Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window. Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.

Configure failure policy

You can use the failure_policy parameter of the aiplatform.PipelineJob class to configure whether a pipeline should fail immediately if one of the task fails.

The following failure policy configurations are supported in Vertex AI Pipelines:

Fail fast( failure_policy = 'fast' ): Choose this configuration if you want the pipeline to stop scheduling new tasks after a task fails. Tasks that are already scheduled continue running until they are completed.
Fail slow( failure_policy = 'slow' ): Choose this configuration if you want the pipeline to continue to run even after a task fails. The pipeline continues to run until all tasks have been executed.

Note: If you don't specify the failure_policy parameter for a pipeline, the failure policy configuration is set to slow , by default.

Use the following code sample to configure the failure policy for a pipeline using the Vertex AI SDK for Python:

 job = aiplatform.PipelineJob(display_name = ' DISPLAY_NAME 
',
                             template_path = ' COMPILED_PIPELINE_PATH 
',
                             pipeline_root = ' PIPELINE_ROOT 
',
                             project = ' PROJECT_ID 
',
                             location = ' LOCATION 
',
                             failure_policy = ' FAILURE_POLICY 
')

Replace the following:

DISPLAY_NAME : The name of the pipeline, this will show up in the Google Cloud console.
COMPILED_PIPELINE_PATH : The path to your compiled pipeline YAML file. It can be a local path or a Google Cloud Storage URI.
PIPELINE_ROOT : Specify a Cloud Storage URI that your pipelines service account can access. The artifacts of your pipeline runs are stored within the pipeline root.
PROJECT_ID : The Google Cloud project that this pipeline runs in.
LOCATION : The region that the pipeline runs in. For more information about the regions that Vertex AI Pipelines is available in, see the Vertex AI locations guide . If you don't set this parameter, the default location set in aiplatform.init is used.
FAILURE_POLICY : Specify the failure policy for the entire pipeline. The following configurations are available:
- To configure the pipeline to fail after one task fails, enter fast .
- To configure the pipeline to continue scheduling tasks after one task fails, enter slow .
If you don't set this parameter, the failure policy configuration is set to slow , by default.