Meta·Software Engineer·Onsite - System Design / Architecture·Intermediate

IntermediateRejected

May 2026

Summary

Meta system design round for a software engineer role, and it went sideways fast. I came in prepared for a large-scale distributed problem and spent half an hour going down that road before the interviewer revealed he just wanted a simple single-machine solution for a small school. The recruiter later confirmed this round failed because I never properly nailed down requirements up front.

Questions Asked (1)

Design a ticket booking system.

System DesignTechnical Trade-offsAdaptability & Ambiguity

Author's notes

I walked in with a fully memorized large-scale design and just started reciting it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a high-level architecture that handles high concurrency and prevents double-booking. Focus on trade-offs between consistency, availability, and scalability, and be prepared to dive deep into critical components like seat locking and payment integration.

Pro tip: Proactively discuss how you would handle failures and edge cases, such as payment timeouts or seat lock expiration, as this demonstrates production-level thinking. Also, quantify your design decisions with back-of-the-envelope calculations to show scalability awareness.

1. Clarify Requirements and Scope

Ask questions to understand functional and non-functional requirements, such as expected traffic, consistency needs, and supported features (e.g., seat selection, payment). Define the scope to avoid over-engineering.

2. High-Level Design

Sketch the main components: clients, load balancers, application servers, databases, caches, and message queues. Explain how a user flows through the system from browsing to booking.

3. Deep Dive into Critical Components

Focus on the seat locking mechanism, database schema, and concurrency control. Discuss how to prevent double-booking using techniques like optimistic locking, distributed locks, or reservations with TTL.

4. Address Scalability and Reliability

Explain how to scale reads and writes, handle spikes in traffic, and ensure high availability. Mention caching, sharding, replication, and asynchronous processing.

5. Discuss Trade-offs and Alternatives

Compare different approaches (e.g., SQL vs NoSQL, strong vs eventual consistency) and justify your choices based on requirements. Acknowledge potential bottlenecks and mitigation strategies.

Key Points to Mention

Concurrency control mechanisms to prevent double-booking (e.g., optimistic locking, distributed locks, seat reservation with TTL).
Database design: schema for events, seats, bookings, and users; indexing strategies; and choice of SQL vs NoSQL based on consistency and scalability needs.
Caching strategies to handle read-heavy workloads (e.g., caching event details and seat availability) and cache invalidation.
Asynchronous processing for tasks like payment confirmation, email notifications, and seat release using message queues.
Scalability techniques: horizontal scaling, sharding, read replicas, and load balancing.
Handling failures and edge cases: payment timeouts, seat lock expiration, idempotent operations, and graceful degradation.

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