Kubernetes

Managing k8s is challenging, so we've decided to separate k8s deployments here - CRIB

This documentation is outdated, and we are using it only internally to run our soak tests. For v2 tests please check this example and read CRIB docs

We run our software in Kubernetes.

Local k3d setup

  1. make install
  2. (Optional) Install Lens from here or use k9s as a low resource consumption alternative from here or from source here
  3. Setup your docker resources, 6vCPU/10Gb RAM are enough for most CL related tasks
  4. make create_cluster
  5. make install_monitoring Note: this will be actively connected to the server, the final log when it is ready isForwarding from [::1]:3000 -> 3000 and you can continue with the steps below in another terminal.
  6. Check your contexts with kubectl config get-contexts
  7. Switch context kubectl config use-context k3d-local
  8. Read here and do some deployments
  9. Open Grafana on localhost:3000 with admin/sdkfh26!@bHasdZ2 login/password and check the default dashboard
  10. make stop_cluster
  11. make delete_cluster

Typical problems

  1. Not enough memory/CPU or cluster is slow Recommended settings for Docker are (Docker -> Preferences -> Resources):
    • 6 CPU
    • 10Gb MEM
    • 50-150Gb Disk
  2. NodeHasDiskPressure errors, pods get evicted Use make docker_prune to clean up all pods and volumes