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The AWS Certified DevOps Engineer - Professional certification exam requires a deep understanding of AWS services, DevOps practices, continuous delivery, automation, and security. Candidates must have a solid understanding of the principles of DevOps and how to implement them in an AWS environment. They should also have experience in designing and implementing scalable, fault-tolerant, and highly available systems on AWS.

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The AWS Certified DevOps Engineer - Professional certification is intended for individuals who are responsible for designing, managing, and implementing DevOps practices and tools in their organizations. AWS Certified DevOps Engineer - Professional certification is ideal for DevOps engineers, software developers, system administrators, and IT professionals who want to demonstrate their expertise in AWS and DevOps.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q571-Q576):

NEW QUESTION # 571
A company has a website in an AWS Elastic Beanstalk load balancing and automatic scaling environment. This environment has an Amazon RDS MySQL instance configured as its database resource. After a sudden increase in traffic, the website started dropping traffic. An administrator discovered that the application on some instances is not responding as the result of out-of-memory errors. Classic Load Balancer marked those instances as out of service, and the health status of Elastic Beanstalk enhanced health reporting is degraded. However, Elastic Beanstalk did not replace those instances. Because of the diminished capacity behind the Classic Load Balancer, the application response times are slower for the customers. Which action will permanently fix this issue?

A. Write a cron script for restraining the web server process when memory is full, and deploy it with AWS Systems Manager.
B. Clone the Elastic Beanstalk environment. When the new environment is up, swap CNAME and terminate the earlier environment.
C. Temporarily change the maximum number of instances in the Auto Scaling group to allow the group to support more traffic.
D. Change the setting for the Auto Scaling group health check from Amazon EC2 to Elastic Load Balancing, and increase the capacity of the group.

Answer: C

NEW QUESTION # 572
An application is being deployed with two Amazon EC2 Auto Scaling groups, each configured with an Application Load Balancer. The application is deployed to one of the Auto Scaling groups and an Amazon Route 53 alias record is pointed to the Application Load Balancer of the last deployed Auto Scaling group.
Deployments alternate between the two Auto Scaling groups.
Home security devices are making requests into the application. The Development team notes that new requests are coming into the old stack days after the deployment. The issue is caused by devices that are not observing the Time to Live (TTL) setting on the Amazon Route 53 alias record.
What steps should the DevOps Engineer take to address the issue with requests coming to the old stacks, while creating minimal additional resources?

A. Reduce the application to one Application Load Balancer. Create two target groups named Blue and Green. Create a rule on the Application Load Balancer pointed to a single target group. Add logic to the deployment to update the Application Load Balancer rule to the target group of the newly deployed Auto Scaling group.
B. Move the application to an AWS Elastic Beanstalk application with two environments. Perform new deployments on the non-live environment. After a deployment, perform an Elastic Beanstalk CNAME swap to make the newly deployed environment the live environment.
C. Create an Amazon CloudFront distribution. Set the two existing Application Load Balancers as origins on the distribution. After a deployment, update the CloudFront distribution behavior to send requests to the newly deployed Auto Scaling group.
D. Create a fleet of Amazon EC2 instances running HAProxy behind an Application Load Balancer. The HAProxy instances will proxy the requests to one of the existing Auto Scaling groups. After a deployment the HAProxy instances are updated to send requests to the newly deployed Auto Scaling group.

Answer: A

NEW QUESTION # 573
A Developer is designing a continuous deployment workflow for a new Development team to facilitate the process for source code promotion in AWS. Developers would like to store and promote code for deployment from development to production while maintaining the ability to roll back that deployment if it fails.
Which design will incur the LEAST amount of downtime?

A. Create one repository in AWS CodeCommit. Create a development branch to hold merged changes. Use AWS CodeBuild to build and test the code stored in the development branch triggered on a new commit.
Merge to the master and deploy to production by using AWS CodeDeploy for a blue/green deployment.
B. Create one repository for development code in AWS CodeCommit and another repository to hold the production code. Use AWS CodeBuild to merge development and production repositories, and deploy to production by using AWS CodeDeploy for a blue/green deployment.
C. Create a shared Amazon S3 bucket for the Development team to store their code. Set up an Amazon CloudWatch Events rule to trigger an AWS Lambda function that deploys the code to production by using AWS CodeDeploy for a blue/green deployment.
D. Create one repository for each Developer in AWS CodeCommit and another repository to hold the production code. Use AWS CodeBuild to merge development and production repositories, and deploy to production by using AWS CodeDeploy for a blue/green deployment.

Answer: C

NEW QUESTION # 574
A DevOps engineer has automated a web service deployment using AWS CodePipeline with the following steps:
- An AWS CodeBuild project compiles the deployment artifact and runs
unit tests.
- An AWS CodeDeploy deployment group deploys the web service to Amazon
EC2 instances in the staging environment.
- A CodeDeploy deployment group deploys the web service to EC2
instances in the production environment.
The quality assurance (QA) team has asked for permission to inspect the build artifact before the deployment to the production environment occurs. The QA team wants to run an internal automated penetration testing tool (invoked using a REST API call) to run some manual tests.
Which combination of actions will fulfill this request? (Choose two.)

A. Modify the buildspec.yml file for the compilation stage to require manual approval before completion.
B. Update the CodeDeploy deployment group so it requires manual approval to proceed.
C. Update the pipeline to invoke a Lambda function that triggers the REST API for the automated penetration testing tool.
D. Insert a manual approval action between the test and deployment actions of the pipeline.
E. Update the pipeline to directly trigger the REST API for the automated penetration testing tool.

Answer: C,D

NEW QUESTION # 575
A company using AWS CodeCommit for source control wants to automate its continuous integration and continuous deployment pipeline on AWS in its development environment. The company has three requirements:
1. There must be a legal and a security review of any code change to make sure sensitive information is not leaked through the source code.
2. Every change must go through unit testing.
3. Every change must go through a suite of functional testing to ensure functionality.
In addition, the company has the following requirements for automation:
1. Code changes should automatically trigger the CI/CD pipellline.
2. Any failure in the pipeline should notify devops-admin@xyz.com.
3. There must be an approval to stage the assets to Amazon S3 after tests have been performed.
What should a DevOps Engineer do to meet all of these requirements while following CI/CD best practices?

A. Commit to the development branch and trigger AWS CodePipeline from the development branch.
Make an individual stage in CodePipeline for security review, unit tests, functional tests, and manual approval. Use Amazon CloudWatch metrics to detect changes in pipeline stages and Amazon SES for emailing devops-admin@xyz.com.
B. Commit to the development branch and trigger AWS CodePipeline from the development branch.
Make an individual stage in CodePipeline for security review, unit tests, functional tests, and manual approval. Use Amazon CloudWatch Events to detect changes in pipeline stages and Amazon SNS for emailing devops-admin@xyz.com.
C. Commit to mainline and trigger AWS CodePipeline from mainline. Make an individual stage in CodePipeline for security review, unit tests, functional tests, and manual approval. Use Amazon CloudWatch Events to detect changes in pipeline stages and Amazon SES for emailing devops- admin@xyz.com.
D. Commit to mainline and trigger AWS CodePipeline from mainline. Make an individual stage in CodePipeline for security review, unit tests, functional tests, and manual approval. Use AWS CloudTrail logs to detect changes in pipeline stages and Amazon SNS for emailing devops- admin@xyz.com.

Answer: B

NEW QUESTION # 576
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