DOP-C02 AWS Certified DevOps Engineer – Professional Free Practice Questions and Answers

A team deploys a containerized service to Amazon ECS on AWS Fargate. They need gradual traffic shifting and automatic rollback when the new version breaches an alarm. Which deployment approach best meets the requirement?

• A. Use an ECS blue/green deployment with CodeDeploy and CloudWatch alarms
• B. Update the service task definition directly and restart every task at once
• C. Use a scheduled Lambda function to change the desired task count
• D. Deploy through an EC2 Auto Scaling instance refresh

A pipeline must prevent two teams from applying Terraform changes to the same environment at the same time. The state must be shared and protected from accidental loss. Which design is most suitable?

• A. Store state on an engineer’s workstation and email it after each apply
• B. Use an S3 remote state backend with encryption and DynamoDB state locking
• C. Keep state in the source repository as an unencrypted file
• D. Use separate local state files for every pipeline run

An application emits structured JSON logs from containers in an Amazon EKS cluster. Operators need centralized search and dashboards with minimal changes to application code. What should they do?

• A. Configure a cluster log agent to collect container logs and send them to CloudWatch Logs
• B. Write logs only to each pod’s ephemeral filesystem
• C. Store log files in container image layers
• D. Send all logs to an EC2 instance over an unauthenticated port

A deployment pipeline needs database credentials at runtime. The credentials must be rotated without embedding them in source code or build artifacts. Which solution is best?

• A. Place credentials in a plaintext pipeline variable file committed to Git
• B. Store credentials in AWS Secrets Manager, grant the workload a scoped IAM role, and enable rotation
• C. Hard-code credentials in the container image and rebuild quarterly
• D. Pass credentials as command-line arguments to every deployment step

A service on an EC2 Auto Scaling group experiences predictable daily demand spikes. The team wants capacity ready before the spike while retaining automatic adjustment for unexpected load. What should they configure?

• A. Scheduled scaling for the expected pattern and a dynamic scaling policy for deviations
• B. Manually change desired capacity after customers report delays
• C. Disable health checks during peak hours
• D. Use only a fixed desired capacity all year