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conda-env-kernel-image

README.md

Conda Environments as Kernels

Overview

This custom image sample demonstrates how to create a custom Conda environment in a Docker image and use it as a custom kernel in SageMaker Studio.

The Conda environment must have the appropriate kernel package installed, for e.g., ipykernel for a Python kernel. This example creates a Conda environment called myenv with a few Python packages (see environment.yml) and the ipykernel. SageMaker Studio will automatically recognize this Conda environment as a kernel named conda-env-myenv-py (See app-image-config-input.json)

Building the image

Build the Docker image and push to Amazon ECR.

# Modify these as required. The Docker registry endpoint can be tuned based on your current region from https://docs.aws.amazon.com/general/latest/gr/ecr.html#ecr-docker-endpoints
REGION=<aws-region>
ACCOUNT_ID=<aws-account-id>


# Build and push the image
IMAGE_NAME=conda-env-kernel
aws --region ${REGION} ecr get-login-password | docker login --username AWS --password-stdin ${ACCOUNT_ID}.dkr.ecr.${REGION}.amazonaws.com/smstudio-custom
docker build . -t ${IMAGE_NAME} -t ${ACCOUNT_ID}.dkr.ecr.${REGION}.amazonaws.com/smstudio-custom:${IMAGE_NAME}
docker push ${ACCOUNT_ID}.dkr.ecr.${REGION}.amazonaws.com/smstudio-custom:${IMAGE_NAME}

Using with SageMaker Studio

Create a SageMaker Image (SMI) with the image in ECR.

# Role in your account to be used for SMI. Modify as required.

ROLE_ARN=arn:aws:iam::${ACCOUNT_ID}:role/RoleName
aws --region ${REGION} sagemaker create-image \
    --image-name ${IMAGE_NAME} \
    --role-arn ${ROLE_ARN}

aws --region ${REGION} sagemaker create-image-version \
    --image-name ${IMAGE_NAME} \
    --base-image "${ACCOUNT_ID}.dkr.ecr.${REGION}.amazonaws.com/smstudio-custom:${IMAGE_NAME}"

# Verify the image-version is created successfully. Do NOT proceed if image-version is in CREATE_FAILED state or in any other state apart from CREATED.
aws --region ${REGION} sagemaker describe-image-version --image-name ${IMAGE_NAME}

Create a AppImageConfig for this image

aws --region ${REGION} sagemaker create-app-image-config --cli-input-json file://app-image-config-input.json

Create a Domain, providing the SageMaker Image and AppImageConfig in the Domain input. Replace the placeholders for VPC ID, Subnet IDs, and Execution Role in create-domain-input.json

aws --region ${REGION} sagemaker create-domain --cli-input-json file://create-domain-input.json

If you have an existing Domain, you can also use the update-domain

aws --region ${REGION} sagemaker update-domain --cli-input-json file://update-domain-input.json

Create a User Profile, and start a Notebook using the SageMaker Studio launcher.