Problems / Agents and tools, medium
A chat agent handles 300 turns a second. Each turn reads the thread’s state, runs the agent and writes the state back. Users often send a second message before the first run finishes, so two runs on one thread read the same state and the last write wins.
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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.
300 requests a second for 30 seconds: 100% turn (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 Chat agent API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| Chat agent APIApp service | Load balancer forwards to it.Calls Thread state, Model.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 500 slots · timeout 30 s |
| Thread stateSQL database | Chat agent API calls it.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases. | 16 vCPU · 200 connections |
| ModelLLM endpoint | Chat agent API calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 3000 streams |