Send Custom Pipelines to Datadog

Docs > Continuous Integration Visibility > Datadog の CI Pipeline Visibility > Send Custom Pipelines to Datadog

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Overview

You can send custom pipelines through HTTP using the public API endpoint. For more information about how pipeline executions are modeled, see Pipeline Data Model and Execution Types.

Compatibility

Pipeline Visibility	Platform	Definition
Running pipelines	Running pipelines	View pipeline executions that are running.
Custom tags and measures at runtime	Custom tags and measures at runtime	Configure custom tags and measures at runtime.
Manual steps	Manual steps	View manually triggered pipelines.
Parameters	Parameters	Set custom parameters when a pipeline is triggered.
Partial retries	Partial pipelines	View partially retried pipeline executions.
Pipeline failure reasons	Pipeline failure reasons	Identify pipeline failure reasons from error messages.
Queue time	Queue time	View the amount of time pipeline jobs sit in the queue before processing.

Configure CI Visibility

To send pipeline events programmatically to Datadog, ensure that your DD_API_KEY is configured.

Set the headers of your HTTP request:
- DD-API-KEY: Your Datadog API key.
- Content-Type: application/json.

Prepare the payload body by entering information about the pipeline execution in a cURL command:

Parameter Name	Description	Example Value
Unique ID	The UUID of the pipeline run. The ID has to be unique across retries and pipelines, including partial retries.	`b3262537-a573-44eb-b777-4c0f37912b05`
Name	The name of the pipeline. All pipeline runs for the builds should have the same name.	`Documentation Build`
Git Repository	The Git repository URL that triggered the pipeline.	`https://github.com/Datadog/documentation`
Commit Author	The commit author email that triggered the pipeline.	`contributor@github.com`
Commit SHA	The commit hash that triggered the pipeline.	`cf852e17dea14008ac83036430843a1c`
Status	The final status of the pipeline. Allowed enum values: `success`, `error`, `canceled`, `skipped`, `blocked`, or `running`.	`success`
Partial Retry	Whether or not the pipeline was a partial retry of a previous attempt. This field expects a boolean value (`true` or `false`). A partial retry is one which only runs a subset of the original jobs.	`false`
Start	Time when the pipeline run started (it should not include any queue time). The time format must be RFC3339.	`2024-08-22T11:36:29-07:00`
End	Time when the pipeline run finished. The time format must be RFC3339.	`2024-08-22T14:36:00-07:00`
URL	The URL to look at the pipeline in the CI provider UI.	`http://your-ci-provider.com/pipeline/{pipeline-id}`

For example, this payload sends a CI pipeline event to Datadog:

   curl -X POST "https://api.datadoghq.com/api/v2/ci/pipeline" \
   -H "Content-Type: application/json" \
   -H "DD-API-KEY: <YOUR_API_KEY>" \
   -d @- << EOF
   {
     "data": {
       "attributes": {
         "resource": {
           "level": "pipeline",
           "unique_id": "b3262537-a573-44eb-b777-4c0f37912b05",
           "name": "Documentation Build",
           "git": {
             "repository_url": "https://github.com/Datadog/documentation",
             "author_email": "contributor@github.com",
             "sha": "cf852e17dea14008ac83036430843a1c"
           },
           "status": "success",
           "start": "2024-08-22T11:36:29-07:00",
           "end": "2024-08-22T14:36:00-07:00",
           "partial_retry": false,
           "url": ""
         }
       },
       "type": "cipipeline_resource_request"
     }
   }
   EOF
   

After sending your pipeline event to Datadog, you can integrate additional event types such as stage, job, and step. For more information, see the Send Pipeline Event endpoint.

Running pipelines

Pipeline events sent with the status set to running have the same unique_id as the final pipeline event. Running pipelines can be updated by adding more information while they are still running. A running pipeline consists of the following events:

The initial running pipeline event with the status set to running.
Optionally, N running pipeline events that update the pipeline with more information, with the same unique_id and the status set to running.
The final pipeline event without a running status and the same unique_id.

Note: The most recent value may not always be the one displayed in the UI when a field is updated. For example, if the tag my_tag is set to value1 in the first running pipeline, and then is updated to value2, you may see value1 instead of value2 in the UI. It is recommended to only update running pipelines by adding more fields instead modifying existing ones.