# How Amazon SageMaker Processing Runs Your Processing Container Image
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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](https://github.com/NVIDIA/nvidia-docker).