DOP-C02 Exam Dumps - AWS Certified DevOps Engineer - Professional

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Question # 9

A company builds a container image in an AWS CodeBuild project by running Docker commands. After the container image is built, the CodeBuild project uploads the container image to an Amazon S3 bucket. The CodeBuild project has an 1AM service role that has permissions to access the S3 bucket.

A DevOps engineer needs to replace the S3 bucket with an Amazon Elastic Container Registry (Amazon ECR) repository to store the container images. The DevOps engineer creates an ECR private image repository in the same AWS Region of the CodeBuild project. The DevOps engineer adjusts the 1AM service role with the permissions that are necessary to work with the new ECR repository. The DevOps engineer also places new repository information into the docker build command and the docker push command that are used in the buildspec.yml file.

When the CodeBuild project runs a build job, the job fails when the job tries to access the ECR repository.

Which solution will resolve the issue of failed access to the ECR repository?

Update the buildspec.yml file to log in to the ECR repository by using the aws ecr get-login-password AWS CLI command to obtain an authentication token. Update the docker login command to use the authentication token to access the ECR repository.

Add an environment variable of type SECRETS_MANAGER to the CodeBuild project. In the environment variable, include the ARN of the CodeBuild project ' s lAM service role. Update the buildspec.yml file to use the new environment variable to log in with the docker login command to access the ECR repository.

Update the ECR repository to be a public image repository. Add an ECR repository policy that allows the 1AM service role to have access.

Update the buildspec.yml file to use the AWS CLI to assume the 1AM service role for ECR operations. Add an ECR repository policy that allows the 1AM service role to have access.

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Question # 10

A company needs to increase the security of the container images that run in its production environment. The company wants to integrate operating system scanning and programming language package vulnerability scanning for the containers in its CI/CD pipeline. The CI/CD pipeline is an AWS CodePipeline pipeline that includes an AWS CodeBuild project, AWS CodeDeploy actions, and an Amazon Elastic Container Registry (Amazon ECR) repository.

A DevOps engineer needs to add an image scan to the CI/CD pipeline. The CI/CD pipeline must deploy only images without CRITICAL and HIGH findings into production.

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

Use Amazon ECR basic scanning.

Use Amazon ECR enhanced scanning.

Configure Amazon ECR to submit a Rejected status to the CI/CD pipeline when the image scan returns CRITICAL or HIGH findings.

Configure an Amazon EventBridge rule to invoke an AWS Lambda function when the image scan is completed. Configure the Lambda function to consume the Amazon Inspector scan status and to submit an Approved or Rejected status to the CI/CD pipeline.

Configure an Amazon EventBridge rule to invoke an AWS Lambda function when the image scan is completed. Configure the Lambda function to consume the Clair scan status and to submit an Approved or Rejected status to the CI/CD pipeline.

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Question # 11

A company runs a fleet of Amazon EC2 instances in a VPC. The company ' s employees remotely access the EC2 instances by using the Remote Desktop Protocol (RDP). The company wants to collect metrics about how many RDP sessions the employees initiate every day. Which combination of steps will meet this requirement? (Select THREE.)

Create an Amazon EventBridge rule that reacts to EC2 Instance State-change Notification events.

Create an Amazon CloudWatch Logs log group. Specify the log group as a target for the EventBridge rule.

Create a flow log in VPC Flow Logs.

Create an Amazon CloudWatch Logs log group. Specify the log group as a destination for the flow log.

Create a log group metric filter.

Create a log group subscription filter. Use EventBridge as the destination.

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Question # 12

A company manages a web application that runs on Amazon EC2 instances behind an Application Load Balancer (ALB). The EC2 instances run in an Auto Scaling group across multiple Availability Zones. The application uses an Amazon RDS for MySQL DB instance to store the data. The company has configured Amazon Route 53 with an alias record that points to the ALB.

A new company guideline requires a geographically isolated disaster recovery (DR > site with an RTO of 4 hours and an RPO of 15 minutes.

Which DR strategy will meet these requirements with the LEAST change to the application stack?

Launch a replica environment of everything except Amazon RDS in a different Availability Zone Create an RDS read replica in the new Availability Zone: and configure the new stack to point to the local RDS DB instance. Add the new stack to the Route 53 record set by using a hearth check to configure a failover routing policy.

Launch a replica environment of everything except Amazon RDS in a different AWS. Region Create an RDS read replica in the new Region and configure the new stack to point to the local RDS DB instance. Add the new stack to the Route 53 record set by using a health check to configure a latency routing policy.

Launch a replica environment of everything except Amazon RDS ma different AWS Region. In the event of an outage copy and restore the latest RDS snapshot from the primary. Region to the DR Region Adjust the Route 53 record set to point to the ALB in the DR Region.

Launch a replica environment of everything except Amazon RDS in a different AWS Region. Create an RDS read replica in the new Region and configure the new environment to point to the local RDS DB instance. Add the new stack to the Route 53 record set by using a health check to configure a failover routing policy. In the event of an outage promote the read replica to primary.

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Question # 13

A company releases a new application in a new AWS account. The application includes an AWS Lambda function that processes messages from an Amazon Simple Queue Service (Amazon SOS) standard queue. The Lambda function stores the results in an Amazon S3 bucket for further downstream processing. The Lambda function needs to process the messages within a specific period of time after the messages are published. The Lambda function has a batch size of 10 messages and takes a few seconds to process a batch of messages.

