View pipeline job logs

After you define, build, and run a pipeline, you can view and query log entries for your pipeline job and pipeline tasks. Learn more about log entries for the Vertex AI API.

This feature has costs associated with it. Learn more about Cloud Logging pricing.

View Vertex AI logs for pipeline jobs

Use the following instructions to view logs for your Vertex AI Pipelines jobs in the Google Cloud console or the Google Cloud CLI.

Console

1. Enable the Cloud Logging API:

   Enable the API

2. In the Google Cloud console, go to the Logs Explorer:

   Go to the Logs Explorer

3. Select an existing Vertex AI project at the top of the page.

4. In the Query builder, add the following:

   • Resource: Select Vertex Pipelines Job. In the dialog, select a Vertex AI Pipelines job.
   • Log names: In the Vertex AI section, select aiplatform.googlapis.com/pipeline_job_events.
   • Severity: Select a log level.
   • Time range: Select a preset range or create a custom range.

gcloud

1. Run the following command to enable the Cloud Logging API:

   gcloud services enable logging.googleapis.com
   

2. Execute the gcloud logging read command:

   Linux, macOS, or Cloud Shell

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_events" \
       --limit=LIMIT

   Windows (PowerShell)

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_events" `
       --limit=LIMIT

   Windows (cmd.exe)

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_events" ^
       --limit=LIMIT

    

View Vertex AI logs for pipeline tasks

Use the following instructions to view logs for your Vertex AI Pipelines tasks in the Google Cloud console or the Google Cloud CLI.

Console

1. Enable the Cloud Logging API:

   Enable the API

2. In the Google Cloud console, go to the Logs Explorer:

   Go to the Logs Explorer

3. Select an existing Vertex AI project at the top of the page.

4. In the Query builder, add the following:

   • Resource: Select Vertex Pipelines Job. In the dialog, select a Vertex AI Pipelines job.
   • Log names: In the Vertex AI section, select aiplatform.googlapis.com/pipeline_job_task_events.
   • Severity: Select a log level.
   • Time range: Select a preset range or create a custom range.

gcloud

1. Run the following command to enable the Cloud Logging API:

   gcloud services enable logging.googleapis.com
   

2. Execute the gcloud logging read command:

   Linux, macOS, or Cloud Shell

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_task_events" \
       --limit=LIMIT

   Windows (PowerShell)

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_task_events" `
       --limit=LIMIT

   Windows (cmd.exe)

   Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.

   gcloud logging read "projects/PROJECT_ID/logs/aiplatform.googleapis.com/pipeline_job_task_events" ^
       --limit=LIMIT

    

What's next

• Learn how to view pipeline metrics.

• Learn how to create custom metrics in the Logs Explorer to monitor the pipeline job failure rate.

• Learn how to configure email notifications.