setup-local-kubernetes
Set up a local Kubernetes development environment using kind, k3d, or minikube for fast inner-loop development. Covers cluster creation, ingress configuration, local registry setup, and integration with development tools like Skaffold and Tilt for automatic rebuild and redeploy workflows. Use when needing a local Kubernetes environment for development, testing manifests or Helm charts before production deployment, wanting fast automatic rebuild-and-redeploy cycles, or learning Kubernetes without cloud costs.
Best use case
setup-local-kubernetes is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Set up a local Kubernetes development environment using kind, k3d, or minikube for fast inner-loop development. Covers cluster creation, ingress configuration, local registry setup, and integration with development tools like Skaffold and Tilt for automatic rebuild and redeploy workflows. Use when needing a local Kubernetes environment for development, testing manifests or Helm charts before production deployment, wanting fast automatic rebuild-and-redeploy cycles, or learning Kubernetes without cloud costs.
Teams using setup-local-kubernetes should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/setup-local-kubernetes/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How setup-local-kubernetes Compares
| Feature / Agent | setup-local-kubernetes | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Set up a local Kubernetes development environment using kind, k3d, or minikube for fast inner-loop development. Covers cluster creation, ingress configuration, local registry setup, and integration with development tools like Skaffold and Tilt for automatic rebuild and redeploy workflows. Use when needing a local Kubernetes environment for development, testing manifests or Helm charts before production deployment, wanting fast automatic rebuild-and-redeploy cycles, or learning Kubernetes without cloud costs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Setup Local Kubernetes
Create a local Kubernetes development environment for fast iteration and testing.
## When to Use
- Need local Kubernetes environment for application development
- Want to test Kubernetes manifests and Helm charts before deploying to production
- Require fast inner-loop development with automatic rebuild and redeploy
- Testing multi-service applications with service dependencies
- Learning Kubernetes without cloud costs
- CI/CD pipeline testing locally before pushing changes
- Need isolated environment for experimentation and debugging
## Inputs
- **Required**: Docker Desktop or Docker Engine installed
- **Required**: At least 4GB RAM available for cluster
- **Required**: Choice of local cluster tool (kind, k3d, or minikube)
- **Optional**: Application source code to deploy
- **Optional**: Kubernetes version preference
- **Optional**: Development tool preference (Skaffold, Tilt, or manual)
- **Optional**: Number of worker nodes needed
## Procedure
> See [Extended Examples](references/EXAMPLES.md) for complete configuration files and templates.
### Step 1: Install Local Kubernetes Cluster Tool
Choose and install kind, k3d, or minikube based on your requirements.
**Install kind (Kubernetes in Docker):**
```bash
# Linux example
curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.20.0/kind-linux-amd64
chmod +x ./kind
sudo mv ./kind /usr/local/bin/kind
# Verify installation
kind version
```
**Install k3d (k3s in Docker):**
```bash
# Linux/macOS
curl -s https://raw.githubusercontent.com/k3d-io/k3d/main/install.sh | bash
# Verify installation
k3d version
```
**Install minikube:**
```bash
# Linux example
curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64
sudo install minikube-linux-amd64 /usr/local/bin/minikube
# Verify installation
minikube version
```
Install kubectl if not already present:
```bash
# Linux example
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
chmod +x kubectl
sudo mv kubectl /usr/local/bin/
kubectl version --client
```
> See references/EXAMPLES.md for macOS and Windows installation commands.
**Expected:** Tool binary installed and in PATH. Version command returns expected version. kubectl available for cluster interaction.
**On failure:**
- Ensure Docker is running: `docker ps`
- Check system PATH includes installation directory
- For permission issues, verify sudo/admin rights
- On macOS, may need to allow binary in Security & Privacy settings
- Windows users: ensure running terminal as Administrator
### Step 2: Create Local Cluster with Configuration
Create a multi-node cluster with ingress and local registry support.
