DOP-C02 Exam Dumps - Amazon Web Services AWS Certified Professional Questions and Answers

Create an EC2 Image Builder Pipeline that Uses a Container Recipe to Build the Image:

EC2 Image Builder simplifies the creation, maintenance, validation, and sharing of container images.

By using a container recipe, you can define the base image, components, and validation tests for your container image.

Configure the Pipeline to Distribute the Image to Amazon Elastic Container Registry (Amazon ECR) Repositories in All Three Regions:

Amazon ECR provides a secure, scalable, and reliable container registry.

Configuring the pipeline to distribute the image to ECR repositories in us-west-2, us-east-2, and eu-central-1 ensures that the image is available in all required regions.

Configure the Pipeline to Run Weekly:

Setting the pipeline to run on a weekly schedule ensures that the base image is regularly updated and published, incorporating any new security configurations or updates.

By using EC2 Image Builder to automate the creation and distribution of the container image, the solution ensures that the base image is consistently maintained and available across multiple regions with minimal management overhead.

ALBs with Auto Scaling across AZs ensure high availability in each Region.

Aurora global database supports cross-Region read replicas with low latency for reads and is recommended for multi-Region high availability.

Route 53 latency-based routing sends users to the closest Region.

RDS without global database (Options B, D) has higher replication lag and less resilience.

Using CloudFront in front of ALBs (Options C and D) adds caching but is not required for latency-based routing and increases complexity.

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

Deploy CloudWatch Agent + Fluent Bit (supported by Amazon EKS integration) to forward metrics and logs. Create CloudWatch Alarms for CPU/memory/node metrics and metric log filters for Autoscaler logs, triggering SNS notifications when anomalies occur. This pattern matches AWS guidance on “Monitoring EKS clusters with CloudWatch Container Insights and alarms.”

The correct answer is A.

A comprehensive and detailed explanation is:

Option A is correct because it meets the requirements with the most operational efficiency. Updating the ecommerce application to emit a JSON object to a CloudWatch log group for each processed transaction is a simple and cost-effective way to collect the data needed for the dashboard. Using CloudWatch Logs Insights to query the log group and to visualize the results in a pie chart format is also a convenient and integrated solution that leverages the existing CloudWatch dashboards. Attaching the results to the desired CloudWatch dashboard is straightforward and does not require any additional steps or services.

Option B is incorrect because it introduces unnecessary complexity and cost. Updating the ecommerce application to emit a JSON object to an Amazon S3 bucket for each processed transaction is a valid way to store the data, but it requires creating and managing an S3 bucket and its permissions. Using Amazon Athena to query the S3 bucket and to visualize the results in a pie chart format is also a valid way to analyze the data, but it incurs charges based on the amount of data scanned by each query. Exporting the results from Athena and attaching them to the desired CloudWatch dashboard is also an extra step that adds more overhead and latency.

Option C is incorrect because it uses AWS X-Ray for an inappropriate purpose. Updating the ecommerce application to use AWS X-Ray for instrumentation is a good practice for monitoring and tracing distributed applications, but it is not designed for aggregating product transaction details. Creating a new X-Ray subsegment and adding an annotation for each processed transaction is possible, but it would clutter the X-Ray service map and make it harder to debug performance issues. Using X-Ray traces to query the data and to visualize the results in a pie chart format is also possible, but it would require custom code and logic that are not supported by X-Ray natively. Attaching the results to the desired CloudWatch dashboard is also not supported by X-Ray directly, and would require additional steps or services.

Option D is incorrect because it introduces unnecessary complexity and cost. Updating the ecommerce application to emit a JSON object to a CloudWatch log group for each processed transaction is a simple and cost-effective way to collect the data needed for the dashboard, as in option A. However, creating an AWS Lambda function to aggregate and write the results to Amazon DynamoDB is redundant, as CloudWatch Logs Insights can already perform aggregation queries on log data. Creating a Lambda subscription filter for the log file is also redundant, as CloudWatch Logs Insights can already access log data directly. Attaching the results to the desired CloudWatch dashboard would also require additional steps or services, as DynamoDB does not support native integration with CloudWatch dashboards.

 Impact of Removing FullAWSAccess and Adding Policy for EC2 Actions:

The FullAWSAccess policy allows all actions on all resources by default. Removing this policy from the Department OU will limit the permissions that accounts within this OU inherit from the parent OU.

