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AWS Certified Professional DOP-C01 Exam Dumps

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Total 272 questions

AWS Certified DevOps Engineer - Professional Questions and Answers

Question 29

A development team manages website deployments using AWS CodeDeploy blue/green deployments. The application is running on Amazon EC2 instances behind an Application Load Balancer in an Auto Scaling group.

When deploying a new revision, the team notices the deployment eventually fails, but it takes a long time to fail. After further inspection, the team discovers the AllowTrafflc lifecycle event ran for an hour and eventually failed without providing any other information. The team wants to ensure failure notices are delivered more quickly while maintaining application availability even upon failure.

Which combination of actions should be taken to meet these requirements? (Select TWO.)

Options:

A.

Change the deployment configuration to CodeDeployDefault.AIIAtOnce to speed up the deployment process by deploying to all of the instances at the same time.

B.

Create a CodeDeploy trigger for the deployment failure event and make the deployment fail as soon as a single health check failure is detected.

C.

Reduce the HealthChecklntervalSeconds and UnhealthyThresholdCount values within the target group health checks to decrease the amount of time it takes for the application to be considered unhealthy.

D.

Use the appspec.yml file to run a script on the AllowTraffic hook to perform lighter health checks on the application instead of making CodeDeploy wait for the target group health checks to pass.

E.

Use the appspec.yml file to run a script on the BeforeAllowTraffic hook to perform health checks on the application and fail the deployment if the health checks performed by the script are not successful.

Question 30

A company is beginning to move to the AWS Cloud. Internal customers are classified into two groups according to their AWS skills: beginners and experts.

The DevOps Engineer needs to build a solution to allow beginners to deploy a restricted set of AWS architecture blueprints expresses as AWS CloudFormation templates. Deployment should only be possible on predetermined Virtual Private Clouds (VPCs). However, expert users should be able to deploy blueprints without constraints. Experts should also be able to access other AWS services, as needed.

How can the Engineer implement a solution to meet these requirements with the LEAST amount of overhead?

Options:

A.

Apply constraints to the parameters in the templates, limiting the VPCs available for deployments. Store the templates on Amazon S3. Create an IAM group for beginners and give them access to the templates and CloudFormation. Create a separate group for experts, giving them access to the templates, CloudFormation, and other AWS services.

B.

Store the templates on Amazon S3. Use AWS Service Catalog to create a portfolio of products based on those templates. Apply template constraints to the products with rules limiting VPCs available for deployments. Create an IAM group for beginners giving them access to the portfolio. Create a separate group for experts giving them access to the templates, CloudFormation, and other AWS services.

C.

Store the templates on Amazon S3. Use AWS Service Catalog to create a portfolio of products based on those templates. Create an IAM role restricting VPCs available for creation of AWS resources. Apply a launch constraint to the products using this role. Create an IAM group for beginners giving them access to the portfolio. Create a separate group for experts giving them access to the portfolio and other AWS services.

D.

Create two templates for each architecture blueprint where only one of them limits the VPC available for deployments. Store the templates in Amazon DynamoDB. Create an IAM group for beginners giving them access to the constrained templates and CloudFormation. Create a separate group for experts giving them access to the unconstrained templates, CloudFormation, and other AWS services.

Question 31

A company has a mission-critical application on AWS that uses automatic scaling. The company wants the deployment lifecycle to meet the following parameters

•The application must be deployed one instance at a time to ensure the remaining fleet continues to serve traffic.

•the application is CPU intensive and must ho closely monitored

•the deployment must automatically roll back if the CPU utilization of the deployment instance exceeds 85%

Which solution will meet these requirements'?

Options:

A.

Use AWS CloudForrnation to create an AWS Step Functions state machine and Auto Scaling lifecycle hooks to move to one instance at a time into a wait state. Use AWS Systems Manager automation to deploy the update to each instance and move it back into the Auto Scaling group using the heartbeat timeout

B.

Use AWS CodeDeploy with Amazon EC2 Auto Scaling Configure an alarm tied to the CPU utilization metric Use the CodeDeployDefault OneAtAtime configuration as a deployment strategy Configure automatic rollbacks within the deployment group to roll back the deployment if the alarm thresholds are breached

C.

Use AWS Elastic Beanstalk for load balancing and AWS Auto Scaling Configure an alarm tied to the CPU utilization metric Configure rolling deployments with a fixed batch size of one instance Enable enhanced health to monitor the status of the deployment and roll back based on the alarm previously created

D.

Use AWS Systems Manager to perform a blue/green deployment with Amazon EC2 Auto Scaling Configure an alarm tied to the CPU utilization metric Deploy updates one at a time Configure automatic rollbacks within the Auto Scaling group to roll back the deployment if the alarm thresholds are breached.

Question 32

A company is using an AWS CloudFormation template to deploy web applications. The template requires that manual changes be made for each of the three major environments: production, staging, and development. The current sprint includes the new implementation and configuration of AWS CodePipeline for automated deployments.

What changes should the DevOps Engineer make to ensure that the CloudFormation template is reusable across multiple pipelines?

Options:

A.

Use a CloudFormation custom resource to query the status of the CodePipeline to determine which environment is launched. Dynamically alter the launch configuration of the Amazon EC2 instances.

B.

Set up a CodePipeline pipeline for each environment to use input parameters. Use CloudFormation mappings to switch associated UserData for the Amazon EC2 instances to match the environment being launched.

C.

Set up a CodePipeline pipeline that has multiple stages, one for each development environment. Use AWS Lambda functions to trigger CloudFormation deployments to dynamically alter the UserData of the Amazon EC2 instances launched in each environment.

D.

Use CloudFormation input parameters to dynamically alter the LaunchConfiguration and UserData sections of each Amazon EC2 instance every time the CloudFormation stack is updated.

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Total 272 questions