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Design Ticket Booking Auto Release

Last updated: Mar 29, 2026

Quick Overview

Design Ticket Booking Auto Release evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • medium
  • Meta
  • System Design
  • Software Engineer

Design Ticket Booking Auto Release

Company: Meta

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

##### Question Design a ticket-booking system where a reserved ticket automatically returns to the inventory if payment is not completed within 30 minutes. Discuss data model, reservation flow, concurrency handling, timeout processing, and consistency guarantees.

Quick Answer: Design Ticket Booking Auto Release evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/System Design/Meta

Design Ticket Booking Auto Release

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Jul 29, 2025, 8:05 AM
mediumSoftware EngineerTechnical ScreenSystem Design
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Design Ticket Booking Auto Release

System Design: Auto-expiring Ticket Reservations

Problem

Design a ticket-booking system where a reserved ticket automatically returns to the inventory if payment is not completed within 30 minutes.

Discuss and propose a design for:

  1. Data model and state machine.
  2. Reservation and payment flow.
  3. Concurrency control to prevent overselling.
  4. Timeout processing (auto-expiry) at scale.
  5. Consistency guarantees and failure handling.

Assumptions

  • Tickets can be either seat-based (assigned seats) or general admission (GA) with a capacity count.
  • A reservation places a temporary hold for 30 minutes. If payment is completed within that window, the reservation becomes a purchase; otherwise, it expires and inventory is released.
  • High read/write throughput; horizontally scalable services.
  • Payment is processed by an external provider and can succeed/timeout/arrive late.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
  • State explicit assumptions before making sizing or architecture decisions.
  • Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers

  • A scoped requirements summary with concrete non-goals and success metrics.
  • API, data model, architecture, consistency, capacity, and operations.
  • Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
  • A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions

  • What breaks first at 10x traffic or data volume?
  • How would you degrade gracefully during dependency failures?
  • What metrics and alerts would prove the design is healthy after launch?

Submit Your Answer to Earn 20XP

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