Adding a policy that allows only Amazon EC2 API operations will restrict the permissions to EC2 actions only.

 Permissions of Administrative IAM Roles:

The administrative IAM roles in the Engineering OU have the AdministratorAccess policy attached, which grants full access to all AWS services and resources.

Since SCPs are restrictions that apply at the organizational level, removing FullAWSAccess and replacing it with a policy allowing only EC2 actions means that for all accounts in the Engineering OU:

They will have full access to EC2 actions due to the new SCP.

They will be restricted in other actions that are not covered by the SCP, hence, non-EC2 API actions will be denied.

 Conclusion:

All API actions on EC2 resources will be allowed.

All other API actions will be denied due to the absence of a broader allow policy.

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.

Use a Service Control Policy (SCP) with a Null condition on lambda:VpcIds to deny Lambda function creation or update when not VPC-attached. This enforces compliance across all accounts automatically without manual remediation, aligning with AWS Control Tower governance recommendations.

The correct answer is C. Using AWS Config to identify and audit all EC2 instances based on their host placement configuration is the most efficient and scalable solution to ensure compliance with the software licensing requirement. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. By creating a custom AWS Config rule that triggers a Lambda function to verify host placement, the DevOps engineer can automate the process of checking whether the instances are running on EC2 Dedicated Hosts or not. The Lambda function can return a NON_COMPLIANT result if the instance is not running on an EC2 Dedicated Host, and the AWS Config report can provide a summary of the compliance status of the instances. This solution requires the least administrative overhead compared to the other options.

Option A is incorrect because using AWS Systems Manager Configuration Compliance to scan and build a database of noncompliant EC2 instances based on their host placement configuration is a more complex and costly solution than using AWS Config. AWS Systems Manager Configuration Compliance is a feature of AWS Systems Manager that enables you to scan your managed instances for patch compliance and configuration inconsistencies. To use this feature, the DevOps engineer would need to install the Systems Manager Agent on each EC2 instance, create a State Manager association to run the put-compliance-items API action periodically, and use a DynamoDB table to store the instance IDs of noncompliant resources. This solution would also require more API calls and storage costs than using AWS Config.

Option B is incorrect because using custom Java code running on an EC2 instance to check and terminate noncompliant EC2 instances is a more cumbersome and error-prone solution than using AWS Config. This solution would require the DevOps engineer to write and maintain the Java code, set up EC2 Auto Scaling for the instance, use an SQS queue and another worker instance to process the instance IDs, use a Lambda function and an SNS topic to terminate and notify the noncompliant instances, and handle any potential failures or exceptions in the workflow. This solution would also incur more compute, storage, and messaging costs than using AWS Config.

Option D is incorrect because using AWS CloudTrail to identify and audit EC2 instances by analyzing the EC2 RunCommand API action is a less reliable and accurate solution than using AWS Config. AWS CloudTrail is a service that enables you to monitor and log the API activity in your AWS account. The EC2 RunCommand API action is used to execute commands on one or more EC2 instances. However, this API action does not necessarily indicate the host placement of the instance, and it may not capture all the instances that are running on EC2 Dedicated Hosts or not. Therefore, option D would not provide a comprehensive and consistent audit of the EC2 instances.

Comprehensive & Detailed Explanation (150–250 words):

AWS Control Tower provides Account Factory and Account Factory Customizations (AFC) as the lowest-overhead and most scalable method for creating and configuring new accounts. AFC allows you to define blueprints that include mandatory baseline resources such as IAM roles, logging configurations, guardrails, network settings, and tagging standards. When accounts are created through Account Factory using a customization blueprint, all controls and baseline configurations are applied automatically during provisioning, without any additional automation steps or StackSet deployments.

Option B requires running StackSets after the account is created, which adds manual management overhead and defeats the built-in automation advantages of Control Tower. Options C and D rely on manually provisioning accounts via AWS Organizations, which bypasses Control Tower’s governance and would require custom Lambda or StackSet automation to replicate controls that Control Tower already provides automatically.

Because the question explicitly asks for the least operational overhead, the correct answer is to use the Control Tower AFC blueprint, ensuring every account is born compliant with the required guardrails and baseline configuration.