Tempo
Grafana Tempo is an open-source, high-scale distributed tracing backend designed for teams that need to debug performance issues in complex, microservice-based architectures without incurring the storage costs of traditional tracing systems.
Publisher review
Grafana Tempo is an open-source, high-scale distributed tracing backend designed for teams that need to debug performance issues in complex, microservice-based architectures without incurring the storage costs of traditional tracing systems. It is particularly suited for organizations already using the Grafana observability stack, as it integrates natively with Grafana dashboards, Loki for logs, and Mimir for metrics. Tempo's primary audience includes SREs, platform engineers, and backend developers who require a cost-effective way to ingest and query large volumes of trace data while maintaining compatibility with widely adopted tracing protocols like Jaeger, Zipkin, and OpenTelemetry.
Tempo operates on a fundamentally different storage model than many competitors: it requires only object storage (such as S3, GCS, or Azure Blob Storage) to persist trace data, eliminating the need for a separate indexing database. This design reduces operational overhead and storage costs. Key capabilities include trace-by-ID lookup, search based on service name, duration, and tags, and the ability to generate metrics from spans (e.g., request rate, error rate, and duration) using its built-in metrics generation pipeline. Tempo also supports advanced features like cost attribution (introduced in version 2.9 preview), which lets teams attribute tracing costs to specific services or teams. The backend is designed to be efficient at scale, with a goal of outperforming Jaeger or Zipkin in storage and query efficiency while remaining compatible with their data formats.
In the open-source tracing landscape, Tempo directly competes with Jaeger and Zipkin. While Jaeger has historically required a dedicated storage backend like Elasticsearch or Cassandra, Tempo's reliance on object storage alone makes it significantly cheaper to operate at scale. Zipkin is simpler but less performant for high-throughput environments. Tempo's integration with the Grafana ecosystem gives it an edge for organizations already using Grafana for dashboards and alerting, but it can be used standalone. The project is actively maintained by Grafana Labs, with regular releases (e.g., version 2.9 preview in September 2024) and a growing community.
The honest trade-offs: Tempo's learning curve is steep for new users, particularly when building advanced dashboards or setting up alerting rules, as it requires familiarity with Grafana's query language and Tempo's own configuration. It does not offer built-in trace analysis or root-cause detection out of the box—users must rely on external tools like TraceTrest or manual inspection. While object storage reduces costs, it can introduce higher query latency compared to indexed backends like Elasticsearch. Finally, Tempo's search capabilities are less powerful than Jaeger's for complex, ad-hoc queries, as it prioritizes simplicity and cost over full-text indexing.
How it works
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Open-source distributed tracing
Free to use and modify under an open-source license, with no vendor lock-in for trace storage or querying.
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Object storage backend
Requires only S3, GCS, or Azure Blob Storage to operate, eliminating the need for a separate indexing database.
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Trace search and lookup
Allows searching for specific traces by ID, service name, duration, and tags for targeted debugging.
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Metrics generation from spans
Automatically generates rate, error, and duration metrics from ingested spans for real-time monitoring.
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Cost attribution
Introduced in version 2.9 preview, enables attributing tracing costs to specific services or teams.
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Multi-protocol compatibility
Accepts traces in Jaeger, Zipkin, and OpenTelemetry formats, easing migration from existing tools.
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Grafana native integration
Integrates directly with Grafana dashboards, Loki logs, and Mimir metrics for unified observability.
Strengths and trade-offs
Strengths
- Cost-effective operation: Tempo requires only object storage (e.g., S3) to run, reducing infrastructure costs compared to Jaeger's need for Elasticsearch or Cassandra.
- High scalability: Designed to handle high-scale distributed tracing workloads with efficient storage and querying, as stated in its official documentation.
- Native Grafana integration: Works seamlessly with Grafana dashboards, Loki, and Mimir, providing a unified observability experience for existing Grafana users.
- Open-source and vendor-neutral: Fully open-source with no proprietary dependencies, allowing teams to self-host or use any compatible object storage.
Trade-offs
- Steep learning curve for new users: Building advanced dashboards or setting up alerting in Grafana requires significant familiarity with the toolchain, as noted in G2 reviews.
- No built-in trace analysis: Lacks native root-cause detection or automated trace analysis, requiring external tools like TraceTrest for deep debugging.
- Higher query latency than indexed backends: Object storage can introduce slower query response times compared to Elasticsearch-based solutions like Jaeger.
- Limited ad-hoc search capabilities: Tempo prioritizes cost and simplicity over full-text indexing, making complex, ad-hoc queries less powerful than Jaeger's.
