Start by clarifying requirements and scale (e.g., number of couriers, orders, update frequency) and then walk through the system end-to-end: mobile GPS ingestion, stream processing, storage, ETA/route computation, order assignment, and live map rendering. Emphasize trade-offs (e.g., consistency vs. latency, push vs. pull) and failure handling at each stage.
Pro tip: Focus on the data flow and how you handle real-time updates efficiently—use a pub/sub model and in-memory stores for live tracking, while persisting to a durable store for history. Also, proactively discuss privacy (e.g., data retention, anonymization) and failure recovery (e.g., idempotent processing, dead-letter queues).
Ask about expected number of couriers, orders per day, update frequency, latency requirements, and geographic distribution. This will drive architectural decisions.
Sketch the main components: mobile clients, ingestion layer (e.g., API gateway, message queue), stream processing (e.g., Kafka, Flink), storage (e.g., Redis for live, Cassandra for history), services for ETA/route, assignment, and map rendering.
Detail the design of critical parts: GPS ingestion (batching, compression), stream processing (windowing, state), ETA computation (traffic, historical data), order assignment (matching algorithm), and live map updates (WebSocket, geohashing).
Discuss how to scale each component (sharding, partitioning), privacy measures (encryption, anonymization, retention policies), and failure handling (retries, idempotency, circuit breakers, fallbacks).
Highlight key trade-offs made (e.g., consistency vs. availability, cost vs. performance) and suggest potential improvements or monitoring strategies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.