Amazon Web Services DOP-C02 Exam Questions Free Practice Test

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Questions # 21:

A company has application code in an AWS CodeConnections compatible Git repository. The company wants to configure unit tests to run when pull requests are opened. The company wants to ensure that the test status is visible in pull requests when the tests are completed. The company wants to save output data files that the tests generate to an Amazon S3 bucket after the tests are finished. Which combination of solutions will meet these requirements? (Select THREE.)

Options:

Create an IAM service role to allow access to the resources that are required to run the tests.

Create a pipeline in AWS CodePipeline that has a test stage. Create a trigger to run the pipeline when pull requests are created or updated. Add a source action to report test results.

Create an AWS CodeBuild project to run the tests. Enable webhook triggers to run the tests when pull requests are created or updated. Enable build status reporting to report test results.

Create a buildspec.yml file that has a reports section to upload output files when the tests have finished running.

Create a buildspec.yml file that has an artifacts section to upload artifacts when the tests have finished running.

Create an appspec.yml file that has a files section to upload output files when the tests have finished running.

Expert Solution

Questions # 22:

A company uses AWS Organizations and AWS Control Tower to manage all the company's AWS accounts. The company uses the Enterprise Support plan.

A DevOps engineer is using Account Factory for Terraform (AFT) to provision new accounts. When new accounts are provisioned, the DevOps engineer notices that the support plan for the new accounts is set to the Basic Support plan. The DevOps engineer needs to implement a solution to provision the new accounts with the Enterprise Support plan.

Which solution will meet these requirements?

Options:

Use an AWS Config conformance pack to deploy the account-part-of-organizations AWS Config rule and to automatically remediate any noncompliant accounts.

Create an AWS Lambda function to create a ticket for AWS Support to add the account to the Enterprise Support plan. Grant the Lambda function the support:ResolveCase permission.

Add an additional value to the control_tower_parameters input to set the AWSEnterpriseSupport parameter as the organization's management account number.

Set the aft_feature_enterprise_support feature flag to True in the AFT deployment input configuration. Redeploy AFT and apply the changes.

Expert Solution

Questions # 23:

A growing company manages more than 50 accounts in an organization in AWS Organizations. The company has configured its applications to send logs to Amazon CloudWatch Logs.

A DevOps engineer needs to aggregate logs so that the company can quickly search the logs to respond to future security incidents. The DevOps engineer has created a new AWS account for centralized monitoring.

Which combination of steps should the DevOps engineer take to make the application logs searchable from the monitoring account? (Select THREE.)

Options:

In the monitoring account, download an AWS CloudFormation template from CloudWatch to use in Organizations. Use CloudFormation StackSets in the organization's management account to deploy the CloudFormation template to the entire organization.

Create an AWS CloudFormation template that defines an IAM role. Configure the role to allow logs-amazonaws.com to perform the logs:Link action if the aws:ResourceAccount property is equal to the monitoring account ID. Use CloudFormation StackSets in the organization's management account to deploy the CloudFormation template to the entire organization.

Create an IAM role in the monitoring account. Attach a trust policy that allows logs.amazonaws.com to perform the iam:CreateSink action if the aws:PrincipalOrgld property is equal to the organization ID.

In the organization's management account, enable the logging policies for the organization.

use CloudWatch Observability Access Manager in the monitoring account to create a sink. Allow logs to be shared with the monitoring account. Configure the monitoring account data selection to view the Observability data from the organization ID.

In the monitoring account, attach the CloudWatchLogsReadOnlyAccess AWS managed policy to an IAM role that can be assumed to search the logs.

Expert Solution

Questions # 24:

A company is developing a web application that runs on Amazon EC2 Linux instances. The application requires monitoring of custom performance metrics. The company must collect metrics for API response times and database query latency across multiple instances. Which solution will generate the custom metrics with the LEAST operational overhead?

Options:

Install the Amazon CloudWatch agent on the instances. Configure the agent to collect the custom metrics. Instrument the application to send the metrics to the agent.

Use Amazon Managed Service for Prometheus to scrape the custom metrics from the application. Use the Amazon CloudWatch agent to forward the metrics to CloudWatch.

Create a custom AWS Lambda function that polls the application endpoints and database at regular intervals. Program the Lambda function to calculate the custom metrics and to send the metrics to Amazon CloudWatch by using PutMetricData API calls.

Implement custom logging in the application code to record the custom metrics. Use Amazon CloudWatch Logs Insights to extract and analyze the metrics.

Expert Solution

Questions # 25:

A company’s web app runs on EC2 with a relational database. The company wants highly available multi-Region architecture with latency-based routing for global customers.

Which solution meets these requirements?

