The setup took forever, like 10+ minutes of the interviewer fumbling with the environment, so by the time we got to the actual problem I was half-distracted.
Start by clarifying requirements and scale (e.g., number of users, orders per second, location update frequency). Then design the high-level architecture, explicitly comparing trade-offs for cart persistence (e.g., client-side vs. server-side, database choices) and real-time driver location updates (e.g., polling vs. WebSockets, geospatial indexing). Finally, dive into data models and scaling strategies for each component.
Pro tip: Emphasize the trade-offs between consistency, latency, and cost for each design choice, and relate them to business impact (e.g., cart abandonment, delivery ETA accuracy). This shows you think beyond technical implementation.
Ask questions to understand functional and non-functional requirements: expected number of users, orders per second, driver location update frequency, consistency needs, and budget constraints.
Sketch the main components: client apps, API gateway, cart service, order service, driver location service, databases, and message queues. Explain how they interact.
Compare options: client-side (local storage) vs. server-side (database, cache). Discuss consistency, scalability, and user experience implications (e.g., cross-device sync, cart abandonment).
Evaluate approaches: polling vs. WebSockets vs. SSE. Discuss data storage (geospatial indexes like Redis GEO or PostGIS), update frequency, and scalability.
Propose schemas for carts, orders, and driver locations. Discuss sharding, replication, and caching strategies to handle scale.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.