Spent the first few minutes just trying to scope it down because stock trading can mean a hundred different things.
Start by clarifying the scope (e.g., retail vs. institutional, asset classes, expected scale) and then focus on core components: order management, matching engine, market data, and persistence. Emphasize trade-offs between consistency, latency, and scalability, and discuss how you would handle high throughput and fault tolerance.
Pro tip: Show awareness of regulatory and financial constraints (e.g., SEC rules, audit trails) and how they influence design decisions like immutability and exactly-once processing.
Ask questions to understand functional and non-functional requirements: user types, order types, expected throughput, latency, consistency needs, and regulatory constraints.
Sketch the main components: API gateway, order service, matching engine, market data service, persistence layer, and notification service. Explain data flow.
Focus on the matching engine (e.g., order book data structure, matching algorithms) and data storage (e.g., time-series DB for trades, relational for orders). Discuss concurrency and consistency.
Explain how to scale horizontally (e.g., sharding by symbol), ensure fault tolerance (replication, leader election), and handle peak loads (backpressure, queues).
Summarize key trade-offs (e.g., latency vs. consistency, SQL vs. NoSQL) and propose monitoring, alerting, and deployment strategies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.