In the post Using Custom Source Actions in AWS CodePipeline for Increased Visibility for Third-Party Source Control, we demonstrated using custom actions in AWS CodePipeline and a worker that periodically polls for jobs and processes further to get the artifact from the Git repository. In this post, we discuss using an event-driven architecture to trigger an AWS CodePipeline pipeline that has a third-party Git repository within the source stage that is part of a custom action.

Instead of using a worker to periodically poll for available jobs across all pipelines, we can define a custom source action on a particular pipeline to trigger an Amazon CloudWatch Events rule when the webhook on CodePipeline receives an event and puts it into an In Progress state. This works exactly like how CodePipeline works with natively supported Git repositories like AWS CodeCommit or GitHub as a source.

Solution architecture

The following diagram shows how you can use an event-driven architecture with a custom source stage that is associated with a third-party Git repository that isn’t supported by CodePipeline natively. For our use case, we use GitLab, but you can use any Git repository that supports Git webhooks.

3rdparty-gitblog-new.jpg

The architecture includes the following steps:

1. A user commits code to a Git repository.

2. The commit invokes a Git webhook.

3. This invokes a CodePipeline webhook.

4. The CodePipeline source stage is put into In Progress status.

5. The source stage action triggers a CloudWatch Events rule that indicates the stage started.

6. The CloudWatch event triggers an AWS Lambda function.

7. The function polls for the job details of the custom action.

8. The function also triggers AWS CodeBuild and passes all the job-related information.

9. CodeBuild gets the public SSH key stored in AWS Secrets Manager (or user name and password, if using HTTPS Git access).

10. CodeBuild clones the repository for a particular branch.

11. CodeBuild zips and uploads the archive to the CodePipeline artifact store Amazon Simple Storage Service (Amazon S3) bucket.

12. A Lambda function sends a success message to the CodePipeline source stage so it can proceed to the next stage.

Similarly, with the same setup, if you chose a release change for the pipeline that has custom source stage, a CloudWatch event is triggered, which triggers a Lambda function, and the same process repeats until it gets the artifact from the Git repository.

Solution overview

To set up the solution, you complete the following steps:

1. Create an SSH key pair for authenticating to the Git repository.

2. Publish the key to Secrets Manager.

3. Launch the AWS CloudFormation stack to provision resources.

4. Deploy a sample CodePipeline and test the custom action type.

5. Retrieve the webhook URL.

6. Create a webhook and add the webhook URL.

Creating an SSH key pair
You first create an SSH key pair to use for authenticating to the Git repository using ssh-keygen on your terminal. See the following code:

ssh-keygen -t rsa -b 4096 -C "[email protected]"

Follow the prompt from ssh-keygen and give a name for the key, for example codepipeline_git_rsa. This creates two new files in the current directory: codepipeline_git_rsa and codepipeline_git_rsa.pub.

Make a note of the contents of codepipeline_git_rsa.pub and add it as an authorized key for your Git user. For instructions, see Adding an SSH key to your GitLab account.

Publishing the key
Publish this key to Secrets Manager using the AWS Command Line Interface (AWS CLI):

export SecretsManagerArn=$(aws secretsmanager create-secret --name codepipeline_git \
--secret-string file://codepipeline_git_rsa --query ARN --output text)

Make a note of the ARN, which is required later.

Alternative, you can create a secret on the Secrets Manager console.

Make sure that the lines in the private key codepipeline_git are the same when the value to the secret is added.

Launching the CloudFormation stack

Clone the git repository aws-codepipeline-third-party-git-repositories that contains the AWS CloudFormation templates and AWS Lambda function code using the below command:

git clone https://github.com/aws-samples/aws-codepipeline-third-party-git-repositories.git .

