Which solution will meet these requirements with the LEAST operational overhead?
Use Amazon Elastic Container Service (Amazon ECS) with Amazon EC2 Spot Instances to process the images. Configure Amazon Simple Queue Service (Amazon SQS) to orchestrate the workflow. Store the processed files in Amazon Elastic File System (Amazon EFS).
Use AWS Batch jobs to process the images. Use AWS Step Functions to orchestrate the workflow. Store the processed files in an Amazon S3 bucket.
Use AWS Lambda functions and Amazon EC2 Spot Instances to process the images. Store the processed files in Amazon FSx.
Deploy a group of Amazon EC2 instances to process the images. Use AWS Step Functions to orchestrate the workflow. Store the processed files in an Amazon Elastic Block Store (Amazon EBS) volume.
Explanations:
While Amazon ECS with EC2 Spot Instances can handle workloads efficiently, it requires managing the underlying ECS cluster and instances, which adds operational overhead. Amazon SQS can orchestrate the workflow, but the overall complexity and management of ECS are higher than necessary for the requirements.
AWS Batch is designed for efficiently processing large numbers of batch jobs without managing infrastructure, providing a serverless way to run image processing jobs. AWS Step Functions simplifies orchestration of the workflow, and Amazon S3 is ideal for storing large files with built-in durability and scalability, minimizing operational overhead.
Using AWS Lambda functions introduces a limit on execution time and is generally not suited for large image processing tasks that take longer to complete. Combining Lambda with EC2 Spot Instances adds complexity, requiring management of the EC2 instances. Storing files in Amazon FSx is not optimal for this scenario.
Deploying Amazon EC2 instances requires managing the instances and infrastructure, increasing operational overhead. AWS Step Functions can orchestrate workflows, but using Elastic Block Store (EBS) limits storage to the instance’s lifecycle, making it less suitable for large processed files compared to S3.