Google Kubernetes Engine (GKE) supports hybrid clusters with x86 and Arm based nodes. The Arm-based nodes can be deployed on the C4A family of virtual machines. The C4A VMs are based on
Google Axion
, Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU.
On your local machine, install the following tools.
You will need a Google Cloud account . Create an account if needed.
Three tools are required on your local machine. Follow the links to install the required tools.
This section assumes that you have a GKE cluster with 3 x86-based nodes running in your environment. If you do not have the cluster then follow the official google docs to create one.
Setup the following environment variables:
export PROJECT_ID=<your-project-id>
export ZONE=<zone id - us-central1-c>
export CLUSTER_NAME=<your-cluster-name>
The github project repository listed below contains all the required files to follow this learning path. Clone it to your local machine:
git clone https://github.com/pbk8s/gke-arm
Create a docker repository in the Google Artifact Registry with the following command:
gcloud artifacts repositories create docker-repo \
--repository-format=docker \
--location=<your-region> \
--description="Docker repository for multi-arch images"
Replace <your-region> in the command above with the location where you want the create the repository storage.
Configure the cli to authenticate the docker repository in the Artifact Registry:
gcloud auth configure-docker us-central1-docker.pkg.dev
Build the docker image for the existing x86-based version of application:
docker build -t us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/x86-hello:v0.0.1 .
Push the docker image you created to the docker repository:
docker push us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/x86-hello:v0.0.1
Retrieve the GKE cluster credentials:
gcloud container clusters get-credentials $CLUSTER_NAME --zone $ZONE --project $PROJECT_ID
Update the docker image with a tool called Kustomize. This tool allows you to customize kubernetes objects.
$(cd k8s/overlays/x86 && kustomize edit set image hello=us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/x86-hello:v0.0.1)
kubectl apply -k k8s/overlays/x86
To access the application from outside your cluster, deploy the following kubernetes service:
kubectl apply -f k8s/hello-service.yaml
After an external IP is assigned to this service, open a browser and access the webpage as shown:
http://$external_ip
Alternatively, you can also use the curl command to access the webpage:
curl -w '\n' http://$external_ip
You should see output similar to what is shown below:
Hello from NODE:gke-multi-arch-cluster-default-pool-45537239-q83v, POD:x86-hello-deployment-9e7b823ed8-xutvf, CPU PLATFORM:linux/amd64
Use the following command to add an Arm-based node pool with VM type c4a-standard-2 to your GKE cluster:
gcloud container node-pools create arm-pool \
--cluster $CLUSTER_NAME \
--zone $ZONE \
--machine-type=c4a-standard-2 \
--num-nodes=3
After the Arm-nodes are successfully added to the cluster, run the following command to check if both types of nodes show up in the cluster:
kubectl get nodes -o wide
The output should show both x86 and Arm-based nodes.
You have now successfully setup a hybrid cluster with both x86 and Arm64 architecture nodes.
In a hybrid cluster setup with nodes from different architectures (x86 and Arm64), GKE adds a taint on the nodes to avoid the possibility of scheduling pods on wrong architecture. A node taint lets the kubernetes scheduler know that a particular node is designated for one architecture only. A toleration lets you designate pods that can be used on tainted nodes.
In the github repository view the following yaml file:
cat k8s/overlays/arm/add_arm_support.yaml
In this file, refer to the section shown below:
nodeSelector:
kubernetes.io/arch: arm64
This field specifies that the application should only run on Arm-based nodes. After applying this file, GKE adds a toleration that matches the taint on Arm nodes, so that it can schedule the Arm-based application pods on these nodes.
The application used in this learning path is developed in Go language. Check the contents of following file:
cat Dockerfile_arm
In this file, the architecture flag is set to GOARCH=arm64. This way, the application built will be compatible with Arm. You can now use the following set of commands to build the docker image and push it to registry:
docker build -t us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/arm-hello:v0.0.1 -f Dockerfile_arm .
docker push us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/arm-hello:v0.0.1
Now, using taints and tolerations deploy this application in the cluster:
$(cd k8s/overlays/arm && kustomize edit set image hello=us-central1-docker.pkg.dev/$PROJECT_ID/docker-repo/arm-hello:v0.0.1)
kubectl apply -k k8s/overlays/arm
After the application gets deployed, check the status of pods with the following command:
kubectl get pods
Open a web browser and hit the external IP URL or use curl command as shown below:
curl -w '\n' http://$external_ip
Refresh the browser a couple of times and you should see the output from both x86 and Arm compatible versions of the application.
The output will be similar to what is shown below:
Hello from NODE:gke-multi-arch-cluster-default-pool-45537239-q83v, POD:x86-hello-deployment-9e7b823ed8-xutvf, CPU PLATFORM:linux/amd64
Hello from NODE:gke-multi-arch-cluster-arm-pool-n381qvv-bqcr, POD:arm-hello-deployment-21b8d2exfc-o8q33, CPU PLATFORM:linux/arm64
You have now migrated your existing x86-based application to run on an Arm-based GKE cluster and made it multi-arch.