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Free AWS-DEVOPS-ENGINEER-PROFESSIONAL Exam Braindumps (page: 6)

Page 5 of 53
PDF with 208 Questions

A company is using AWS CodePipeline to automate its release pipeline. AWS CodeDeploy is being used in the pipeline to deploy an application to Amazon ECS using the blue/green deployment model. The company wants to implement scripts to test the green version of the application before shifting tra c. These scripts will complete in 5 minutes or less. If errors are discovered during these tests, the application must be rolled back.
Which strategy will meet these requirements?

  1. Add a stage to the CodePipeline pipeline between the source and deploy stages. Use AWS CodeBuild to create an execution environment and build commands in the buildspec le to invoke test scripts. If errors are found, use the aws deploy stop-deployment command to stop the deployment.
  2. Add a stage to the CodePipeline pipeline between the source and deploy stages. Use this stage to execute an AWS Lambda function that will run the test scripts. If errors are found, use the aws deploy stop-deployment command to stop the deployment.
  3. Add a hooks section to the CodeDeploy AppSpec le. Use the AfterAllowTestTra c lifecycle event to invoke an AWS Lambda function to run the test scripts. If errors are found, exit the Lambda function with an error to trigger rollback.
  4. Add a hooks section to the CodeDeploy AppSpec le. Use the AfterAllowTra c lifecycle event to invoke the test scripts. If errors are found, use the aws deploy stop-deployment CLI command to stop the deployment.

Answer(s): C


Reference:

https://docs.aws.amazon.com/codedeploy/latest/userguide/reference-appspec- le-structure-hooks.html



A company requires an RPO of 2 hours and an RTO of 10 minutes for its data and application at all times. An application uses a MySQL database and Amazon
EC2 web servers. The development team needs a strategy for failover and disaster recovery. Which combination of deployment strategies will meet these requirements? (Choose two.)

  1. Create an Amazon Aurora cluster in one Availability Zone across multiple Regions as the data store. Use Aurora's automatic recovery capabilities in the event of a disaster.
  2. Create an Amazon Aurora global database in two Regions as the data store. In the event of a failure, promote the secondary Region as the master for the application.
  3. Create an Amazon Aurora multi-master cluster across multiple Regions as the data store. Use a Network Load Balancer to balance the database tra c in different Regions.
  4. Set up the application in two Regions and use Amazon Route 53 failover-based routing that points to the Application Load Balancers in both Regions. Use health checks to determine the availability in a given Region. Use Auto Scaling groups in each Region to adjust capacity based on demand.
  5. Set up the application in two Regions and use a multi-Region Auto Scaling group behind Application Load Balancers to manage the capacity based on demand. In the event of a disaster, adjust the Auto Scaling group's desired instance count to increase baseline capacity in the failover Region.

Answer(s): B,D



An Amazon EC2 instance is running in a Virtual Private Cloud (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 for this error? (Choose two.)

  1. The S3 bucket default encryption is enabled
  2. There is an error in the S3 bucket policy
  3. The object has been moved to Amazon Glacier
  4. There is an error in the IAM role con guration
  5. S3 versioning is enabled

Answer(s): B,D



A DevOps team manages an API running on-premises that serves as a backend for an Amazon API Gateway endpoint. Customers have been complaining about high response latencies, which the development team has veri ed using the API Gateway latency metrics in Amazon CloudWatch. To identify the cause, the team needs to collect relevant data without introducing additional latency.
Which actions should be taken to accomplish this? (Choose two.)

  1. Install the CloudWatch agent server side and con gure the agent to upload relevant logs to CloudWatch.
  2. Enable AWS X-Ray tracing in API Gateway, modify the application to capture request segments, and upload those segments to X-Ray during each request.
  3. Enable AWS X-Ray tracing in API Gateway, modify the application to capture request segments, and use the X-Ray daemon to upload segments to X-Ray.
  4. Modify the on-premises application to send log information back to API Gateway with each request.
  5. Modify the on-premises application to calculate and upload statistical data relevant to the API service requests to CloudWatch metrics.

Answer(s): A,C






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