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AWS DevOps Engineer Professional Exam Practice Questions – 14

Posted on December 17, 2020 By DesiBanjara No Comments on AWS DevOps Engineer Professional Exam Practice Questions – 14

Amazon AWS DevOps Engineer Professional Exam Practice Questions

Below are some Free practice questions for Amazon AWS Certification Exam – AWS DevOps Engineer Professional Exam which can help you to prepare for exam and pass with good marks. These are not real exam questions but similar to the questions you can get in exam so practicing these question will boost your confidence.

Question -72

A DevOps Engineer must improve the monitoring of a Finance team payments microservice that handles transactions for an e-commerce platform. The microservice runs on multiple Amazon EC2 instances. The Finance team would like to know the number of payments per minute, and the team would like to be notified when this metric falls below a specified threshold.
How can this be cost-effectively automated?

A. Have the Development team log successful transactions to an application log. Set up Logstash on each instance, which sends logs to an Amazon ES cluster. Create a Kibana dashboard for the Finance team that graphs the metric.

B. Have the Development team post the number of successful transactions to Amazon CloudWatch as a custom metric. Create a CloudWatch alarm when the threshold is breached and use Amazon SNS to notify the Finance team.

C. Have the Development team log successful transactions to an application log. On each instance, set up the Amazon CloudWatch Logs agent to send application logs to CloudWatch Logs. Use an EC2 instance to monitor a metric filter and send notifications to the Finance team.

D. Have the Development team log successful transactions to an application log. Set up the Amazon CloudWatch agent on each instance. Create a CloudWatch alarm when the threshold is breached and use Amazon SNS to notify the Finance team.

Correct Answer: B

Reference:

https://aws.amazon.com/premiumsupport/knowledge-center/cloudwatch-custom-metrics/



Question -73

A company is migrating an application to AWS that runs on a single Amazon EC2 instance. Because of licensing limitations, the application does not support horizontal scaling. The application will be using Amazon Aurora for its database.
How can the DevOps Engineer architect automated healing to automatically recover from EC2 and Aurora failures, in addition to recovering across Availability
Zones (AZs), in the MOST cost-effective manner?

A. Create an EC2 Auto Scaling group with a minimum and maximum instance count of 1, and have it span across AZs. Use a single-node Aurora instance.

B. Create an EC2 instance and enable instance recovery. Create an Aurora database with a read replica in a second AZ and promote it to a primary database instance if the primary database instance fails.

C. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to start a new EC2 instance in an available AZ when the instance status reaches a failure state. Create an Aurora database with a read replica in a second AZ and promote it to a primary database instance when the primary database instance fails.

D. Assign an Elastic IP address on the instance. Create a second EC2 instance in a second AZ. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to move the Elastic IP address to the second instance when the first instance fails. Use a single-node Aurora instance.

Correct Answer: C



Question -74

An Application team has three environments for their application: development, pre-production, and production. The team recently adopted AWS CodePipeline.
However, the team has had several deployments of misconfigured or nonfunctional development code into the production environment, resulting in user disruption and downtime. The DevOps Engineer must review the pipeline and add steps to identify problems with the application before it is deployed.
What should the Engineer do to identify functional issues during the deployment process? (Choose two.)

A. Use Amazon Inspector to add a test action to the pipeline. Use the Amazon Inspector Runtime Behavior Analysis Inspector rules package to check that the deployed code complies with company security standards before deploying it to production.

B. Using AWS CodeBuild to add a test action to the pipeline to replicate common user activities and ensure that the results are as expected before progressing to production deployment.

C. Create an AWS CodeDeploy action in the pipeline with a deployment configuration that automatically deploys the application code to a limited number of instances. The action then pauses the deployment so that the QA team can review the application functionality. When the review is complete, CodeDeploy resumes and deploys the application to the remaining production Amazon EC2 instances.

D. After the deployment process is complete, run a testing activity on an Amazon EC2 instance in a different region that accesses the application to simulate user behavior. If unexpected results occur, the testing activity sends a warning to an Amazon SNS topic. Subscribe to the topic to get updates.

E. Add an AWS CodeDeploy action in the pipeline to deploy the latest version of the development code to pre-production. Add a manual approval action in the pipeline so that the QA team can test and confirm the expected functionality. After the manual approval action, add a second CodeDeploy action that deploys the approved code to the production environment.

Correct Answer: BE

Reference:

https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-test

https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-deploy



Question -75

A DevOps Engineer is responsible for the deployment of a PHP application. The Engineer is working in a hybrid deployment, with the application running on both on-premises servers and Amazon EC2 instances. The application needs access to a database containing highly confidential information. Application instances need access to database credentials, which must be encrypted at rest and in transit before reaching the instances.

How should the Engineer automate the deployment process while also meeting the security requirements?

A. Use AWS Elastic Beanstalk with a PHP platform configuration to deploy application packages to the instances. Store database credentials on AWS Systems Manager Parameter Store using the Secure String data type. Define an IAM role for Amazon EC2 allowing access, and decrypt only the database credentials. Associate this role to all the instances.

