YouTubeDifficulty: Advanced
How YouTube Works: Video Transcoding & Storage
YouTube ingests hundreds of hours of video every minute. The architecture involves massive blob storage, distributed transcoding pipelines, and a highly optimized CDN.
High-Level Architecture
[Creator] -> (Upload Service) -> [Blob Storage] -> (Message Queue) -> [Transcoding Servers] -> [CDN]Database Design
Vitess (a scaling system for MySQL) is used to handle billions of metadata rows. Bigtable stores video thumbnails.
Caching Strategy
Edge caching places the most popular videos on servers physically closest to the users, minimizing buffering.
Scaling & APIs
Scaling: Videos are chunked upon upload, and transcoding jobs are distributed across thousands of worker nodes simultaneously via Pub/Sub queues.
API Design: RESTful APIs for metadata and gRPC for internal microservice communication.
Real-World Challenges
- •Handling explosive viral video traffic.
- •Deduplication to prevent storing identical video uploads.
- •Copyright scanning during the processing phase.