Problems / Scaling, easy

The slow ramp

Traffic grows from 800 to 2,400 req/s over the run. The API is sized for today.

Solve it in the labTake it as a mock interview

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Your goals

Success ≥ 99%, p99 ≤ 500 ms all the way to the end.

Test cases

Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 5; 1 of them are hidden until then.

  1. As given. The problem’s own traffic, scheduled failures and seed.
  2. Peak hour. 25% more traffic than the problem states, with the same failures.
  3. A slow dependency. The main data store or model answers twice as slowly for part of the run.
  4. A server dies. One replica of the service with the most replicas is killed for part of the run.

The traffic

800 requests a second, ramping to 3× for 30 seconds: 90% reads, 10% writes.

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic 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 serviceLoad balancer forwards to it.Calls Redis cache (checked first), Postgres.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s.2 replicas × 120 slots · timeout 1.0 s
Redis cacheCacheAPI 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 databaseAPI 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

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