B. Use AWS CodeDeploy to deploy application packages to the instances. Store database credentials on AWS Systems Manager Parameter Store using the Secure String data type. Define an IAM policy for allowing access, and decrypt only the database credentials. Attach the IAM policy to the role associated to the instance profile for CodeDeploy-managed instances, and to the role used for on-premises instances registration on CodeDeploy.

C. Use AWS CodeDeploy to deploy application packages to the instances. Store database credentials on AWS Systems Manager Parameter Store using the Secure String data type. Define an IAM role with an attached policy that allows decryption of the database credentials. Associate this role to all the instances and on-premises servers.

D. Use AWS CodeDeploy to deploy application packages to the instances. Store database credentials in the AppSpec file. Define an IAM policy for allowing access to only the database credentials. Attach the IAM policy to the role associated to the instance profile for CodeDeploy-managed instances and the role used for on-premises instances registration on CodeDeploy.

Correct Answer: C

Reference:

https://docs.aws.amazon.com/systems-manager/latest/userguide/managed_instances.html

https://docs.aws.amazon.com/codedeploy/latest/userguide/instances-on-premises-register-instance.html



Question -76

A company has a single Developer writing code for an automated deployment pipeline. The Developer is storing source code in an Amazon S3 bucket for each project. The company wants to add more Developers to the team but is concerned about code conflicts and lost work. The company also wants to build a test environment to deploy newer versions of code for testing and allow Developers to automatically deploy to both environments when code is changed in the repository.
What is the MOST efficient way to meet these requirements?

A. Create an AWS CodeCommit repository for each project, use the master branch for production code, and create a testing branch for code deployed to testing. Use feature branches to develop new features and pull requests to merge code to testing and master branches.

B. Create another S3 bucket for each project for testing code, and use an AWS Lambda function to promote code changes between testing and production buckets. Enable versioning on all buckets to prevent code conflicts.

C. Create an AWS CodeCommit repository for each project, and use the master branch for production and test code with different deployment pipelines for each environment. Use feature branches to develop new features.

D. Enable versioning and branching on each S3 bucket, use the master branch for production code, and create a testing branch for code deployed to testing. Have Developers use each branch for developing in each environment.

Correct Answer: C




Question -77

After presenting a working proof of concept for a new application that uses AWS API Gateway, a Developer must set up a team development environment for the project. Due to a tight timeline, the Developer wants to minimize time spent on infrastructure setup, and would like to reuse the code repository created for the proof of concept. Currently, all source code is stored in AWS CodeCommit.

Company policy mandates having alpha, beta, and production stages with separate Jenkins servers to build code and run tests for every stage. The Development
Manager must have the ability to block code propagation between admins at any time. The Security team wants to make sure that users will not be able to modify the environment without permission.

How can this be accomplished?

A. Create API Gateway alpha, beta, and production stages. Create a CodeCommit trigger to deploy code to the different stages using an AWS Lambda function.

B. Create API Gateway alpha, beta, and production stages. Create an AWS CodePipeline that pulls code from the CodeCommit repository. Create CodePipeline actions to deploy code to the API Gateway stages.

C. Create Jenkins servers for the alpha, beta, and production stages on Amazon EC2 instances. Create multiple CodeCommit triggers to deploy code to different stages using an AWS Lambda function.

D. Create an AWS CodePipeline pipeline that pulls code from the CodeCommit repository. Create alpha, beta, and production stages with Jenkins servers on CodePipeline.

Correct Answer: D

Reference:

https://docs.aws.amazon.com/codebuild/latest/userguide/sample-pipeline-multi-input-output.html



Question -78

An online company uses Amazon EC2 Auto Scaling extensively to provide an excellent customer experience while minimizing the number of running EC2 instances. The company’s self-hosted Puppet environment in the application layer manages the configuration of the instances. The IT manager wants the lowest licensing costs and wants to ensure that whenever the EC2 Auto Scaling group scales down, removed EC2 instances are deregistered from the Puppet master as soon as possible.

How can the requirement be met?

A. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. Use CodeDeploy to install the Puppet agent. When the Auto Scaling group scales out, run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 Auto Scaling lifecycle hook to trigger de-registration from the Puppet master. EC2_INSTANCE_TERMINATING

B. Bake the AWS CodeDeploy agent into the base AMI. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and execute a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the CodeDeploy ApplicationStop lifecycle hook to run a script to de-register the instance from the Puppet master.

C. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 user data instance stop script to run a script to de-register the instance from the Puppet master.

D. Bake the AWS Systems Manager agent into the base AMI. When the Auto Scaling group scales out, use the AWS Systems Manager to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the Systems Manager instance stop lifecycle hook to run a script to de-register the instance from the Puppet master.

Correct Answer: A




Previous->AWS DevOps Engineer Professional Exam Practice Questions – 13



More Amazon AWS Certification Exam Questions:

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AWS DevOps Engineer Professional Exam Tags:Amazon, Amazon AWS Certification Exam, Amazon CloudWatch, Amazon EC2, Amazon Route 53, Application Load Balancer, AutoScaling, AWS DevOps Engineer Professional Exam, AWS Lambda, Certification Exam, CloudFormation, CodeDeploy, EC2, EC2 Auto Scaling group, Kinesis, Practice Questions

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