Free Amazon Web Services DOP-C02 Practice Exam with Questions & Answers | Set: 11

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

CodeDeploy supports TimeBasedLinear traffic shifting for ECS blue/green deployments. Traffic increments by linearPercentage every linearInterval until 100%. This provides zero-downtime gradual rollout — as per CodeDeploy ECS Blue/Green Traffic Shifting documentation.

Activate AWS Control Tower Guardrail:

Use AWS Control Tower to activate a detective guardrail that checks whether RDS storage is encrypted.

Create SNS Topic for Notifications:

Set up an Amazon Simple Notification Service (SNS) topic in the audit account to receive notifications about non-compliant databases.

Create EventBridge Rule to Filter Non-compliant Events:

Create an Amazon EventBridge rule that filters events related to the guardrail ' s findings on non-compliant RDS instances.

Configure the rule to send notifications to the SNS topic when non-compliant events are detected.

Subscribe Security Engineer ' s Email to SNS Topic:

Subscribe the security engineer ' s email address to the SNS topic to receive notifications when non-compliant databases are detected.

By using AWS Control Tower to activate a detective guardrail and setting up SNS notifications for non-compliant events, the company can efficiently monitor and ensure that all RDS databases are encrypted at rest.

Step 1: Understanding Lambda Permissions and AWS Config

The custom AWS Config rule evaluates resources and invokes an AWS Lambda function when a compliance check is triggered. For AWS Config to invoke the Lambda function, it requires permission to do so.

Issue: The Lambda function fails to execute because AWS Config doesn ' t have permission to invoke it.

Action: Modify the resource-based policy of the Lambda function to grant AWS Config permission to invoke the Lambda function.

Why: Without this permission, AWS Config cannot trigger the Lambda function, which is why the evaluation fails.

AWS Systems Manager Patch Manager automates patch scanning and installation. Integrating with AWS Config enables compliance reporting and auto-remediation. This provides centralized patch compliance management per AWS Ops best practices.

Configure the Systems Manager Document to Use the aws-downloadContent Plugin with a sourceType of GitHub and sourcelnfo with the Repository Details:

The aws-downloadContent plugin can download content from various sources, including GitHub, which is necessary for bootstrapping the laptops with the code stored in the GitHub repository.

schemaVersion: ' 2.2 '

description: " Download and run bootstrap script from GitHub "

mainSteps:

- action: aws:downloadContent

name: downloadBootstrapScript

inputs:

sourceType: GitHub

sourceInfo: ' { " owner " : " my-org " , " repository " : " my-repo " , " path " : " scripts/bootstrap.sh " , " getOptions " : " branch:main " } '

destinationPath: /tmp/bootstrap.sh

- action: aws:runShellScript

name: runBootstrapScript

inputs:

runCommand:

- chmod +x /tmp/bootstrap.sh

- /tmp/bootstrap.sh

This setup ensures that the bootstrap code is downloaded from GitHub and executed on the laptops using Systems Manager.

To archive CloudWatch Logs to S3 with long-term retention, you need:

a streaming mechanism to move data from CloudWatch Logs to S3, and

an S3 Lifecycle policy to handle tiering and expiration.

Option B uses a CloudWatch Logs subscription filter that targets Amazon Data Firehose . Firehose provides managed, scalable streaming from CloudWatch Logs to S3 with optional buffering and transformation. This is the AWS-recommended pattern for exporting continuous log streams with minimal operational overhead. Option C is not valid because CloudWatch Logs subscription filters cannot directly target S3; they must target Kinesis, Firehose, or Lambda.

Once logs are in S3, the company wants to keep them rarely accessed after 90 days and retained for 10 years. Option D configures an S3 lifecycle policy to transition logs to S3 Glacier Instant Retrieval after 90 days, which is a low-cost archival tier with relatively fast access, and to expire (delete) logs after 3,650 days (10 years). This precisely matches the retention requirement.

Option E uses Reduced Redundancy, which is a legacy storage class and not optimized for long-term archival. Therefore, the correct combination is B and D .

To restore the functionality of the Auto Scaling group after the AMI was deleted, the DevOps engineer needs to create a new AMI and update the Auto Scaling group to use it. The DevOps engineer can create a new AMI by copying the most recent public AMI of the operating system that the EC2 instances use. This will ensure that the new AMI has the same operating system as the custom AMI that was deleted. The DevOps engineer can then create a new launch template that uses the new AMI and update the Auto Scaling group to use the new launch template. This will allow the Auto Scaling group to launch new instances with the new AMI.

 Create an Amazon Elastic File System (Amazon EFS) File System with Targets in Multiple Availability Zones:

Amazon EFS provides a scalable and highly available network file system that supports the NFS protocol. EFS is ideal for Linux instances as it allows multiple instances to read and write data concurrently.

Setting up EFS with targets in multiple Availability Zones ensures high availability and durability.