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Grafana Tempo

By Grafana Labs

AdvancedTool7.5K learners

Grafana Tempo is an open source, high-scale distributed tracing backend by Grafana Labs that stores traces cheaply using object storage and minimal indexing, designed to work closely with Grafana, Loki, and Prometheus.

Definition

Grafana Tempo is an open source, high-scale distributed tracing backend by Grafana Labs that stores traces cheaply using object storage and minimal indexing, designed to work closely with Grafana, Loki, and Prometheus.

Overview

Tempo addresses the same cost problem in tracing that Grafana Loki addresses in logging: storing and indexing every field of every trace at scale gets expensive fast. Instead of building a heavily indexed trace store, Tempo indexes traces only by trace ID and stores the trace data itself in cheap object storage (like S3-compatible storage), relying on that minimal index for fast retrieval when you already know which trace you're looking for. Because Tempo doesn't build rich secondary indexes, it's typically paired with metrics or logs to discover which trace IDs are worth investigating — for example, exemplars in Prometheus metrics or log lines in Loki that reference a trace ID can link directly into Tempo to pull up the full distributed tracing waterfall for that request. This tight integration is central to Grafana Labs' philosophy of correlating metrics, logs, and traces through shared identifiers rather than building one monolithic tool. Tempo supports ingestion from multiple tracing protocols and formats, including OpenTelemetry, Jaeger, and Zipkin, making it a flexible backend for teams standardizing on open instrumentation rather than being locked into a single tracing vendor's format. It's typically deployed alongside Grafana, Loki, and a Prometheus-compatible metrics store as part of an open source observability stack.

Key Features

  • Minimal indexing (trace ID only) backed by cheap object storage
  • Support for multiple tracing protocols including OpenTelemetry, Jaeger, and Zipkin
  • Deep integration with Grafana for visualizing trace waterfalls
  • Exemplar linking from Prometheus metrics directly into specific traces
  • Log-to-trace correlation when paired with Grafana Loki
  • Horizontally scalable, designed for very high trace volume ingestion

Use Cases

Storing and querying distributed traces cost-effectively at scale
Correlating a metrics spike or log error with the exact trace that caused it
Debugging latency and failures across microservices via trace waterfalls
Standardizing tracing ingestion around OpenTelemetry across an organization
Running an open source tracing backend alongside Grafana and Loki

Frequently Asked Questions