 것을 허용하지 않기 때문에 SQL 서버 호스트와 통신할 수 있는 별도 호스트에 Datadog 에이전트를 설치해야 합니다. 에이전트를 설치하고 실행하는 데는 여러 가지 방법이 있습니다.

AlwaysOn 사용자의 경우 에이전트를 별도 서버에 설치하고 리스너 엔드포인트를 통해 클러스터에 연결해야 합니다. 왜냐하면 가용 그룹(AG)의 보조 복제본에 관한 정보가 주 복제본에서 수집되기 때문입니다. 또 에이전트를 이렇게 설치하면 이벤트 장애 조치를 발견하고 해결하는 데 도움이 됩니다.

To start collecting SQL Server telemetry, first install the Datadog Agent.

Create the SQL Server Agent conf file C:\ProgramData\Datadog\conf.d\sqlserver.d\conf.yaml. See the sample conf file for all available configuration options.

init_config:
instances:
  - dbm: true
    host: '<HOSTNAME>,<SQL_PORT>'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    include_ao_metrics: true  # Optional: For AlwaysOn users
    agent_jobs:               # Optional: For monitoring SQL Server Agent jobs
      enabled: true
      collection_interval: 15
      history_row_limit: 10000
    tags:  # Optional
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>'

To use Windows Authentication, set connection_string: "Trusted_Connection=yes" and omit the username and password fields.

The agent supports SQL Server Browser Service in versions 7.41+. To enable SSBS, provide a port of 0 in the host string: <HOSTNAME>,0.

Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.

Supported Drivers

Microsoft ADO

The recommended ADO provider is Microsoft OLE DB Driver. Ensure the driver is installed on the host where the agent is running.

connector: adodbapi
adoprovider: MSOLEDBSQL19  # Replace with MSOLEDBSQL for versions 18 and lower

The other two providers, SQLOLEDB and SQLNCLI, are considered deprecated by Microsoft and should no longer be used.

ODBC

The recommended ODBC driver is Microsoft ODBC Driver. Ensure the driver is installed on the host where the Agent is running.

connector: odbc
driver: '{ODBC Driver 18 for SQL Server}'

Once all Agent configuration is complete, restart the Datadog Agent.

Validate

Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.

To start collecting SQL Server telemetry, first install the Datadog Agent.

On Linux, the Datadog Agent additionally requires an ODBC SQL Server driver to be installed—for example, the Microsoft ODBC driver. Once an ODBC SQL Server is installed, copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.

Use the odbc connector and specify the proper driver as indicated in the odbcinst.ini file.

Create the SQL Server Agent conf file /etc/datadog-agent/conf.d/sqlserver.d/conf.yaml. See the sample conf file for all available configuration options.

init_config:
instances:
  - dbm: true
    host: '<HOSTNAME>,<SQL_PORT>'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: odbc
    driver: '<Driver from the `odbcinst.ini` file>'
    include_ao_metrics: true  # Optional: For AlwaysOn users
    agent_jobs:               # Optional: For monitoring SQL Server Agent jobs
      enabled: true
      collection_interval: 15
      history_row_limit: 10000
    tags:  # Optional
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>'

Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.

Once all Agent configuration is complete, restart the Datadog Agent.

Validate

Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.

To configure the Database Monitoring Agent running in a Docker container, set the Autodiscovery Integration Templates as Docker labels on your Agent container.

Note: The Agent must have read permission on the Docker socket for Autodiscovery of labels to work.

Replace the values to match your account and environment. See the sample conf file for all available configuration options.

export DD_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
export DD_AGENT_VERSION=7.35.0

docker run -e "DD_API_KEY=${DD_API_KEY}" \
  -v /var/run/docker.sock:/var/run/docker.sock:ro \
  -l com.datadoghq.ad.check_names='["sqlserver"]' \
  -l com.datadoghq.ad.init_configs='[{}]' \
  -l com.datadoghq.ad.instances='[{
    "dbm": true,
    "host": "<HOSTNAME>,<SQL_PORT>",
    "connector": "odbc",
    "driver": "FreeTDS",
    "username": "datadog",
    "password": "<PASSWORD>",
    "include_ao_metrics": true,  # Optional: For AlwaysOn users
    "agent_jobs": {              # Optional: For monitoring SQL Server Agent jobs
      "enabled": true
      "collection_interval": 15
      "history_row_limit": 10000
    }
    "tags": [
      "service:<CUSTOM_SERVICE>"
      "env:<CUSTOM_ENV>"
    ]
  }]' \
  gcr.io/datadoghq/agent:${DD_AGENT_VERSION}

Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.

