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AWS Certified DevOps Engineer - Professional Questions and Answers

Question 1

A company uses AWS Key Management Service (AWS KMS) keys and manual key rotation to meet regulatory compliance requirements. The security team wants to be notified when any keys have not been rotated after 90 days.

Which solution will accomplish this?

Options:

Configure AWS KMS to publish to an Amazon Simple Notification Service (Amazon SNS) topic when keys are more than 90 days old.

Configure an Amazon EventBridge event to launch an AWS Lambda function to call the AWS Trusted Advisor API and publish to an Amazon Simple Notification Service (Amazon SNS) topic.

Develop an AWS Config custom rule that publishes to an Amazon Simple Notification Service (Amazon SNS) topic when keys are more than 90 days old.

Configure AWS Security Hub to publish to an Amazon Simple Notification Service (Amazon SNS) topic when keys are more than 90 days old.

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Question 2

A company has deployed a new platform that runs on Amazon Elastic Kubernetes Service (Amazon EKS). The new platform hosts web applications that users frequently update. The application developers build the Docker images for the applications and deploy the Docker images manually to the platform.

The platform usage has increased to more than 500 users every day. Frequent updates, building the updated Docker images for the applications, and deploying the Docker images on the platform manually have all become difficult to manage.

The company needs to receive an Amazon Simple Notification Service (Amazon SNS) notification if Docker image scanning returns any HIGH or CRITICAL findings for operating system or programming language package vulnerabilities.

Which combination of steps will meet these requirements? (Select TWO.)

Options:

Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files. Create a pipeline in AWS CodePipeline. Use an Amazon S3 event to invoke the pipeline when a newer version of the Dockerfile is committed. Add a stop to the pipeline to initiate the AWS CodeBuild project.

Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files. Create a pipeline in AWS CodePipeline. Use an Amazon EvenlBridge event to invoke the pipeline when a newer version of the Dockerfile is committed. Add a step to the pipeline to initiate the AWS CodeBuild project.

Create an AWS CodeBuild project that builds the Docker images and stores the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository. Turn on basic scanning for the ECR repository. Create an Amazon EventBridge rule that monitors Amazon GuardDuty events. Configure the EventBridge rule to send an event to an SNS topic when the finding-severity-counts parameter is more than 0 at a CRITICAL or HIGH level.

Create an AWS CodeBuild project that builds the Docker images and stores the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository. Turn on enhanced scanning for the ECR repository. Create an Amazon EventBridge rule that monitors ECR image scan events. Configure the EventBridge rule to send an event to an SNS topic when the finding-severity-counts parameter is more than 0 at a CRITICAL or HIGH level.

Create an AWS CodeBuild project that scans the Dockerfile. Configure the project to build the Docker images and store the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository if the scan is successful. Configure an SNS topic to provide notification if the scan returns any vulnerabilities.

Answer:

B, D

Explanation:

 Step 1: Automate Docker Image Deployment using AWS CodePipeline

The first challenge is the manual process of building and deploying Docker images. To address this, you can use AWS CodePipeline to automate the process. AWS CodePipeline integrates with CodeCommit (for source code and Dockerfile storage) and CodeBuild (to build Docker images and store them in Amazon Elastic Container Registry (ECR)).

Action: Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files. Then, create a pipeline in AWS CodePipeline that triggers on new commits via an Amazon EventBridge event.

Why: This automation significantly reduces the manual effort of building and deploying Docker images when updates are made to the codebase.

[Reference: AWS documentation on AWS CodePipeline and CodeCommit Integration., This corresponds to Option B: Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files. Create a pipeline in AWS CodePipeline. Use an Amazon EventBridge event to invoke the pipeline when a newer version of the Dockerfile is committed. Add a step to the pipeline to initiate the AWS CodeBuild project.,  Step 2: Enabling Enhanced Scanning on Amazon ECR and Monitoring VulnerabilitiesTo scan for vulnerabilities in Docker images, Amazon ECR provides both basic and enhanced scanning options. Enhanced scanning offers deeper and more frequent scans, and integrates with Amazon EventBridge to send notifications based on findings., Action: Turn on enhanced scanning for the Amazon ECR repository where the Docker images are stored. Use Amazon EventBridge to monitor image scan events and trigger an Amazon SNS notification if any HIGH or CRITICAL vulnerabilities are found., Why: Enhanced scanning provides a detailed analysis of operating system and programming language package vulnerabilities, which can trigger notifications in real-time., Reference: AWS documentation on Enhanced Scanning for Amazon ECR., This corresponds to Option D: Create an AWS CodeBuild project that builds the Docker images and stores the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository. Turn on enhanced scanning for the ECR repository. Create an Amazon EventBridge rule that monitors ECR image scan events. Configure the EventBridge rule to send an event to an SNS topic when the finding-severity-counts parameter is more than 0 at a CRITICAL or HIGH level., , , , ]

Question 3

A company ' s application has an API that retrieves workload metrics. The company needs to audit, analyze, and visualize these metrics from the application to detect issues at scale.

Which combination of steps will meet these requirements? (Select THREE).

Options:

Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon S3 bucket.

Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon DynamoDB table that has a DynamoDB stream enabled.

Create an AWS Glue crawler to catalog the workload metric data in the Amazon S3 bucket. Create views in Amazon Athena for the cataloged data.

Connect an AWS Glue crawler to the Amazon DynamoDB stream to catalog the workload metric data. Create views in Amazon Athena for the cataloged data.

Create Amazon QuickSight datasets from the Amazon Athena views. Create a QuickSight analysis to visualize the workload metric data as a dashboard.

Create an Amazon CloudWatch dashboard that has custom widgets that invoke AWS Lambda functions. Configure the Lambda functions to query the workload metrics data from the Amazon Athena views.

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