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Azure Pipelines is a continuous integration and delivery service that supports any language, platform, or cloud.
Set up CI Visibility for Azure Pipelines to gain real time insights into your CI/CD workflows, track pipeline performance, analyze inefficiencies, and manage your deployment operations.
| Pipeline Visibility | Platform | Definition |
|---|---|---|
| CI jobs failure analysis | CI jobs failure analysis | Use LLM models on relevant logs to analyze the root cause of failed CI jobs. |
| Logs correlation | Logs correlation | Correlate pipeline and job spans to logs. Requires job log collection. |
| Custom tags and measures at runtime | Custom tags and measures at runtime | Configure custom tags and measures at runtime. |
| Custom spans | Custom spans | Configure custom spans for your pipelines. |
| Filter CI Jobs on the critical path | Filter CI Jobs on the critical path | Filter by jobs on the critical path. |
| Execution time | Execution time | View the amount of time pipelines have been running jobs. |
This table shows the mapping of concepts between Datadog CI Visibility and Azure Pipelines:
| Datadog | Azure Pipelines |
|---|---|
| Pipeline | Pipeline |
| Stage | Stage |
| Job | Job |
| Not available in Datadog | Step |
After the Azure App is created and installed, enable CI Visibility for the organizations and projects you want Datadog to monitor.
Verify that your Azure DevOps organization is linked to a Microsoft Entra tenant. See the Azure source code setup instructions for guidance on connecting Azure DevOps projects to Datadog.
In Datadog, navigate to Software Delivery → CI Visibility → Add a Pipeline Provider → Azure Pipelines.
Click Configure next to the Azure DevOps organization you want to enable.
To enable CI Visibility for the entire organization, toggle Enable CI Visibility. Future projects detected by the Azure app will automatically be enabled.
To enable CI Visibility for individual projects:
Pipelines appear in Datadog immediately after CI Visibility is enabled for an organization or project.
The Datadog integration for Azure Pipelines works by using service hooks to send data to Datadog.
Install the Datadog CI Visibility extension from the Azure Marketplace. There are several extensions starting with Datadog, make sure that you are installing the Datadog CI Visibility extension.
For each project, go to Project settings > Service hooks in Azure DevOps and select the green plus (+) icon to create a subscription.
Create a subscription to the Datadog CI Visibility service for each of the following webhook types. These event types are required and must be enabled individually.
Click Next to continue to the next step and set the following:
<span class="js-region-param region-param" data-region-param="dd_site"></span>Click Finish.
Datadog offers a script to help you enable service hooks across multiple or all of your Azure projects using the Azure API. The script requires Python 3 and the requests package.
To run the script, you need:
The script supports environment variables DD_API_KEY and DD_SITE, and flags parameters --dd-api-key and --dd-site.
For more information, you can run the following command:
./service_hooks.py --help
Example for enabling the hooks in all projects:
./service_hooks.py \
--dd-api-key ******************** \
--az-user "John Doe" \
--az-token ********************** \
--az-org datadoghq \
--threads 4
Example for enabling the hooks in specified projects:
./service_hooks.py \
--dd-api-key ******************** \
--az-user "John Doe" \
--az-token ********************** \
--az-org datadoghq \
projectName1 projectName2
You can set custom tags for all pipeline and job spans from your Azure projects to improve traceability. For more information, see Custom Tags and Measures.
To enable log collection for Azure DevOps pipelines:
Set up the Datadog Azure DevOps integration by following the steps in the Azure integration tile.
In Datadog, open CI/CD Optimization > Settings > Azure DevOps.
Enable log pulling for Azure DevOps.
Logs are billed separately from CI Visibility. Log retention, exclusion, and indexes are configured in Log Management. Logs for Azure jobs can be identified by the datadog.product:cipipeline and source:azurepipelines tags.
If job logs collection is enabled, CI Visibility uses LLM models to compute the analysis for failed CI jobs based on relevant logs coming from Azure Pipelines.
You can also add job failure analysis to a PR comment. See the guide on using PR comments.
For a full explanation, see the guide on using CI jobs failure analysis.
The CI Pipeline List and Executions pages populate with data after the workflows finish.
The CI Pipeline List page shows data for only the default branch of each repository. For more information, see Search and Manage CI Pipelines.
Additional helpful documentation, links, and articles:
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