I jumped straight to a queue-based approach and started talking about rate limiting before I'd even scoped the problem properly.
Start by clarifying requirements and scale (e.g., expected traffic, ticket inventory, fairness guarantees), then outline a high-level architecture that separates read and write paths, uses queues for asynchronous processing, and employs caching and rate limiting. Finally, dive into trade-offs around consistency, availability, and cost, and propose a phased rollout with monitoring.
Pro tip: Emphasize the importance of idempotency and exactly-once processing in payment and ticket allocation to prevent double-selling, and discuss how you'd handle failures gracefully with retries and dead-letter queues.
Ask questions to understand expected concurrent users, ticket inventory size, fairness requirements, and budget constraints. Define functional and non-functional requirements.
Propose a microservices-based architecture with separate services for inventory, orders, payments, and notifications. Use a load balancer, API gateway, and CDN for static content.
Discuss strategies like optimistic locking, distributed locks, or queue-based serialization to manage ticket inventory. Ensure idempotent operations and use a database with strong consistency for critical writes.
Explain how to scale horizontally with stateless services, use caching (e.g., Redis) for hot data, and implement rate limiting and throttling to protect the system.
Describe failover mechanisms, retries with exponential backoff, circuit breakers, and comprehensive monitoring/alerting. Plan for load testing and gradual rollout.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.