There's so much surface area here it's easy to spin out.
Start by clarifying requirements and scale (e.g., daily active users, upload volume, view distribution) to scope the design. Then propose a high-level architecture covering video upload, processing, storage, delivery, and metadata, and dive into key components like transcoding, CDN, and database choices. Finally, discuss trade-offs and how to handle bottlenecks.
Pro tip: Emphasize the read-heavy nature of video streaming and how it drives decisions like CDN usage, caching, and denormalization. Also, mention cost optimization for storage and bandwidth, as it's critical for a platform like YouTube.
Ask about expected user base, upload rates, view patterns, and features like live streaming or recommendations. Estimate storage and bandwidth needs to inform design decisions.
Outline the main components: client apps, API gateway, upload service, transcoding pipeline, storage (object store + CDN), metadata database, and recommendation service. Explain how they interact.
Detail the upload and transcoding workflow (e.g., chunked uploads, message queue, parallel transcoding), storage strategy (hot vs. cold, CDN caching), and metadata modeling (sharding, denormalization for reads).
Discuss how to scale each component (e.g., CDN for delivery, sharding for DB, autoscaling for transcoding), handle failures (redundancy, retries), and ensure low latency globally.
Compare alternatives (e.g., SQL vs. NoSQL, push vs. pull CDN), justify choices based on requirements, and mention cost optimizations like tiered storage and adaptive bitrate streaming.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.