AWS Certified Solutions Architect – Professional — Question 319

A solutions architect needs to advise a company on how to migrate its on-premises data processing application to the AWS Cloud. Currently, users upload input files through a web portal. The web server then stores the uploaded files on NAS and messages the processing server over a message queue. Each media file can take up to 1 hour to process. The company has determined that the number of media files awaiting processing is significantly higher during business hours, with the number of files rapidly declining after business hours.
What is the MOST cost-effective migration recommendation?

Answer options

• A. Create a queue using Amazon SQS. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in an Amazon S3 bucket.
• B. Create a queue using Amazon MQ. Configure the existing web server to publish to the new queue. When there are messages in the queue, create a new Amazon EC2 instance to pull requests from the queue and process the files. Store the processed files in Amazon EFS. Shut down the EC2 instance after the task is complete.
• C. Create a queue using Amazon MQ. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in Amazon EFS.
• D. Create a queue using Amazon SQS. Configure the existing web server to publish to the new queue. Use Amazon EC2 instances in an EC2 Auto Seating group to pull requests from the queue and process the files. Scale the EC2 instances based on the SQS queue length. Store the processed files in an Amazon S3 bucket.

Correct answer: D

Explanation

Amazon S3 provides the most cost-effective storage solution for the processed files compared to Amazon EFS. Because individual file processing can take up to 1 hour, AWS Lambda is not viable due to its maximum execution timeout of 15 minutes, making EC2 instances the correct choice. Using an EC2 Auto Scaling group based on SQS queue depth allows the application to dynamically scale down to save costs when demand drops after business hours.