Amazon Exam DOP-C02 Topic 8 Question 34 Discussion

Actual exam question for Amazon's DOP-C02 exam

Question #: 34
Topic #: 8

A company runs an application on Amazon EC2 instances. The company uses a series of AWS CloudFormation stacks to define the application resources. A developer performs updates by building and testing the application on a laptop and then uploading the build output and CloudFormation stack templates to Amazon S3. The developer's peers review the changes before the developer performs the CloudFormation stack update and installs a new version of the application onto the EC2 instances.

The deployment process is prone to errors and is time-consuming when the developer updates each EC2 instance with the new application. The company wants to automate as much of the application deployment process as possible while retaining a final manual approval step before the modification of the application or resources.

The company already has moved the source code for the application and the CloudFormation templates to AWS CodeCommit. The company also has created an AWS CodeBuild project to build and test the application.

Which combination of steps will meet the company's requirements? (Choose two.)

ACreate an application group and a deployment group in AWS CodeDeploy. Install the CodeDeploy agent on the EC2 instances.

BCreate an application revision and a deployment group in AWS CodeDeploy. Create an environment in CodeDeploy. Register the EC2 instances to the CodeDeploy environment.

CUse AWS CodePipeline to invoke the CodeBuild job, run the CloudFormation update, and pause for a manual approval step. After approval, start the AWS CodeDeploy deployment.

DUse AWS CodePipeline to invoke the CodeBuild job, create CloudFormation change sets for each of the application stacks, and pause for a manual approval step. After approval, run the CloudFormation change sets and start the AWS CodeDeploy deployment.

EUse AWS CodePipeline to invoke the CodeBuild job, create CloudFormation change sets for each of the application stacks, and pause for a manual approval step. After approval, start the AWS CodeDeploy deployment.

Show Suggested Answer

Suggested Answer: D

Step 2: Using an SQS Dead-Letter Queue (DLQ) Configuring a dead-letter queue (DLQ) for SQS will ensure that messages with invalid data, or those that cannot be processed successfully, are moved to the DLQ. This prevents such messages from clogging the queue and allows the system to focus on processing valid messages.

Action: Configure an SQS dead-letter queue for the main queue.

Why: A DLQ helps isolate problematic messages, preventing them from continuously reappearing in the queue and causing processing delays for valid messages.

Step 3: Maintaining the Lambda Function's Batch Size Keeping the current batch size allows the Lambda function to continue processing multiple messages at once. By addressing the failed items separately, there's no need to increase or reduce the batch size.

Action: Maintain the Lambda function's current batch size.

Why: Changing the batch size is unnecessary if the invalid messages are properly handled by reporting failed items and using a DLQ.

This corresponds to Option D: Keep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SQS dead-letter queue.

by Stephane at Sep 18, 2024, 08:57 AM

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