App Observability

---
name: app-observability
license: Apache-2.0
description: Get RED metrics + service maps + frontend RUM + AI/LLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50/p95/p99 latency, exemplar-to-trace, traces-to-logs / profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session replay, `pushError`, React + router integration, `TracingInstrumentation` for browser → backend trace correlation), and AI Observability via OpenLIT (token / cost / latency, GPU, hallucination + toxicity evals). Use when standing up APM for a service, wiring an Alloy OTLP receiver + forwarding to Cloud, instrumenting a React frontend for RUM, debugging why service-map edges are missing, monitoring LLM cost drift, or correlating a frontend error to its backend trace — even when the user says "set up APM", "show service map", "monitor browser perf", "session replay", "RUM SDK", or "watch our OpenAI bill" without naming App / Frontend / AI Observability.
---

# Grafana Cloud Application Observability

> **Docs**: https://grafana.com/docs/grafana-cloud/monitor-applications/

Three products that share the same OTLP + Mimir / Loki / Tempo / Pyroscope plumbing:

1. **Application Observability** — APM from OTel spanmetrics
2. **Frontend Observability** — Faro Web SDK, RUM + session replay
3. **AI Observability** — LLM / vector-DB monitoring via OpenLIT

## Prerequisites

- Grafana Cloud stack + OTLP endpoint + numeric instance ID + API key with `MetricsPublisher` + `LogsPublisher` + `TracesPublisher`
- For APM: app instrumented with OTel SDK; for Frontend: a web app + Faro app key; for AI: Python ≥ 3.10
- Grafana Alloy as the local OTLP receiver (recommended)

## Common Workflows

### 1. Stand up APM — Alloy receiver → Grafana Cloud + verify