Set up Tracing on a GitLab Pipeline

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Overview

GitLab is a DevOps platform that automates the software development lifecycle with integrated CI/CD features, enabling you to deploy applications quickly and securely.

Set up tracing in GitLab to collect data on your pipeline executions, analyze performance bottlenecks, troubleshoot operational issues, and optimize your deployment workflows.

Compatibility

Pipeline Visibility	Platform	Definition
Running pipelines	Running pipelines	View pipeline executions that are running. Queued or waiting pipelines show with status “Running” on Datadog.
Partial retries	Partial pipelines	View partially retried pipeline executions.
Manual steps	Manual steps	View manually triggered pipelines.
Queue time	Queue time	View the amount of time pipeline jobs sit in the queue before processing.
Logs correlation	Logs correlation	Correlate pipeline spans to logs and enable job log collection.
Infrastructure metric correlation	Infrastructure metric correlation	Correlate jobs to infrastructure host metrics for self-hosted GitLab runners.
Custom pre-defined tags	Custom pre-defined tags	Set custom tags to all generated pipeline, stages, and job spans.
Custom tags and measures at runtime	Custom tags and measures at runtime	Configure custom tags and measures at runtime.
Parameters	Parameters	Set custom `env` or `service` parameters when a pipeline is triggered.
Pipeline failure reasons	Pipeline failure reasons	Identify pipeline failure reasons from error messages.
Approval wait time	Approval wait time	View the amount of time jobs and pipelines wait for manual approvals.
Execution time	Execution time	View the amount of time pipelines have been running jobs. Gitlab refers to this metric as `duration`. Duration in Gitlab and execution time may show different values. Gitlab does not take into consideration jobs that failed due to certain kinds of failures (such as runner system failures).
Custom spans	Custom spans	Configure custom spans for your pipelines.

The following GitLab versions are supported:

GitLab.com (SaaS)
GitLab >= 14.1 (self-hosted)
GitLab >= 13.7.0 (self-hosted) with the datadog_ci_integration feature flag enabled

Configure the Datadog integration

Configure the integration on a project or group by going to Settings > Integrations > Datadog for each project or group you want to instrument.

Configure the integration on a project or group by going to Settings > Integrations > Datadog for each project or group you want to instrument. You can also activate the integration at the GitLab instance level by going to Admin > Settings > Integrations > Datadog.

Enable the datadog_ci_integration feature flag to activate the integration.

Run one of the following commands, which use GitLab’s Rails Runner, depending on your installation type:

From Omnibus Installations:

sudo gitlab-rails runner "Feature.enable(:datadog_ci_integration)"

From Source Installations:

sudo -u git -H bundle exec rails runner \
  -e production \
  "Feature.enable(:datadog_ci_integration)"

From Kubernetes Installations:

kubectl exec -it <task-runner-pod-name> -- \
  /srv/gitlab/bin/rails runner "Feature.enable(:datadog_ci_integration)"

Then, configure the integration on a project by going to Settings > Integrations > Datadog for each project you want to instrument.

Due to a bug in early versions of GitLab, the Datadog integration cannot be enabled at group or instance level on GitLab versions < 14.1, even if the option is available on GitLab's UI.

Direct support with webhooks is not under development. Unexpected issues could happen. Datadog recommends that you update GitLab instead.

For older versions of GitLab, you can use webhooks to send pipeline data to Datadog.

Go to Settings > Webhooks in your repository (or GitLab instance settings), and add a new webhook:

URL: https://webhook-intake./api/v2/webhook/?dd-api-key=<API_KEY> where <API_KEY> is your Datadog API key.
Secret Token: Leave this field empty.
Trigger: Select Job events and Pipeline events.

To set custom env or service parameters, add more query parameters in the webhooks URL. For example, &env=<YOUR_ENV>&service=<YOUR_SERVICE_NAME>.

Set custom tags

To set custom tags to all the pipeline and job spans generated by the integration, add a URL-encoded query parameter tags with key:value pairs separated by commas to the URL.

If a key:value pair contains any commas, surround it with quotes. For example, to add key1:value1,"key2: value with , comma",key3:value3, the following string would need to be appended to the Webhook URL: ?tags=key1%3Avalue1%2C%22key2%3A+value+with+%2C+comma%22%2Ckey3%3Avalue3.

Fill in the integration configuration settings:

Active: Enables the integration.
Datadog site: Specifies which Datadog site to send data to.
Default: datadoghq.com
Selected site:
API URL (optional): Allows overriding the API URL used for sending data directly, only used in advanced scenarios.
Default: (empty, no override)
API key: Specifies which Datadog API key to use when sending data.
Service (optional): Specifies which service name to attach to each span generated by the integration. Use this to differentiate between GitLab instances.
Default: gitlab-ci
Env (optional): Specifies which environment (env tag) to attach to each span generated by the integration. Use this to differentiate between groups of GitLab instances (for example, staging or production).
Default: none
Tags (optional): Specifies any custom tags to attach to each span generated by the integration. Provide one tag per line in the format: key:value.
Default: (empty, no additional tags)
Note: Available only in GitLab.com and GitLab >= 14.8 self-hosted.

You can test the integration with the Test settings button (only available when configuring the integration on a project). After it’s successful, click Save changes to finish the integration set up. If the button fails, click Save changes and check that the first webhooks sent are successful by looking at the history in the “Recent events” section below.

Advanced configuration

Set custom tags

You can set custom tags for all pipeline and job spans from your GitLab projects to improve traceability. For more information, see Custom Tags and Measures.

