Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin.
grafana-tempo/SKILL.md
---
name: tempo
license: Apache-2.0
description: Stand up Grafana Tempo as a cost-efficient distributed-tracing backend that only needs object storage, and write TraceQL queries against it. Covers OTLP + Jaeger + Zipkin ingestion, the distributor → live-store → block-builder → object-storage write path, metrics-generator for RED spanmetrics + service graphs, Helm `tempo-distributed` deployment, multi-tenant `X-Scope-OrgID`, TraceQL span / resource / event scopes, structural operators (`>>`, `<<`), `rate()` + `quantile_over_time` metrics, and the traces-to-logs / metrics / profiles datasource links. Use when deploying Tempo, writing a TraceQL query for slow / errored requests, debugging "no traces showing in Explore", sizing queriers / compactors, configuring S3 / GCS / Azure block storage, or wiring trace ↔ log ↔ profile correlation — even when the user says "tracing backend", "find slow requests", "show me the service graph", "store traces in S3", "Jaeger compatible store", or "what called this span" without naming Tempo.
---
# Grafana Tempo
> **Docs**: https://grafana.com/docs/tempo/latest/
Cost-efficient distributed tracing. Accepts OTLP / Jaeger / Zipkin / OpenCensus / Kafka. Stores Parquet blocks in S3/GCS/Azure.
## Prerequisites
- Docker (quick start) or Kubernetes (production)
- Object storage bucket (S3/GCS/Azure) for distributed deployments
- An OTLP-emitting app or `tempo-cli` for synthetic traffic
- A Grafana stack with a Tempo datasource for querying
## Common Workflows
### 1. Stand up Tempo locally + verify ingestion
```bash
# 1. Start the official Docker Compose example