Now you should have the below files in the cloned repository

cfn/
|--sample_pipeline_custom.yaml
`--third_party_git_custom_action.yaml
lambda/
`--lambda_function.py

Launch the CloudFormation stack using the template third_party_git_custom_action.yaml from the cfn directory. The main resources created by this stack are:

1. CodePipeline Custom Action Type. ResourceType: AWS::CodePipeline::CustomActionType
2. Lambda Function. ResourceType: AWS::Lambda::Function
3. CodeBuild Project. ResourceType: AWS::CodeBuild::Project
4. Lambda Execution Role. ResourceType: AWS::IAM::Role
5. CodeBuild Service Role. ResourceType: AWS::IAM::Role

These resources help uplift the logic for connecting to the Git repository, which for this post is GitLab.

Upload the Lambda function code to any S3 bucket in the same Region where the stack is being deployed. To create a new S3 bucket, use the following code (make sure to provide a unique name):

export ACCOUNT_ID=$(aws sts get-caller-identity --query Account --output text)
export S3_BUCKET_NAME=codepipeline-git-custom-action-${ACCOUNT_ID} aws s3 mb s3://${S3_BUCKET_NAME} --region us-east-1

Then zip the contents of the function and upload to the S3 bucket (substitute the appropriate bucket name):

export ZIP_FILE_NAME="codepipeline_git.zip"
zip -jr ${ZIP_FILE_NAME} ./lambda/lambda_function.py && \
aws s3 cp codepipeline_git.zip \
s3://${S3_BUCKET_NAME}/${ZIP_FILE_NAME}

If you don’t have a VPC and subnets that Lambda and CodeBuild require, you can create those by launching the following CloudFormation stack.

Run the following AWS CLI command to deploy the third-party Git source solution stack:

export vpcId="vpc-123456789"
export subnetId1="subnet-12345"
export subnetId2="subnet-54321"
export GIT_SOURCE_STACK_NAME="thirdparty-codepipeline-git-source"
aws cloudformation create-stack \
--stack-name ${GIT_SOURCE_STACK_NAME} \
--template-body file://$(pwd)/cfn/third_party_git_custom_action.yaml \
--parameters ParameterKey=SourceActionVersion,ParameterValue=1 \
ParameterKey=SourceActionProvider,ParameterValue=CustomSourceForGit \
ParameterKey=GitPullLambdaSubnet,ParameterValue=${subnetId1}\\,${subnetId2} \
ParameterKey=GitPullLambdaVpc,ParameterValue=${vpcId} \
ParameterKey=LambdaCodeS3Bucket,ParameterValue=${S3_BUCKET_NAME} \
ParameterKey=LambdaCodeS3Key,ParameterValue=${ZIP_FILE_NAME} \
--capabilities CAPABILITY_IAM

Alternatively, launch the stack by choosing Launch Stack:

cloudformation-launch-stack.png

For more information about the VPC requirements for Lambda and CodeBuild, see Internet and service access for VPC-connected functions and Use AWS CodeBuild with Amazon Virtual Private Cloud, respectively.

A custom source action type is now available on the account where you deployed the stack. You can check this on the CodePipeline console by attempting to create a new pipeline. You can see your source type listed under Source provider.

codepipeline-source-stage-dropdown.png

Testing the pipeline

We now deploy a sample pipeline and test the custom action type using the template sample_pipeline_custom.yaml from the cfn directory . You can run the following AWS CLI command to deploy the CloudFormation stack:

Note: Please provide the GitLab repository url to SSH_URL environment variable that you have access to or create a new GitLab project and repository. The example url "[email protected]:kirankumar15/test.git" is for illustration purposes only.

export SSH_URL="[email protected]:kirankumar15/test.git"
export SAMPLE_STACK_NAME="third-party-codepipeline-git-source-test"
aws cloudformation create-stack \
--stack-name ${SAMPLE_STACK_NAME}\
--template-body file://$(pwd)/cfn/sample_pipeline_custom.yaml \
--parameters ParameterKey=Branch,ParameterValue=master \
ParameterKey=GitUrl,ParameterValue=${SSH_URL} \
ParameterKey=SourceActionVersion,ParameterValue=1 \
ParameterKey=SourceActionProvider,ParameterValue=CustomSourceForGit \
ParameterKey=CodePipelineName,ParameterValue=sampleCodePipeline \
ParameterKey=SecretsManagerArnForSSHPrivateKey,ParameterValue=${SecretsManagerArn} \
ParameterKey=GitWebHookIpAddress,ParameterValue=34.74.90.64/28 \
--capabilities CAPABILITY_IAM

