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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 ' s application uses a fleet of Amazon EC2 On-Demand Instances to analyze and process data. The EC2 instances are in an Auto Scaling group. The Auto Scaling group is a target group for an Application Load Balancer (ALB). The application analyzes critical data that cannot tolerate interruption. The application also analyzes noncritical data that can withstand interruption.

The critical data analysis requires quick scalability in response to real-time application demand. The noncritical data analysis involves memory consumption. A DevOps engineer must implement a solution that reduces scale-out latency for the critical data. The solution also must process the noncritical data.

Which combination of steps will meet these requirements? (Select TWO.)

Options:

A.

For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new version of the launch template that has detailed monitoring enabled. use Spot Instances.

B.

For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new version of the launch template that has detailed monitoring enabled. Use On-Demand Instances.

C.

For the critical data. modify the existing Auto Scaling group. Create a lifecycle hook to ensure that bootstrap scripts are completed successfully. Ensure that the application on the instances is ready to accept traffic before the instances are registered. Create a new version of the launch template that has detailed monitoring enabled.

D.

For the noncritical data, create a second Auto Scaling group that uses a launch template. Configure the launch template to install the unified Amazon CloudWatch agent and to configure the CloudWatch agent with a custom memory utilization metric. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

E.

For the noncritical data, create a second Auto Scaling group. Choose the predefined memory utilization metric type for the target tracking scaling policy. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

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Question 2

A company needs to update its order processing application to improve resilience and availability. The application requires a stateful database and uses a single-node Amazon RDS DB instance to store customer orders and transaction history. A DevOps engineer must make the database highly available.

Which solution will meet this requirement?

Options:

A.

Migrate the database to Amazon DynamoDB global tables. Configure automatic failover between AWS Regions by using Amazon Route 53 health checks.

B.

Migrate the database to Amazon EC2 instances in multiple Availability Zones. Use Amazon Elastic Block Store (Amazon EBS) Mult-Attach to connect all the instances to a single EBS volume.

C.

Use the RDS DB instance as the source instance to create read replicas in multiple Availability Zones. Deploy an Application Load Balancer to distribute read traffic across the read replicas.

D.

Modify the RDS DB instance to be a Multi-AZ deployment. Verify automatic failover to the standby instance if the primary instance becomes unavailable.

Question 3

A company is developing a mobile app that requires extensive automated testing across multiple device types. The company is using AWS CodePipeline for its CI/CD pipeline. The company must implement a scalable testing solution that can handle increased test loads as the app grows. Which solution will meet these requirements with the LEAST management overhead?

Options:

A.

Integrate AWS Device Farm with the pipeline to run the tests and scale as needed.

B.

Deploy a fleet of Amazon EC2 instances with various mobile device emulators and auto scaling to run the tests. Create a custom AWS Lambda function to invoke EC2 test runs.

C.

Implement a containerized testing solution that uses Amazon Elastic Container Service (Amazon ECS) with auto scaling. Configure the pipeline to invoke an AWS Lambda function to start the test runs on the ECS cluster.

D.

Use AWS Lambda functions with custom runtime emulators to run the tests. Integrate the Lambda functions with the pipeline.