Ticketmaster System Design Explained | Design a Flash Sale Ticket Booking System

How does Ticketmaster survive millions of users clicking "Buy Tickets" at exactly the same second? Why do you end up #245,812 in the waiting room, and how does the system ensure that the same seat is never sold twice? In this deep dive, we design a production-scale Ticket Booking System like Ticketmaster, BookMyShow, StubHub, Eventbrite, and AXS from scratch. We'll cover how modern ticketing platforms handle flash-sale traffic spikes, implement fair virtual waiting rooms, atomically reserve seats, generate secure QR codes, prevent bots and scalpers, and scale globally using Redis, Kafka, PostgreSQL, CDN, WebSockets, and distributed microservices. Whether you're preparing for: System Design Interviews Senior Software Engineer Interviews Staff Engineer Interviews Principal Engineer Interviews Backend Engineering Distributed Systems this tutorial covers the production architecture behind one of the hardest concurrency problems in software engineering. 📚 What You'll Learn ✅ Functional & Non-Functional Requirements ✅ Capacity Estimation ✅ High-Level Architecture ✅ Virtual Waiting Room Design ✅ Flash Sale Traffic Handling ✅ Queue Management & Fairness ✅ Seat Reservation using Redis Lua Scripts ✅ Preventing Double Booking ✅ Barcode & QR Code Generation ✅ Fraud Detection & Anti-Bot Systems ✅ Resale Marketplace ✅ Payment Processing ✅ Observability & Monitoring ✅ Production Grade Improvements ✅ Principal Engineer Design Questions ⏱ Chapters 0:00 Cold Open — The Flash-Sale Problem 1:34 Functional Requirements 3:37 Non-Functional Requirements 5:23 Capacity Estimation 7:05 API Design 9:31 Data Model 10:30 High-Level Architecture 13:10 Deep Dive: Virtual Waiting Room 16:35 Deep Dive: Seat Reservation (Redis Lua) 18:36 Deep Dive: Fraud Detection 21:21 Deep Dive: Barcode & Ticket Integrity 23:18 Deep Dive: Resale Marketplace 24:34 Principal / Staff Questions 25:29 Observability & Monitoring 27:12 Data Lineage & Traceability 28:57 Wrap-Up