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DOP-C02 Exam Dumps - Amazon Web Services AWS Certified Professional Questions and Answers

Question # 44

A company has developed a serverless web application that is hosted on AWS. The application consists of Amazon S3. Amazon API Gateway, several AWS Lambda functions, and an Amazon RDS for MySQL database. The company is using AWS CodeCommit to store the source code. The source code is a combination of AWS Serverless Application Model (AWS SAM) templates and Python code.

A security audit and penetration test reveal that user names and passwords for authentication to the database are hardcoded within CodeCommit repositories. A DevOps engineer must implement a solution to automatically detect and prevent hardcoded secrets.

What is the MOST secure solution that meets these requirements?

Options:

A.

Enable Amazon CodeGuru Profiler. Decorate the handler function with @with_lambda_profiler(). Manually review the recommendation report. Write the secret to AWS Systems Manager Parameter Store as a secure string. Update the SAM templates and the Python code to pull the secret from Parameter Store.

B.

Associate the CodeCommit repository with Amazon CodeGuru Reviewer. Manually check the code review for any recommendations. Choose the option to protect the secret. Update the SAM templates and the Python code to pull the secret from AWS Secrets Manager.

C.

Enable Amazon CodeGuru Profiler. Decorate the handler function with @with_lambda_profiler(). Manually review the recommendation report. Choose the option to protect the secret. Update the SAM templates and the Python code to pull the secret from AWS Secrets Manager.

D.

Associate the CodeCommit repository with Amazon CodeGuru Reviewer. Manually check the code review for any recommendations. Write the secret to AWS Systems Manager Parameter Store as a string. Update the SAM templates and the Python code to pull the secret from Parameter Store.

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Question # 45

A company wants to use AWS development tools to replace its current bash deployment scripts. The company currently deploys a LAMP application to a group of Amazon EC2 instances behind an Application Load Balancer (ALB). During the deployments, the company unit tests the committed application, stops and starts services, unregisters and re-registers instances with the load balancer, and updates file permissions. The company wants to maintain the same deployment functionality through the shift to using AWS services.

Which solution will meet these requirements?

Options:

A.

Use AWS CodeBuild to test the application. Use bash scripts invoked by AWS CodeDeploy's appspec.yml file to restart services, and deregister and register instances with the ALB. Use the appspec.yml file to update file permissions without a custom script.

B.

Use AWS CodePipeline to move the application from the AWS CodeCommit repository to AWS CodeDeploy. Use CodeDeploy's deployment group to test the application, unregister and re-register instances with the ALB. and restart services. Use the appspec.yml file to update file permissions without a custom script.

C.

Use AWS CodePipeline to move the application source code from the AWS CodeCommit repository to AWS CodeDeploy. Use CodeDeploy to test the application. Use CodeDeploy's appspec.yml file to restart services and update permissions without a custom script. Use AWS CodeBuild to unregister and re-register instances with the ALB.

D.

Use AWS CodePipeline to trigger AWS CodeBuild to test the application. Use bash scripts invoked by AWS CodeDeploy's appspec.yml file to restart services. Unregister and re-register the instances in the AWS CodeDeploy deployment group with the ALB. Update the appspec.yml file to update file permissions without a custom script.

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Question # 46

A company has an application that is using a MySQL-compatible Amazon Aurora Multi-AZ DB cluster as the database. A cross-Region read replica has been created for disaster recovery purposes. A DevOps engineer wants to automate the promotion of the replica so it becomes the primary database instance in the event of a failure.

Which solution will accomplish this?

Options:

A.

Configure a latency-based Amazon Route 53 CNAME with health checks so it points to both the primary and replica endpoints. Subscribe an Amazon SNS topic to Amazon RDS failure notifications from AWS CloudTrail and use that topic to invoke an AWS Lambda function that will promote the replica instance as the primary.

B.

Create an Aurora custom endpoint to point to the primary database instance. Configure the application to use this endpoint. Configure AWS CloudTrail to run an AWS Lambda function to promote the replica instance and modify the custom endpoint to point to the newly promoted instance.

C.

Create an AWS Lambda function to modify the application's AWS CloudFormation template to promote the replica, apply the template to update the stack, and point the application to the newly promoted instance. Create an Amazon CloudWatch alarm to invoke this Lambda function after the failure event occurs.

D.

Store the Aurora endpoint in AWS Systems Manager Parameter Store. Create an Amazon EventBridge event that detects the database failure and runs an AWS Lambda function to promote the replica instance and update the endpoint URL stored in AWS Systems Manager Parameter Store. Code the application to reload the endpoint from Parameter Store if a database connection fails.

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Question # 47

A company is implementing a well-architected design for its globally accessible API stack. The design needs to ensure both high reliability and fast response times for users located in North America and Europe.

