AWS Certified Professional DOP-C02 Amazon Web Services Study Notes

 The UserData property of the AWS: AutoScaling: LaunchConfiguration resource can be used to specify a script that runs when the EC2 instances are launched. This script can include the ECS cluster name as an environment variable for the ECS agent running on the EC2 instances. This way, the EC2 instances will register with the correct ECS cluster. Option A is incorrect because the AWS: ECS: Cluster resource does not have a property to reference the EC2 instances. Option C is incorrect because the EC2 instances are launched by the Auto Scaling group, not by the AWS: EC2: Instance resource. Option D is incorrect because using a custom resource and a Lambda function is unnecessary and overly complex for this scenario. References: AWS::AutoScaling::LaunchConfiguration, Amazon ECS Container Agent Configuration

Running unit tests in the build phase and aborting on failure (OnFailure=ABORT) prevents deployment if tests fail.

AWS CDK assertions module provides programmatic unit tests against synthesized templates (Option D).

The --rollback flag relates to CloudFormation stack rollback, not test gating.

The --require-approval flag controls manual approvals, not test outcomes.

cdk diff checks for changes but is not a unit test and may not catch logical errors.

Using CodePipeline + CodeConnections Git repo provides version control, automated deployment, and rollback. Each template includes AWS::ControlTower::EnableControl for OU-level guardrails. AWS Control Tower documentation recommends this GitOps automation model.

Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production. Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git-based tools and will not provide the same level of revision control as AWS CodeCommit. References:

AWS CodeCommit

Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)