The core design wasn't too bad to sketch out but the race condition piece is where I got stuck.
Start by clarifying functional and non-functional requirements, then estimate scale (users, auctions, bids per second). Design the data model and high-level architecture, focusing on how to handle bid concurrency and automatic auction closing reliably.
Pro tip: Emphasize idempotency and exactly-once processing for bid placement and auction closing, as these are critical in a distributed auction system to prevent double bids or missed winners.
Ask about expected user base, auction volume, bid rate, latency requirements, and consistency needs. Define core features: create auction, place bid, auto-close, determine winner.
Define entities: User, Auction (with start/end time, status), Bid (with amount, timestamp, bidder). Consider indexes for efficient queries like highest bid per auction.
Outline components: API servers, auction service, bid service, database (SQL for transactions or NoSQL for scale), cache, message queue for async processing, and a scheduler for auction closing.
Discuss strategies for bid concurrency: optimistic locking, distributed locks, or serializable transactions. Ensure bids are processed in order and only valid bids accepted.
Design a reliable mechanism to close auctions at end time: use a distributed scheduler (e.g., cron with leader election) or delay queue. Ensure exactly-once processing and notify winner.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.