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Learn How to Build and Deploy a Multi-architecture Application on Amazon EKS

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8 Apr 2024CPOL5 min read 3.2K   3   1
How to build and deploy a multi-architecture application with x86/amd64 and arm64-based container images on Amazon EKS

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Who Is This For?

This is an advanced topic for software developers who want to understand how to build and deploy a multi-architecture application with x86/amd64 and arm64-based container images on Amazon EKS.

What Will You Learn?

Upon completion of this learning path, you will be able to:

  • Build x86/amd64 and arm64 container images with docker buildx and docker manifest
  • Understand the nuances of building a multi-architecture container image
  • Deploy a multi-arch container application across multiple architectures in a single Amazon EKS cluster

Prerequisites

Before starting, you will need the following:

Multi-architecture Amazon EKS cluster with x86 and Arm-based (Graviton) Nodes

A multi-architecture Kubernetes cluster runs workloads on multiple hardware architectures, typically arm64 and amd64. To learn more about multi-architecture Kubernetes, you can create a hybrid cluster in Amazon EKS and gain some practical experience with arm64 and amd64 nodes. This will also help you understand multi-architecture container images.

Before You Begin

You will need an AWS account. Create an account if needed.

Three tools are required on your local machine. Follow the links to install the required tools.

Create a Multi-Architecture Amazon EKS Cluster

Use eksctl to create a multi-architecture Amazon EKS cluster. Create a file named cluster.yaml with the contents below using a file editor of your choice.

YAML
apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig

metadata:
  name: multi-arch-cluster
  region: us-east-1

nodeGroups:
  - name: x86-node-group
    instanceType: m5.large
    desiredCapacity: 2
    volumeSize: 80
  - name: arm64-node-group
    instanceType: m6g.large
    desiredCapacity: 2
    volumeSize: 80

Run the eksctl command to create the EKS cluster:

eksctl create cluster -f cluster.yaml

This command will create a cluster that has 2 x86/amd64 nodes and 2 arm64 nodes. When the cluster is ready, use the following command to check the nodes:

Azure-CLI
kubectl get nodes

The output should look similar to:

NAME                                          STATUS   ROLES    AGE     VERSION
ip-172-31-10-206.eu-west-1.compute.internal   Ready    <none>   9m56s   v1.28.1-eks-43840fb
ip-172-31-16-133.eu-west-1.compute.internal   Ready    <none>   9m59s   v1.28.1-eks-43840fb
ip-172-31-19-140.eu-west-1.compute.internal   Ready    <none>   8m32s   v1.28.1-eks-43840fb
ip-172-31-40-45.eu-west-1.compute.internal    Ready    <none>   8m32s   v1.28.1-eks-43840fb 

To check the architecture of the nodes, execute the following command:

Azure-CLI
kubectl get node -o jsonpath='{.items[*].status.nodeInfo.architecture}'

The output should show two architectures for four nodes:

arm64 amd64 amd64 arm64 

Multi-Architecture Containers

Multi-architecture container images are the easiest way to deploy applications and hide the underlying hardware architecture. Building multi-architecture images is slightly more complex compared to building single-architecture images. Docker provides two ways to create multi-architecture images:

  • docker buildx - builds both architectures at the same time
  • docker manifest - builds each architecture separately and joins them together into a multi-architecture image

Shown below is a simple Go application you can use to learn about multi-architecture Kubernetes clusters. Create a file named hello.go with the contents below:

go
package main

import (
    "fmt"
    "log"
    "net/http"
    "os"
    "runtime"
)

func handler(w http.ResponseWriter, r *http.Request) {
    fmt.Fprintf(w, "Hello from image NODE:%s, POD:%s, CPU PLATFORM:%s/%s",
        os.Getenv("NODE_NAME"), os.Getenv("POD_NAME"), runtime.GOOS, runtime.GOARCH)
}

func main() {
    http.HandleFunc("/", handler)
    log.Fatal(http.ListenAndServe(":8080", nil))
}

Create another file named go.mod with the following content:

module example.com/arm
go 1.21

Create a Dockerfile with the following content:

