Problems / Scaling, medium

Write-heavy ledger

A ledger service is 60% writes at 1,500 req/s on a 2-vCPU database. Read replicas won’t help writes.

Solve it in the labTake it as a mock interview

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Your goals

Success ≥ 99%, p99 ≤ 500 ms.

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 6; 2 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

1,500 requests a second for 30 seconds: 40% reads, 60% 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 Postgres.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
PostgresSQL databaseAPI calls it.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases.2 vCPU · 60 connections

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