All problems

Food Delivery

Order placement shares the fleet with a nonstop courier-location firehose.

medium~20 min Pro Simulator · +110 ptsTheory +44 pts
The build

Keep orders flowing and couriers trackable through the dinner peak while an instance dies and the orders store blips.

Courier phones fire a constant stream of location pings alongside every order placed — a queue has to absorb that firehose before it reaches the store, while a geo cache keeps 'where's my courier' a fast lookup instead of a database hit.

Components in play

  • Regional LBSpreads order and ping traffic across the fleet.
  • Order servicePlaces orders and records courier pings.
  • Courier ping ingestAbsorbs the constant courier-location firehose.
  • Courier geo cacheIn-memory live courier positions for fast lookups.
  • Orders storeDurable order lifecycle state.

Graded on these SLOs

  • ≥ 97.00%Orders succeed
  • ≤ 130 msOrder + tracking p99
  • ≥ 10k rpsServe the dinner peak
  • ≤ 90%Fleet headroom
  • ≤ 9Lean footprint
Base 10,000 rps46s run 3 scripted failures

The brief

Design the backend for a meal-delivery app: diners place orders while every courier's phone fires a constant stream of location pings. The ping firehose can't be allowed to compete with order placement for capacity, and 'where's my courier' has to stay a fast in-memory lookup — not a database query — while orders themselves must survive a store blip during the dinner rush.

Functional

  • Place and confirm an order
  • Ingest continuous courier location pings
  • Show a diner where their courier currently is

Non-functional

  • The ping firehose must not starve order placement
  • Courier location lookups are low-latency, served from memory
  • Orders survive a dinner-peak traffic spike and a store blip

Warm-up: design decisions

Optional theory to prime the calls a senior engineer would make before you build.

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