LakeRunner Quick Start

Ready to see how Cardinal LakeRunner (opens in a new tab) can turn an S3 bucket into a production-grade Observability stack in minutes? 🚀
This Quick Start will walk you through the steps to get a demo LakeRunner stack installed on your local machine, with sample telemetry data being generated by the OpenTelemetry Demo apps (opens in a new tab), explorable in Grafana.
Prerequisites
- Docker Desktop (opens in a new tab), Rancher Desktop (opens in a new tab), or equivalent
- kind (opens in a new tab), minikube (opens in a new tab), or equivalent (
brew install kind
orbrew install minikube
) - kubectl (opens in a new tab) (
brew install kubectl
) - Helm (opens in a new tab) 3.14+ (
brew install helm
)
In your Docker/Rancher Desktop (or equivalent) settings, ensure that you have allocated the maximum available CPU and Memory limits, and at least 200GB of disk space.
Install LakeRunner
- Create a local cluster using
kind
orminikube
kind create cluster
- Ensure that your
kubectl
context is set to the local cluster.
kubectl config use-context kind-kind
- Download and run the LakeRunner install script.
curl -sSL -o install.sh https://raw.githubusercontent.com/cardinalhq/lakerunner-cli/main/scripts/install.sh
chmod +x install.sh
./install.sh
- Follow the on-screen prompts until the installation is complete.
(We recommend using the default values for all prompts during a local install for the fastest and most seamless experience.)
Explore Data in Grafana
The LakeRunner install script also installs a local Grafana (opens in a new tab), bundled with a preconfigured Cardinal LakeRunner Datasource plugin.
Wait for ~5 minutes for the OpenTelemetry Demo apps to generate some sample telemetry data. Then, access Grafana at http://localhost:3000
and login with the default credentials:
- Username:
admin
- Password:
admin
Navigate to the Explore
tab, select the Cardinal
datasource, and try running some queries to explore logs and metrics.