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DOP-C02 Exam Dumps : AWS Certified DevOps Engineer - Professional

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AWS Certified DevOps Engineer - Professional Questions and Answers

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 uses AWS Organizations and AWS Control Tower to manage all the company ' s AWS accounts. The company uses the Enterprise Support plan.

A DevOps engineer is using Account Factory for Terraform (AFT) to provision new accounts. When new accounts are provisioned, the DevOps engineer notices that the support plan for the new accounts is set to the Basic Support plan. The DevOps engineer needs to implement a solution to provision the new accounts with the Enterprise Support plan.

Which solution will meet these requirements?

Options:

A.

Use an AWS Config conformance pack to deploy the account-part-of-organizations AWS Config rule and to automatically remediate any noncompliant accounts.

B.

Create an AWS Lambda function to create a ticket for AWS Support to add the account to the Enterprise Support plan. Grant the Lambda function the support:ResolveCase permission.

C.

Add an additional value to the control_tower_parameters input to set the AWSEnterpriseSupport parameter as the organization ' s management account number.

D.

Set the aft_feature_enterprise_support feature flag to True in the AFT deployment input configuration. Redeploy AFT and apply the changes.