Problems / Scaling, hard
Every request checks a session with an auth service (40 slots) and runs a query on a search index (32 slots, 4 ms of CPU each), at 1,500 req/s.
Free to open. Runs in your browser, no sign-up.
Success ≥ 99%, p99 ≤ 500 ms.
1,500 requests a second for 30 seconds: 90% reads, 10% writes.
What each component does in this design, and what calls it. The simulator mimics each one from these settings.
| Component | Its job here | Settings |
|---|---|---|
| Load balancerLoad balancer | Traffic enters here.Calls API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| APIApp service | Load balancer forwards to it.Calls Auth service, Redis cache (checked first), Postgres, Search index.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 200 slots · timeout 1.0 s |
| Redis cacheCache | API checks it first for reads.An in-memory cache like Redis usually answers in well under a millisecond inside one region. | 95% hit rate |
| PostgresSQL database | API reads it when Redis cache misses. API calls it for writes.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases. | 8 vCPU · 60 connections |
| Auth serviceAuth / identity service | API calls it.Short-lived access tokens plus refresh tokens limit the damage if a token leaks. | 40 slots |
| Search indexSearch index | API calls it for reads.Search engines build an inverted index: each word points to the documents that contain it. | 32 slots |
Try it first. Open one hint at a time if you get stuck.
Two dependencies on the same path; each needs capacity for all the traffic.
Slots needed = rate × seconds per call; CPU needed = rate × CPU per call.
Give both more capacity: slots for auth, slots and vCPU for search.
Give the auth service and the search index more capacity ("double the auth service capacity", "double the search index capacity").