Grafana Loki: like Prometheus, but for logs
There are many log aggregation systems which provide tons of features but lots of developers still SSH and grep/tail the logs on machines even today! The solutions they were using were either too pricey or complicated to run/maintain. In fact, people were being asked to log less which we think is an anti-pattern for logs.
In this talk I’ll introduce Grafana Loki: a new take on log aggregation. Loki is a log aggregation system inspired by Prometheus and designed specifically with Kubernetes pod logs in mind. By storing compressed, unstructured logs and only indexing metadata, Loki is simpler to operate and cheaper to run.
This talk will include discussion of the design and motivation behind Grafana Loki, an architectural overview and demos of its various functionality.
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 labels 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.
It’s early days, but so far the response to the project has been overwhelming, with nearly 7k GitHub stars and over 12hrs at the top spot on Hacker News.
The session will cover the following things:
1. Intro to Loki
2. Motivation behind Loki
7. Leveraging Loki in production
Sandeep is a Software Engineer, working at Grafana Labs on Loki & Cortex. After trying his hands at different areas including Data Security, Blockchain and HRM, he is living his dream working with one of the pioneers in Observability and Monitoring space, Grafana Labs. In his free time, Sandeep likes to read books, play tennis and watch movies/web series.