Design a ticket booking system (like Ticketmaster).

Summary

Hold seats with short-lived reservations (atomic seat-state transitions or Redis locks with TTL), complete payment within the hold window, and protect hot on-sales with a virtual waiting room that admits users at a controlled rate.

Requirements

• Browse events and seat maps
• Reserve specific seats; no double booking
• Payment within a hold window (e.g., 10 min)
• Huge spikes for popular events

API

GET  /api/events/{id}/seats            → seat map with availability
POST /api/events/{id}/holds  {"seat_ids": ["A1","A2"]} → {hold_id, expires_at}
POST /api/holds/{id}/purchase  Idempotency-Key: ...

Data Model

seats(event_id, seat_id, status /* available|held|sold */, hold_id, hold_expires_at, version,
      PRIMARY KEY (event_id, seat_id))
holds(id, user_id, event_id, expires_at, status)
orders(id, hold_id UNIQUE, user_id, total_minor, status)

Architecture

A waiting room service issues signed admission tokens at a controlled rate. Admitted users load cached seat maps (refreshed frequently) and request holds; the booking service atomically transitions seats from available to held with a conditional update (WHERE status='available') for all requested seats in one transaction. Payment completes the purchase; a sweeper or TTL releases expired holds.

Deep Dives

• Double booking: conditional updates or optimistic locking per seat
• Waiting room: queue position, fairness, bot protection
• Seat map reads: cached and pushed via SSE; holds are the source of truth
• General admission: decrement a counter instead of seats

Scaling

• Partition by event
• Cache event and seat-map reads heavily
• Throttle writes via admission control

Comparison / Tradeoffs

What interviewers look for

A structured approach: clarify requirements and scale, sketch the API and data model, draw the high-level architecture, then go deep on the hardest component and discuss trade-offs, bottlenecks and failure modes.

Follow-up questions

• How do you stop bots from buying all tickets?
• How do you handle payment failures after the hold expires?