engineering · 1 min read
Observability for the LLM Gateway: What to Measure and Alert On
The four golden signals for an LLM gateway are not the same as for an HTTP service. Here is what to measure, what to alert on and what to ignore.
BABhogar AI TeamProduct & Engineering
The four golden signals (latency, errors, traffic, saturation) need adapting for AI. Token throughput and per-call cost matter more than raw RPS; refusal rate matters more than HTTP error rate.
Why it matters
Most teams either over-instrument (drowning in noise) or under-instrument (flying blind). The middle path: a small set of high-signal metrics with budgets and alerts.
How Bhogar AI approaches it
Bhogar AI gateway emits standardised metrics for latency p50/p95/p99, token throughput, cost per second, refusal rate, fallback rate, cache hit rate and per-tenant quotas - with default alert thresholds.
- Latency p50/p95/p99 per route and provider
- Token throughput and cost per second
- Refusal, fallback and cache-hit rates
- Per-tenant quota dashboards
- Default alert thresholds and runbooks
What you get
Gateway customers detect provider regressions, cost surprises and quality drifts within minutes instead of hours or days.