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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:
Sep 30, 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 in a highly regulated industry is building an artifact by using AWS CodeBuild and AWS CodePipeline. The company must connect to an external authenticated API during the building process.

The company ' s DevOps engineer needs to encrypt the build outputs by using an AWS Key Management Service (AWS KMS) key. The external API credentials must be reset each month. The DevOps engineer has created a new key in AWS KMS.

Which solution will meet these requirements?

Options:

A.

Store the API credentials in AWS Systems Manager Parameter Store. Update the key policy for the CodeBuild IAM service role to have access to the KMS key. Set CODEBUILD_KMS_KEY_ID as the new key ID.

B.

Store the API credentials in AWS Systems Manager Parameter Store. Update the key policy for the CodePipeline IAM service role to have access to the KMS key. Add the key to the pipeline.

C.

Store the API credentials in AWS Secrets Manager. Update the key policy for the CodeBuild IAM service role to have access to the KMS key. Set CODEBUILD_KMS_KEY_ID as the new key ID.

D.

Store the API credentials in AWS Secrets Manager. Update the key policy for the CodePipeline IAM service role to have access to the KMS key. Add the key to the pipeline.

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Question 2

A company has an AWS account named PipelineAccount. The account manages a pipeline in AWS CodePipeline. The account uses an IAM role named CodePipeline_Service_Role and produces an artifact that is stored in an Amazon S3 bucket. The company uses a customer managed AWS KMS key to encrypt objects in the S3 bucket.

A DevOps engineer wants to configure the pipeline to use an AWS CodeDeploy application in an AWS account named CodeDeployAccount to deploy the produced artifact.

The DevOps engineer updates the KMS key policy to grant the CodeDeployAccount account permission to use the key. The DevOps engineer configures an IAM role named DevOps_Role in the CodeDeployAccount account that has access to the CodeDeploy resources that the pipeline requires. The DevOps engineer updates an Amazon EC2 instance role that operates within the CodeDeployAccount account to allow access to the S3 bucket and the KMS key that is in the PipelineAccount account.

Which additional steps will meet these requirements?

Options:

A.

Update the S3 bucket policy to grant the CodeDeployAccount account access to the S3 bucket. Configure the DevOps_Role IAM role to have an IAM trust policy that allows the PipelineAccount account to assume the role. Update the CodePipeline_Service_Role IAM role to grant permission to assume the DevOps_Role role.

B.

Update the S3 bucket policy to grant the CodeDeployAccount account access to the S3 bucket. Configure the DevOps_Role IAM role to have an IAM trust policy that allows the PipelineAccount account to assume the role. Update the DevOps_Role IAM role to grant permission to assume CodePipeline_Service_Role role.

C.

Update the S3 bucket policy to grant the PipelineAccount account access to the S3 bucket. Configure the DevOps_Role IAM role to have an IAM trust policy that allows the PipelineAccount account to assume the role. Update the CodePipeline_Service_Role IAM to grant permission to assume the DevOps_Role role.

D.

Update the S3 bucket policy to grant the CodeDeployAccount account access to the S3 bucket. Configure the DevOps_Role IAM role to have an IAM trust policy that allows the CodeDeployAccount account to assume the role. Update the CodePipeline_Service_Role IAM role to grant permission to assume the DevOps_Role role.

Question 3

A company ' s application has an API that retrieves workload metrics. The company needs to audit, analyze, and visualize these metrics from the application to detect issues at scale.

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

Options:

A.

Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon S3 bucket.

B.

Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon DynamoDB table that has a DynamoDB stream enabled.

C.

Create an AWS Glue crawler to catalog the workload metric data in the Amazon S3 bucket. Create views in Amazon Athena for the cataloged data.

D.

Connect an AWS Glue crawler to the Amazon DynamoDB stream to catalog the workload metric data. Create views in Amazon Athena for the cataloged data.

E.

Create Amazon QuickSight datasets from the Amazon Athena views. Create a QuickSight analysis to visualize the workload metric data as a dashboard.

F.

Create an Amazon CloudWatch dashboard that has custom widgets that invoke AWS Lambda functions. Configure the Lambda functions to query the workload metrics data from the Amazon Athena views.

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