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Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

Exam Code:
DOP-C02
Exam Name:
AWS Certified DevOps Engineer - Professional
Certification:
AWS Certified Professional
Vendor:
Amazon Web Services
Questions:
449
Last Updated:
Oct 5, 2026
Exam Status:
Stable
Amazon Web Services DOP-C02

DOP-C02: AWS Certified Professional Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified DevOps Engineer - Professional Questions and Answers

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Question 1

A company has an application that runs on Amazon EC2 instances in an Auto Scaling group. The application processes a high volume of messages from an Amazon Simple Queue Service (Amazon SQS) queue.

A DevOps engineer noticed that the application took several hours to process a group of messages from the SQS queue. The average CPU utilization of the Auto Scaling group did not cross the threshold of a target tracking scaling policy when processing the messages. The application that processes the SQS queue publishes logs to Amazon CloudWatch Logs.

The DevOps engineer needs to ensure that the queue is processed quickly.

Which solution meets these requirements with the LEAST operational overhead?

Options:

A.

Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Schedule an Amazon EventBridge rule to run the Lambda function every hour. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scal

B.

Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Create a CloudWatch subscription filter for the application logs with the Lambda function as the target. Create a target tracking scaling policy for the Auto Scaling group that

C.

Create a target tracking scaling policy for the Auto Scaling group. In the target tracking policy, use the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to calculate how many messages are in the queue for each number of instances by using metric math. Use the calculated attribute to scale in and out.

D.

Create an AWS Lambda function that logs the ApproximateNumberOfMessagesVisible attribute of the SQS queue to a CloudWatch Logs log group. Schedule an Amazon EventBridge rule to run the Lambda function every 5 minutes. Create a metric filter to count the number of log events from a CloudWatch logs group. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.

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Question 2

A company has a stateless web application that is deployed on Amazon EC2 instances. The EC2 instances are in a target group behind an Application Load Balancer (ALB). Amazon Route 53 manages the application domain.

The company updates the application UI and develops a beta version of the application. The company wants to test the beta version on 10% of its traffic.

Which solution will meet these requirements with the LEAST number of configuration changes?

Options:

A.

Deploy the beta version to new EC2 instances in a new target group. Associate the new target group with a new ALB. Update the existing Route 53 record to use a weighted routing policy. Add a new Route 53 record that points to the new ALB with the same routing policy. Assign a weight of 90 to the existing record. Assign a weight of 10 to the new record.

B.

Deploy the beta version to new EC2 instances in a new target group. Associate the new target group with the same ALB listener rule. Assign a weight of 90 to the existing target group. Assign a weight of 10 to the new target group.

C.

Refactor the application to implement a feature flag for the beta version by using AWS AppConfig. Use the feature flag to enable the beta version for 10% of the EC2 instances.

D.

Containerize and deploy the application on Amazon Elastic Container Service (Amazon ECS). Use AWS CodeDeploy to deploy the beta version by using the CodeDeployDefault.ECSCanary10Percent15Minutes deployment configuration.

Question 3

A company wants to set up a continuous delivery pipeline. The company stores application code in a private GitHub repository. The company needs to deploy the application components to Amazon Elastic Container Service (Amazon ECS). Amazon EC2, and AWS Lambda. The pipeline must support manual approval actions.

Which solution will meet these requirements?

Options:

A.

Use AWS CodePipeline with Amazon ECS. Amazon EC2, and Lambda as deploy providers.

B.

Use AWS CodePipeline with AWS CodeDeploy as the deploy provider.

C.

Use AWS CodePipeline with AWS Elastic Beanstalk as the deploy provider.

D.

Use AWS CodeDeploy with GitHub integration to deploy the application.

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