Grafana Loki

Loki is a log aggregation system designed to store and query logs from all your applications and infrastructure.

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Quick links

Loki on GitHub

Docs

Demo: Getting started with logging and Loki

Demo: Scalable logging with Grafana Loki

Grafana Loki

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. It does not index the contents of the logs, but rather a set of labels for each log stream.

The Loki project was started at Grafana Labs in 2018, and announced at KubeCon Seattle. Loki is released under the AGPLv3 license.

Grafana Labs is proud to lead the development of the Loki project, building first-class support for Loki into Grafana, and ensuring Grafana Labs customers receive Loki support and features they need.

Why use Grafana Loki?

It’s really easy to get started because you can send logs in any format, from any source, using a wide array of clients

100% persistence to object storage means you get petabyte scale, high throughput and cost-effective & durable storage

Build metrics and generate alerts from your log lines

No ingestion log formatting requirements gives you more flexibility and the option to format at query time

Tail your logs in realtime to see the logs as they come into the system, update the logs after every certain time, view logs for a particular date, etc.

Natively integrates with Prometheus, Grafana and K8s so you can seamlessly move between metrics, logs and traces within a single UI

Loki takes a unique approach by only indexing the metadata rather than the full text of the log lines:

Loki’s minimal indexing approach means that storing the same set of logs in Loki requires far less storage than with other solutions

Log any and all formats
Fast writes
Tiny indexes

Cheaper to run
Simpler to operate
Fast queries

Cut and slice your logs in dynamic ways (Flexible)

How does Grafana Loki work?

Pull in any logs with Promtail

Promtail is a logs collector built specifically for Loki. It uses the same service discovery as Prometheus and includes analogous features for labeling, transforming, and filtering logs before ingestion into Loki.

Store the logs in Loki

Loki does not index the text of logs. Instead, entries are grouped into streams and indexed with labels.Not only does this reduce costs, it also means log lines are available to query within milliseconds of being received by Loki.

Use LogQL to explore

Use Loki’s powerful query language, LogQL, to explore your logs. Run LogQL queries directly within Grafana to visualize your logs alongside other data sources, or with LogCLI, for those who prefer a command line experience.

Alert on your logs

Set up alerting rules for Loki to evaluate on your incoming log data. Configure Loki to send the resulting alerts to a Prometheus Alertmanager so they can then get routed to the right team.