Integrate with Datadog Teams

To display and filter the teams associated with your pipelines, add team:<your-team> as a custom tag. The custom tag name must match your Datadog Teams team handle exactly.

Correlate infrastructure metrics to jobs

If you are using self-hosted GitLab runners, you can correlate jobs with the infrastructure that is running them.

Datadog infrastructure correlation is possible using different methods:

Tagging runners with hostname

The GitLab runner must have a tag of the form host:<hostname>. Tags can be added while registering a new runner. As a result, this method is only available when the runner is directly running the job.

This excludes executors that are autoscaling the infrastructure in order to run the job (such as the Kubernetes, Docker Autoscaler, or Instance executors) as it is not possible to add tags dynamically for those runners.

For existing runners:

Add tags through the UI by going to Settings > CI/CD > Runners and editing the appropriate runner.

Add tags by updating the runner’s config.toml. Or add tags through the UI by going to Settings > CI/CD > Runners and editing the appropriate runner.

After these steps, CI Visibility adds the hostname to each job. To see the metrics, click on a job span in the trace view. In the drawer, a new tab named Infrastructure appears which contains the host metrics.

Instance and Docker Autoscaler executors

CI Visibility also supports Infrastructure metrics for “Instance” and “Docker Autoscaler” executors. For more information, see the Correlate Infrastructure Metrics with GitLab Jobs guide.

Other executors

CI Visibility does not support Infrastructure metrics for other executors such as the Kubernetes executor.

View error messages for pipeline failures

Error messages are supported for GitLab versions 15.2.0 and above.

For failed GitLab pipeline executions, each error under the Errors tab within a specific pipeline execution displays a message associated with the error type from GitLab.

The following table describes the message and domain correlated with each error type. Any unlisted error type results in a Job failed error message and an unknown error domain.

Error Type	Error Domain	Error Message
`unknown_failure`	unknown	Failed due to unknown reason.
`config_error`	user	Failed due to error on CI/CD configuration file.
`external_validation_failure`	unknown	Failed due to external pipeline validation.
`user_not_verified`	user	The pipeline failed due to the user not being verified.
`activity_limit_exceeded`	provider	The pipeline activity limit was exceeded.
`size_limit_exceeded`	provider	The pipeline size limit was exceeded.
`job_activity_limit_exceeded`	provider	The pipeline job activity limit was exceeded.
`deployments_limit_exceeded`	provider	The pipeline deployments limit was exceeded.
`project_deleted`	provider	The project associated with this pipeline was deleted.
`api_failure`	provider	API failure.
`stuck_or_timeout_failure`	unknown	Pipeline is stuck or timed out.
`runner_system_failure`	provider	Failed due to runner system failure.
`missing_dependency_failure`	unknown	Failed due to missing dependency.
`runner_unsupported`	provider	Failed due to unsupported runner.
`stale_schedule`	provider	Failed due to stale schedule.
`job_execution_timeout`	unknown	Failed due to job timeout.
`archived_failure`	provider	Archived failure.
`unmet_prerequisites`	unknown	Failed due to unmet prerequisite.
`scheduler_failure`	provider	Failed due to schedule failure.
`data_integrity_failure`	provider	Failed due to data integrity.
`forward_deployment_failure`	unknown	Deployment failure.
`user_blocked`	user	Blocked by user.
`ci_quota_exceeded`	provider	CI quota exceeded.
`pipeline_loop_detected`	user	Pipeline loop detected.
`builds_disabled`	user	Build disabled.
`deployment_rejected`	user	Deployment rejected.
`protected_environment_failure`	provider	Environment failure.
`secrets_provider_not_found`	user	Secret provider not found.
`reached_max_descendant_pipelines_depth`	user	Reached max descendant pipelines.
`ip_restriction_failure`	provider	IP restriction failure.

Collect job logs

The following GitLab versions support collecting job logs:

GitLab.com (SaaS)
GitLab >= 15.3 (self-hosted) only if you are using object storage to store job logs
GitLab >= 14.8 (self-hosted) by enabling the datadog_integration_logs_collection feature flag

Job logs are collected in Log Management and are automatically correlated with the GitLab pipeline in CI Visibility. Log files larger than one GiB are truncated.

To enable collection of job logs:

Click the Enable job logs collection checkbox in the GitLab integration Settings > Integrations > Datadog.
Click Save changes.

Datadog downloads log files directly from your GitLab logs object storage with temporary pre-signed URLs. This means that for Datadog servers to access the storage, the storage must not have network restrictions The endpoint, if set, should resolve to a publicly accessible URL.

Click Enable job logs collection checkbox in the GitLab integration under Settings > Integrations > Datadog.
Click Save changes.

Enable the datadog_integration_logs_collection feature flag in your GitLab. This allows you to see the Enable job logs collection checkbox in the GitLab integration under Settings > Integrations > Datadog.
Click Enable job logs collection.
Click Save changes.

Logs are billed separately from CI Visibility. Log retention, exclusion, and indexes are configured in Log Management. Logs for GitLab jobs can be identified by the datadog.product:cipipeline and source:gitlab tags.

For more information about processing job logs collected from the GitLab integration, see the Processors documentation.

View partial and downstream pipelines

You can use the following filters to customize your search query in the CI Visibility Explorer.

The Pipeline executions page with Partial Pipeline:retry entered in the search query

Facet Name	Facet ID	Possible Values
Downstream Pipeline	`@ci.pipeline.downstream`	`true`, `false`
Manually Triggered	`@ci.is_manual`	`true`, `false`
Partial Pipeline	`@ci.partial_pipeline`	`retry`, `paused`, `resumed`