LakeRunner
Quick Start

LakeRunner Quick Start

LakeRunner

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

  1. Docker Desktop (opens in a new tab), Rancher Desktop (opens in a new tab), or equivalent
  2. kind (opens in a new tab), minikube (opens in a new tab), or equivalent (brew install kind or brew install minikube)
  3. kubectl (opens in a new tab) (brew install kubectl)
  4. 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

  1. Create a local cluster using kind or minikube
kind create cluster
  1. Ensure that your kubectl context is set to the local cluster.
kubectl config use-context kind-kind
  1. Download and run the LakeRunner install script.
curl -sSL -o lakerunner-standalone-poc.sh https://raw.githubusercontent.com/cardinalhq/charts/refs/heads/main/install-scripts/lakerunner-standalone-poc.sh
chmod +x lakerunner-standalone-poc.sh
./lakerunner-standalone-poc.sh --standalone

By default, this will install support for metrics and logs. You can specify which signal types: --signals logs,metrics,traces.

  1. 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.

WelcomeQuick Start