What Is Grafana Tempo?

Grafana Tempo is an open-source, easy-to-operate distributed tracing backend built by Grafana Labs. Unlike traditional tracing systems that index trace data for search, Tempo stores traces in object storage and retrieves them by trace ID only. This design dramatically reduces operational complexity and storage costs while integrating seamlessly with Grafana, Loki, and Prometheus for a complete observability stack.

Why Tempo Matters

Traditional tracing backends like Jaeger with Elasticsearch require significant infrastructure to index and search trace data. Tempo eliminates this complexity by not indexing traces at all. Instead, it relies on exemplars from Prometheus, log-to-trace correlation from Loki, and trace-to-log links in Grafana to navigate to the right trace, making it dramatically cheaper to operate at scale.

Teams that understand and adopt grafana tempo gain a significant operational advantage, reducing manual effort and improving the reliability and scalability of their infrastructure. As cloud-native adoption accelerates, familiarity with grafana tempo has become a core competency for DevOps engineers, platform teams, and site reliability engineers working in production Kubernetes and cloud environments.

How Tempo Works

Tempo accepts trace data from any OpenTelemetry-compatible source, including Jaeger, Zipkin, and OpenTelemetry Collector. It stores the raw trace data in object storage like S3 or GCS without indexing the content. To find a trace, you need its trace ID, obtainable through Prometheus exemplars, Loki log correlation, or TraceQL queries. Grafana provides the unified interface for navigating between metrics, logs, and traces.

Understanding how grafana tempo fits into the broader cloud-native ecosystem is important for making informed architecture decisions. It works alongside other tools and practices in the DevOps and platform engineering space, and choosing the right combination depends on your team's specific requirements, scale, and operational maturity.

Key Features

Object Storage Backend

Stores all trace data in S3 or GCS with no indexes, making it extremely cost-effective for high-volume tracing.

TraceQL

A query language designed for distributed traces that enables searching and filtering based on span attributes.

Multi-Format Ingestion

Accepts traces from Jaeger, Zipkin, OpenTelemetry, and other formats without requiring format conversion.

Grafana Integration

Seamlessly integrates with Grafana for navigating between metrics, logs, and traces in a single pane of glass.

Common Use Cases

Storing distributed traces from all microservices at a fraction of the cost of Elasticsearch-backed Jaeger.

Navigating from a Prometheus alert to relevant traces using exemplars linked to Tempo trace IDs.

Correlating Loki logs with Tempo traces to understand the full context of application errors.

Running TraceQL queries to find traces matching specific patterns like high-latency database calls.

How Obsium Helps

Obsium's managed observability team helps organizations implement and optimize grafana tempo as part of production-grade infrastructure. Whether you are adopting grafana tempo for the first time or looking to improve an existing implementation, our engineers bring hands-on experience across cloud platforms and Kubernetes environments. Learn more about our managed observability services →