Add STOPPED to the failure cases for Sagemaker Training Jobs #42423
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ferruzzi
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Sep 23, 2024
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Oh, I have so little knowledge about AWS and Sagemaker, feel afraid to judge and approve this thing :-( |
It's a very large ball of wax, that's for sure. I'm not entirely sure why you were auto-added to the reviewers list, I didn't intentionally tag you. |
vincbeck
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User pointed out that Airflow will mark a failed Sagemaker Training Job as a successful task. Looking into the issue, Sagemaker treats "Stopped" as a failure state for this endpoint, not a successful terminal state. [Sagemaker Docs here]
To reproduce:
Run a DAG with a SagemakerTrainingOperator task. Once the training starts, open the AWS console and stop the job. Airflow will see that the job has ended but mark the task as successful.
After this change, those steps will show the task marked as failed as expected.