TL;DR — Grafana turns metrics, traces, and logs into dashboards and alerts. It is the visual front end for your observability stack, especially useful when you need one place to watch GPUs, queues, latency, and model usage.
What it is
Grafana is an open-source visualization and alerting platform. It reads from data sources like Prometheus, Loki, Tempo, and Elasticsearch, then presents dashboards, alerts, and exploration views.
Why it exists
AI platforms produce too many numbers to watch in raw logs. Grafana makes them navigable, giving teams a common screen for cluster health, model performance, and cost signals.
How it works
Grafana connects to data sources, executes queries, and renders panels. Alerts can fire from dashboard rules or unified alerting. That makes it a good place to combine infra metrics and LLM telemetry on one wallboard.
Key features
- Dashboarding for metrics and traces.
- Alerting with routing and silence management.
- Plugins for many backends.
- Templating for reusable views across clusters.
Quick start
{
"datasource": "Prometheus",
"panel": "GPU memory utilization",
"query": "avg(gpu_memory_used_bytes) by (pod)"
}When to use, when to skip
Use it when you want humans to understand the platform at a glance. Skip it only if you have another visualization layer that already covers the same telemetry.
vs / alongside
| Tool | Role | Note |
|---|---|---|
| Grafana | Visualization | Dashboard layer |
| Prometheus | Metrics store | Primary datasource |
| OpenTelemetry | Instrumentation | Feeds data |
| Langfuse | LLM observability | Specialized dashboarding |
References
- Grafana — project home.
- Grafana docs — dashboards and alerting.
- grafana/grafana — source.
Verified against Grafana docs, May 2026.