Selected DOP-C02 AWS Certified Professional Questions Answers

The requirements clearly indicate the need for modern CodePipeline capabilities , strict execution ordering, Git tag–based triggers, and loose coupling between pipelines. CodePipeline V2 introduces execution modes such as QUEUED and SUPERSEDED , along with native support for advanced trigger filtering when using AWS CodeConnections.

The requirement that the pipeline must wait for the previous run to finish directly maps to QUEUED mode , which ensures that pipeline executions run sequentially rather than replacing in-progress executions. SUPERSEDED mode would cancel the running execution, which violates the requirement.

Triggering the pipeline when new Git tags are pushed is supported through CodePipeline V2 trigger filters using refs/tags/*. Branch-based triggers would not satisfy this condition.

Finally, the requirement that an existing deployment pipeline runs in response to new container images is best met using Amazon EventBridge , which natively emits events for ECR image push actions . EventBridge allows decoupled, event-driven orchestration between pipelines without tight dependencies or custom scripting. This is the AWS-recommended approach for pipeline-to-pipeline coordination.

Options C and D rely on CodePipeline V1 , which lacks modern trigger filtering and execution control. Option B incorrectly uses SUPERSEDED mode and branch-based triggers.

Therefore, Option A correctly combines CodePipeline V2 , QUEUED execution mode , tag-based triggers , and EventBridge-driven pipeline chaining , meeting all requirements with best practices and minimal operational complexity.

Enabling EKS control plane logs to CloudWatch captures API requests. CloudWatch Container Insights collects node and pod-level performance data with no additional infrastructure. AWS recommends this integrated observability solution for minimal management overhead.

 Use AWS Step Functions to Orchestrate Processing:

AWS Step Functions allow you to build distributed applications by combining AWS Lambda functions or other AWS services into workflows.

Decoupling the processing into Step Functions tasks enables you to retry individual steps without reprocessing the entire record.

 Architectural Steps:

Create a web application to pass records to AWS Step Functions:

The web application can be a simple frontend that receives input and triggers the Step Functions workflow.

Define a Step Functions state machine:

Each step in the state machine represents a processing stage. If a step fails, Step Functions can retry the step based on defined conditions.

Use AWS Lambda functions:

Lambda functions can be used to handle each processing step. These functions can be stateless and handle specific tasks, reducing the complexity of error handling and reprocessing logic.

 Operational Efficiency:

Using Step Functions and Lambda improves operational efficiency by providing built-in error handling, retries, and state management.

This architecture scales automatically and isolates failures to individual steps, ensuring only failed steps are retried.