**Create kind cluster:**
```yaml
# kind-config.yaml (abbreviated)
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
name: dev-cluster
locale: caveman-lite
source_locale: en
source_commit: 82c77053
translator: "Julius Brussee homage — caveman"
translation_date: "2026-04-19"
nodes:
- role: control-plane
extraPortMappings:
- containerPort: 80
hostPort: 80
- containerPort: 443
hostPort: 443
- role: worker
- role: worker
```
```bash
# Create cluster
kind create cluster --config kind-config.yaml
# Install ingress-nginx
kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/static/provider/kind/deploy.yaml
# Create local registry
docker run -d --restart=always -p 5000:5000 --name kind-registry registry:2
docker network connect kind kind-registry
```
> See references/EXAMPLES.md for complete kind-config.yaml with registry mirrors and ingress configuration.
**Create k3d cluster:**
```bash
# Create cluster with ingress and registry
k3d cluster create dev-cluster \
--port "80:80@loadbalancer" \
--port "443:443@loadbalancer" \
--agents 2 \
--registry-create k3d-registry:5000
```
**Create minikube cluster:**
```bash
# Create cluster with multiple nodes
minikube start \
--nodes=3 \
--cpus=2 \
--memory=4096 \
--driver=docker \
--addons=ingress,registry,metrics-server
```
Test cluster:
```bash
# Deploy test application
kubectl create deployment hello --image=k8s.gcr.io/echoserver:1.4
kubectl expose deployment hello --type=NodePort --port=8080
kubectl port-forward service/hello 8080:8080
# Clean up test
kubectl delete deployment,service hello
```
**Expected:** Multi-node cluster running with control plane and worker nodes. Ingress controller installed and ready. Local registry accessible at localhost:5000. kubectl context set to new cluster. Test deployment successful.
**On failure:**
- Check Docker has sufficient resources (4GB+ memory recommended)
- Verify no port conflicts: `lsof -i :80,443,5000,6550`
- For kind: ensure Docker desktop Kubernetes is disabled (conflicts)
- For k3d: check Docker network connectivity
- For minikube: try different driver (virtualbox, hyperv, kvm2)
- Review cluster creation logs: `kind get clusters`, `k3d cluster list`, `minikube logs`
### Step 3: Configure Development Workflow Tools
Set up Skaffold or Tilt for automated rebuild and redeploy.
**Install Skaffold:**
```bash
# Linux example
curl -Lo skaffold https://storage.googleapis.com/skaffold/releases/latest/skaffold-linux-amd64
chmod +x skaffold
sudo mv skaffold /usr/local/bin
skaffold version
```
**Create Skaffold configuration:**
```yaml
# skaffold.yaml (abbreviated)
apiVersion: skaffold/v4beta7
kind: Config
metadata:
name: my-app
build:
# ... (see EXAMPLES.md for complete configuration)
```
> See references/EXAMPLES.md for complete skaffold.yaml with profiles, file sync, and port forwarding.
**Install Tilt:**
```bash
# Linux/macOS
curl -fsSL https://raw.githubusercontent.com/tilt-dev/tilt/master/scripts/install.sh | bash
tilt version
```
**Create Tiltfile:**
```python
# Tiltfile (abbreviated)
allow_k8s_contexts('kind-dev-cluster')
docker_build(
'localhost:5000/my-app',
'.',
live_update=[
sync('./src', '/app/src'),
]
)
k8s_yaml(['k8s/deployment.yaml', 'k8s/service.yaml'])
k8s_resource('my-app', port_forwards='8080:8080')
```
> See references/EXAMPLES.md for complete Tiltfile with live updates, Helm charts, and custom buttons.
Create sample Kubernetes manifests:
```yaml
# k8s/deployment.yaml (abbreviated)
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
spec:
replicas: 1
template:
spec:
containers:
- name: app
image: localhost:5000/my-app
ports:
- containerPort: 8080
```
> See references/EXAMPLES.md for complete manifests with service, ingress, and resource limits.
