Integrate SOCI-indexed images with Studio example - Amazon SageMaker AI
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Integrate SOCI-indexed images with Studio example

You must reference the SOCI-indexed image tag to use SOCI-indexed images in Studio, rather than the original container image tag. Use the tag you specified during the SOCI conversion process (e.g., SOCI_IMAGE_TAG in the Create SOCI indexes with nerdctl and SOCI CLI example).

Integrate SOCI-indexed images example

  1. First set your variables for the Amazon CLI commands that follow. The following is an example of setting up your variables.

    ACCOUNT_ID="111122223333"
REGION="us-east-1"
IMAGE_NAME="sagemaker-image-name"
IMAGE_CONFIG_NAME="sagemaker-image-config-name"
ROLE_ARN="your-role-arn"
DOMAIN_ID="domain-id"
SOCI_IMAGE_TAG="soci-indexed-image-tag"

    Variable definitions:

    • ACCOUNT_ID is your Amazon Web Services account ID

    • REGION is the Amazon Web Services Region of your Amazon ECR private registry

    • IMAGE_NAME is the name of your SageMaker image

    • IMAGE_CONFIG_NAME is the name of your SageMaker image configuration

    • ROLE_ARN is the ARN of your execution role with the permissions listed in Required IAM permissions

    • DOMAIN_ID is the domain ID

      Note

      If you are attaching the image to a SageMaker Unified Studio project and you need clarification on which domain to use, see View the SageMaker AI domain details associated with your project.

    • SOCI_IMAGE_TAG is the tag of your SOCI-indexed image

  2. Export your region:

    export AWS_REGION=$REGION

  3. Create a SageMaker image:

    aws sagemaker create-image \
    --image-name "$IMAGE_NAME" \
    --role-arn "$ROLE_ARN"

  4. Create a SageMaker Image Version using your SOCI index URI:

    IMAGE_INDEX_URI="$ACCOUNT_ID.dkr.ecr.$REGION.amazonaws.com/$IMAGE_NAME:$SOCI_IMAGE_TAG"

aws sagemaker create-image-version \
    --image-name "$IMAGE_NAME" \
    --base-image "$IMAGE_INDEX_URI"

  5. Create an application image configuration and update your Amazon SageMaker AI domain to include the custom image for your app. You can do this for Code Editor, based on Code-OSS, Visual Studio Code - Open Source (Code Editor) and JupyterLab applications. Choose the application option below to view the steps.

    Code Editor

    Create an application image configuration for Code Editor:

    aws sagemaker create-app-image-config \
    --app-image-config-name "$IMAGE_CONFIG_NAME" \
    --code-editor-app-image-config '{ "FileSystemConfig": { "MountPath": "/home/sagemaker-user", "DefaultUid": 1000, "DefaultGid": 100 } }'

    Update your Amazon SageMaker AI domain to include the custom image for Code Editor:

    aws sagemaker update-domain \
    --domain-id "$DOMAIN_ID" \
    --default-user-settings '{
        "CodeEditorAppSettings": {
        "CustomImages": [{
            "ImageName": "$IMAGE_NAME", 
            "AppImageConfigName": "$IMAGE_CONFIG_NAME"
        }]
    }
}'
    JupyterLab

    Create an application image configuration for JupyterLab:

    aws sagemaker create-app-image-config \
    --app-image-config-name "$IMAGE_CONFIG_NAME" \
    --jupyter-lab-app-image-config '{ "FileSystemConfig": { "MountPath": "/home/sagemaker-user", "DefaultUid": 1000, "DefaultGid": 100 } }'

    Update your Amazon SageMaker AI domain to include the custom image for JupyterLab:

    aws sagemaker update-domain \
    --domain-id "$DOMAIN_ID" \
    --default-user-settings '{
        "JupyterLabAppSettings": {
        "CustomImages": [{
            "ImageName": "$IMAGE_NAME", 
            "AppImageConfigName": "$IMAGE_CONFIG_NAME"
        }]
    }
}'

  6. After you update your domain to include your custom image, you can create an application in Studio using your custom image. When you Launch a custom image in Studio ensure that you are using your custom image.