The scope is massive and the first few minutes are basically a trap if you try to cover everything.
Start by clarifying requirements and scale, then design the core data model and APIs for each feature, and finally dive deep into the feed generation and fan-out strategy. Focus on trade-offs between push and pull models for the feed, and how to handle hot users and celebrity accounts.
Pro tip: Emphasize the hybrid fan-out approach: push for normal users and pull for celebrities, and discuss how to handle feed ranking with machine learning. Also, mention the importance of idempotency and deduplication in likes and comments to handle retries.
Ask about functional and non-functional requirements: daily active users, read/write ratio, latency targets, and consistency needs. Estimate storage and bandwidth for photos and metadata.
Sketch the main components: clients, API gateway, services (user, photo, feed, social graph, search), and storage (object store, SQL/NoSQL, cache). Define core entities: User, Photo, Follow, Like, Comment.
Design the upload flow: client requests pre-signed URL, uploads directly to object storage, then notifies service to process (resize, thumbnail, metadata). Discuss CDN for serving images.
Explain the hybrid fan-out: on photo upload, push to followers' feed caches for normal users; for celebrities, pull their posts at read time. Discuss feed ranking and pagination.
Design the social graph storage (e.g., adjacency list with sharding). For likes/comments, use a distributed counter and store comments in a scalable DB. For search, use inverted index and consider Elasticsearch.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the requirements and scale (e.g., number of users, read/write ratio, latency SLAs). Then compare push (fan-out on write) and pull (fan-out on read) models, discussing hybrid approaches and trade-offs like latency, cost, and complexity. Conclude with a recommendation tailored to the scenario.
Pro tip: Emphasize that the choice depends on the specific use case: push is great for low-latency reads but can be expensive for high fan-out, while pull is simpler but may add read latency. Mention that real systems often use a hybrid approach, like push for active users and pull for inactive ones.
Ask about scale (users, QPS), read/write ratio, latency requirements, and consistency needs to frame the problem.
Describe fan-out on write: when a user posts, the update is pushed to all followers' feeds. Discuss pros (fast reads) and cons (write amplification, high latency for celebrities).
Describe fan-out on read: feeds are generated on demand by pulling posts from followed users. Discuss pros (simple writes, no precomputation) and cons (slower reads, repeated work).
Contrast the two models on dimensions like latency, cost, scalability, and complexity. Highlight scenarios where each excels.
Suggest a hybrid approach (e.g., push for most users, pull for celebrities) and discuss how to handle edge cases like inactive users or ranking.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Relational for users and follow graph, key-value for precomputed feeds, blob storage plus CDN for media.
Start by clarifying the scale and access patterns (e.g., read-heavy feeds, write-heavy follows) to justify your choices. Then walk through each entity—users, follows, feeds, media—describing the data model (SQL vs NoSQL, schema) and storage engine (e.g., MySQL, Cassandra, S3) with trade-offs. Finally, tie it together by explaining how data flows between components to serve a feed.
Pro tip: Emphasize denormalization and caching for feed generation, and mention how you'd handle hot users (celebrities) with fan-out on write vs read. This shows you understand real-world trade-offs at Meta scale.
Ask about expected scale (DAU, QPS), read/write ratio, latency requirements, and consistency needs. This sets the stage for justified design choices.
Propose a user table (SQL or wide-column) with user ID, profile info, and a follow graph (e.g., adjacency list in a graph DB or denormalized tables). Discuss sharding by user ID.
Explain feed options: fan-out on write (precomputed timelines) vs fan-out on read (pull-based). Choose a hybrid for celebrities, and describe storage (e.g., Redis for hot feeds, Cassandra for persistent timelines).
Store media in blob storage (e.g., S3) with CDN for delivery. Keep metadata (URL, dimensions, owner) in a database, and discuss deduplication and transcoding pipelines.
Recap key decisions (e.g., denormalization, caching) and how they address scale. Mention potential bottlenecks and how you'd evolve the design (e.g., adding a graph DB for follows).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I picked the celebrity fan-out problem since we'd already touched it.
Pick the area where you have the strongest technical depth and can clearly articulate trade-offs, then structure your answer around requirements, high-level design, deep dive, and trade-offs. Show how your solution scales, handles failures, and meets latency/consistency needs, while proactively comparing alternatives.
Pro tip: Choose the area that naturally connects to the rest of the system design you've already discussed, and explicitly state why you're choosing it—this shows strategic thinking and avoids appearing random. Also, quantify where possible (e.g., QPS, storage, latency targets) to demonstrate practical experience.
Ask clarifying questions to understand functional and non-functional requirements, such as expected QPS, data volume, latency targets, and consistency needs. Establish the scope and constraints before diving in.
Sketch the main components and data flow for the chosen area, identifying key services, storage, and messaging. Keep it abstract but cover the end-to-end path.
Zoom into the most challenging parts, such as data partitioning, caching, consistency, or failure handling. Explain your design choices and how they address the requirements.
Compare your approach with alternative solutions, highlighting pros and cons in terms of scalability, latency, cost, and complexity. Justify why your design is optimal for the given constraints.
Identify potential bottlenecks and single points of failure, and describe mitigation strategies like replication, sharding, or backpressure. Show proactive thinking about reliability and operability.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.