Loki’s Path to GA: Adding Structure to Unstructured Logs

Loki, launched at KubeCon North America in December and inspired by Prometheus, is a service designed for efficient storage, search, and aggregation of logs, with seamless integration into Grafana. It is adaptable to both microservices and monolithic architectures, correlating logs and metrics to help users save costs. One of its most requested features involves the manipulation of log lines, allowing for operations such as extracting labels and metrics, setting timestamps, and modifying log entries before they are sent to Loki. This functionality is facilitated by a log processing pipeline that utilizes stages such as JSON and regex to extract and manipulate log data, improving query performance through the use of labels. The pipeline is designed to be flexible, allowing for the addition of new stages to accommodate diverse use cases. Future developments may include capabilities for splitting log lines and sharing pipeline configurations to enhance usability and collaboration.

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