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Difficulty: MediumHigh-Performing and Elastic Compute Solutions

A media company is designing a high-performing backend solution to transcode user-uploaded video files. Each video transcoding job takes between 20 to 30 minutes to complete, and the workload is continuous throughout the day. The company wants to minimize the operational overhead of managing servers while ensuring the system scales dynamically to handle the continuous processing load. Which compute solution should a solutions architect recommend to meet these requirements?

  1. A
    Package the transcoding application as an AWS Lambda function and trigger it directly from Amazon S3 bucket upload events.
  2. Package the transcoding application as a container and run it on Amazon Elastic Container Service (Amazon ECS) using the AWS Fargate launch type.Answer
  3. C
    Run the transcoding application on Amazon EC2 instances in an Auto Scaling group, storing the video files on an Amazon Elastic Block Store (Amazon EBS) gp3 volume with Multi-Attach enabled to share data across instances.
  4. D
    Run the transcoding application on a fleet of Amazon EC2 instances launched within a spread placement group to maximize network throughput and minimize node-to-node latency during the transcoding process.

Answer

Package the transcoding application as a container and run it on Amazon Elastic Container Service (Amazon ECS) using the AWS Fargate launch type.
The correct option is to package the application as a container and run it on Amazon ECS with AWS Fargate. Fargate is a serverless compute engine for containers that removes the need to provision and manage EC2 instances, minimizing operational overhead. Because ECS tasks do not have the strict 15-minute execution limit found in AWS Lambda, they can run to completion for the 20 to 30-minute transcoding workloads.

Step-by-Step Solution

1
Analyze the workload runtime requirements.
Identify that the transcoding jobs require 20 to 30 minutes of continuous compute execution.
This rules out compute options with short execution timeouts, such as AWS Lambda's 15-minute limit.
2
Evaluate the management overhead and scaling constraints.
Determine that serverless container orchestration (AWS Fargate) is preferred over managing EC2 Auto Scaling groups to meet the goal of minimal operational overhead.
AWS Fargate handles provisioning, configuring, and scaling the virtual machines, leaving only container management to the user.
3
Verify storage and network requirements against the options.
Confirm that EBS gp3 does not support Multi-Attach and spread placement groups do not optimize network performance.
Ensures that the selected architectural pattern is technically feasible and optimal under AWS service limits.

Key Concept

Selecting appropriate compute services based on execution time limits, scaling requirements, and operational management constraints.
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High-Performing and Elastic Compute Solutions

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