Q61 — AWS SAA-C03 Ch.13

Question 61 of 100 | ← Chapter 13

Q961. 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?

Correct Answer: 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

Explanation

The solution that best meets the requirements of scalability, cost-effectiveness, and processing large video files is 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.Here's why:Scalability: EC2 instances in an Auto Scaling group can automatically scale up or down based on demand, ensuring that the company can handle the increasing volume of video processing. Cost-Effectiveness: EC2 instances are a cost-effective solution for compute-intensive tasks like video processing. Auto Scaling ensures that you only pay for the resources you use. S3 Standard for Video Content: S3 Standard provides high durability and availability for storing video content.SQS for Decoupling: SQS allows for decoupling of processing tasks, ensuring that the processing pipeline can handle large volumes of videos without bottlenecks.ALB for Load Balancing: ALB distributes traffic across the EC2 instances, ensuring high availability and efficient resource utilization.Why other options are less suitable:A. Use AWS Lambda functions to process videos. Store video metadata in Amazon DynamoDB. Store video content in Amazon S3 Intelligent-Tiering: Lambda functions are great for short-lived tasks, but processing terabyte-sized videos for 20 minutes might exceed Lambda's execution time limits. 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: While ECS and Fargate offer scalability, they might not be the most cost-effective solution for this scenario, especially if the video processing is a consistent workload. 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: EKS is a powerful container orchestration platform, but it might be overkill for this scenario. Glacier Deep Archive is designed for long-term storage and is not suitable for frequently accessed video content.In summary:Option C provides a balanced approach that combines the scalability of EC2 Auto Scaling, the cost- effectiveness of S3 Standard, and the decoupling capabilities of SQS. This solution is well-suited for handling the company's increasing video processing needs while remaining cost-effective.