Validate

Run the Agent’s status subcommand and look for sqlserver under the Checks section. Alternatively, navigate to the Databases page in Datadog to get started.

If you have a Kubernetes cluster, use the Datadog Cluster Agent for Database Monitoring.

If cluster checks are not already enabled in your Kubernetes cluster, follow the instructions to enable cluster checks. You can configure the Cluster Agent either with static files mounted in the Cluster Agent container, or by using Kubernetes service annotations:

Command line with Helm

Execute the following Helm command to install the Datadog Cluster Agent on your Kubernetes cluster. Replace the values to match your account and environment:

helm repo add datadog https://helm.datadoghq.com
helm repo update

helm install <RELEASE_NAME> \
  --set 'datadog.apiKey=<DATADOG_API_KEY>' \
  --set 'clusterAgent.enabled=true' \
  --set 'clusterChecksRunner.enabled=true' \
  --set "clusterAgent.confd.sqlserver\.yaml=cluster_check: true
init_config:
instances:
  - dbm: true
    host: <HOSTNAME>\,1433
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: 'odbc'
    driver: 'FreeTDS'
    include_ao_metrics: true  # Optional: For AlwaysOn users
    agent_jobs:               # Optional: For monitoring SQL Server Agent jobs
      enabled: true
      collection_interval: 15
      history_row_limit: 10000
    tags:  # Optional
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>'"\
  datadog/datadog

Configure with mounted files

To configure a cluster check with a mounted configuration file, mount the configuration file in the Cluster Agent container on the path: /conf.d/sqlserver.yaml:

cluster_check: true  # Make sure to include this flag
init_config:
instances:
  - dbm: true
    host: '<HOSTNAME>'
    port: <SQL_PORT>
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: 'odbc'
    driver: 'FreeTDS'
    include_ao_metrics: true  # Optional: For AlwaysOn users
    agent_jobs:               # Optional: For monitoring SQL Server Agent jobs
      enabled: true
      collection_interval: 15
      history_row_limit: 10000
    tags:  # Optional
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>

Configure with Kubernetes service annotations

Rather than mounting a file, you can declare the instance configuration as a Kubernetes Service. To configure this check for an Agent running on Kubernetes, create a Service in the same namespace as the Datadog Cluster Agent:

apiVersion: v1
kind: Service
metadata:
  name: sqlserver-datadog-check-instances
  annotations:
    ad.datadoghq.com/service.check_names: '["sqlserver"]'
    ad.datadoghq.com/service.init_configs: '[{}]'
    ad.datadoghq.com/service.instances: |
      [
        {
          "dbm": true,
          "host": "<HOSTNAME>",
          "port": "<SQL_PORT>",
          "username": "datadog",
          "password": "ENC[datadog_user_database_password]",
          "connector": "odbc",
          "driver": "FreeTDS",
          "include_ao_metrics": true,  # Optional: For AlwaysOn users
          "agent_jobs": {              # Optional: For monitoring SQL Server Agent jobs
            "enabled": true
            "collection_interval": 15
            "history_row_limit": 10000
          }
          "tags": ["service:<CUSTOM_SERVICE>", "env:<CUSTOM_ENV>"]  # Optional
        }
      ]      
spec:
  ports:
  - port: 1433
    protocol: TCP
    targetPort: 1433
    name: sqlserver

The Cluster Agent automatically registers this configuration and begins running the SQL Server check.

To avoid exposing the datadog user’s password in plain text, use the Agent’s secret management package and declare the password using the ENC[] syntax.

에이전트 설정 예시

Connecting with DSN using the ODBC driver on Linux

Locate the odbc.ini and odbcinst.ini files. By default, these are placed in the /etc directory when installing ODBC.
Copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.

Configure your DSN settings as follows:

odbcinst.ini must provide at least one section header and ODBC driver location.

Example:

[ODBC Driver 18 for SQL Server]
Description=Microsoft ODBC Driver 18 for SQL Server
Driver=/opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18.3.so.2.1
UsageCount=1

odbc.ini must provide a section header and a Driver path that matches odbcinst.ini.

Example:

[datadog]
Driver=/opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18.3.so.2.1

Update the /etc/datadog-agent/conf.d/sqlserver.d/conf.yaml file with your DSN information.

