Grafana Loki: Like Prometheus but for Logs

Loki is a horizontally-scalable, highly-available 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 labels for each log stream.

Loki initially targets Kubernetes logging, using Prometheus service discovery to gather labels and metadata about log streams. By using the same index and labels as Prometheus, Loki enables you to easily switch between metrics and logs, enhancing observability and streamlining the incident response process – a workflow we have built into the latest version of Grafana.

In this talk we will discuss the motivation behind Loki, its design and architecture, and what the future holds. We will also discuss the inspiration from Prometheus and how a tight integration with Prometheus lets us provide a seamless debugging workflow, and how LogQL, a query language for logs inspired by PromQL, fits into the picture.

Loki is an open source project, Apache licensed with over 7K GitHub stars and an active community. We aim to cut a production ready 1.0 by the end of 2019.

Vorkenntnisse

* a basic understanding of Prometheus would help understand the design decisions behind Loki

Lernziele

* Learn about how to connect the different pillars of observability (metrics, logs and traces) to have a seamless production incident debugging workflow.
* Learn about the trend in log aggregation: Index free systems, with Loki as an implementation of the idea.
* Learn about how you can get more out of your installed Prometheus.