This is documentation for the next version of Loki. For the latest stable release, go to the latest version.
Grafana Loki is a log aggregation tool, and it is the core of a fully-featured logging stack.
Loki is a datastore optimized for efficiently holding log data. The efficient indexing of log data distinguishes Loki from other logging systems. Unlike other logging systems, a Loki index is built from labels, leaving the original log message unindexed.
An agent (also called a client) acquires logs, turns the logs into streams, and pushes the streams to Loki through an HTTP API. The Promtail agent is designed for Loki installations, but many other Agents seamlessly integrate with Loki.
Loki indexes streams. Each stream identifies a set of logs associated with a unique set of labels. A quality set of labels is key to the creation of an index that is both compact and allows for efficient query execution.
LogQL is the query language for Loki.
Efficient memory usage for indexing the logs
By indexing on a set of labels, the index can be significantly smaller than other log aggregation products. Less memory makes it less expensive to operate.
Loki allows multiple tenants to utilize a single Loki instance. The data of distinct tenants is completely isolated from other tenants. Multi-tenancy is configured by assigning a tenant ID in the agent.
LogQL, Loki’s query language
Users of the Prometheus query language, PromQL, will find LogQL familiar and flexible for generating queries against the logs. The language also facilitates the generation of metrics from log data, a powerful feature that goes well beyond log aggregation.
Loki can be run as a single binary; all the components run in one process.
Loki is designed for scalability, as each of Loki’s components can be run as microservices. Configuration permits scaling the microservices individually, permitting flexible large-scale installations.
Many agents (clients) have plugin support. This allows a current observability structure to add Loki as their log aggregation tool without needing to switch existing portions of the observability stack.
Loki seamlessly integrates with Grafana, providing a complete observability stack.
Related Loki resources
Getting started with logging and Grafana Loki (APAC timezone)
Join this webinar to learn why correlating metrics and logs is critical across the development lifecycle, and how Loki helps reduce logging costs and operations overhead.
Logging with Loki: Essential configuration settings
This webinar focuses on Grafana Loki configuration including agents Promtail and Docker; the Loki server; and Loki storage for popular backends.