SageMaker / Client / create_app_image_config

create_app_image_config#

SageMaker.Client.create_app_image_config(**kwargs)#

Creates a configuration for running a SageMaker AI image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.

See also: AWS API Documentation

Request Syntax

response = client.create_app_image_config(
    AppImageConfigName='string',
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ],
    KernelGatewayImageConfig={
        'KernelSpecs': [
            {
                'Name': 'string',
                'DisplayName': 'string'
            },
        ],
        'FileSystemConfig': {
            'MountPath': 'string',
            'DefaultUid': 123,
            'DefaultGid': 123
        }
    },
    JupyterLabAppImageConfig={
        'FileSystemConfig': {
            'MountPath': 'string',
            'DefaultUid': 123,
            'DefaultGid': 123
        },
        'ContainerConfig': {
            'ContainerArguments': [
                'string',
            ],
            'ContainerEntrypoint': [
                'string',
            ],
            'ContainerEnvironmentVariables': {
                'string': 'string'
            }
        }
    },
    CodeEditorAppImageConfig={
        'FileSystemConfig': {
            'MountPath': 'string',
            'DefaultUid': 123,
            'DefaultGid': 123
        },
        'ContainerConfig': {
            'ContainerArguments': [
                'string',
            ],
            'ContainerEntrypoint': [
                'string',
            ],
            'ContainerEnvironmentVariables': {
                'string': 'string'
            }
        }
    }
)
Parameters:

  • AppImageConfigName (string) –

    [REQUIRED]

    The name of the AppImageConfig. Must be unique to your account.

  • Tags (list) –

    A list of tags to apply to the AppImageConfig.

    • (dict) –

      A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

      You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.

      For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.

      • Key (string) – [REQUIRED]

        The tag key. Tag keys must be unique per resource.

      • Value (string) – [REQUIRED]

        The tag value.

  • KernelGatewayImageConfig (dict) –

    The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.

    • KernelSpecs (list) – [REQUIRED]

      The specification of the Jupyter kernels in the image.

      • (dict) –

        The specification of a Jupyter kernel.

        • Name (string) – [REQUIRED]

          The name of the Jupyter kernel in the image. This value is case sensitive.

        • DisplayName (string) –

          The display name of the kernel.

    • FileSystemConfig (dict) –

      The Amazon Elastic File System storage configuration for a SageMaker AI image.

      • MountPath (string) –

        The path within the image to mount the user’s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.

      • DefaultUid (integer) –

        The default POSIX user ID (UID). If not specified, defaults to 1000.

      • DefaultGid (integer) –

        The default POSIX group ID (GID). If not specified, defaults to 100.

  • JupyterLabAppImageConfig (dict) –

    The JupyterLabAppImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in JupyterLab.

    • FileSystemConfig (dict) –

      The Amazon Elastic File System storage configuration for a SageMaker AI image.

      • MountPath (string) –

        The path within the image to mount the user’s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.

      • DefaultUid (integer) –

        The default POSIX user ID (UID). If not specified, defaults to 1000.

      • DefaultGid (integer) –

        The default POSIX group ID (GID). If not specified, defaults to 100.

    • ContainerConfig (dict) –

      The configuration used to run the application image container.

      • ContainerArguments (list) –

        The arguments for the container when you’re running the application.

        • (string) –

      • ContainerEntrypoint (list) –

        The entrypoint used to run the application in the container.

        • (string) –

      • ContainerEnvironmentVariables (dict) –

        The environment variables to set in the container

        • (string) –

          • (string) –

  • CodeEditorAppImageConfig (dict) –

    The CodeEditorAppImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in Code Editor.

    • FileSystemConfig (dict) –

      The Amazon Elastic File System storage configuration for a SageMaker AI image.

      • MountPath (string) –

        The path within the image to mount the user’s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.

      • DefaultUid (integer) –

        The default POSIX user ID (UID). If not specified, defaults to 1000.

      • DefaultGid (integer) –

        The default POSIX group ID (GID). If not specified, defaults to 100.

    • ContainerConfig (dict) –

      The configuration used to run the application image container.

      • ContainerArguments (list) –

        The arguments for the container when you’re running the application.

        • (string) –

      • ContainerEntrypoint (list) –

        The entrypoint used to run the application in the container.

        • (string) –

      • ContainerEnvironmentVariables (dict) –

        The environment variables to set in the container

        • (string) –

          • (string) –

Return type:

dict

Returns:

Response Syntax

{
    'AppImageConfigArn': 'string'
}

Response Structure

  • (dict) –

    • AppImageConfigArn (string) –

      The ARN of the AppImageConfig.

Exceptions