How Amazon SageMaker Processing Runs Your Processing Container Image - Amazon SageMaker AI
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

How Amazon SageMaker Processing Runs Your Processing Container Image

Amazon SageMaker Processing runs your processing container image in a similar way as the following command, where AppSpecification.ImageUri is the Amazon ECR image URI that you specify in a CreateProcessingJob operation. 

docker run [AppSpecification.ImageUri]

This command runs the ENTRYPOINT command configured in your Docker image.

You can also override the entrypoint command in the image or give command-line arguments to your entrypoint command using the AppSpecification.ContainerEntrypoint and AppSpecification.ContainerArgument parameters in your CreateProcessingJob request. Specifying these parameters configures Amazon SageMaker Processing to run the container similar to the way that the following command does. 

 docker run --entry-point [AppSpecification.ContainerEntrypoint] [AppSpecification.ImageUri] [AppSpecification.ContainerArguments]

For example, if you specify the ContainerEntrypoint to be [python3, -v, /processing_script.py] in your CreateProcessingJob request, and ContainerArguments to be [data-format, csv], Amazon SageMaker Processing runs your container with the following command. 

 python3 -v /processing_script.py data-format csv

When building your processing container, consider the following details:

  • Amazon SageMaker Processing decides whether the job completes or fails depending on the exit code of the command run. A processing job completes if all of the processing containers exit successfully with an exit code of 0, and fails if any of the containers exits with a non-zero exit code.

  • Amazon SageMaker Processing lets you override the processing container's entrypoint and set command-line arguments just like you can with the Docker API. Docker images can also configure the entrypoint and command-line arguments using the ENTRYPOINT and CMD instructions. The way CreateProcessingJob's ContainerEntrypoint and ContainerArgument parameters configure a Docker image's entrypoint and arguments mirrors how Docker overrides the entrypoint and arguments through the Docker API:

    • If neither ContainerEntrypoint nor ContainerArguments are provided, Processing uses the default ENTRYPOINT or CMD in the image.

    • If ContainerEntrypoint is provided, but not ContainerArguments, Processing runs the image with the given entrypoint, and ignores the ENTRYPOINT and CMD in the image.

    • If ContainerArguments is provided, but not ContainerEntrypoint, Processing runs the image with the default ENTRYPOINT in the image and with the provided arguments.

    • If both ContainerEntrypoint and ContainerArguments are provided, Processing runs the image with the given entrypoint and arguments, and ignores the ENTRYPOINT and CMD in the image.

  • You must use the exec form of the ENTRYPOINT instruction in your Dockerfile (ENTRYPOINT ["executable", "param1", "param2"]) instead of the shell form (ENTRYPOINT command param1 param2). This lets your processing container receive SIGINT and SIGKILL signals, which Processing uses to stop processing jobs with the StopProcessingJob API.

  • /opt/ml and all its subdirectories are reserved by SageMaker AI. When building your Processing Docker image, don't place any data required by your processing container in these directories.

  • If you plan to use GPU devices, make sure that your containers are nvidia-docker compatible. Include only the CUDA toolkit in containers. Don't bundle NVIDIA drivers with the image. For more information about nvidia-docker, see NVIDIA/nvidia-docker.