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Free AWS Certified DevOps Engineer - Professional DOP-C02 Exam Braindumps (page: 39)

Page 38 of 90
PDF with 354 Questions

A company has microservices running in AWS Lambda that read data from Amazon DynamoDB. The Lambda code is manually deployed by developers after successful testing. The company now needs the tests and deployments be automated and run in the cloud. Additionally, traffic to the new versions of each microservice should be incrementally shifted over time after deployment.
What solution meets all the requirements, ensuring the MOST developer velocity?

  1. Create an AWS CodePipeline configuration and set up a post-commit hook to trigger the pipeline after tests have passed. Use AWS CodeDeploy and create a Canary deployment configuration that specifies the percentage of traffic and interval.
  2. Create an AWS CodeBuild configuration that triggers when the test code is pushed. Use AWS CloudFormation to trigger an AWS CodePipeline configuration that deploys the new Lambda versions and specifies the traffic shift percentage and interval.
  3. Create an AWS CodePipeline configuration and set up the source code step to trigger when code is pushed. Set up the build step to use AWS CodeBuild to run the tests. Set up an AWS CodeDeploy configuration to deploy, then select the CodeDeployDefault.LambdaLinear10PercentEvery3Minutes option.
  4. Use the AWS CLI to set up a post-commit hook that uploads the code to an Amazon S3 bucket after tests have passed Set up an S3 event trigger that runs a Lambda function that deploys the new version. Use an interval in the Lambda function to deploy the code over time at the required percentage.

Answer(s): C



A company is building a web and mobile application that uses a serverless architecture powered by AWS Lambda and Amazon API Gateway. The company wants to fully automate the backend Lambda deployment based on code that is pushed to the appropriate environment branch in an AWS CodeCommit repository.
The deployment must have the following:
• Separate environment pipelines for testing and production
• Automatic deployment that occurs for test environments only
Which steps should be taken to meet these requirements?

  1. Configure a new AWS CodePipeline service. Create a CodeCommit repository for each environment. Set up CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
  2. Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create a CodeCommit repository for each environment. Set up each CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
  3. Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Set up each CodePipeline to retrieve the source code from the appropriate branch in the repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
  4. Create an AWS CodeBuild configuration for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Push the Lambda function code to an Amazon S3 bucket. Set up the deployment step to deploy the Lambda functions from the S3 bucket.

Answer(s): C



A DevOps engineer wants to find a solution to migrate an application from on premises to AWS. The application is running on Linux and needs to run on specific versions of Apache Tomcat, HAProxy, and Varnish Cache to function properly. The application's operating system-level parameters require tuning. The solution must include a way to automate the deployment of new application versions. The infrastructure should be scalable and faulty servers should be replaced automatically.
Which solution should the DevOps engineer use?

  1. Upload the application as a Docker image that contains all the necessary software to Amazon ECR. Create an Amazon ECS cluster using an AWS Fargate launch type and an Auto Scaling group. Create an AWS CodePipeline pipeline that uses Amazon ECR as a source and Amazon ECS as a deployment provider.
  2. Upload the application code to an AWS CodeCommit repository with a saved configuration file to configure and install the software. Create an AWS Elastic Beanstalk web server tier and a load balanced-type environment that uses the Tomcat solution stack. Create an AWS CodePipeline pipeline that uses CodeCommit as a source and Elastic Beanstalk as a deployment provider.
  3. Upload the application code to an AWS CodeCommit repository with a set of .ebextensions files to configure and install the software. Create an AWS Elastic Beanstalk worker tier environment that uses the Tomcat solution stack. Create an AWS CodePipeline pipeline that uses CodeCommit as a source and Elastic Beanstalk as a deployment provider.
  4. Upload the application code to an AWS CodeCommit repository with an appspec.yml file to configure and install the necessary software. Create an AWS CodeDeploy deployment group associated with an Amazon EC2 Auto Scaling group. Create an AWS CodePipeline pipeline that uses CodeCommit as a source and CodeDeploy as a deployment provider.

Answer(s): D



A DevOps engineer is using AWS CodeDeploy across a fleet of Amazon EC2 instances in an EC2 Auto Scaling group. The associated CodeDeploy deployment group, which is integrated with EC2 Auto Scaling, is configured to perform in-place deployments with CodeDeployDefault.OneAtATime. During an ongoing new deployment, the engineer discovers that, although the overall deployment finished successfully, two out of five instances have the previous application revision deployed. The other three instances have the newest application revision.
What is likely causing this issue?

  1. The two affected instances failed to fetch the new deployment.
  2. A failed AfterInstall lifecycle event hook caused the CodeDeploy agent to roll back to the previous version on the affected instances.
  3. The CodeDeploy agent was not installed in two affected instances.
  4. EC2 Auto Scaling launched two new instances while the new deployment had not yet finished, causing the previous version to be deployed on the affected instances.

Answer(s): D






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