backend
personal
Video Processing Pipeline
Containerized video processing application with queue-based job processing for high-volume transcoding.
V
backend
Overview
Built a scalable video processing pipeline that handles video uploads, transcoding to multiple formats, and CDN delivery. The system processes thousands of videos daily using Docker containers and queue-based architecture.
The Challenge
Processing large video files efficiently while maintaining quality and providing real-time progress updates to users.
The Solution
Implemented a microservices architecture with separate containers for different processing stages. Used FFmpeg for transcoding and Redis for job queuing with progress tracking.
Key Features
Asynchronous video processing
Multiple output formats
Thumbnail generation
Progress tracking
Error recovery
S3 storage integration
Technologies Used
Go
Python
FFmpeg
Docker
Redis
PostgreSQL
FastAPI
AWS S3