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Package that enables deployment of AWS CDK stacks in parallel.

Project description

B.AwsCdkParallel

A python based package that enables AWS CDK parallel stack deployments.

Description

One of the biggest downsides of AWS CDK IaC tool is the sequential deployments. If you have many stacks within your project - it can take hours and hours till everything gets deployed. Wouldn't it be cool to parallelize them? According to AWS CDK tool maintainers - they are not even thinking right now to include such functionality. Hence, this project was built. This project allows you to run traditional cdk deploy * and cdk destroy * -f. But the main trick is that it can do it in parallel - massively increasing the speed of your deployments.

Remarks

Biomapas aims to modernise life-science industry by sharing its IT knowledge with other companies and the community. This is an open source library intended to be used by anyone. Improvements and pull requests are welcome.

Related technology

  • Python 3
  • AWS CDK
  • AWS CloudFormation

Assumptions

The project assumes the following:

  • You have basic-good knowledge in python programming.
  • You have basic-good knowledge in AWS.
  • You have very good knowledge in AWS CDK.

Useful sources

Install

The project is built and uploaded to PyPi. Install it by using pip.

pip install b_aws_cdk_parallel

Or directly install it through source.

pip install .

Usage & Examples

from parallel.deployment_executor import DeploymentExecutor
from parallel.deployment_type import DeploymentType

if __name__ == '__main__':
    executor = DeploymentExecutor(deployment_type=DeploymentType.DEPLOY)
    executor.run()

Testing

This project currently has no tests.

Contribution

Found a bug? Want to add or suggest a new feature?
Contributions of any kind are gladly welcome. You may contact us directly, create a pull-request or an issue in github platform. Lets modernize the world together.

Release history

0.3.0

  • Add ability to specify CDK path and environment variables for processes.

0.2.0

  • Add ability to retry main deployment too.

0.1.0

  • Refactor project to make it more debug-friendly.

0.0.2

  • Upgrade dependencies.

0.0.1

  • Initial build.

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