Options:

ALB in each Region with Auto Scaling groups; Aurora global database with read replicas; Route 53 latency-based routing to ALBs.

ALB in each Region with Auto Scaling groups; RDS primary in one Region with read replicas in others; Route 53 failover routing to ALBs.

Elastic Beanstalk with ALB in each Region; Aurora global database with read replicas; CloudFront with custom origins for ALBs; Route 53 latency-based routing to CloudFront.

Elastic Beanstalk with ALB in each Region; RDS primary in one Region with read replicas; CloudFront with custom origins for ALBs; Route 53 failover routing to CloudFront.

Expert Solution

Questions # 26:

A company is using AWS CodeDeploy to automate software deployment. The deployment must meet these requirements:

• A number of instances must be available to serve traffic during the deployment Traffic must be balanced across those instances, and the instances must automatically heal in the event of failure.

• A new fleet of instances must be launched for deploying a new revision automatically, with no manual provisioning.

• Traffic must be rerouted to the new environment to half of the new instances at a time. The deployment should succeed if traffic is rerouted to at least half of the instances; otherwise, it should fail.

• Before routing traffic to the new fleet of instances, the temporary files generated during the deployment process must be deleted.

• At the end of a successful deployment, the original instances in the deployment group must be deleted immediately to reduce costs.

How can a DevOps engineer meet these requirements?

Options:

Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group with the deployment group. Use the Automatically copy Auto Scaling group option. and use CodeDeployDefault.OneAtAtime as the deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the AllowTraffic hook within appspec.yml to delete the temporary files.

Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, create a custom deployment configuration with minimum healthy hosts defined as 50%. and assign the configuration to the deployment group. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, an

Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically copy Auto scaling group option, and use CodeDeployDefault.HalfAtAtime as the deployment configuration. Instruct AWSCodeDeploy to terminate the original instances in the deployment group, and use the BeforeAlIowTraffic hook within appspec.yml to delete t

Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group and Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefaulLAIIatOnce as a deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BlockTraffic hook within appspec.yml to delete the temporary fi

Expert Solution

Answer

Explanation

Step 1: Use a Blue/Green Deployment StrategyA blue/green deployment strategy is necessary to meet the requirement of launching a new fleet of instances for each deployment and ensuring availability. In a blue/green deployment, the new version (green environment) is deployed to a separate set of instances, while the old version (blue environment) remains active. After testing the new version, traffic can be gradually shifted.

Action: Use AWS CodeDeploy's blue/green deployment configuration.

Why: Blue/green deployment minimizes downtime and ensures that traffic is shifted only to healthy instances.

[Reference: AWS documentation on Blue/Green Deployment., Step 2: Use an Application Load Balancer and Auto Scaling GroupThe Application Load Balancer (ALB) is essential to balance traffic across multiple instances, and Auto Scaling ensures the deployment scales automatically to meet demand., Action: Associate the Auto Scaling group and Application Load Balancer target group with the deployment group., Why: This configuration ensures that traffic is evenly distributed and that instances automatically scale based on traffic load., Reference: AWS documentation on Deploying with Auto Scaling and Load Balancing., Step 3: Use Custom Deployment ConfigurationThe company requires that traffic be rerouted to at least half of the instances to succeed. AWS CodeDeploy allows you to configure custom deployment settings with specific thresholds for healthy hosts., Action: Create a custom deployment configuration where 50% of the instances must be healthy., Why: This ensures that the deployment continues only if at least 50% of the new instances are healthy., Reference: AWS documentation on Deployment Configurations., Step 4: Clean Temporary Files Using HooksBefore routing traffic to the new environment, the temporary files generated during the deployment must be deleted. This can be achieved using the BeforeAllowTraffic hook in the appspec.yml file., Action: Use the BeforeAllowTraffic lifecycle event hook to clean up temporary files before routing traffic to the new environment., Why: This ensures that the environment is clean before the new instances start serving traffic., Reference: AWS documentation on AppSpec File Hooks., Step 5: Terminate Original Instances After DeploymentAfter a successful deployment, AWS CodeDeploy can automatically terminate the original instances (blue environment) to save costs., Action: Instruct AWS CodeDeploy to terminate the original instances after the new instances are healthy., Why: This helps in cost reduction by removing unused instances after the deployment., Reference: AWS documentation on Terminate Old Instances., This corresponds to Option C: Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefault.HalfAtATime as the deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BeforeAllowTraffic hook within appspec.yml to delete the temporary files., , ]

Questions # 27:

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?

Options:

The two affected instances failed to fetch the new deployment.

A failed Afterinstall lifecycle event hook caused the CodeDeploy agent to roll back to the previous version on the affected instances

The CodeDeploy agent was not installed in two affected instances.

