Problems / AI systems, medium
Your chat product depends on one model provider. At 20 s it is down for 15 seconds.
Free to open. Runs in your browser, no sign-up.
Success ≥ 99% through the outage.
40 requests a second for 45 seconds: 100% chat (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 gateway (keys, routing, retries).Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| AI gateway (keys, routing, retries)App service | Load balancer forwards to it.Calls Prompt cache.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 2 replicas × 400 slots · timeout 20 s |
| Prompt cachePrompt cache | AI gateway (keys, routing, retries) calls it.Calls Primary model (provider A).Providers can cache a long repeated prompt prefix, cutting cost and time to first token. | 2000 slots · 20% hit rate |
| Primary model (provider A)LLM endpoint | Prompt cache calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 400 streams · 3,000 calls/min |
Try it first. Open one hint at a time if you get stuck.
Nothing of yours is overloaded.
Real gateways fail over to a second provider.
Add a fallback model from another provider (“fix it”).