Grafana Labs develops an open-core observability platform comprising four main components: Loki (logs), Tempo (distributed traces), Mimir (long-term metrics), and the Grafana visualization layer. All four are built on object storage backends (S3, GCS, Azure Blob) and designed around a query-time cost model rather than full ingest indexing.
Deployment options: self-host the full LGTM stack under AGPLv3, use Grafana Cloud (managed SaaS), or deploy Grafana Enterprise on-premises with commercial support. Data portability is maintained across all three paths.
Sift correlates logs, metrics, and traces during active incidents to surface probable root cause signals. The AI query assistant generates working PromQL and LogQL from natural-language descriptions. Adaptive Telemetry drops high-cardinality dimensions and low-signal metrics in the ingest pipeline before storage, reducing costs without manual cardinality management. Grafana Alerting supports multi-dimensional rules that fan out across every matching label combination.