Example:

instances:
  - dbm: true
    host: 'localhost,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: 'odbc'
    driver: '{ODBC Driver 18 for SQL Server}' # This is the section header of odbcinst.ini
    dsn: 'datadog' # This is the section header of odbc.ini

Restart the Agent.

Using AlwaysOn

Note: For AlwaysOn users, the Agent must be installed on a separate server and connected to the cluster through the listener endpoint. This is because information about Availability Group (AG) secondary replicas is collected from the primary replica. Additionally, installing the Agent in this way helps to keep it up and running in the event of a failover.

instances:
  - dbm: true
    host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    include_ao_metrics: true  # If Availability Groups is enabled
    include_fci_metrics: true   # If Failover Clustering is enabled

Monitoring SQL Server Agent Jobs

Note: For monitoring SQL Server Agent jobs, the Datadog Agent must have access to the [msdb] database. Monitoring of SQL Server Agent jobs is supported on SQL Server versions 2016 and newer. Starting from Agent v7.57, the Datadog Agent can collect SQL Server Agent job metrics and histories. To enable this feature, set enabled to true in the agent_jobs section of the SQL Server integration configuration file. The collection_interval and history_row_limit fields are optional.

instances:
  - dbm: true
    host: 'shopist-prod,1433'
    username: datadog
    password: '<PASSWORD>'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    agent_jobs:
      enabled: true
      collection_interval: 15
      history_row_limit: 10000

Collecting schemas

Starting from Agent v7.56, the Datadog Agent can collect schema information from SQLServer databases. To enable this feature, use the schemas_collection option. Schemas are collected on databases for which the Agent has CONNECT access.

Note: For schema collection on RDS instances, it is necessary to grant explicit CONNECT access to the datadog user for each database on the instance. See Grant the Agent access for more details.

Use the database_autodiscovery option to avoid specifying each logical database. See the sample sqlserver.d/conf.yaml for more details.

init_config:
instances:
 # This instance detects every logical database automatically
  - dbm: true
        host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    database_autodiscovery:
      enabled: true
    schemas_collection:
      enabled: true
    # Optional: enable metric collection for indexes
    include_index_usage_metrics: true
# This instance only collects schemas and index metrics from the `users` database
  - dbm: true
        host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    database: users
    schemas_collection:
      enabled: true
    include_index_usage_metrics: true

One Agent connecting to multiple hosts

It is common to configure a single Agent host to connect to multiple remote database instances (see Agent installation architectures for DBM). To connect to multiple hosts, create an entry for each host in the SQL Server integration config. In these cases, Datadog recommends limiting the number of instances per Agent to a maximum of 10 database instances to guarantee reliable performance.

init_config:
instances:
  - dbm: true
    host: 'example-service-primary.example-host.com,1433'
    username: datadog
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    password: 'ENC[datadog_user_database_password]'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
  - dbm: true
    host: 'example-service–replica-1.example-host.com,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
  - dbm: true
    host: 'example-service–replica-2.example-host.com,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
    [...]

Running custom queries

To collect custom metrics, use the custom_queries option. See the sample sqlserver.d/conf.yaml for more details.

init_config:
instances:
  - dbm: true
    host: 'localhost,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    custom_queries:
    - query: SELECT age, salary, hours_worked, name FROM hr.employees;
      columns:
        - name: custom.employee_age
          type: gauge
        - name: custom.employee_salary
           type: gauge
        - name: custom.employee_hours
           type: count
        - name: name
           type: tag
      tags:
        - 'table:employees'

Working with hosts through a remote proxy

If the Agent must connect to a database host through a remote proxy, all telemetry is tagged with the hostname of the proxy rather than the database instance. Use the reported_hostname option to set a custom override of the hostname detected by the Agent.

init_config:
instances:
  - dbm: true
    host: 'localhost,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    reported_hostname: products-primary
  - dbm: true
    host: 'localhost,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    reported_hostname: products-replica-1

Discovering ports automatically

SQL Server Browser Service, Named Instances, and other services can automatically detect port numbers. You can use this instead of hardcoding port numbers in connection strings. To use the Agent with one of these services, set the port field to 0.

For example, a Named Instance config:

init_config:
instances:
  - host: <hostname\instance name>
    port: 0

RDS 통합 설치

AWS에서 좀 더 포괄적인 데이터베이스 메트릭과 로그를 수집하려면 RDS 통합을 설치하세요.

참고 자료

추가 유용한 문서, 링크 및 기사:

기본 SQ 통합설명서

일반적인 문제 트러블슈팅설명서