Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate, as it does not index the contents of the logs, but rather a set of labels for each log stream.
Promtail is an agent which ships the contents of local logs to a private Grafana Loki instance or Grafana Cloud. It is usually deployed to every machine that has applications needed to be monitored.
Tempo is an open source, easy-to-use, and high-scale distributed tracing backend. Tempo is cost-efficient, requiring only object storage to operate, and is deeply integrated with Grafana, Prometheus, and Loki. Tempo can ingest common open source tracing protocols, including Jaeger, Zipkin, and OpenTelemetry.
Mimir lets you scale metrics to 1 billion active series and beyond, with high availability, multi-tenancy, durable storage, and blazing fast query performance over long periods of time.
I am assuming you are already familiar with Grafana and Prometheus
- Kubernetes Cluster >= v1.26
- Familiarity with Grafana, Prometheus, Loki, Promtail, Tempo and Mimir
- ...
- Profit?
kubectl apply -k ./deploymentThis will deploy the following services in monitoring namespace:
- Grafana - preconfigured with Prometheus, Loki and Tempo as data sources
- Prometheus
- Loki
- Promtail - preconfigured to push data to Loki
- Tempo
Once deployed, access Grafana UI via:
kubectl port-forward -n monitoring svc/grafana 3000:3000Here is how to guide from Grafana / Loki
This is an attempt to demystify the different components of LGTM Stack, deploying the full stack can seem overwhelming, breaking it down to smaller composable pieces will hopefully help you better understand each service and its configuration.
Our latest and greatest source of grafana-loki-on-k8s can be found on [GitHub]. Fork us!
We would ❤️ you to contribute by making a pull request.
Please read the official Contribution Guide for more information on how you can contribute.