Amazon Web Services DOP-C02 Study & Exam Dumps 2025

AWS Certified DevOps Engineer - Professional Questions and Answers

Question 1

A company is adopting AWS CodeDeploy to automate its application deployments for a Java-Apache Tomcat application with an Apache Webserver. The development team started with a proof of concept, created a deployment group for a developer environment, and performed functional tests within the application. After completion, the team will create additional deployment groups for staging and production.

The current log level is configured within the Apache settings, but the team wants to change this configuration dynamically when the deployment occurs, so that they can set different log level configurations depending on the deployment group without having a different application revision for each group.

How can these requirements be met with the LEAST management overhead and without requiring different script versions for each deployment group?

Options:

Tag the Amazon EC2 instances depending on the deployment group. Then place a script into the application revision that calls the metadata service and the EC2 API to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference the script as part of the AfterInstall lifecycle hook in the appspec.yml file.

Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ NAME to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file.

Create a CodeDeploy custom environment variable for each environment. Then place a script into the application revision that checks this environment variable to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the ValidateService lifecycle hook in the appspec.yml file.

Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ID to identify which deployment group the instance is part of to configure the log level settings. Reference this script as part of the Install lifecycle hook in the appspec.yml file.

Buy Now

Question 2

A company sends its AWS Network Firewall flow logs to an Amazon S3 bucket. The company then analyzes the flow logs by using Amazon Athena. The company needs to transform the flow logs and add additional data before the flow logs are delivered to the existing S3 bucket. Which solution will meet these requirements?

Options:

Create an AWS Lambda function to transform the data and to write a new object to the existing S3 bucket. Configure the Lambda function with an S3 trigger for the existing S3 bucket. Specify all object create events for the event type. Acknowledge the recursive invocation.

Enable Amazon EventBridge notifications on the existing S3 bucket. Create a custom EventBridge event bus. Create an EventBridge rule that is associated with the custom event bus. Configure the rule to react to all object create events for the existing S3 bucket and to invoke an AWS Step Functions workflow. Configure a Step Functions task to transform the data and to write the data into a new S3 bucket.

Create an Amazon EventBridge rule that is associated with the default EventBridge event bus. Configure the rule to react to all object create events for the existing S3 bucket. Define a new S3 bucket as the target for the rule. Create an EventBridge input transformation to customize the event before passing the event to the rule target.

Create an Amazon Data Firehose delivery stream that is configured with an AWS Lambda transformer. Specify the existing S3 bucket as the destination. Change the Network Firewall logging destination from Amazon S3 to Firehose.

Question 3

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

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

Get Free DOP-C02 Questions and Answers

New Year Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

DOP-C02: AWS Certified Professional Exam 2025 Study Guide Pdf and Test Engine

Related Amazon Web Services Exams

AWS Certified DevOps Engineer - Professional Questions and Answers

Options:

Answer:

Explanation:

Options:

Answer:

Options:

Answer:

Explanation:

CompTIA

Fortinet

Microsoft

Salesforce