Serverless MediaOps: Automating Video Workflows with AI on Amazon Web Services

Session Notes

Problem Overview

• Manual video processing
• Slow turnaround time
• Hard to scale or automate
• Heavy ops / server maintenance Traditional Video Workflow Summary
• [ 1 ] Input:
• Content is manually managed through initial operations.
• Manual tasks
• Long processing time
• Servers utilized
• Transcoding backlog
• [ 2 ] Operations Flow:
• Input goes to a Cron Job (a scheduling utility).
• The cron job triggers Encoding.
• Metadata is generated and stored on EC2 Servers.
• After encoding/storage, the content undergoes Content Review.
• The reviewed content is then pushed to the audience.
• [ 3 ] Output:
• The final consumption stage on a computer monitor, representing distribution.

What is MediaOps?

• MediaOps = DevOps for video workflows
• Automates ingest → processing → delivery
• Reduces manual steps
• Ensures consistent, scalable pipelines
• Improves quality, speed, and reliability A four-step Media Operations (MediaOps) workflow:
• Ingest: The process of taking in media content.
• Process: The stage where media is prepared or modified.
• Quality/Metadata: The step involving quality control and adding relevant data about the media.
• Delivery: The final stage where the media is distributed or made available to its destination. Core Amazon Web Services
• S3 – ingest & storage
• Lambda – event-driven logic
• Step Functions – orchestration
• MediaConvert – transcoding
• Rekognition / Bedrock – analysis & AI metadata
• CloudFront – global delivery

AI Automation Layer

• Scene analysis (Rekognition)
• Auto-generated metadata (Bedrock)
• Intelligent decisions: reprocess, flag, publish
• Event-driven orchestration (Lambda + Step Functions) AI Automation Layer Workflow Summary AI-driven video content workflow:
• Input: A Video Output is directed into the automation system.
• AI Automation: The core processing uses AI services, Rekognition and Bedrock.
• Outputs/Actions: Based on the AI analysis, the system can trigger one of three actions:
• [ 1 ] Reprocess: Send the content back for further processing.
• [ 2 ] Flag: Mark the content for manual review or attention.
• [ 3 ] Publish: Distribute the content live. Key Benefits
• Key benefits encompass eliminating 80% of manual operations
• Accelerating publish time by 10 times
• Achieving automatic scalability, enhancing discoverability and compliance with AI-generated consistent quality and metadata.