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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
Questions:
449
Last Updated:
Aug 29, 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

Question 1

A DevOps engineer manages a Java-based application that runs in an Amazon Elastic Container Service (Amazon ECS) cluster on AWS Fargate. Auto scaling has not been configured for the application. The DevOps engineer has determined that the Java Virtual Machine (JVM) thread count is a good indicator of when to scale the application. The application serves customer traffic on port 8080 and makes JVM metrics available on port 9404. Application use has recently increased. The DevOps engineer needs to configure auto scaling for the application. Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Deploy the Amazon CloudWatch agent as a container sidecar. Configure the CloudWatch agent to retrieve JVM metrics from port 9404. Create CloudWatch alarms on the JVM thread count metric to scale the application. Add a step scaling policy in Fargate to scale up and scale down based on the CloudWatch alarms.

B.

Deploy the Amazon CloudWatch agent as a container sidecar. Configure a metric filter for the JVM thread count metric on the CloudWatch log group for the CloudWatch agent. Add a target tracking policy in Fargate. Select the metric from the metric filter as a scale target.

C.

Create an Amazon Managed Service for Prometheus workspace. Deploy AWS Distro for OpenTelemetry as a container sidecar to publish the JVM metrics from port 9404 to the Prometheus workspace. Configure rules for the workspace to use the JVM thread count metric to scale the application. Add a step scaling policy in Fargate. Select the Prometheus rules to scale up and scaling down.

D.

Create an Amazon Managed Service for Prometheus workspace. Deploy AWS Distro for OpenTelemetry as a container sidecar to retrieve JVM metrics from port 9404 to publish the JVM metrics from port 9404 to the Prometheus workspace. Add a target tracking policy in Fargate. Select the Prometheus metric as a scale target.

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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 video-sharing company stores its videos in Amazon S3. The company has observed a sudden increase in video access requests, but the company does not know which videos are most popular. The company needs to identify the general access pattern for the video files. This pattern includes the number of users who access a certain file on a given day, as well as the numb A DevOps engineer manages a large commercial website that runs on Amazon EC2 The website uses Amazon Kinesis Data Streams to collect and process web togs The DevOps engineer manages the Kinesis consumer application, which also runs on Amazon EC2

Sudden increases of data cause the Kinesis consumer application to (all behind and the Kinesis data streams drop records before the records can be processed The DevOps engineer must implement a solution to improve stream handling

Which solution meets these requirements with the MOST operational efficiency ' '

er of pull requests for certain files.

How can the company meet these requirements with the LEAST amount of effort?

Options:

A.

Activate S3 server access logging. Import the access logs into an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.

B.

Activate S3 server access logging. Use Amazon Athena to create an external table with the log files. Use Athena to create a SQL query to analyze the access patterns.

C.

Invoke an AWS Lambda function for every S3 object access event. Configure the Lambda function to write the file access information, such as user. S3 bucket, and file key, to an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.

D.

Record an Amazon CloudWatch Logs log message for every S3 object access event. Configure a CloudWatch Logs log stream to write the file access information, such as user, S3 bucket, and file key, to an Amazon Kinesis Data Analytics for SQL application. Perform a sliding window analysis.