Start by clarifying requirements and scale, then design a layered architecture that separates read-heavy seat map queries from write-heavy booking transactions. Focus on the critical path: seat selection, hold with expiry, and payment idempotency, using distributed locks and optimistic concurrency to prevent overselling. Address wait queues, anti-bot, audit logs, and real-time updates as cross-cutting concerns with appropriate technologies.
Pro tip: Emphasize that holds should be implemented as short-lived reservations with a TTL, and that payment idempotency must be enforced at the database level with unique constraints on idempotency keys. This shows you understand the practical pitfalls of distributed systems.
Ask about expected traffic (e.g., millions of concurrent users), seat map size, event popularity, and consistency vs. availability trade-offs. Define functional and non-functional requirements.
Propose a microservices-based architecture with separate services for seat map, booking, payment, and notification. Use a CDN for static seat maps, a read-optimized database for availability, and a write-optimized database for bookings.
Design a seat hold system using a distributed cache (e.g., Redis) with TTL for temporary holds. Use optimistic locking or distributed locks to prevent double-booking. Ensure holds expire automatically and release seats.
Implement payment processing with idempotency keys to avoid duplicate charges. Use a transactional outbox pattern to ensure consistency between payment and booking status. Handle refunds with a similar idempotent approach.
Introduce a virtual waiting queue to manage traffic spikes. Implement anti-bot measures like CAPTCHA, rate limiting, and behavioral analysis. Use WebSockets or server-sent events for real-time seat availability updates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.