The company needs a solution that is cost-effective, highly available, and scalable.
Which solution will meet these requirements?
A.
Use AWS Lambda functions to process the videos. Store video metadata in Amazon DynamoDB. Store video content in Amazon S3 Intelligent-Tiering.
B.
Use Amazon Elastic Container Service (Amazon ECS) with the AWS Fargate launch type to implement microservices to process videos. Store video metadata in Amazon Aurora. Store video content in Amazon S3 Intelligent-Tiering.
C.
Use Amazon EMR to process the videos with Apache Spark. Store video content in Amazon FSx for Lustre. Use Amazon Kinesis Data Streams to ingest videos in real time.
D.
Deploy a containerized video processing application on Amazon Elastic Kubernetes Service (Amazon EKS) with the Amazon EC2 launch type. Store video metadata in Amazon RDS in a single Availability Zone. Store video content in Amazon S3 Glacier Deep Archive.
AWS Lambda is not suitable for long-running jobs that can take up to 20 minutes, as Lambda has a maximum execution duration of 15 minutes.
Amazon ECS with AWS Fargate allows you to run containers without managing EC2 instances, providing a scalable and highly available environment. You can scale Fargate tasks to handle large and parallel video processing jobs. Amazon Aurora is a highly available, managed relational database. S3 Intelligent-Tiering is cost-effective for storing large video files with variable access patterns.
AWS Documentation Extract:
"AWS Fargate lets you run containers without managing servers or clusters, providing a highly available and scalable compute environment. Fargate is suitable for running data processing workloads that require long-running compute tasks."
(Source: AWS Fargate documentation, Use Cases)
A: Lambda is not suitable for long-running (over 15 min) or heavy compute jobs.
C: Amazon EMR is optimized for big data analytics, not specific video processing. FSx for Lustre and Kinesis are not best fit for this use case.
D: EKS with EC2 adds operational overhead and RDS in a single AZ is not highly available; Glacier Deep Archive is not suitable for frequently accessed video files.
[Reference: AWS Certified Solutions Architect – Official Study Guide, Containerized and Serverless Processing., ]
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