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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:
Aug 1, 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 is developing a web application that runs on Amazon EC2 Linux instances. The application requires monitoring of custom performance metrics. The company must collect metrics for API response times and database query latency across multiple instances. Which solution will generate the custom metrics with the LEAST operational overhead?

Options:

A.

Install the Amazon CloudWatch agent on the instances. Configure the agent to collect the custom metrics. Instrument the application to send the metrics to the agent.

B.

Use Amazon Managed Service for Prometheus to scrape the custom metrics from the application. Use the Amazon CloudWatch agent to forward the metrics to CloudWatch.

C.

Create a custom AWS Lambda function that polls the application endpoints and database at regular intervals. Program the Lambda function to calculate the custom metrics and to send the metrics to Amazon CloudWatch by using PutMetricData API calls.

D.

Implement custom logging in the application code to record the custom metrics. Use Amazon CloudWatch Logs Insights to extract and analyze the metrics.

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Question 2

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.

Question 3

A SaaS company uses ECS (Fargate) behind an ALB and CodePipeline + CodeDeploy for blue/green deployments. They need automatic, incremental traffic shifting over time with no downtime.

Which solution will meet these requirements?

Options:

A.

Use TimeBasedLinear in appspec.yaml with defined percentage and interval.

B.

Use AllAtOnce deployment configuration.

C.

Use TimeBasedCanary.

D.

Configure weighted routing on ALB manually.

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