As load increases on the application ' s first day of service, messages in the queue accumulate at a greater rate than the Lambda function can process the messages. Some messages miss the required processing timelines. The logs show that many messages in the queue have data that is not valid. The company needs to meet the timeline requirements for messages that have valid data.

Which solution will meet these requirements?

Increase the Lambda function ' s batch size. Change the SOS standard queue to an SOS FIFO queue. Request a Lambda concurrency increase in the AWS Region.

Reduce the Lambda function ' s batch size. Increase the SOS message throughput quota. Request a Lambda concurrency increase in the AWS Region.

Increase the Lambda function ' s batch size. Configure S3 Transfer Acceleration on the S3 bucket. Configure an SOS dead-letter queue.

Keep the Lambda function ' s batch size the same. Configure the Lambda function to report failed batch items. Configure an SOS dead-letter queue.

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Answer:

Explanation:

Step 1: Handling Invalid Data with Failed Batch ItemsThe Lambda function is processing batches of messages, and some messages contain invalid data, causing processing delays. Lambda provides the capability to report failed batch items, which allows valid messages to be processed while skipping invalid ones. This functionality ensures that the valid messages are processed within the required timeline.

Action: Keep the Lambda function ' s batch size the same and configure it to report failed batch items.

Why: By reporting failed batch items, the Lambda function can skip invalid messages and continue processing valid ones, ensuring that they meet the processing timeline.

[Reference: AWS documentation on Lambda batch item failure handling., Step 2: Using an SQS Dead-Letter Queue (DLQ)Configuring a dead-letter queue (DLQ) for SQS will ensure that messages with invalid data, or those that cannot be processed successfully, are moved to the DLQ. This prevents such messages from clogging the queue and allows the system to focus on processing valid messages., Action: Configure an SQS dead-letter queue for the main queue., Why: A DLQ helps isolate problematic messages, preventing them from continuously reappearing in the queue and causing processing delays for valid messages., Reference: AWS documentation on Amazon SQS Dead-Letter Queues., Step 3: Maintaining the Lambda Functionâ€™s Batch SizeKeeping the current batch size allows the Lambda function to continue processing multiple messages at once. By addressing the failed items separately, there's no need to increase or reduce the batch size., Action: Maintain the Lambda function's current batch size., Why: Changing the batch size is unnecessary if the invalid messages are properly handled by reporting failed items and using a DLQ., This corresponds to Option D: Keep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SQS dead-letter queue., , , , ]

Question # 14

A company uses AWS CodePipeline pipelines to automate releases of its application A typical pipeline consists of three stages build, test, and deployment. The company has been using a separate AWS CodeBuild project to run scripts for each stage. However, the company now wants to use AWS CodeDeploy to handle the deployment stage of the pipelines.

The company has packaged the application as an RPM package and must deploy the application to a fleet of Amazon EC2 instances. The EC2 instances are in an EC2 Auto Scaling group and are launched from a common AMI.

Which combination of steps should a DevOps engineer perform to meet these requirements? (Choose two.)

Create a new version of the common AMI with the CodeDeploy agent installed. Update the IAM role of the EC2 instances to allow access to CodeDeploy.

Create a new version of the common AMI with the CodeDeploy agent installed. Create an AppSpec file that contains application deployment scripts and grants access to CodeDeploy.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the Auto Scaling group as the deployment target. Add a step to the CodePipeline pipeline to use EC2 Image Builder to create a new AMI. Configure CodeDeploy to deploy the newly created AMI.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the Auto Scaling group as the deployment target. Update the CodePipeline pipeline to use the CodeDeploy action to deploy the application.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the EC2 instances that are launched from the common AMI as the deployment target. Update the CodePipeline pipeline to use the CodeDeploy action to deploy the application.

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Question # 15

An Amazon EC2 instance is running in a VPC and needs to download an object from a restricted Amazon S3 bucket. When the DevOps engineer tries to download the object, an AccessDenied error is received,

What are the possible causes tor this error? (Select TWO,)

The 53 bucket default encryption is enabled.

There is an error in the S3 bucket policy.

The object has been moved to S3 Glacier.

There is an error in the IAM role configuration.

S3 Versioning is enabled.

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Question # 16

A company has an on-premises application that is written in Go. A DevOps engineer must move the application to AWS. The company ' s development team wants to enable blue/green deployments and perform A/B testing.

Which solution will meet these requirements?

Deploy the application on an Amazon EC2 instance, and create an AMI of the instance. Use the AMI to create an automatic scaling launch configuration that is used in an Auto Scaling group. Use Elastic Load Balancing to distribute traffic. When changes are made to the application, a new AMI will be created, which will initiate an EC2 instance refresh.

Use Amazon Lightsail to deploy the application. Store the application in a zipped format in an Amazon S3 bucket. Use this zipped version to deploy new versions of the application to Lightsail. Use Lightsail deployment options to manage the deployment.

Use AWS CodeArtifact to store the application code. Use AWS CodeDeploy to deploy the application to a fleet of Amazon EC2 instances. Use Elastic Load Balancing to distribute the traffic to the EC2 instances. When making changes to the application, upload a new version to CodeArtifact and create a new CodeDeploy deployment.

Use AWS Elastic Beanstalk to host the application. Store a zipped version of the application in Amazon S3. Use that location to deploy new versions of the application. Use Elastic Beanstalk to manage the deployment options.

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