ferruzzi opened a new pull request, #42423: URL: https://github.com/apache/airflow/pull/42423
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](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/describe_training_job.html)] 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. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
