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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 10, 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 uses S3 to store images and requires multi-Region DR with two-way replication and ≤15-minute latency.

Which steps meet the requirements? (Select THREE.)

Options:

A.

Enable S3 Replication Time Control (RTC) for each replication rule.

B.

Create S3 Multi-Region Access Point (active/passive).

C.

Call SubmitMultiRegionAccessPointRoutes during failover.

D.

Enable S3 Transfer Acceleration.

E.

Use Route 53 ARC routing control.

F.

Use Route 53 ARC to shift traffic during failover.

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Question 2

A company uses AWS CodePipeline and AWS CodeDeploy to deploy application code to Amazon EC2 instances. The EC2 instances send application logs and CodeDeploy logs to Amazon CloudWatch.

Recently, the company manually rolled back a deployment because of application errors. The company wants to automate the rollback process when application errors occur.

Which solution will meet these requirements?

Options:

A.

Create a CloudWatch metric based on the application logs. Create a CloudWatch alarm based on the metric that will activate when application errors occur. Change the deployment group settings to use the CloudWatch alarm configuration. Configure the deployment group to use an auto rollback configuration.

B.

Configure a CloudWatch alarm that uses a custom metric for application errors that are recorded in the CodeDeploy agent logs. Configure the current deployment to use the CloudWatch alarm for its alarm configuration. Configure the deployment to use an auto rollback configuration.

C.

Create an AWS Lambda function that will create a new deployment by using the last successful application deployment. Create an Amazon EventBridge rule that matches events from CodeDeploy that have a deployment status of FAILURE. Configure the EventBridge rule to target the Lambda function.

D.

Create an AWS Lambda function that will create a new deployment group for the application deployment. Create a CloudWatch alarm based on metrics from the application logs. Configure the alarm to activate when an application error occurs on an EC2 instance. Configure the CloudWatch alarm to invoke the Lambda function.

Question 3

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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