Wide open question and I spent the first few minutes just trying to scope it down because 'Twitter' is basically everything.
Start by clarifying the scope and core features of Twitter (e.g., posting tweets, following, timeline generation) and non-functional requirements like scale, latency, and availability. Then, design a high-level architecture that separates concerns (e.g., tweet storage, fan-out service, timeline cache) and dive into critical components like timeline generation and storage choices, discussing trade-offs. Finally, address bottlenecks and scaling strategies such as sharding, caching, and using a hybrid push-pull model for fan-out.
Pro tip: Proactively discuss the trade-offs between fan-out on write vs. fan-out on read, and propose a hybrid approach based on user activity (e.g., push for normal users, pull for celebrities). This shows you understand real-world constraints and can balance competing priorities.
Ask questions to define functional requirements (e.g., post tweets, follow users, view timeline, search) and non-functional requirements (e.g., 500M tweets/day, low latency, high availability).
Sketch the main components: clients, load balancers, API servers, tweet service, timeline service, user service, and storage layers (SQL/NoSQL, cache). Explain data flow for posting and viewing tweets.
Discuss fan-out strategies: push (write) vs. pull (read) vs. hybrid. Explain how to handle celebrities and inactive users, and how to use caching (e.g., Redis) for fast timeline retrieval.
Choose appropriate databases (e.g., MySQL for user data, Cassandra for tweets) and discuss sharding, replication, and indexing. Address how to scale to millions of reads/writes per second.
Identify potential bottlenecks (e.g., hot users, timeline generation latency) and propose solutions (e.g., precomputed timelines, CDN for media). Summarize key trade-offs made.
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