Lakerunner
Lakerunner transforms an S3-compatible bucket into a production-grade Observability stack in minutes.
What is Lakerunner?
Lakerunner is an open-source observability data lake that stores logs, metrics, and traces in cloud object storage (S3, GCS, Azure Blob). It provides:
- Cost-effective storage - Store petabytes of observability data at object storage prices
- Fast queries - Columnar format with intelligent indexing for sub-second queries
- Native Grafana integration - Query your data lake directly from Grafana
- Kubernetes-native - Deploy with Helm, auto-scales with demand
Architecture
Lakerunner separates ingest and query into independent, horizontally scalable paths that share only object storage and a lightweight metadata index in PostgreSQL.
For more detail, see the dedicated Ingestion and Query architecture pages.
Deployment Options
Lakerunner supports two deployment modes:
| Mode | Use Case | Infrastructure |
|---|---|---|
| Kubernetes POC | Proof of concept with real cloud resources | Any Kubernetes cluster |
| Production | Full HA deployment | Production Kubernetes with autoscaling |
Getting Started
Ready to deploy? Head to the Installation Guide to get started with our interactive setup wizard.
Prerequisites
Before installing Lakerunner, ensure you have:
- kubectl - Kubernetes CLI
- Helm 3.14+ - Package manager for Kubernetes
- Kubernetes cluster 1.28+ (local or cloud)
For POC and Production deployments, you’ll also need:
- S3-compatible object storage with notification capability (S3, GCS, or Azure Blob)
- PostgreSQL 16+ database
Reach out to support@cardinalhq.io for support or to ask questions not answered in our documentation.