Alternatively, choose Launch stack:

cloudformation-launch-stack.png

Retrieving the webhook URL
When the stack creation is complete, retrieve the CodePipeline webhook URL from the stack outputs. Use the following AWS CLI command:

aws cloudformation describe-stacks \
--stack-name ${SAMPLE_STACK_NAME}\ --output text \
--query "Stacks[].Outputs[?OutputKey=='CodePipelineWebHookUrl'].OutputValue"

For more information about stack outputs, see Outputs.

Creating a webhook

You can use an existing GitLab repository or create a new GitLab repository and follow the below steps to add a webhook to it.
To create your webhook, complete the following steps:

1. Navigate to the Webhooks Settings section on the GitLab console for the repository that you want to have as a source for CodePipeline.

2. For URL, enter the CodePipeline webhook URL you retrieved in the previous step.

3. Select Push events and optionally enter a branch name.

4. Select Enable SSL verification.

5. Choose Add webhook.

gitlab-webhook.png

For more information about webhooks, see Webhooks.

We’re now ready to test the solution.

Testing the solution

To test the solution, we make changes to the branch that we passed as the branch parameter in the GitLab repository. This should trigger the pipeline. On the CodePipeline console, you can see the Git Commit ID on the source stage of the pipeline when it succeeds.

Note: Please provide the GitLab repository url that you have access to or create a new GitLab repository. and make sure that it has buildspec.yml in the contents to execute in AWS CodeBuild project in the Build stage. The example url "[email protected]:kirankumar15/test.git" is for illustration purposes only.

Enter the following code to clone your repository:

git clone [email protected]:kirankumar15/test.git .

Add a sample file to the repository with the name sample.txt, then commit and push it to the repository:

echo "adding a sample file" >> sample_text_file.txt
git add ./
git commit -m "added sample_test_file.txt to the repository"
git push -u origin master

The pipeline should show the status In Progress.

codepipeline_inprogress.png

After few minutes, it changes to Succeeded status and you see the Git Commit message on the source stage.

codepipeline_succeeded.png

You can also view the Git Commit message by choosing the execution ID of the pipeline, navigating to the timeline section, and choosing the source action. You should see the Commit message and Commit ID that correlates with the Git repository.

codepipeline-commit-msg.png

Troubleshooting

If the CodePipeline fails, check the Lambda function logs for the function with the name GitLab-CodePipeline-Source-${ACCOUNT_ID}. For instructions on checking logs, see Accessing Amazon CloudWatch logs for AWS Lambda.

If the Lambda logs has the CodeBuild build ID, then check the CodeBuild run logs for that build ID for errors. For instructions, see View detailed build information.

Cleaning up

Delete the CloudFormation stacks that you created. You can use the following AWS CLI commands:

aws cloudformation delete-stack --stack-name ${SAMPLE_STACK_NAME} aws cloudformation delete-stack --stack-name ${GIT_SOURCE_STACK_NAME}

Alternatively, delete the stack on the AWS CloudFormation console.

Additionally, empty the S3 bucket and delete it. Locate the bucket in the ${SAMPLE_STACK_NAME} stack. Then use the following AWS CLI command:

aws s3 rb s3://${S3_BUCKET_NAME} --force

You can also delete and empty the bucket on the Amazon S3 console.

Conclusion

You can use the architecture in this post for any Git repository that supports webhooks. This solution also works if the repository is reachable only from on premises, and if the endpoints can be accessed from a VPC. This event-driven architecture works just like using any natively supported source for CodePipeline.

 

About the Author

kirankumar.jpegKirankumar Chandrashekar is a DevOps consultant at AWS Professional Services. He focuses on leading customers in architecting DevOps technologies. Kirankumar is passionate about Infrastructure as Code and DevOps. He enjoys music, as well as cooking and travelling.

 

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