Problems / AI security and governance, easy
Every chat checks a data-access policy service with 8 slots and 40 ms per check.
Free to open. Runs in your browser, no sign-up.
Success ≥ 99%, time to first token p99 ≤ 2.5 s.
250 requests a second for 30 seconds: 100% request (reads).
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 AI app.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| AI appApp service | Load balancer forwards to it.Calls Tool policy engine, 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 |
| Tool policy engineTool policy engine | AI app calls it.A policy engine checks each tool call against what this agent, user and data may do. | 8 slots |
| ModelLLM endpoint | AI app calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 2000 streams |
Try it first. Open one hint at a time if you get stuck.
8 ÷ 0.04 s = 200 checks a second.
Look at what got through, or what was wrongly blocked: which filter is responsible for this kind of traffic?
Give the policy engine more capacity.