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job_history_window: int=1,
job_duration_tolerance: int=60
) -> FeatureJobStatusResult


Returns a report on the recent activity of scheduled feature jobs associated with a Deployment object. The report includes recent runs for these jobs, whether they were successful, and the duration of the jobs. This provides a summary of the health of the feature, and whether online features are updated in a timely manner

Failed and late jobs can occur due to various reasons, including insufficient compute capacity. Check your data warehouse logs for more details on the errors. If the errors are due to insufficient compute capacity, you can consider upsizing your instances.


  • job_history_window: int
    default: 1
    History window in hours.

  • job_duration_tolerance: int
    default: 60
    Maximum duration before job is considered later, in seconds.


  • FeatureJobStatusResult


>>> deployment = catalog.get_deployment("feature_deployment")
>>> deployment.get_feature_jobs_status()