Problems / AI products, medium

SRE agent runs too long

An on-call SRE agent investigates incidents in 15 steps of model calls and tool queries.

Free to open. Runs in your browser, no sign-up.

Your goals

Success ≥ 95% of tasks, p99 ≤ 90 s.

2 requests a second for 45 seconds: 100% task (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 Agent API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header.	–
Agent APIApp service	Load balancer forwards to it.Calls Agent orchestrator.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s.	3 replicas × 500 slots · timeout 180 s
Agent orchestratorAgent orchestrator	Agent API calls it.Calls Model, MCP tool servers.An agent loops: think, call a tool, read the result, repeat until done.	400 slots · 15 steps
ModelLLM endpoint	Agent orchestrator calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second.	300 streams
MCP tool serversTool / MCP server	Agent orchestrator calls it.Tools give the model actions such as search or database queries; each call is another round trip.	200 slots

Try it first. Open one hint at a time if you get stuck.

Hint 1

1% tool failures over 15 steps.

Hint 2

Find the red card first, then its capacity: slots ÷ seconds per request.

One way to solve it

Cap the agent’s steps.