Question 1

A DevOps engineer is working on a project that is hosted on Amazon Linux and has failed a security review. The DevOps manager has been asked to review the company buildspec.yaml file for an AWS CodeBuild project and provide recommendations. The buildspec.yaml file is configured as follows:

What changes should be recommended to comply with AWS security best practices? (Choose three.)

Options :

A : Add a post-build command to remove the temporary files from the container before termination to ensure they cannot be seen by other CodeBuild users.

B : Update the CodeBuild project role with the necessary permissions and then remove the AWS credentials from the environment variable.

C : Store the DB_PASSWORD as a SecureString value in AWS Systems Manager Parameter Store and then remove the DB_PASSWORD from the environment variables.

D : Move the environment variables to the ‘db-deploy-bucket’ Amazon S3 bucket, add a prebuild stage to download, then export the variables.

E : Use AWS Systems Manager run command versus sec and ssh commands directly to the instance.

F : Scramble the environment variables using XOR followed by Base64, add a section to install, and then run XOR and Base64 to the build phase.

Answer: B,D,E

Question 2

A space exploration company receives telemetry data from multiple satellites. Small packets of data are received through Amazon API Gateway and are placed directly into an Amazon Simple Queue Service (Amazon SQS) standard queue. A custom application is subscribed to the queue and transforms the data into a standard format.

Because of inconsistencies in the data that the satellites produce, the application is occasionally unable to transform the data. In these cases, the messages remain in the SQS queue. A DevOps engineer must develop a solution that retains the failed messages and makes them available to scientists for review and future processing.

Which solution will meet these requirements?

Options :

A : Configure AWS Lambda to poll the SQS queue and invoke a Lambda function to check whether the queue messages are valid. If validation fails, send a copy of the data that is not valid to an Amazon S3 bucket so that the scientists can review and correct the data. When the data is corrected, amend the message in the SQS queue by using a replay Lambda function with the corrected data.

B : Convert the SQS standard queue to an SQS FIFO queue. Configure AWS Lambda to poll the SQS queue every 10 minutes by using an Amazon EventBridge schedule. Invoke the Lambda function to identify any messages with a SentTimestamp value that is older than 5 minutes, push the data to the same location as the application-s output location, and remove the messages from the queue.

C : Create an SQS dead-letter queue. Modify the existing queue by including a redrive policy that sets the Maximum Receives setting to 1 and sets the dead-letter queue ARN to the ARN of the newly created queue. Instruct the scientists to use the dead-letter queue to review the data that is not valid. Reprocess this data at a later time.

D : Configure API Gateway to send messages to different SQS virtual queues that are named for each of the satellites. Update the application to use a new virtual queue for any data that it cannot transform, and send the message to the new virtual queue. Instruct the scientists to use the virtual queue to review the data that is not valid. Reprocess this data at a later time.

Answer: C

Question 3

A company has a web application that is hosted on Amazon EC2 instances. The company is deploying the application into multiple AWS Regions. The application consists of dynamic content such as WebSocket-based real-time product updates. The company uses Amazon Route 53 to manage all DNS records. Which solution will provide multi-Region access to the application with the LEAST latency?

Options :

A : Deploy an Application Load Balancer (ALB) in front of the EC2 instances in each Region. Create a Route 53 A record with a latency-based routing policy. Add IP addresses of the ALBs as the value of the record.

B : Deploy an Application Load Balancer (ALB) in front of the EC2 instances in each Region. Deploy an Amazon CloudFront distribution with an origin group that contains the ALBs as origins. Create a Route 53 alias record that points to the CloudFront distribution's DNS address.

C : Deploy a Network Load Balancer (NLB) in front of the EC2 instances in each Region. Create a Route 53 A record with a multivalue answer routing policy. Add IP addresses of the NLBs as the value of the record.

D : Deploy a Network Load Balancer (NLB) in front of the EC2 instances in each Region. Deploy an AWS Global Accelerator standard accelerator with an endpoint group for each NLB. Create a Route 53 alias record that points to the accelerator's DNS address.

Answer: A

Question 4

A DevOps engineer is building the infrastructure for an application. The application needs to run on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster that includes Amazon EC2 instances. The EC2 instances need to use an Amazon Elastic File System (Amazon EFS) file system as a storage backend. The Amazon EFS Container Storage Interface (CSI) driver is installed on the EKS cluster.

When the DevOps engineer starts the application, the EC2 instances do not mount the EFS file system.

Which solutions will fix the problem? (Choose three.)

Options :

A : Switch the EKS nodes from Amazon EC2 to AWS Fargate.

B : Add an inbound rule to the EFS file system’s security group to allow NFS traffic from the EKS cluster.

C : Create an IAM role that allows the Amazon EFS CSI driver to interact with the file system

D : Set up AWS DataSync to configure file transfer between the EFS file system and the EKS nodes.

E : Create a mount target for the EFS file system in the subnet of the EKS nodes.

F : Disable encryption or the EFS file system.

Answer: B,C,F

Question 5

A company has developed a serverless web application that is hosted on AWS. The application consists of Amazon S3. Amazon API Gateway, several AWS Lambda functions, and an Amazon RDS for MySQL database. The company is using AWS CodeCommit to store the source code. The source code is a combination of AWS Serverless Application Model (AWS SAM) templates and Python code.

A security audit and penetration test reveal that user names and passwords for authentication to the database are hardcoded within CodeCommit repositories. A DevOps engineer must implement a solution to automatically detect and prevent hardcoded secrets.

What is the MOST secure solution that meets these requirements?

Options :

A : Enable Amazon CodeGuru Profiler. Decorate the handler function with @with_lambda_profiler(). Manually review the recommendation report. Write the secret to AWS Systems Manager Parameter Store as a secure string. Update the SAM templates and the Python code to pull the secret from Parameter Store.

B : Associate the CodeCommit repository with Amazon CodeGuru Reviewer. Manually check the code review for any recommendations. Choose the option to protect the secret. Update the SAM templates and the Python code to pull the secret from AWS Secrets Manager.

C : Enable Amazon CodeGuru Profiler. Decorate the handler function with @with_lambda_profiler(). Manually review the recommendation report. Choose the option to protect the secret. Update the SAM templates and the Python code to pull the secret from AWS Secrets Manager.

D : Associate the CodeCommit repository with Amazon CodeGuru Reviewer. Manually check the code review for any recommendations. Write the secret to AWS Systems Manager Parameter Store as a string. Update the SAM templates and the Python code to pull the secret from Parameter Store.

Answer: B

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