Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.
Get started with Grafana Phlare
In March 2023, Grafana Labs acquired Pyroscope, the company behind the eponymous open source continuous profiling project. As a result, the Pyroscope and Grafana Phlare projects will be merged under the new name Grafana Pyroscope. To learn more, read our recent blog post about the news.
Choose one of the following options to get started with Grafana Phlare:
The written tutorial below provides a series of imperative commands to start a single Phlare process, or monolith, which is designed for users getting started with the project.
The following video tutorial uses
docker-composeto declaratively deploy Phlare and Grafana.
There’s supposed to be a video here, but for some reason there isn’t. Either we entered the id wrong (oops!), or Vimeo is down. If it’s the latter, we’d expect they’ll be back up and running soon. In the meantime, check out our blog!
For more information on the different ways to deploy Phlare, see Grafana Phlare deployment modes.
Before you begin
Verify that you have installed Docker.
Download and configure Phlare
Download Grafana Phlare.
You can use Docker or download a binary to install Phlare.
To install with Docker, run the following command:
docker pull grafana/phlare:latest
To use a local binary:
Download the appropriate release asset for your operating system and architecture and make it executable.
For example, for Linux with the AMD64 architecture:
# Download Grafana Phlare v0.1.1 and unpack it to the current folder curl -fL https://github.com/grafana/phlare/releases/download/v0.1.1/phlare_0.1.1_linux_amd64.tar.gz | tar xvz
To run Grafana Phlare as a monolith and with local filesystem storage, you can create your own file, or use a demo configuration file.
To create your own file, write the following YAML configuration to a file called
# Do not use this configuration in production. # It is for demonstration purposes only. scrape_configs: - job_name: "default" scrape_interval: "15s" static_configs: - targets: ["127.0.0.1:4100"]
To use a demo file, download our demo configuration:
curl -fLo demo.yaml https://raw.githubusercontent.com/grafana/phlare/main/cmd/phlare/phlare.yaml
In a terminal, run one of the following commands:
docker network create phlare-demo docker run --rm --name phlare --network=phlare-demo -p 4100:4100 --volume "$(pwd)"/demo.yaml:/etc/phlare/demo.yaml grafana/phlare:latest --config.file=/etc/phlare/demo.yaml
Using a local binary:
Verify that Phlare is ready. Grafana Phlare listens on port
Configure Phlare to scrape profiles.
By default, Grafana Phlare is configured to scrape itself. To scrape more profiles, you must configure the
scrape_configssection of the configuration file.
To learn more about language integrations and the Phlare agent, refer to Grafana Phlare Agent.
Add a Phlare data source and query data
In a new terminal, run a local Grafana server using Docker:
docker run --rm --name=grafana -p 3000:3000 -e "GF_FEATURE_TOGGLES_ENABLE=flameGraph" --network=phlare-demo grafana/grafana:main
In a browser, go to the Grafana server at http://localhost:3000/datasources.
Sign in using the default username
Use the following settings to configure a Phlare data source to query the local Grafana Phlare server:
Field Value Name Phlare URL http://phlare:4100/
To learn more about adding data sources, see Add a data source.
When you have completed the tasks in this getting started guide, you can query profiles in Grafana Explore and create dashboard panels using the newly configured Grafana Phlare data source. For more information on working with dashboards with Grafana, see Panels and visualizations in the Grafana documentation.