Problems / Resilience, easy
A rate limiter in front of the API allows 1,000 req/s. Normal peak traffic is 1,300 req/s, so real users get 429s.
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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 4; 1 of them are hidden until then.
1,300 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 |
|---|---|---|
| Rate limiterRate limiter | Traffic enters here.Calls Load balancer.Most limiters use a token bucket: tokens refill at the rate, and the bucket size is the burst you allow. | 1,000 req/s |
| Load balancerLoad balancer | Rate limiter forwards to it.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 Redis cache (checked first), 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 |
| 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 |