DOP-C02 Exam Dumps : AWS Certified DevOps Engineer - Professional

The operating system (Amazon Linux) uses yum for package management. To use both the default and a custom repository, the simplest method is to add the custom repository configuration file under /etc/yum.repos.d/ using the yum-config-manager CLI, and enable it. This allows the system to access both repositories during patching automatically.

This approach requires minimal setup and effort and leverages the existing yum patching mechanisms.

Option A and D involve managing multiple patch baselines in Systems Manager Patch Manager, which does not natively support custom repositories — it relies on the underlying OS package manager.

Option B (Direct Connect) is not necessary unless network connectivity is an issue.

Thus, option C meets the requirement with the least effort.

This solution will meet the requirements because it will use a CloudFormation custom resource to execute custom logic during the stack set operation. A custom resource is a resource that you define in your template and that is associated with an AWS Lambda function. The Lambda function runs whenever the custom resource is created, updated, or deleted, and can perform any actions that are supported by the AWS SDK. In this case, the Lambda function can use the GuardDuty API to check whether GuardDuty is already enabled in each target account, and if not, enable it. This way, the DevOps engineer can avoid deploying the stack set to accounts that already have GuardDuty enabled, and prevent failure during the deployment.

Option B is the correct choice and has the least operational overhead because ECR lifecycle policies are the native, managed feature built specifically to automate image cleanup:

ECR lifecycle policies can expire images based on image age (e.g., images older than X days) and can also enforce retaining a minimum number of images (count-based retention), which directly matches the requirement “retain at least a specified number of images.”

Lifecycle policies work for both tagged and untagged images using rule selection and tagging status filters, so the repository stays clean without custom automation.

Why the other options are not appropriate / higher overhead:

A is invalid: ECR is not S3; S3 lifecycle policies do not manage ECR images .

C and D introduce custom automation (Lambda or SSM scripting), scheduling, permissions, error handling, retries, logging, and ongoing maintenance—higher overhead than a managed lifecycle policy.