Problem Statement

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Ticketmaster - Problem Statement

Overview

Design a ticket booking system that handles massive traffic spikes during popular event sales (Taylor Swift, Super Bowl), prevents scalping and bots, ensures fair access, and manages inventory across venues and events globally.

Functional Requirements

Core Ticketing Features

  • Event Management: Create/manage events with venues, dates, pricing tiers
  • Seat Selection: Interactive seat maps with real-time availability
  • Ticket Purchase: Reserve seats, complete payment within time limit
  • Ticket Transfer: Transfer tickets to other users
  • Ticket Resale: Official resale marketplace with price caps
  • Mobile Tickets: QR code tickets for entry validation
  • Waitlist: Join waitlist when sold out, auto-purchase if available

Inventory Management

  • Real-time Availability: Accurate seat availability across all channels
  • Hold Mechanism: Reserve seats during checkout (5-10 minute hold)
  • Release Mechanism: Auto-release unpaid reservations
  • Allocation Rules: VIP pre-sales, fan club access, general public
  • Dynamic Pricing: Adjust prices based on demand (platinum seats)

Anti-Bot and Fairness

  • Queue System: Virtual waiting room during high-demand sales
  • Bot Detection: CAPTCHA, device fingerprinting, behavioral analysis
  • Purchase Limits: Max 4-8 tickets per transaction
  • Verified Fan: Pre-registration with identity verification
  • Rate Limiting: Prevent automated ticket purchasing

User Experience

  • Event Discovery: Search, browse, recommendations
  • Notifications: On-sale alerts, price drop alerts
  • Order History: View past purchases and upcoming events
  • Account Management: Payment methods, preferences, loyalty points

Non-Functional Requirements

Performance

  • Concurrent Users: Handle 10 million concurrent users during major sales
  • Ticket Sales Rate: Process 50,000 ticket purchases per minute
  • Page Load Time: <2 seconds for event pages
  • Checkout Time: Complete purchase within 3 minutes
  • Queue Wait Time: Transparent wait time estimates

Scalability

  • Daily Events: Support 100,000+ events globally
  • Annual Tickets: Sell 500 million tickets per year
  • Traffic Spikes: Handle 100x normal traffic during major sales
  • Geographic Distribution: Serve users in 30+ countries

Reliability

  • System Uptime: 99.99% availability
  • No Double-Booking: Guarantee each seat sold only once
  • Payment Success: 99.9% payment success rate
  • Data Durability: Zero ticket data loss

Fairness and Security

  • Fair Access: First-come-first-served with anti-bot measures
  • Fraud Prevention: Detect stolen cards, fake accounts
  • Scalper Prevention: Limit resale prices, verify buyers
  • PCI Compliance: Secure payment processing

Scale Constraints

Traffic Patterns

Normal Day: 100K concurrent users, 10K tickets/hour
Major Sale (Taylor Swift): 10M concurrent users, 50K tickets/minute
Peak Load: 100x normal traffic for 1-2 hours

Data Volume

  • Events: 100K active events
  • Tickets: 500M tickets sold annually
  • Users: 100M registered users
  • Transactions: 1M transactions per day during peak

Key Challenges

1. Traffic Spikes

  • 10M users trying to buy 50K tickets simultaneously
  • Need virtual queue to manage demand
  • Scale infrastructure 100x in minutes

2. Inventory Consistency

  • Prevent double-booking across distributed systems
  • Handle concurrent purchase attempts for same seat
  • Maintain accuracy during high contention

3. Bot Prevention

  • Sophisticated bots bypass CAPTCHA
  • Scalpers use multiple accounts and IPs
  • Need multi-layered defense strategy

4. Fair Access

  • Balance speed vs fairness
  • Prevent wealthy users from buying all tickets
  • Ensure real fans get tickets, not scalpers

Success Metrics

Business Metrics

  • Tickets Sold: 500M+ annually
  • Revenue: $15B+ gross ticket sales
  • Market Share: #1 in primary ticket sales
  • Customer Satisfaction: 4.0+ rating

Technical Metrics

  • Checkout Success Rate: >95% for users who reach checkout
  • Bot Detection Rate: Block >99% of bot traffic
  • Double-Booking Rate: <0.001% of transactions
  • System Uptime: 99.99% availability

This problem requires handling extreme traffic spikes, ensuring inventory consistency, preventing fraud, and maintaining fairness - making it one of the most challenging system design problems.