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?

The correct solution leverages Amazon ECS with AWS Fargate for scalable, serverless container orchestration, ideal for processing terabyte-sized videos that take up to 20 minutes. Fargate eliminates server management overhead, making it cost-effective and highly scalable. Amazon Aurora provides a highly available and scalable relational database for video metadata. Amazon S3 Intelligent-Tiering optimizes storage costs by automatically moving data between access tiers based on usage patterns, suitable for varying access needs of video content. Incorrect options: AWS Lambda has a maximum execution duration of 15 minutes, which is insufficient for processing videos that can take up to 20 minutes. Using Amazon EC2 instances in an Auto Scaling group requires managing underlying servers, which is less cost-effective and scalable than Fargate for this workload. S3 Standard is not as cost-optimized as Intelligent-Tiering for varying access patterns. Amazon EKS on Amazon EC2 still requires managing EC2 instances. Storing video metadata in Amazon RDS in a single Availability Zone lacks high availability. Amazon S3 Glacier Deep Archive has retrieval times of hours to days, making it unsuitable for content that users consume daily.