Spent the first few minutes trying to scope it properly because the question is massive.
Start by clarifying requirements and scale (e.g., millions of concurrent users, global availability, content types). Then design the high-level architecture covering content ingestion, storage, delivery, and client playback, and dive into key components like CDN, transcoding, and recommendation. Finally, discuss trade-offs (e.g., cost vs. latency, consistency vs. availability) and how you would monitor and scale the system.
Pro tip: Emphasize Amazon's leadership principles like Customer Obsession and Dive Deep by tying design decisions to user experience (e.g., low startup latency) and operational excellence (e.g., automated scaling).
Ask questions to understand functional (e.g., upload, stream, search, recommendations) and non-functional requirements (e.g., latency, availability, scalability). Estimate scale: number of users, videos, concurrent streams, and data volume.
Outline the main components: client apps, API gateway, content ingestion pipeline, storage (S3), transcoding service, metadata database, CDN, and recommendation engine. Draw a simple diagram to illustrate data flow.
Pick 2-3 critical areas to detail, such as video transcoding (formats, bitrates, parallel processing), CDN strategy (edge caching, multi-CDN), and adaptive bitrate streaming (HLS/DASH). Discuss data models and APIs.
Discuss trade-offs: e.g., consistency vs. availability for metadata, cost vs. performance for storage tiers, and push vs. pull CDN. Identify potential bottlenecks (e.g., database sharding, cache invalidation) and mitigation strategies.
Cover monitoring, logging, alerting, and auto-scaling. Discuss deployment strategies (e.g., blue-green) and how to handle failures (e.g., CDN failover, retries). Mention cost optimization and security (DRM, authentication).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.