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TikTok·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Jul 2026

Summary

TikTok system design round, one massive question that basically covered every angle of a flash-sale ticketing system. The scope was genuinely intimidating and I left feeling like I'd only scratched the surface on half the topics.

Questions Asked (1)

Q1

Design a high-concurrency ticketing system for limited inventory (like a sold-out concert) that can handle millions of simultaneous purchase attempts without overselling. You need to cover admission control, inventory correctness, bot mitigation, idempotency, hot-key sharding, APIs, data modeling, caching, async messaging, consistency tradeoffs, failure handling, capacity planning, and monitoring.

System DesignTechnical Trade-offsData Modeling
Author's notes

This was essentially thirteen questions wrapped in one.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (scale, consistency, latency) and then walk through the system from admission control to purchase completion, emphasizing how each component prevents overselling and handles failures. Focus on the critical path: inventory reservation with atomic operations, idempotency, and async processing, while discussing trade-offs between consistency and availability.

Pro tip: Emphasize that overselling is prevented by making inventory decrement atomic and idempotent, and that the real challenge is managing the thundering herd through admission control and queueing. Show awareness that perfect consistency at scale requires accepting some latency and eventual consistency in non-critical paths.

1. Clarify Requirements and Scale

Ask about expected traffic (e.g., millions of concurrent users), inventory size, latency requirements, and consistency needs. Define success metrics like zero overselling and high availability.

2. Design Admission Control and Bot Mitigation

Propose a virtual waiting room with rate limiting, CAPTCHA, and token-based admission to smooth traffic and block bots. Use a queue to serialize purchase attempts.

3. Ensure Inventory Correctness and Idempotency

Use atomic decrement operations (e.g., Redis Lua scripts or database transactions) with optimistic locking. Implement idempotency keys to deduplicate requests and prevent double purchases.

4. Handle Hot-Key Sharding and Caching

Shard inventory by ticket type or event to distribute load. Cache inventory counts with write-through or write-behind strategies, ensuring cache consistency with the source of truth.

5. Design Async Messaging and Failure Handling

Use a message queue (e.g., Kafka) to process orders asynchronously, with retries and dead-letter queues. Implement compensation logic for failed payments and release inventory.

6. Plan Capacity and Monitoring

Estimate resource needs based on peak QPS and design for horizontal scaling. Set up monitoring for inventory levels, queue depths, error rates, and latency, with alerts for anomalies.

Key Points to Mention

  • Admission control via virtual waiting room and rate limiting to handle thundering herd
  • Atomic inventory decrement using Redis Lua scripts or database transactions with optimistic locking
  • Idempotency keys to ensure exactly-once processing of purchase requests
  • Hot-key sharding by event or ticket type to distribute load across partitions
  • Async order processing with message queues and compensation for failures
  • Trade-offs between strong consistency (for inventory) and eventual consistency (for other data), and how to monitor and scale the system

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.