ARG T

#
# Build: 1st stage
#
FROM golang:1.21-alpine as builder
ARG TARCH
WORKDIR /app
COPY go.mod .
COPY hello.go .
RUN GOARCH=${TARCH} go build -o /hello && \
    apk add --update --no-cache file && \
    file /hello

#
# Release: 2nd stage
#
FROM ${T}alpine
WORKDIR /
COPY --from=builder /hello /hello
RUN apk add --update --no-cache file
CMD [ "/hello" ]

Build Multi-architecture Docker Images with Docker buildx

With these files, you can build your docker image. Log in to Amazon ECR and create a repository named multi-arch-app.

Run the following command to build and push the docker image to the repository:

BAT
docker buildx create --name multiarch --use --bootstrap
docker buildx build -t <your-docker-repo-path>/multi-arch:latest --platform linux/amd64,linux/arm64 --push .

Replace <your-docker-repo-path> in the command above to the location of your repository.

You should now see the docker image in your repository.

Build Multi-Architecture Docker Images with Docker Manifest

You can also use docker manifest to create a multi-architecture image from two single-architecture images. Create another repository in Amazon ECR with the name multi-arch-demo. Use the following command to build an amd64 image:

BAT
docker build build -t <your-docker-repo-path>/multi-arch-demo:amd64 --build-arg TARCH=amd64 --build-arg T=amd64/ .
docker push <your-docker-repo-path>/multi-arch-demo:amd64

Replace <your-docker-repo-path> in the command above to the location of your repository.

Build an arm64 image by executing the following commands on an arm64 machine:

BAT
docker build build -t <your-docker-repo-path>/multi-arch-demo:arm64 --build-arg TARCH=amd64 --build-arg T=amd64v8/ .
docker push <your-docker-repo-path>/multi-arch-demo:arm64

Again, replace <your-docker-repo-path> in the commands above to the location of your repository.

After building individual containers for each architecture, merge them into a single image by running the commands below on either architecture:

BAT
docker manifest create <your-docker-repo-path>/multi-arch-demo:latest \
--amend <your-docker-repo-path>/multi-arch-demo:arm64 \
--amend <your-docker-repo-path>/multi-arch-demo:amd64
docker manifest push --purge <your-docker-repo-path>/multi-arch-demo:latest

You should see three images in the ECR repository - one for each architecture (amd64 and arm64) and a combined multi-architecture image.

Deploy Kubernetes Service in EKS Cluster

You can now create a service to deploy the application. Create a file named hello-service.yaml with the following contents:

YAML
apiVersion: v1
kind: Service
metadata:
  name: hello-service
  labels:
    app: hello
    tier: web
spec:
  type: LoadBalancer
  ports:
    - port: 80
      targetPort: 8080
  selector:
    app: hello
    tier: web

Deploy the service and run the following command:

Azure-CLI
kubectl apply -f hello-service.yaml

Deploy amd64 Application

Create a text file named amd64-deployment.yaml with the contents below. The amd64 image will only run on amd64 nodes. The nodeSelector is used to make sure the container is only scheduled on amd64 nodes.

YAML
apiVersion: apps/v1
kind: Deployment
metadata:
  name: amd-deployment
  labels:
    app: hello
spec:
  replicas: 1
  selector:
    matchLabels:
      app: hello
      tier: web
  template:
    metadata:
      labels:
        app: hello
        tier: web
    spec:
      containers:
      - name: hello
        image: <your-docker-repo-path>/multi-arch-demo:amd64
        imagePullPolicy: Always
        ports:
          - containerPort: 8080
        env:
          - name: NODE_NAME
            valueFrom:
              fieldRef:
                fieldPath: spec.nodeName
          - name: POD_NAME
            valueFrom:
              fieldRef:
                fieldPath: metadata.name
        resources:
          requests:
            cpu: 300m
      nodeSelector:
        kubernetes.io/arch: amd64

Use the following command to deploy the application:

Azure-CLI
kubectl apply -f amd64-deployment.yaml

The output should show a single pod running.

