Using AWS CDK Pipelines and AWS Lambda for multi-branch pipeline management and infrastructure deployment.

This project shows how to use the AWS CDK Pipelines module to follow a Gitflow development model using AWS CDK. Software development teams often follow a strict branching strategy during the development lifecycle of a solution. It is common for newly created branches to need their own isolated copy of infrastructure resources in order to develop new features.

CDK Pipelines is a construct library module for painless continuous delivery of AWS CDK applications. CDK Pipelines are self-updating: if you add application stages or stacks, the pipeline automatically reconfigures itself to deploy those new stages and/or stacks.

The following solution creates a new AWS CDK Pipeline within a development account for every new branch created in the source repository (AWS CodeCommit). When a branch is deleted, the pipeline and all related resources are destroyed from the account as well. This GitFlow model for infrastructure provisioning allows developers to work independently from each other, concurrently, even in the same stack of the application.

Overview of the solution

Prerequisites

Before setting up this project, you should have the following prerequisites:

• An AWS account
• AWS CDK installed
• Python3 installed

Initial setup

Create a new AWS CodeCommit repository in the AWS Account and region where you want to deploy the pipeline and upload the source code from this repository. In the config.ini file, change the repository_name and region variables accordingly.

Make sure to set up a fresh python environment. Install the dependencies:

pip install -r requirements.txt

Run the initial-deploy.sh script to bootstrap the development and production environments and to deploy the default pipeline. You’ll be asked to provide the following parameters: (1) Development account ID, (2) Development account AWS profile name (3) Production account ID, (4) Production account AWS profile name.

sh ./initial-deploy.sh --dev_account_id <YOUR DEV ACCOUNT ID> -- dev_profile_name <YOUR DEV PROFILE NAME> --prod_account_id <YOUR PRODUCTION ACCOUNT ID> --prod_profile_name <YOUR PRODUCTION PROFILE NAME>

How to use

Lambda S3 trigger project from AWS CDK Samples is used as infrastructure resources to demonstrate this solution. The content is placed inside the src directory and is deployed by the pipeline. Replace the content of this repository with your infrastructure code. Use CDK Constructs to combine your infrastructure code into one stack and reference this in the application stage inside src/application_stage.py.

Create a feature branch

On your machine’s local copy of the repository, create a new feature branch using the git commands below. Replace user-feature-123 with a unique name for your feature branch. Note: this feature branch name must comply with the AWS CodePipeline naming restrictions for it will be used to name a unique pipeline later in this walkthrough.

# Create the feature branch
git checkout -b user-feature-123
git push origin user-feature-123

The first AWS Lambda function will deploy the CodeBuild project which then deployes the feature pipeline. This can take a few minutes. You can log into the AWS Console and see the CodeBuild project running under AWS CodeBuild. After the build is successfully finished, you can see the deployed feature pipeline under AWS CodePipelines.

Destroy a feature branch

There are two common ways for removing feature branches. The first one is related to a pull request, also known as a “PR”, which occurs when merging a feature branch back into the default branch. Once it is merged, the feature branch will be automatically closed. The second way is to delete the feature branch explicitly by running the below git commands.

# delete branch local
git branch -d user-feature-123

# delete branch remote
git push origin --delete user-feature-123

Security

See CONTRIBUTING for more information.

License

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