Pass the Amazon Web Services AWS Certified Professional DOP-C02 Questions and answers with CertsForce

Step 1: Enabling AWS Config for the OrganizationThe first step is to enable AWS Config across the AWS Organization. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. By enabling AWS Config, you can ensure that all S3 buckets within the organization are tracked and evaluated according to compliance rules.

Action: Turn on AWS Config for all AWS accounts in the organization.

Why: AWS Config will help monitor all resources (like S3 buckets) in real time to detect whether they are compliant with security policies.

To meet the requirements, the DevOps engineer needs to configure the CloudWatch alarm to stop the EC2 instances when the average of the NetworkPacketsIn metric is less than 5 for at least 3 hours in a 12-hour time window. This means that the alarm should trigger when 3 out of 12 datapoints are below the threshold of 5. The alarm should also treat missing data as not breaching the threshold, so that the EC2 instances continue to run if there is no data for the metric during the evaluation period. The DevOps engineer can add an EC2 action to stop the instance when the alarm enters the ALARM state, which is a built-in action type for CloudWatch alarms.

CodeDeploy deployment failures must be diagnosed using deployment-specific logs and related application logs. CodeDeploy writes detailed logs on the target EC2 instances under /opt/codedeploy-agent/deployment-root/ (for example in logs and deployment-logs subdirectories). These logs include information about lifecycle events (BeforeInstall, AfterInstall, ApplicationStart, etc.), script execution failures, permissions issues, and any exit codes returned by deployment hooks.

Option C correctly points to CodeDeploy agent logs on the EC2 instances as the primary source for root cause analysis. Additionally, application-level logs streamed to Amazon CloudWatch Logs help validate whether the application itself is working correctly after deployment. For complex, multi-tier applications, AWS X-Ray can trace requests end to end, helping determine if issues are caused by downstream dependencies instead of the deployment process.

Options A, B, and D focus on network flow, generic performance, or high-level checks, none of which provide sufficient, deployment-level detail for CodeDeploy. Trusted Advisor and AWS Health do not surface step-by-step deployment log data. Therefore, the combination of CodeDeploy logs on the instances, CloudWatch Logs, and (optionally) X-Ray is the correct troubleshooting approach.

The problem is that the DevOps engineer cannot assume the OrganizationAccountAccessRole IAM role in the new member account that joined AnyCompany’s management account through an Organizations invitation. The solution is to create a new IAM role with the same name and trust policy in the new member account.

Option A is incorrect, as it does not address the root cause of the error. The DevOps engineer’s IAM user already has permission to assume the OrganizationAccountAccessRole IAM role in any member account, as this is the default role name that AWS Organizations creates when a new account joins an organization. The error occurs because the new member account does not have this role, as it was not created by AWS Organizations.

Option B is incorrect, as it does not address the root cause of the error. An SCP is a policy that defines the maximum permissions for account members of an organization or organizational unit (OU). An SCP does not grant permissions to IAM users or roles, but rather limits the permissions that identity-based policies or resource-based policies grant to them. An SCP also does not affect how IAM roles are assumed by other principals.

Option C is correct, as it addresses the root cause of the error. By creating a new IAM role with the same name and trust policy as the OrganizationAccountAccessRole IAM role in the new member account, the DevOps engineer can assume this role and access the account. The new role should have the AdministratorAccess AWS managed policy attached, which grants full access to all AWS resources in the account. The trust policy should allow the management account to assume the role, which can be done by specifying the management account ID as a principal in the policy statement.

Option D is incorrect, as it assumes that the new member account already has the OrganizationAccountAccessRole IAM role, which is not true. The new member account does not have this role, as it was not created by AWS Organizations. Editing the trust policy of a non-existent role will not solve the problem.

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

 Step 1: Creating a Centralized Domain in the Shared Services Account

To manage application package dependencies across multiple accounts, the most efficient solution is to create a centralized domain in the shared services account. This allows all application teams to access and manage package repositories within the same domain, ensuring consistency and centralization.

Action: Create a domain in the shared services account.

Why: A single, centralized domain reduces the need for redundant management in each application team's account.

Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer Documents Only:

For cross-account deployments, CodePipeline must assume a role in the target account. Configure S3 bucket policy to allow the target account (CodeDeployAccount) access, trust relationship in DevOps_Role to allow assumption by the pipeline’s account (PipelineAccount), and update CodePipeline_Service_Role with sts:AssumeRole permissions. This cross-account pipeline setup is documented in “Cross-Account Access for AWS CodePipeline.”

EC2 Image Builder is the recommended AWS-native service for automating the creation, validation, and distribution of AMIs. It integrates directly with AWS Organizations, allowing AMIs to be automatically shared with all accounts. The service also supports scheduled builds (e.g., monthly), significantly reducing operational overhead. This design is referenced in AWS documentation: “Automate OS image creation and distribution securely across multiple accounts using EC2 Image Builder.”

 Modify the Build Stage to Add a Test Action with a RunOrder Value of 2:

The build stage in AWS CodePipeline can have multiple actions. By adding a test action with a runOrder value of 2, the test action will execute after the initial build action completes.

 Use AWS CodeBuild as the Action Provider to Run Unit Tests:

AWS CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages.

Using CodeBuild to run unit tests ensures that the tests are executed in a controlled environment and that only the code changes that pass the unit tests proceed to the deploy stage.

Example configuration in CodePipeline:

{

"name": "BuildStage",

"actions": [

{

"name": "Build",

"actionTypeId": {

"category": "Build",

"owner": "AWS",

"provider": "CodeBuild",

"version": "1"

},

"runOrder": 1

},

{

"name": "Test",

"actionTypeId": {

"category": "Test",

"owner": "AWS",

"provider": "CodeBuild",

"version": "1"

},

"runOrder": 2

}

]

}

By integrating the unit tests into the build stage and ensuring they run after the build process, the pipeline guarantees that only code changes passing all unit tests are deployed.

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