Test development workflow:
```bash
# Using Skaffold
skaffold dev --port-forward
# Using Tilt
tilt up
# Add entry to /etc/hosts for ingress
echo "127.0.0.1 my-app.local" | sudo tee -a /etc/hosts
curl http://my-app.local
```
**Expected:** Skaffold or Tilt watching for file changes. Code changes trigger automatic rebuild and redeploy. Hot reload working for supported languages. Port forwarding allows local access. Logs streaming in terminal/UI. Build caching makes rebuilds fast.
**On failure:**
- Verify Docker daemon accessible: `docker ps`
- Check if local registry reachable: `curl http://localhost:5000/v2/_catalog`
- For file sync issues, ensure paths in config match actual structure
- Review Skaffold/Tilt logs for build errors
- Ensure Dockerfile has proper base image and builds successfully: `docker build .`
- Check resource limits not causing OOMKills: `kubectl describe pod -l app=my-app`
### Step 4: Set Up Local Storage and Databases
Configure persistent storage and deploy database services for testing.
**Create local storage class:**
```yaml
# local-storage.yaml (abbreviated)
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: local-path
provisioner: rancher.io/local-path
# ... (see EXAMPLES.md for complete configuration)
```
> See references/EXAMPLES.md for complete storage configuration with PVC templates.
**Deploy PostgreSQL for development:**
```yaml
# postgres-dev.yaml (abbreviated)
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: postgres
spec:
serviceName: postgres
template:
spec:
containers:
- name: postgres
image: postgres:15-alpine
envFrom:
- secretRef:
name: postgres-secret
```
> See references/EXAMPLES.md for complete PostgreSQL StatefulSet with secrets and volume templates.
**Deploy Redis for caching:**
```bash
# Using Helm
helm install redis bitnami/redis \
--set auth.enabled=false \
--set replica.replicaCount=0
```
> See references/EXAMPLES.md for kubectl-based Redis deployment.
Test database connectivity:
```bash
# Apply manifests
kubectl apply -f local-storage.yaml
kubectl apply -f postgres-dev.yaml
# Wait for PostgreSQL
kubectl wait --for=condition=ready pod -l app=postgres --timeout=60s
# Test connection
kubectl exec -it postgres-0 -- psql -U devuser -d devdb -c "SELECT version();"
```
**Expected:** Storage class configured for dynamic provisioning. Database pods running and ready. Services accessible via port-forward or from other pods. Data persists across pod restarts. Resource usage appropriate for development (small limits).
**On failure:**
- Check if storage provisioner installed: `kubectl get storageclass`
- Verify PVC bound to PV: `kubectl get pvc,pv`
- Review pod events for mounting errors: `kubectl describe pod postgres-0`
- For permission issues, check if hostPath directory exists and is writable
- Test database startup: `kubectl logs postgres-0` for PostgreSQL errors
- Ensure no port conflicts for port-forwarding
### Step 5: Configure Observability for Local Development
Add minimal monitoring and logging for debugging.
**Deploy lightweight monitoring stack:**
```bash
# Install metrics-server
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
# For local clusters, disable TLS verification
kubectl patch deployment metrics-server -n kube-system --type='json' -p='[
{"op": "add", "path": "/spec/template/spec/containers/0/args/-", "value": "--kubelet-insecure-tls"}
]'
# Verify metrics
kubectl top nodes
kubectl top pods -A
```
**Set up local logging:**
```bash
# Install stern (multi-pod log tailing)
curl -Lo stern https://github.com/stern/stern/releases/download/v1.26.0/stern_1.26.0_linux_amd64.tar.gz
tar -xzf stern_1.26.0_linux_amd64.tar.gz
sudo mv stern /usr/local/bin/
# Usage
stern my-app --since 1m
```
> See references/EXAMPLES.md for development dashboard ConfigMaps and useful aliases.
**Expected:** Metrics-server providing resource usage data. kubectl top commands working. k9s or dashboard showing cluster status. Logs accessible via stern or kubectl logs. Low overhead monitoring suitable for development.
