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Amazon Exam DOP-C02 Topic 8 Question 34 Discussion

Actual exam question for Amazon's DOP-C02 exam
Question #: 34
Topic #: 8
[All DOP-C02 Questions]

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.)

Show Suggested Answer Hide 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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Arlene
17 days ago
Bring in the CodeDeploy agent! It's like sending in the robot vacuum to clean up after all those manual deployments. Much more efficient.
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Nguyet
2 days ago
A: Create an application group and a deployment group in AWS CodeDeploy. Install the CodeDeploy agent on the EC2 instances.
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Lindsey
26 days ago
Hmm, I guess the developers are finally learning to automate their deployments. About time - no more SSH-ing into each instance like a bunch of sysadmins!
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Angelo
28 days ago
Option E is tempting, but I'd want to ensure the CloudFormation change sets are reviewed before deployment. Better safe than sorry when it comes to production systems.
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Laurel
User 1: Option D sounds like a good choice. It includes a manual approval step before running the CloudFormation change sets.
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Tanesha
1 months ago
I like the idea of using CodePipeline to orchestrate the deployment. Pausing for manual approval before making changes to the production environment is a smart move.
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Leah
3 days ago
E) Use 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.
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Alonzo
19 days ago
D) Use 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.
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Virgie
26 days ago
C) Use 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.
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Ria
1 months ago
C and D seem like the best options to automate the deployment process while retaining manual approval. CodePipeline can handle the integration of the different AWS services to streamline the process.
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Royce
2 months ago
I prefer option D because it not only automates the deployment process with AWS CodePipeline but also creates CloudFormation change sets for each application stack before the manual approval step.
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Kathrine
2 months ago
I agree with Wynell. Option C seems like the best option to streamline the deployment process while still having control over when the changes are made.
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Wynell
2 months ago
I think option C is a good choice because it uses AWS CodePipeline to automate the deployment process and includes a manual approval step.
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