What is the MOST cost-effective migration recommendation?
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.
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.
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.
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.
Explanations:
AWS Lambda is not suitable for tasks requiring up to 1 hour of processing time as it has a maximum timeout of 15 minutes. This makes Lambda unsuitable for the long-running media processing task described.
While Amazon MQ and Amazon EFS can support the workload, using a single EC2 instance is not optimal for handling variable workloads during peak business hours, making this option less cost-effective and scalable.
AWS Lambda has a maximum runtime of 15 minutes, which is insufficient for processing files that take up to an hour. Additionally, Amazon EFS is unnecessary for processed file storage as Amazon S3 would be more cost-effective.
Amazon SQS with EC2 Auto Scaling can handle fluctuating workloads efficiently, scaling EC2 instances based on queue length, which optimizes costs during peak hours. Amazon S3 provides cost-effective storage for processed files.
If I had to guess, I’d say the answer is:
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.