Individual skill
tempo
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.
skills/grafana-lgtm/tempo/SKILL.md
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- Apache-2.0
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# 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