Deploy nginx on Arm

Add the Arm deployment and service

In this section, you’ll add nginx on Arm to your existing cluster, completing your multi-architecture Intel/Arm environment for comprehensive performance comparison.

When you apply the arm_nginx.yaml file, it creates two Kubernetes objects:

• A deployment named nginx-arm-deployment that pulls the multi-architecture nginx image from DockerHub, launches a pod on the Arm node, and mounts the shared ConfigMap as /etc/nginx/nginx.conf
• A service called nginx-arm-svc that acts as a load balancer, targeting pods with both app: nginx-multiarch and arch: arm labels

Copy and paste the following commands into a terminal to download and apply the Arm deployment and service:

    

        
        
curl -o arm_nginx.yaml https://raw.githubusercontent.com/geremyCohen/nginxOnAKS/refs/heads/main/arm_nginx.yaml
kubectl apply -f arm_nginx.yaml

    

You will see output similar to:

    

        
        deployment.apps/nginx-arm-deployment created
service/nginx-arm-svc created

        
    

Examining the deployment configuration

Take a closer look at the arm_nginx.yaml deployment file and you’ll see settings optimized for the Arm architecture:

The nodeSelector value of kubernetes.io/arch: arm64 ensures that the deployment only runs on Arm nodes, utilizing the arm64 version of the nginx container image.

    

        
        
    spec:
      nodeSelector:
        kubernetes.io/arch: arm64

    

The service selector uses both app: nginx-multiarch and arch: arm labels to target only Arm pods. This dual-label approach allows for both architecture-specific and multi-architecture service routing.

    

        
        
  selector:
    app: nginx-multiarch
    arch: arm

    

Verify the deployment

Get the status of nodes, pods, and services by running:

    

        
        
kubectl get nodes,pods,svc -nnginx 

    

Your output should be similar to the following, showing two nodes, two pods, and two services:

    

        
        NAME                                 STATUS   ROLES    AGE   VERSION
node/aks-arm-56500727-vmss000000     Ready    <none>   59m   v1.32.7
node/aks-intel-31372303-vmss000000   Ready    <none>   63m   v1.32.7

NAME                                          READY   STATUS    RESTARTS   AGE
pod/nginx-arm-deployment-5bf8df95db-wznff     1/1     Running   0          36s
pod/nginx-intel-deployment-78bb8885fd-mw24f   1/1     Running   0          9m21s

NAME                      TYPE           CLUSTER-IP     EXTERNAL-IP     PORT(S)        AGE
service/nginx-arm-svc     LoadBalancer   10.0.241.154   48.192.64.197   80:30082/TCP   36s
service/nginx-intel-svc   LoadBalancer   10.0.226.250   20.80.128.191   80:30080/TCP   9m22s

        
    

You can also verify the shared ConfigMap is available:

    

        
        
kubectl get configmap -nnginx

    

The output is similar to:

    

        
        NAME               DATA   AGE
nginx-config       1      10m

        
    

When the pods show Running and the service shows a valid External IP, you’re ready to test the nginx Arm service.

Test the nginx web service on Arm

Run the following command to make an HTTP request to the Arm nginx service using the script you created earlier:

    

        
        
./nginx_util.sh curl arm

    

The response includes both the HTTP data and details about which pod handled the request:

    

        
        Using service endpoint 48.192.64.197 for curl on arm service
Response:
{
  "message": "nginx response",
  "timestamp": "2025-10-24T22:04:59+00:00",
  "server": "nginx-arm-deployment-5bf8df95db-wznff",
  "request_uri": "/"
}
Served by: nginx-arm-deployment-5bf8df95db-wznff

        
    

If you see similar output, you have successfully added Arm nodes to your cluster running nginx.

Compare both architectures

Now you can test both architectures and compare their responses:

    

        
        
./nginx_util.sh curl intel
./nginx_util.sh curl arm

    

Each command routes to its respective architecture-specific service, allowing you to compare performance and verify that your multi-architecture cluster is working correctly.