SageMaker Studio deployment using CDK

This repo contains an example of how to deploy SageMaker Studio using CDK. The project deploys code through a CICD pipeline using CodeCommit, CodeBuild and CodePipelines and gives the abiloity to deploy to prod and to a sandbox environment for testing. Features of the deployment

Deploys SageMaker Studio with IAM or SSO support
Deploys a lifecycle policy that will terminate compute after 60 minutes of being idle
Enabled AWS Glue support through Role permissions

Test examples have been provided under the tests folder and will be executed by the deployment pipelines. THe project also runs tests for black, bandit, radon, xenon and coverage.

Isolated Deployment (No Internet)

It's possible to deploy the solution and configure SageMaker Studio with no internet access. for this deployment type set the "USE_S3_FOR_ASSETS" variable to True and the "SUBNET_DEPLOYMENT_TYPE" to private or private-isolated, depending on your subnet type. This will use an s3 deployed version of auto shutdown script. Some points to consider with this deployment method

To access other AWS services, ensure you have the correct VPC Endpoints in place. A listing can be found here for SageMaker required endpoints. https://docs.aws.amazon.com/sagemaker/latest/dg/studio-notebooks-and-internet-access.html#studio-notebooks-and-internet-access-vpc
To access Pip you can use CodeArtifact to setup a pass through repository.

Dependencies

Production Dependencies

Python 3.7 or above
CDK 2.6

Development Dependencies

bandit - will check for common security issues in Python (https://bandit.readthedocs.io/en/latest/)
black - Code must conform to the black standard. A test will run to ensure it does and if not will fail the deployment. You can install black globally using pipx and then run black . on the repository before you commit. (https://github.com/psf/black)
radon - Provides code metrics (https://radon.readthedocs.io/en/latest/)
xenon - Monitors code complexity (https://xenon.readthedocs.io/en/latest/)
coverage - Provides code coverage for unit tests (https://github.com/nedbat/coveragepy)

Setup and Install

When deploying the solution it will create a code commit repository in your AWS account and start a pipeline deployment. Once you have deployed you can switch from the GitHub repository to your CodeCommit repository.

Clone the repo git clone {GITREPO HERE ONCE CREATED}
Update constants.py with the details of your environment. You must update the items marked as "must update", any other elements you can leave as default. (See table at the end)
Create a virtual environment for Python and install dependencies

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -r requirements.txt

to run tests you will also need to run

pip install -r requirements-dev.txt

Run cdk deploy sagemaker-studio-deployment-toolchain to deploy the CICD components and create the CodeCommit repository
hit yes to deploy. This operation only needs to be performed when you want to deploy the CICD pipelines, or if you want to update them. The deployment of SageMaker studio will be deployed by the CICD pipeline.
Record the output of the repote codecommit endpoint.
You now need to commit the code to your new repository
Disconnect from the GitHub repo and reconnect to CodeCommit

git remote remove origin
git init --initial-branch=main
git remote add origin codecommit::ap-southeast-2://{YOUR_REPO_NAME_HERE}

To confirm the orgin has updated run git remote get-url --all origin

Before the pipeline will run successfully you need to run a cdk synth to generate the cdk.context.json file and check that into source control.

cdk synth

confirm you now have a file in the repository called 'cdk.context.json'. This file contains the details of your VPC's for deployment
Now you can commit your code to the repository.

git add .
git commit -m "initial commit"
git push --set-upstream origin main

go to the aws console, navigate to

Reference

The project uses the following guidelines to structure the repository https://aws.amazon.com/blogs/developer/recommended-aws-cdk-project-structure-for-python-applications/

The project uses the excellent auto-shutdown script from https://github.com/aws-samples/sagemaker-studio-auto-shutdown-extension

Deployment

Clone the repo
run the initialise command which will deploy the repo into your codeocmmmit account cdk deploy sagemaker-studio-deployment-toolchain

git init --initial-branch=main

git remote add origin codecommit::ap-southeast-2://sagemaker-studio-jbash-config-repo
git add .
git commit
git push --set-upstream origin main

Variables