Components · Data and messaging

Geospatial index

Nearby searches and map tiles.

Lesson
Coming soon
Zone
data
Place it
4 cr on the blank canvas, free inside a problem

At a glance

Did you know
Geo indexes split the map into cells, such as geohashes, to find nearby points fast.
Rule of thumb
Dense cities overload single cells: use smaller cells where points cluster.
Watch out
Dense areas are hot cells; large radius queries.

Its settings in ScaleMySystems

What you can change on it in the lab, and what each number does.

Concurrency (slots)
Calls it can work on at once (per instance when autoscaling). Needed slots ≈ calls per second × seconds each takes. Extra calls wait in the queue, then are rejected.
Queue capacity
Calls allowed to wait for a free slot. A bigger queue absorbs bursts but adds waiting time; 0 rejects straight away.
vCPU
CPU cores available. Needed ≈ calls per second × CPU per request ÷ 1000. Above about 90% busy it slows down and may crash.
CPU per request (ms)
CPU time each call burns. Part of what the component is; make the code cheaper to lower it.
Latency (p50) (ms)
Typical time one call takes here, before any calls it makes itself. Slots are held for this long.
Latency (p99) (ms)
The slowest 1% of calls. Callers must set their timeout above this or they cut off healthy calls.
Timeout to dependencies (ms)
How long it waits for each call it makes before giving up. Set it above the dependency’s p99 but low enough that a dead dependency does not hold every slot.
Error rate
Share of calls that fail on their own (bugs, declines, flaky tools). An agent that calls it on every step multiplies this.
Quota (req/min)
Calls allowed per minute (an API key or provider limit). Calls over it get 429s. Needed = calls per second × 60, with headroom.

Problems that start with it

  • Uber: driver location updates Drivers send their location every few seconds: 2,500 updates and lookups a second into a geospatial index with 4 vCPUs and 2 ms of CPU each.
  • Uber: from launch build to real traffic Uber as first shipped: no ETA cache, and the location, ETA and ride services, the geo index, its updaters and the notification workers at an eighth of their real size. 5,000 requests a second: 60% driver location pings, 30% ETA lookups, 10% ride requests. Half of all requests fail.

Full lesson coming soon

Lessons are being added one component at a time: how it works, its settings, a live exercise to break and fix it, interview questions and a short check. See the Circuit breaker lesson for what one looks like.