This is documentation for the next version of Tempo. For the latest stable release, go to the latest version.
Quick start for Tempo
The Tempo repository provides multiple examples to help you quickly get started using Tempo and distributed tracing data.
Every example has a docker-compose.yaml
manifest that includes all of the options needed to explore trace data in Grafana, including resource configuration and trace data generation.
The Tempo examples running with Docker using docker-compose include a version of Tempo and a storage configuration suitable for testing or development.
Before you begin
To follow this guide, you need:
- Git
- Docker
- The Docker Compose plugin (included with Docker Desktop)
Tip
Alternatively, you can try out this example in our interactive learning environment: Quick start for Tempo.
It’s a fully configured environment with all the dependencies installed.
Provide feedback, report bugs, and raise issues in the Grafana Killercoda repository.
Clone the Tempo repository and start Docker
This quick start guide uses the local
example running Tempo as a single binary (monolithic). Any data is stored locally in the tempo-data
folder.
To learn more, read the local storage example README.
Clone the Tempo repository:
git clone https://github.com/grafana/tempo.git
Go into the examples directory:
cd tempo/example/docker-compose/local
Start the services defined in the docker-compose file:
docker compose up -d
Verify that the services are running:
docker compose ps
You should see something like:
docker compose ps NAME COMMAND SERVICE STATUS PORTS local-grafana-1 "/run.sh" grafana running 0.0.0.0:3000->3000/tcp local-k6-tracing-1 "/k6-tracing run /ex…" k6-tracing running local-prometheus-1 "/bin/prometheus --c…" prometheus running 0.0.0.0:9090->9090/tcp local-tempo-1 "/tempo -config.file…" tempo running 0.0.0.0:3200->3200/tcp, 0.0.0.0:4317-4318->4317-4318/tcp, 0.0.0.0:9411->9411/tcp, 0.0.0.0:14268->14268/tcp
Explore the traces in Grafana
As part of the Docker Compose manifest, Grafana is now accessible on port 3000. You can use Grafana to explore the traces generated by the k6-tracing service.
Open a browser and navigate to http://localhost:3000.
Once logged in, navigate to the Explore page, select the Tempo data source and select the Search tab. Select Run query to list the recent traces stored in Tempo. Select one to view the trace diagram:
A couple of minutes after Tempo starts, select the Service graph tab for the Tempo data source in the Explore page. Select Run query to view a service graph, generated by Tempo’s metrics-generator.
To stop the services:
docker compose down -v
Next steps
You have successfully set up Tempo and Grafana to explore traces generated by the k6-tracing service.
Alternative: Complete MLTP example
If you would like to use a demo with multiple telemetry signals, then try the Introduction to Metrics, Logs, Traces, and Profiling in Grafana.
Intro-to-mltp
provides a self-contained environment for learning about Mimir, Loki, Tempo, Pyroscope, and Grafana.
The project includes detailed explanations of each component and annotated configurations for a single-instance deployment.
Data from intro-to-mltp
can also be pushed to Grafana Cloud.
Further reading
Here are some resources to help you learn more about Tempo: