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

In CodePipeline’s execution mode,

PARALLEL mode for pull_request pipelines ensures that multiple feature branches can be tested simultaneously for quick feedback.

QUEUED mode for main_branch ensures deployments run sequentially — each must finish before the next begins, preventing overlap. This configuration aligns with AWS CodePipeline best practices for trunk-based development and concurrent test pipelines.

Enable AWS Config Across the Organization:

AWS Config provides a detailed view of the configuration of AWS resources in your AWS account. It can be used to assess, audit, and evaluate the configurations of your resources.

Enabling AWS Config across the organization ensures that all accounts are monitored for compliance.

Create a Conformance Pack Using the approved-amis-by-id AWS Config Managed Rule:

A conformance pack is a collection of AWS Config rules and remediation actions that can be easily deployed across an organization.

The approved-amis-by-id managed rule checks whether running instances are using approved AMIs.

Deploy the Conformance Pack Across the Organization:

Deploying the conformance pack across the organization ensures that all accounts adhere to the policy of using only approved AMIs.

The conformance pack can be deployed via the AWS Management Console, CLI, or SDKs.

Configure the Rule to Run the AWS-StopEC2Instance AWS Systems Manager Automation Runbook for Non-Compliant EC2 Instances:

The AWS-StopEC2Instance runbook can be configured to automatically stop any EC2 instances that are found to be non-compliant (i.e., not using approved AMIs).

This remediation action ensures that any unauthorized instances are promptly stopped, enforcing the policy without manual intervention.

By following these steps, the solution ensures that all EC2 instances across the organization use approved AMIs, and any non-compliant instances are remediated automatically.

Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer documents only:

During an Amazon ECS service deployment, if tasks fail the Elastic Load Balancing target group health checks, Amazon ECS considers those tasks unhealthy and stops and replaces them. This behavior can cause the deployment to remain incomplete because healthy replacement tasks never become available.

Also, if an essential container in the task exits, the entire task stops. Since the question states that the new tasks enter a stopped state soon after launch, an essential container failure is a direct and highly likely cause.

Why the other options are incorrect:

B. The IAM role used by the DevOps engineer to update the ECS service does not need RunTask permission for the tasks to remain running after launch. A permission issue here would more likely affect the update action itself rather than cause launched tasks to stop shortly afterward.

C. Although CloudWatch Logs configuration problems can affect logging, the missing log group is not the most likely direct reason for ECS tasks to repeatedly stop in this deployment scenario.

D. The task role provides permissions to the application code running inside the container. It is not the role primarily responsible for launching the task. Task startup is typically related to the task execution role, ECS service behavior, container health, and load balancer checks.