Pricing context
Free and open-source (AGPLv3). No paid tiers; users self-host or deploy on their own infrastructure. Grafana Cloud offers managed Tempo with usage-based pricing starting at free tier (500 GB traces/month) and paid plans from $49/month.
Getting started with Tempo
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Download and install Tempo
Download the latest Tempo binary from the official GitHub releases page or use a Docker image. Extract the archive and place the binary in your system PATH, or run the container with docker run grafana/tempo.
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Configure object storage backend
Edit the tempo.yaml configuration file to specify your object storage backend, such as S3, GCS, or Azure Blob Storage. Set the bucket name, region, and authentication credentials under the storage block.
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Set up trace ingestion endpoint
Define the receivers section in tempo.yaml to accept traces via Jaeger, Zipkin, or OpenTelemetry protocols. Configure the listening ports and enable the protocols your applications use to send trace data.
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Send a test trace to Tempo
Instrument a sample application with an OpenTelemetry SDK and configure the exporter to send traces to your Tempo instance's endpoint. Verify ingestion by checking the Tempo logs for successful trace receipt.
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Query traces in Grafana
Add Tempo as a data source in Grafana by providing the URL of your Tempo instance. Use the Explore view to search for traces by ID, service name, or tags, and visualize them in a trace waterfall diagram.
Frequently Asked Questions
What is Grafana Tempo and what does it do?
Grafana Tempo is an open-source distributed tracing backend that stores trace data in object storage like S3. It helps debug performance issues in microservice architectures by enabling trace-by-ID lookup, search by service name, and metrics generation from spans, all without a separate indexing database.
How does Tempo compare to Jaeger or Zipkin for tracing?
Tempo differs from Jaeger and Zipkin by requiring only object storage, reducing costs versus Jaeger's need for Elasticsearch or Cassandra. It outperforms Zipkin in high-throughput environments and integrates natively with Grafana. However, Jaeger offers more powerful ad-hoc search capabilities due to full-text indexing.
What storage does Tempo use and why is it cost-effective?
Tempo uses only object storage like S3, GCS, or Azure Blob Storage to persist trace data, eliminating the need for a separate indexing database. This design reduces operational overhead and storage costs, making it significantly cheaper to operate at scale compared to backends requiring Elasticsearch or Cassandra.
Can Tempo generate metrics from trace spans?
Yes, Tempo includes a built-in metrics generation pipeline that automatically creates rate, error, and duration metrics from ingested spans. This allows real-time monitoring of request performance without additional tools, and the metrics integrate directly with Grafana dashboards for unified observability.
What are the main limitations of Grafana Tempo?
Tempo has a steep learning curve for new users, especially for building advanced dashboards. It lacks built-in trace analysis or root-cause detection, requiring external tools. Object storage can cause higher query latency than indexed backends, and ad-hoc search is less powerful than Jaeger's due to limited indexing.
How does Tempo handle cost attribution for tracing?
Introduced in version 2.9 preview, Tempo's cost attribution feature lets teams assign tracing costs to specific services or teams. This helps organizations understand and optimize their tracing expenses, making it easier to manage budgets in large-scale deployments with multiple stakeholders.
Alternatives
How Tempo compares
Direct head-to-head against 2 competitors. Picked by 7wData.
Tempo
- Pricing
- Free and open-source (AGPLv3). No paid tiers; users self-host or deploy on their own infrastructure. Grafana Cloud offers managed Tempo with usage-based pricing starting at free tier (500 GB traces/month) and paid plans from $49/month.
- Target
- Grafana Tempo is an open-source, high-scale distributed tracing backend designed for teams that need to debug performance issues in complex, microservice-based architectures without incurring the
- Strength
- Cost-effective operation: Tempo requires only object storage (e.g., S3) to run, reducing infrastructure costs compared to Jaeger's need for Elasticsearch or Cassandra.
- Watch for
- Steep learning curve for new users: Building advanced dashboards or setting up alerting in Grafana requires significant familiarity with the toolchain, as noted in G2 reviews.
Tonal
- Pricing
- $3,495 upfront plus $59/month membership
- Target
- Strength-focused users wanting digital resistance up to 200 lbs
- Deployment
- Wall-mounted, professional install
- Strength
- Digital weight system with auto-adjust and spotter mode
- Watch for
- Requires wall mounting; no free weights or barbell exercises
Mirror
- Pricing
- $1,495 plus $39/month membership
- Target
- Cardio and bodyweight workout enthusiasts
- Deployment
- Wall-mounted or floor stand
- Strength
- Sleek, mirror design that blends into home decor
- Watch for
- No included weights; limited for strength training
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Sources
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