The API stack contains the following three tiers:

Amazon API Gateway

AWS Lambda

Amazon DynamoDB

Which solution will meet the requirements?

Options:

A.

Configure Amazon Route 53 to point to API Gateway APIs in North America and Europe using health checks. Configure the APIs to forward requests to a Lambda function in that Region. Configure the Lambda functions to retrieve and update the data in a DynamoDB table in the same Region as the Lambda function.

B.

Configure Amazon Route 53 to point to API Gateway APIs in North America and Europe using latency-based routing and health checks. Configure the APIs to forward requests to a Lambda function in that Region. Configure the Lambda functions to retrieve and update the data in a DynamoDB global table.

C.

Configure Amazon Route 53 to point to API Gateway in North America, create a disaster recovery API in Europe, and configure both APIs to forward requests to the Lambda functions in that Region. Retrieve the data from a DynamoDB global table. Deploy a Lambda function to check the North America API health every 5 minutes. In the event of a failure, update Route 53 to point to the disaster recovery API.

D.

Configure Amazon Route 53 to point to API Gateway API in North America using latency-based routing. Configure the API to forward requests to the Lambda function in the Region nearest to the user. Configure the Lambda function to retrieve and update the data in a DynamoDB table.

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Question # 48

A company has an application that runs on Amazon EC2 instances that are in an Auto Scaling group. When the application starts up. the application needs to process data from an Amazon S3 bucket before the application can start to serve requests.

The size of the data that is stored in the S3 bucket is growing. When the Auto Scaling group adds new instances, the application now takes several minutes to download and process the data before the application can serve requests. The company must reduce the time that elapses before new EC2 instances are ready to serve requests.

Which solution is the MOST cost-effective way to reduce the application startup time?

Options:

A.

Configure a warm pool for the Auto Scaling group with warmed EC2 instances in the Stopped state. Configure an autoscaling:EC2_INSTANCE_LAUNCHING lifecycle hook on the Auto Scaling group. Modify the application to complete the lifecycle hook when the application is ready to serve requests.

B.

Increase the maximum instance count of the Auto Scaling group. Configure an autoscaling:EC2_INSTANCE_LAUNCHING lifecycle hook on the Auto Scaling group. Modify the application to complete the lifecycle hook when the application is ready to serve requests.

C.

Configure a warm pool for the Auto Scaling group with warmed EC2 instances in the Running state. Configure an autoscaling:EC2_INSTANCE_LAUNCHING lifecycle hook on the Auto Scaling group. Modify the application to complete the lifecycle hook when the application is ready to serve requests.

D.

Increase the maximum instance count of the Auto Scaling group. Configure an autoscaling:EC2_INSTANCE_LAUNCHING lifecycle hook on the Auto Scaling group. Modify the application to complete the lifecycle hook and to place the new instance in the Standby state when the application is ready to serve requests.

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Question # 49

A company uses an organization in AWS Organizations to manage several AWS accounts that the company's developers use. The company requires all data to be encrypted in transit.

Multiple Amazon S3 buckets that were created in developer accounts allow unencrypted connections. A DevOps engineer must enforce encryption of data in transit for all existing S3 buckets that are created in accounts in the organization.

Which solution will meet these requirements?

Options:

A.

Use AWS Cloud Formation StackSets to deploy an AWS Network Firewall firewall to each account. Route all outbound requests from the AWS environment through the firewall. Deploy a policy to block access to all outbound requests on port 80.

B.

Use AWS CloudFormation StackSets to deploy an AWS Network Firewall firewall to each account. Route all inbound requests to the AWS environment through the firewall. Deploy a policy to block access to all inbound requests on port 80.

C.

Turn on AWS Config for the organization. Deploy a conformance pack that uses the s3-bucket-ssi-requests-only managed rule and an AWS Systems Manager Automation runbook. Use a runbook that adds a bucket policy statement to deny access to an S3 bucket when the value of the aws:SecureTransport condition key is false.

D.

Turn on AWS Config for the organization. Deploy a conformance pack that uses the s3-buckot-ssl-requests-only managed rule and an AWS Systems Manager Automation runbook. Use a runbook that adds a bucket policy statement to deny access to an S3 bucket when the value of the s3:x-amz-server-side-encryption-aws-kms-key-id condition key is null.

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Question # 50

A company that runs many workloads on AWS has an Amazon EBS spend that has increased over time. The DevOps team notices there are many unattached

EBS volumes. Although there are workloads where volumes are detached, volumes over 14 days old are stale and no longer needed. A DevOps engineer has been tasked with creating automation that deletes unattached EBS volumes that have been unattached for 14 days.

Which solution will accomplish this?

Options:

A.

Configure the AWS Config ec2-volume-inuse-check managed rule with a configuration changes trigger type and an Amazon EC2 volume resource target. Create a new Amazon CloudWatch Events rule scheduled to execute an AWS Lambda function in 14 days to delete the specified EBS volume.

