DOP-C02 Flashcards — Free AWS Certified DevOps Engineer Professional DOP-C02 Study Cards

The parent stack's update policy is set to 'CONTINUE' by default. To prevent this, set 'OnFailure' to 'ROLLBACK' in the stack update options.

None of the provided options are correct. The default update behavior in CloudFormation is to continue on failure. To ensure rollback on update failure, you should set 'RollbackOnFailure' to true in the stack update options (e.g., using the '--rollback-configuration' parameter in the AWS CLI). Option A incorrectly references the creation-only parameter 'OnFailure', while options B, C, and D are factually incorrect. The best practice is to enable rollback on update failure by configuring RollbackOnFailure.

Use predictive scaling with a scheduled scaling policy for known peak times.

Predictive scaling uses historical traffic data to forecast future demand and proactively adjust capacity before a spike occurs. This prevents the CPU from reaching critical levels that cause health check failures, ensuring the ALB always has healthy hosts. Scheduled scaling alone would not adapt to unexpected spikes, but predictive scaling combined with dynamic scaling provides both proactive and reactive resilience.

Use CloudWatch ALB metrics (HTTPCode_ELB_5XX_Count) and create a CloudWatch Alarm on the Sum statistic with a threshold based on total request count.

Option C is correct because ALB automatically publishes the `HTTPCode_ELB_5XX_Count` metric to CloudWatch, and you can create a CloudWatch alarm using the `Sum` statistic over a 5-minute period. To detect when the error rate exceeds 5%, you need to combine this metric with the `RequestCount` metric in a math expression (e.g., `m1/m2*100 > 5`) or use a composite alarm, as the alarm threshold must be based on the ratio of 5xx errors to total requests, not just the raw count.

Use CloudWatch Logs Insights to query application logs for error patterns or deployment markers that coincide with the metric spike.

Option B is correct because CloudWatch Logs Insights allows you to query application logs for error patterns or deployment markers (e.g., new version tags, exception stack traces) that coincide with the metric spike. This directly correlates the scaling event with application-level evidence, enabling rapid root-cause analysis without altering infrastructure or relying on indirect notifications.

Create an IAM role in each member account with a trust policy that allows the Security account, and use AWS CloudFormation StackSets to deploy the roles.

Option A is correct because it uses AWS CloudFormation StackSets to deploy IAM roles across member accounts with a trust policy that allows the Security account to assume them. StackSets ensure that role updates are automatically applied to all accounts in the organization. SCPs can be used in conjunction to enforce that only these specific roles can be assumed.

A previous deployment is still in progress or frozen in the CodeDeploy deployment group.

Option D is correct because CodeDeploy enforces a per-deployment-group concurrency limit of one deployment at a time. If a previous deployment is still in progress or in a 'frozen' state (e.g., due to a failed or stopped deployment that hasn't been explicitly rolled back or cleaned up), new deployments will fail with the 'too many individual instances failed' error even when instances are healthy. The error message is misleading because it reflects CodeDeploy's inability to proceed with the new deployment, not actual instance health issues.