Startup Metrics Dashboard Alternative — Managed API Beyond Prometheus and Grafana

Description and use

A startup adopted Infrai’s managed API to collect per‑turn metrics, creating a lightweight dashboard with latency, cost, and outcome charts, avoiding the overhead of Prometheus/Grafana.

Problem

Small customer‑support AI agents need a latency‑and‑cost dashboard without running full Prometheus/Grafana stacks.

Outcome

The startup achieved a low‑overhead metrics solution that provides actionable insights into turn latency, cost, and outcomes, while keeping infrastructure complexity minimal.

Workflow

• Define a TypeScript type for AgentTurnMetric.
• Implement a MetricsSink interface with a report method.
• Create a BufferedMetricsSink that buffers metrics and sends them via an adapter.
• Use Infrai’s REST API to discover available metrics endpoints.
• Report each completed turn through the sink.
• Store correlation IDs in logs or an event store, not as metric labels.
• Configure a lightweight dashboard to display three charts: p50/p95 latency, cost per turn, outcome counts.

Evidence

A managed metrics endpoint is the practical first choice for a small customer‑support AI agent, provided the application owns the measurement contract.

Source

Use a completed agent turn as the unit of analysis. Its application‑owned record needs a small vocabulary: completion time, input and output tokens, estimated cost, outcome, model family, deployment region, and a correlation ID.

Source

A useful starting view has three charts: p50 and p95 completed‑turn latency, cost per completed turn, and outcome counts.

Source