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Meta·Technical Product Manager·Onsite - System Design / Architecture·Senior

Senior
Jun 2026

Summary

Meta TPM interview with a system design question about building an airline booking platform. Pretty open-ended, which I wasn't fully prepared for.

Questions Asked (1)

Q1

Design an airline booking system.

System DesignTechnical Trade-offsData Modeling
Author's notes

I jumped straight into the database schema and the interviewer had to nudge me back toward requirements.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the scope and requirements of the airline booking system, focusing on key user journeys and business goals. Then, outline a high-level architecture that addresses scalability, data consistency, and trade-offs, and dive into critical components like search, booking, and payment. Finally, discuss how you would measure success and iterate based on metrics.

Pro tip: Emphasize the importance of handling peak loads and concurrency (e.g., seat locking) and tie technical decisions back to user experience and business metrics like conversion rate and booking latency.

1. Clarify Requirements

Ask questions to understand the scope: Is this for a single airline or an aggregator? What are the key features (search, booking, payment, cancellation)? What are the scale and latency requirements?

2. Define Core User Journeys

Identify the primary flows: searching for flights, selecting seats, booking, payment, and post-booking management. Prioritize based on business impact.

3. High-Level Architecture

Sketch a scalable architecture with separate services for search, booking, payment, and inventory. Discuss data stores (SQL vs NoSQL), caching, and load balancing.

4. Deep Dive into Critical Components

Focus on challenging areas: seat inventory management with concurrency control, payment integration, and search performance. Discuss trade-offs (e.g., consistency vs availability).

5. Metrics and Iteration

Define success metrics (e.g., booking conversion, latency, error rates) and how you would monitor and iterate on the system post-launch.

Key Points to Mention

  • Scalability: handling peak traffic during holidays and sales events
  • Data consistency: ensuring seat inventory is accurate and avoiding double-booking
  • Concurrency control: using locks, optimistic concurrency, or distributed transactions
  • Caching strategies: for flight search results and frequently accessed data
  • Payment integration: idempotency, retries, and handling failures
  • Trade-offs: consistency vs availability, latency vs cost, build vs buy

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