Get the external IP assigned to the service you deployed earlier, by executing the following command:

Azure-CLI
kubectl get svc

Use the external-ip from the command output and execute the following command (this IP belongs to the Load Balancer provisioned in your cluster):

BAT
curl -w '\n' http://<external_ip>

You should now see an output similar to what’s shown below:

Hello from image NODE:ip-192-168-32-244.ec2.internal, POD:amd-deployment-7d4d44889d-vzhpd, CPU PLATFORM:linux/amd64 

Deploy arm64 Application

Create a text file named arm64-deployment.yaml with the contents below. Note that the value of nodeSelector is now arm64.

YAML
apiVersion: apps/v1
kind: Deployment
metadata:
  name: arm-deployment
  labels:
    app: hello
spec:
  replicas: 1
  selector:
    matchLabels:
      app: hello
      tier: web
  template:
    metadata:
      labels:
        app: hello
        tier: web
    spec:
      containers:
      - name: hello
        image: <your-docker-repo-path>/multi-arch-demo:arm64
        imagePullPolicy: Always
        ports:
          - containerPort: 8080
        env:
          - name: NODE_NAME
            valueFrom:
              fieldRef:
                fieldPath: spec.nodeName
          - name: POD_NAME
            valueFrom:
              fieldRef:
                fieldPath: metadata.name
        resources:
          requests:
            cpu: 300m
      nodeSelector:
        kubernetes.io/arch: arm64

Deploy the arm64 application by using the command below:

Azure-CLI
kubectl apply -f arm64-deployment.yaml

Execute the following command to check the running pods:

Azure-CLI
kubectl get pods

You should now see two pods running in the cluster, one for amd64 and another one for arm64.

Execute the curl command a few times to see output from both the pods; you should see responses from both the arm64 and amd64 pods.

BAT
curl -w '\n' http://<external_ip>

Deploy Multi-Architecture Application in EKS Cluster

You can now deploy the multi-architecture version of the application in EKS cluster. Create a text file named multi-arch-deployment.yaml with the contents below. The image is the multi-architecture image created with docker buildx and 6 replicas are specified.

YAML
apiVersion: apps/v1
kind: Deployment
metadata:
  name: multi-arch-deployment
  labels:
    app: hello
spec:
  replicas: 6
  selector:
    matchLabels:
      app: hello
      tier: web
  template:
    metadata:
      labels:
        app: hello
        tier: web
    spec:
      containers:
      - name: hello
        image: <your-docker-repo-path>/multi-arch:latest
        imagePullPolicy: Always
        ports:
          - containerPort: 8080
        env:
          - name: NODE_NAME
            valueFrom:
              fieldRef:
                fieldPath: spec.nodeName
          - name: POD_NAME
            valueFrom:
              fieldRef:
                fieldPath: metadata.name
        resources:
          requests:
            cpu: 300m

Deploy the multi-architecture application by using the command below:

Azure-CLI
kubectl apply -f multi-arch-deployment.yaml

Execute the following command to check the running pods:

Azure-CLI
kubectl get pods

The output should show all the pods from three deployments. To test the application, run the following command to check messages from all three versions of the application:

for i in $(seq 1 10); do curl -w '\n' http://<external_ip>; done

The output will show a variety of arm64 and amd64 messages.

You have now deployed an x86/amd64, arm64 and multi-architecture version of the same application in a single Amazon EKS cluster. Leverage these techniques to incrementally migrate your existing x86/amd64 based applications to arm64 in AWS.

Want to continue learning? Visit learn.arm.com to find more tutorials designed to help you develop quality Arm software faster.

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


Written By
United States United States
Pranay is a Principal Solutions Engineer at Arm focusing on developing cloud native solutions spanning cloud to edge deployments with strategic partners. He has over 13+ years of experience designing and implementing wide range of virtualization and cloud solutions and has authored multiple blogs, demos and presented at industry events providing his technical thought leadership.

Comments and Discussions

 
GeneralMy vote of 5 Pin
Ștefan-Mihai MOGA1-Mar-24 21:51
professionalȘtefan-Mihai MOGA1-Mar-24 21:51 

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