Grafana Loki, introduced five years ago, has grown into a popular open-source log aggregation tool, designed to efficiently handle the chaotic nature of logs without predefined schemas by storing everything as strings and adding structure at query time. It leverages Prometheus labels and the distributed system design of Cortex, making it highly scalable and Kubernetes-friendly. The tool's simplicity and adaptability, alongside innovations like the Promtail agent for easy log categorization, have contributed to its widespread adoption. Key features include a small index size, object storage usage, and a query engine that supports various formats through LogQL. Though initially focused on row-oriented storage, Loki is exploring columnar storage for better performance with structured data. It continues to evolve with better log ingestion, OpenTelemetry support, and enhancements in log indexing using Bloom filters. The tool’s success is attributed to its flexibility, scalability, and ability to cater to diverse logging needs, from homelabs to large multi-tenant systems.