Vertex Macro｜Financial Cloud Cloud · AWS Amarathon 2025
Vertex Macro｜Amarathon 2025 Recap 29：Serverless MediaOps: Automating Video Workflows with AI on Amazon Web Services
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.