production/README.md
Currently there are six ways to try out Loki, in order from easier to hardest:
For the various ways to send logs to Loki, see the Send data documentation.
Grafana is offering hosted Loki as part of our broader Grafana Cloud platform. Learn more at grafana.com/loki.
The Docker images for Loki are available on DockerHub.
To test locally, we recommend using the docker-compose.yaml file in this directory. Docker starts containers for Loki and Grafana.
Either git clone this repository locally and cd loki/production, or download a copy of the docker-compose.yaml locally.
Ensure you have the most up-to-date Docker container images:
docker-compose pull
Run the stack on your local Docker:
docker-compose up
Grafana should now be available at http://localhost:3000/.
For instructions on how to query Loki, see our usage docs.
To deploy a cluster of loki locally, please refer to this doc
There are example Nomad jobs that can be used to deploy Loki with Nomad - simple and powerful workload orchestrator from HashiCorp.
Here is the Helm chart used to deploy Loki to Kubernetes:
| Helm Chart version | Loki version | GEL version |
|---|---|---|
| 4.4.3 | 2.7.3 | 1.6.1 |
| 4.4.2 | 2.7.2 | 1.6.1 |
| 4.4.1 | 2.7.0 | 1.6.0 |
| 4.4.0 | 2.7.0 | 1.6.0 |
| 4.3.0 | 2.7.0 | 1.6.0 |
| 4.2.0 | 2.7.0 | 1.6.0 |
| 4.1.0 | 2.7.0 | 1.6.0 |
| 4.0.0 | 2.7.0 | 1.6.0 |
| 3.10.0 | 2.7.0 | 1.6.0 |
| 3.9.0 | 2.7.0 | 1.6.0 |
| 3.8.2 | 2.7.0 | 1.6.0 |
| 3.8.1 | 2.7.0 | 1.6.0 |
| 3.8.0 | 2.7.0 | 1.6.0 |
| 3.7.0 | 2.7.0 | 1.6.0 |
| 3.6.1 | 2.7.0 | 1.6.0 |
| 3.6.0 | 2.7.0 | 1.6.0 |
| 3.5.0 | 2.6.1 | 1.6.0 |
First, see the build from source section of the root readme.
Grafana is Loki's UI. To query your logs you need to start Grafana as well:
$ docker run -ti -p 3000:3000 grafana/grafana:master
Grafana should now be available at http://localhost:3000/. Follow the steps for configuring the datasource in Grafana and set the URL field to http://host.docker.internal:3100.
For instructions on how to use Loki, see our usage docs.
We run Loki on Kubernetes with the help of ksonnet. You can take a look at our production setup.
To learn more about ksonnet, check out its documentation.