We use analytics and advertising cookies to understand how the site is used and whether our ads on Facebook and Instagram work. They are set only if you accept. See our Privacy Policy for details.
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
Unlock it with a subscription.
Try everything free for 7 days. Cancel anytime.
7-day trial, then $8/mo - or $48/yr ($4/mo, save 50%). Cancel anytime.
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.
Mock interview: design Ride-Share Dispatch →