B.

Use Amazon EC2 and Amazon Data Lifecycle Manager to configure a volume lifecycle policy. Set the interval period for unattached EBS volumes to 14 days and set the retention rule to delete. Set the policy target volumes as *.

C.

Create an Amazon CloudWatch Events rule to execute an AWS Lambda function daily. The Lambda function should find unattached EBS volumes and tag them with the current date, and delete unattached volumes that have tags with dates that are more than 14 days old.

D.

Use AWS Trusted Advisor to detect EBS volumes that have been detached for more than 14 days. Execute an AWS Lambda function that creates a snapshot and then deletes the EBS volume.

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Question # 51

A company has a single AWS account that runs hundreds of Amazon EC2 instances in a single AWS Region. New EC2 instances are launched and terminated each hour in the account. The account also includes existing EC2 instances that have been running for longer than a week.

The company's security policy requires all running EC2 instances to use an EC2 instance profile. If an EC2 instance does not have an instance profile attached, the EC2 instance must use a default instance profile that has no IAM permissions assigned.

A DevOps engineer reviews the account and discovers EC2 instances that are running without an instance profile. During the review, the DevOps engineer also observes that new EC2 instances are being launched without an instance profile.

Which solution will ensure that an instance profile is attached to all existing and future EC2 instances in the Region?

Options:

A.

Configure an Amazon EventBridge rule that reacts to EC2 RunInstances API calls. Configure the rule to invoke an AWS Lambda function to attach the default instance profile to the EC2 instances.

B.

Configure the ec2-instance-profile-attached AWS Config managed rule with a trigger type of configuration changes. Configure an automatic remediation action that invokes an AWS Systems Manager Automation runbook to attach the default instance profile to the EC2 instances.

C.

Configure an Amazon EventBridge rule that reacts to EC2 StartInstances API calls. Configure the rule to invoke an AWS Systems Manager Automation runbook to attach the default instance profile to the EC2 instances.

D.

Configure the iam-role-managed-policy-check AWS Config managed rule with a trigger type of configuration changes. Configure an automatic remediation action that invokes an AWS Lambda function to attach the default instance profile to the EC2 instances.

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Question # 52

An ecommerce company is receiving reports that its order history page is experiencing delays in reflecting the processing status of orders. The order processing system consists of an AWS Lambda function that uses reserved concurrency. The Lambda function processes order messages from an Amazon Simple Queue Service (Amazon SQS) queue and inserts processed orders into an Amazon DynamoDB table. The DynamoDB table has auto scaling enabled for read and write capacity.

Which actions should a DevOps engineer take to resolve this delay? (Choose two.)

Options:

A.

Check the ApproximateAgeOfOldestMessage metric for the SQS queue. Increase the Lambda function concurrency limit.

B.

Check the ApproximateAgeOfOldestMessage metnc for the SQS queue Configure a redrive policy on the SQS queue.

C.

Check the NumberOfMessagesSent metric for the SQS queue. Increase the SQS queue visibility timeout.

D.

Check the WriteThrottleEvents metric for the DynamoDB table. Increase the maximum write capacity units (WCUs) for the table's scaling policy.

E.

Check the Throttles metric for the Lambda function. Increase the Lambda function timeout.

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Question # 53

A company has an application that runs on Amazon EC2 instances in an Auto Scaling group. The application processes a high volume of messages from an Amazon Simple Queue Service (Amazon SQS) queue.

A DevOps engineer noticed that the application took several hours to process a group of messages from the SQS queue. The average CPU utilization of the Auto Scaling group did not cross the threshold of a target tracking scaling policy when processing the messages. The application that processes the SQS queue publishes logs to Amazon CloudWatch Logs.

The DevOps engineer needs to ensure that the queue is processed quickly.

Which solution meets these requirements with the LEAST operational overhead?

Options:

A.

Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Schedule an Amazon EventBridge rule to run the Lambda function every hour. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scal

B.

Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Create a CloudWatch subscription filter for the application logs with the Lambda function as the target. Create a target tracking scaling policy for the Auto Scaling group that

C.

Create a target tracking scaling policy for the Auto Scaling group. In the target tracking policy, use the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to calculate how many messages are in the queue for each number of instances by using metric math. Use the calculated attribute to scale in and out.

D.

Create an AWS Lambda function that logs the ApproximateNumberOfMessagesVisible attribute of the SQS queue to a CloudWatch Logs log group. Schedule an Amazon EventBridge rule to run the Lambda function every 5 minutes. Create a metric filter to count the number of log events from a CloudWatch logs group. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.

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Exam Code: DOP-C02
Exam Name: AWS Certified DevOps Engineer - Professional
Last Update: Jun 20, 2025
Questions: 322
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