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Geo-indexing, real-time matching, ETA prediction, and surge. The canonical geo-spatial design problem with hard real-time constraints.
Design the dispatch backend for a ride-share product. Riders open the app and request a ride; the system finds nearby drivers, picks one, notifies driver and rider, tracks the trip in real time, completes payment.
This is the canonical geo-spatial system design question. Strong candidates demonstrate fluency in spatial indexing (geohash, S2, H3), real-time location updates, matching algorithms, and the operational layer (ETAs, surge, fraud).
Asking these before diving into a solution is the difference between a "hire" and a "no signal" rating. Pick the questions whose answers would change your design.
Capacity estimation · architecture with all 9 components explained · 6 deep dives · trade-off analysis · 8 common follow-up questions
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Consistent hashing, eviction, replication, and what really happens when a single hot key takes down the cluster.
Five algorithms, three sharding strategies, one fail-open vs fail-closed decision. The bounded design that surfaces in every backend interview loop.
Reading is the floor. The interview signal is in walking through this live with someone probing follow-ups. Use the AI mock interview to practice talking through requirements, architecture, and trade-offs out loud.
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