Deploy team AI coding workspaces on Kubernetes
kube-coder can run on a shared Kubernetes cluster so each developer gets a separate workspace. Each workspace has its own pod, PVC, ingress route, and settings. Users connect through an address like `https://user.dev.yourdomain.com/`, sign in with GitHub OAuth, and get automatic HTTPS s through cert-manager and .
The request path runs from the browser through oauth2-proxy and nginx-ingress, then into the user’s workspace service and pod. The pod includes server.py, , ttyd, noVNC, tmux, and AI features. The cluster needs one-time setup for an ingress controller, cert-manager, an image registry pull secret, and the base kube-coder Helm release.
After that, each user is deployed by creating values, adding DNS and GitHub OAuth details, validating them, and running `make deploy`. `make USER=` lets the deploy command find the right settings for a specific user.
Key points
- kube-coder creates separate browser workspaces for developers on Kubernetes.
- Each user gets a pod, PVC, ingress route, and .
- GitHub OAuth handles login, and HTTPS s are created automatically.
- The shared-cluster setup is for teams; minikube is the simpler local trial path.
- Per-user deployment uses values files plus `make USER=` and `make deploy`.