Start by clarifying requirements: daily puzzle, user submissions, leaderboard, and score summary. Then design a scalable system with a focus on data modeling for submissions and scores, and APIs for submission and leaderboard retrieval. Discuss trade-offs like consistency vs. availability for leaderboards and consider caching and sharding for scale.
Pro tip: Emphasize idempotency and anti-cheat measures for submissions, as Uber values reliability and fairness. Also, discuss how to handle time zones for daily puzzles and leaderboard resets.
Ask questions to understand scale (DAU, submissions per day), latency requirements, and whether leaderboard is global or segmented. Clarify scoring rules and daily reset behavior.
Sketch components: API gateway, submission service, scoring service, leaderboard service, and data stores. Consider using a message queue for asynchronous processing.
Design schemas for puzzles, submissions, and scores. Use a time-series or wide-column store for submissions and an in-memory data store (e.g., Redis sorted sets) for leaderboards.
Define endpoints for submitting answers, retrieving leaderboard, and fetching user score summary. Include pagination and filtering for leaderboard.
Discuss sharding by puzzle ID or user ID, caching leaderboards, and eventual consistency vs. strong consistency. Address failure scenarios and idempotency.
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