**On failure:**
- For metrics-server TLS errors, apply insecure TLS flag patch
- Check if metrics-server pod running: `kubectl get pods -n kube-system -l k8s-app=metrics-server`
- Verify heapster API available: `kubectl get apiservices | grep metrics`
- For stern, ensure kubectl context is set correctly
- Test basic kubectl access before debugging observability tools
### Step 6: Document Workflow and Create Helpers
Create scripts and documentation for team onboarding.
**Create setup script:**
```bash
#!/bin/bash
# setup-local-cluster.sh (abbreviated)
set -e
echo "=== Local Kubernetes Cluster Setup ==="
# ... (see EXAMPLES.md for complete configuration)
```
> See references/EXAMPLES.md for complete setup script with service deployment and verification.
**Create teardown script:**
```bash
#!/bin/bash
# teardown-local-cluster.sh (abbreviated)
echo "=== Tearing Down Local Cluster ==="
if kind get clusters 2>/dev/null | grep -q dev-cluster; then
kind delete cluster --name dev-cluster
docker stop kind-registry && docker rm kind-registry
fi
docker system prune -f
```
> See references/EXAMPLES.md for complete teardown script and README template.
**Expected:** Setup script creates cluster in one command. Teardown script cleans everything up. README provides clear instructions for common tasks. Team members can get productive quickly.
**On failure:**
- Test scripts manually before distributing
- Add error handling for each step
- Provide troubleshooting section in README
- Create video walkthrough for complex setups
- Maintain scripts as cluster tool versions update
## Validation
- [ ] Local cluster created with multiple nodes
- [ ] Ingress controller installed and responding
- [ ] Local registry accessible and accepting pushes
- [ ] Sample application deploys successfully
- [ ] File sync working (changes reflected without full rebuild)
- [ ] Port forwarding allows local access to services
- [ ] Database services running and accessible
- [ ] Metrics server providing resource usage
- [ ] Logs accessible via kubectl/stern/Tilt
- [ ] Setup/teardown scripts work reliably
- [ ] Documentation clear and up-to-date
- [ ] Team members can onboard in <30 minutes
## Common Pitfalls
- **Insufficient Resources**: Local clusters need 4GB+ RAM, 2+ CPU cores. Check Docker Desktop settings. Reduce replicas and resource requests for development.
- **Port Conflicts**: Ports 80, 443, 5000 commonly used. Check with `lsof -i :<port>` before cluster creation. Adjust port mappings if needed.
- **Slow Rebuilds**: Without proper caching, Docker rebuilds are slow. Use multi-stage builds, .dockerignore, and BuildKit. Enable Skaffold/Tilt caching.
- **Context Confusion**: Multiple kubectl contexts cause confusion. Use `kubectl config current-context` and `kubectx` tool to switch clearly.
- **File Sync Not Working**: Path mismatches between host and container break sync. Verify paths in skaffold.yaml/Tiltfile match Dockerfile WORKDIR.
- **Ingress Not Resolving**: Forgot to add entry to /etc/hosts. Or ingress controller not ready. Wait for controller pods before testing.
- **Database Data Loss**: Default storage ephemeral. Use PersistentVolumes for data that should survive restarts. Be explicit about storage class.
- **Resource Limits Too High**: Don't copy production resource specs to local. Reduce limits significantly for local development to fit in Docker Desktop.
- **Network Isolation**: Local cluster can't always reach host services. Use `host.docker.internal` (Docker Desktop) or ngrok for reverse proxying.
- **Version Skew**: Local cluster version differs from production. Explicitly set Kubernetes version during creation to match production.
## Related Skills
- `deploy-to-kubernetes` - Application deployment patterns tested locally first
- `write-helm-chart` - Helm charts tested in local cluster
- `setup-prometheus-monitoring` - Monitoring setup tested locally
- `configure-ingress-networking` - Ingress configuration validated locally
- `implement-gitops-workflow` - GitOps tested with local cluster
- `optimize-cloud-costs` - Cost optimization strategies developed locallyRelated Skills
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