Deploy your app to Edera

2 min read · Beginner

Deploying to Edera requires one change: adding a runtimeClassName to your pod spec.

Before and after

Standard Kubernetes deployment:

apiVersion: v1
kind: Pod
metadata:
  name: my-app
spec:
  containers:
    - name: my-app
      image: my-app:latest

With Edera isolation:

apiVersion: v1
kind: Pod
metadata:
  name: my-app
spec:
  runtimeClassName: edera  # This is the only change
  containers:
    - name: my-app
      image: my-app:latest

That’s it. Your container now runs in a dedicated virtual machine with hypervisor-level isolation.

What stays the same

• Your container image - No rebuilds, no modifications
• Your Dockerfile - No changes needed
• Environment variables - Work exactly as before
• Networking - Same ports, same service discovery
• Volumes - PersistentVolumes and ConfigMaps work normally
• Resource limits - CPU and memory limits are respected

Verify it’s working

Check that your pod is using the Edera runtime:

kubectl get pod my-app -o jsonpath='{.spec.runtimeClassName}'

Expected output:

edera

Deploy a Deployment or StatefulSet

The same pattern works for any workload type. Add runtimeClassName to the pod template:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      runtimeClassName: edera  # Add this line
      containers:
        - name: my-app
          image: my-app:latest

Next steps

• GPU support - Run AI/ML workloads with GPU passthrough
• Troubleshooting - Common issues and solutions
• How Edera works - Understand what happens under the hood