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Build and automatize the management of your Sagemaker Studio Users using AWS CDK!

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Build and automatize the management of your Sagemaker Studio Users using AWS CDK!

You should explore the contents of this project. It demonstrates a CDK app with an instance of a stack (sagemakerStudioCDK)

How it Works

This project uses a simple structure for sources, tooling and testing. Just execute make to see what you can do.

How to start

You will need to have Python 3.8 installed. After this you just need to call

$ make install

The initialization process also creates a virtualenv within this project, stored under the venv directory. It will also install AWS cdk command by calling npm install -g aws-cdk.

Python

It is tested with Python 3.8.x. You can use make .venv to create Python environment for this project.

To add additional dependencies, for example other CDK libraries, just add them to your setup.py file and rerun the make install command.

PyTest

Project uses PyTest for a simple testing approach. For reference visit: https://docs.pytest.org/en/latest/index.html

AWS CDK

At this point you can now synthesize the CloudFormation template for this code.

cdk synth

After this, use deploy command to deploy CloudFormation stack.

cdk deploy

Review the resources that AWS CDK creates for you in your AWS account and choose yes to deploy the stack.

Diagram

Wait for your stack to be deployed by checking the status on the AWS CloudFormation console.

Enjoy!

Useful commands

  • cdk ls list all stacks in the app
  • cdk synth emits the synthesized CloudFormation template
  • cdk deploy deploy this stack to your default AWS account/region
  • cdk diff compare deployed stack with current state
  • cdk docs open CDK documentation

Cleanup

Follow this step to remove the resources that were deployed in this post.

cdk destroy

When asked to confirm the deletion of the four stacks, select “y”.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

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  • Python 83.9%
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