Problems / Databases, medium
A profile service reads from replicas that lag 1.5 seconds and updates popular rows with read-then-write. Users see old profiles, and some edits vanish.
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No stale reads, no lost updates, success ≥ 99%.
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.
1,500 requests a second for 30 seconds: 60% reads, 40% 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 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 database | API calls it.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases. | 8 vCPU · 60 connections · 2 read replicas |