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.

Expert Solution

Questions # 28:

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?

Options:

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

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

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

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

Expert Solution

Answer

Explanation

The correct answer is D. The scenario requires a solution that can migrate an application from on premises to AWS, run on specific versions of Apache Tomcat, HAProxy, and Varnish Cache, tune the operating system-level parameters, automate the deployment of new application versions, and scale and replace faulty servers automatically. Option D meets all these requirements by using AWS CodeCommit, AWS CodeDeploy, AWS CodePipeline, and Amazon EC2 Auto Scaling. AWS CodeCommit is a fully managed source control service that hosts Git repositories and works with Git-based tools. AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services, including Amazon EC2, AWS Fargate, AWS Lambda, and on-premises servers. AWS CodePipeline is a fully managed continuous delivery service that helps automate the release pipelines for fast and reliable application updates. Amazon EC2 Auto Scaling helps maintain application availability and allows scaling of Amazon EC2 capacity up or down automatically according to the defined conditions. By using these services together, the DevOps engineer can migrate the application code to AWS, configure and install the necessary software using the appspec.yml file, automate the deployment process using the pipeline, and scale and replace the servers using the Auto Scaling group.

Option A is incorrect because AWS Fargate is a serverless compute engine for containers that works with Amazon ECS and Amazon EKS. Fargate removes the need to provision and manage servers, but it also limits the ability to tune the operating system-level parameters, which is a requirement in the scenario. Moreover, Fargate does not support HAProxy and Varnish Cache as sidecar containers, which are needed to run the application properly.

Option B is incorrect because AWS Elastic Beanstalk is a fully managed service that automates the deployment and scaling of web applications and services using familiar servers such as Apache, Nginx, Passenger, and IIS. However, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly. Moreover, Elastic Beanstalk web server tier environments are designed to serve HTTP requests, not to process background tasks, which is the purpose of worker tier environments.

Option C is incorrect because AWS Elastic Beanstalk worker tier environments are designed to process background tasks using a daemon process that runs on each Amazon EC2 instance in the environment. Worker tier environments are not suitable for running web applications that serve HTTP requests, which is the case in the scenario. Moreover, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly.

AWS CodeCommit

AWS CodeDeploy

AWS CodePipeline

Amazon EC2 Auto Scaling

AWS Fargate

AWS Elastic Beanstalk

Questions # 29:

A company is performing vulnerability scanning for all Amazon EC2 instances across many accounts. The accounts are in an organization in AWS Organizations. Each account's VPCs are attached to a shared transit gateway. The VPCs send traffic to the internet through a central egress VPC. The company has enabled Amazon Inspector in a delegated administrator account and has enabled scanning for all member accounts.

A DevOps engineer discovers that some EC2 instances are listed in the "not scanning" tab in Amazon Inspector.

Which combination of actions should the DevOps engineer take to resolve this issue? (Choose three.)

Options:

Verify that AWS Systems Manager Agent is installed and is running on the EC2 instances that Amazon Inspector is not scanning.

Associate the target EC2 instances with security groups that allow outbound communication on port 443 to the AWS Systems Manager service endpoint.

Grant inspector: StartAssessmentRun permissions to the IAM role that the DevOps engineer is using.

Configure EC2 Instance Connect for the EC2 instances that Amazon Inspector is not scanning.

Associate the target EC2 instances with instance profiles that grant permissions to communicate with AWS Systems Manager.

Create a managed-instance activation. Use the Activation Code and the Activation ID to register the EC2 instances.

Expert Solution

Questions # 30:

A company has an AWS CodeDeploy application. The application has a deployment group that uses a single tag group to identify instances for the deployment of ApplicationA. The single tag group configuration identifies instances that have Environment=Production and Name=ApplicattonA tags for the deployment of ApplicationA.

The company launches an additional Amazon EC2 instance with Department=Marketing Environment^Production. and Name=ApplicationB tags. On the next CodeDeploy deployment of ApplicationA. the additional instance has ApplicationA installed on it. A DevOps engineer needs to configure the existing deployment group to prevent ApplicationA from being installed on the additional instance

Which solution will meet these requirements?

Options:

Change the current single tag group to include only the Environment=Production tag Add another single tag group that includes only the Name=ApplicationA tag.

Change the current single tag group to include the Department=Marketmg Environment=Production and Name=ApplicationAtags

Add another single tag group that includes only the Department=Marketing tag. Keep the Environment=Production and Name=ApplicationA tags with the current single tag group

Change the current single tag group to include only the Environment=Production tag Add another single tag group that includes only the Department=Marketing tag

Expert Solution

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