AWS Certified Solutions Architect – Associate (SAA-C03) — Question 1015

A streaming media company is rebuilding its infrastructure to accommodate increasing demand for video content that users consume daily.

The company needs to process terabyte-sized videos to block some content in the videos. Video processing can take up to 20 minutes.

The company needs a solution that will scale with demand and remain cost-effective.

Which solution will meet these requirements?

Answer options

• A. Use AWS Lambda functions to process videos. Store video metadata in Amazon DynamoDB. Store video content in Amazon S3 Intelligent-Tiering.
• B. Use Amazon Elastic Container Service (Amazon ECS) and AWS Fargate to implement microservices to process videos. Store video metadata in Amazon Aurora. Store video content in Amazon S3 Intelligent-Tiering.
• C. Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB) to process videos. Store video content in Amazon S3 Standard. Use Amazon Simple Queue Service (Amazon SQS) for queuing and to decouple processing tasks.
• D. Deploy a containerized video processing application on Amazon Elastic Kubernetes Service (Amazon EKS) on Amazon EC2. Store video metadata in Amazon RDS in a single Availability Zone. Store video content in Amazon S3 Glacier Deep Archive.

Correct answer: B

Explanation

AWS Lambda is unsuitable because it has a strict 15-minute execution limit, which cannot accommodate the 20-minute video processing requirement. Amazon ECS with AWS Fargate allows for serverless container execution without time limits, scaling automatically and cost-effectively to meet demand. Using Amazon S3 Intelligent-Tiering optimizes storage costs for the video content based on access frequency, unlike S3 Glacier Deep Archive which is meant for archiving and has long retrieval times.