Steps to create EKS cluster with EFS#

1. Install CLIs#

a. Install AWS CLI (steps here)#

sudo apt install unzip
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install

b. Install Kubernetes CLI (steps here)#

curl -O https://s3.us-west-2.amazonaws.com/amazon-eks/1.30.0/2024-05-12/bin/linux/amd64/kubectl
chmod +x ./kubectl
mkdir -p $HOME/bin && cp ./kubectl $HOME/bin/kubectl && export PATH=$HOME/bin:$PATH
echo 'export PATH=$HOME/bin:$PATH' >> ~/.bashrc

c. Install EKS CLI (steps here)#

ARCH=amd64
PLATFORM=$(uname -s)_$ARCH
curl -sLO "https://github.com/eksctl-io/eksctl/releases/latest/download/eksctl_$PLATFORM.tar.gz"
curl -sL "https://github.com/eksctl-io/eksctl/releases/latest/download/eksctl_checksums.txt" | grep $PLATFORM | sha256sum --check
tar -xzf eksctl_$PLATFORM.tar.gz -C /tmp && rm eksctl_$PLATFORM.tar.gz
sudo mv /tmp/eksctl /usr/local/bin

d. Install Helm CLI (steps here)#

curl https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3 > get_helm.sh
chmod 700 get_helm.sh
./get_helm.sh

2. Create an EKS cluster#

In this example we create an EKS cluster consisting of two g5.12xlarge compute nodes, each with four NVIDIA A10G GPUs and c5.2xlarge CPU node as control plane. We also setup EFA between the compute nodes.

a. Configure AWS CLI#

aws configure

b. Create a config file for EKS cluster creation#

We have provided an example file here: eks_cluster_config.yaml

apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig

metadata:
  name: wenhant-eks-cluster
  version: "1.30"
  region: us-east-1

availabilityZones:
  - us-east-1a
  - us-east-1b
  - us-east-1c
  - us-east-1d
  - us-east-1e
  - us-east-1f

iam:
  withOIDC: true

managedNodeGroups:
  - name: sys-nodes-2
    instanceType: c5.2xlarge
    minSize: 1
    desiredCapacity: 1
    maxSize: 1
    availabilityZones: ["us-east-1a"]
    iam:
      withAddonPolicies:
        imageBuilder: true
        autoScaler: true
        ebs: true
        efs: true
        awsLoadBalancerController: true
        cloudWatch: true
        albIngress: true

  - name: efa-compute-ng-2
    instanceType: g5.12xlarge
    minSize: 1
    desiredCapacity: 1
    maxSize: 1
    volumeSize: 300
    efaEnabled: true
    privateNetworking: true
    availabilityZones: ["us-east-1a"]
    iam:
      withAddonPolicies:
        imageBuilder: true
        autoScaler: true
        ebs: true
        efs: true
        awsLoadBalancerController: true
        cloudWatch: true
        albIngress: true

[!NOTE] We set minSize and desiredCapacity to be 1 because AWS does not create your cluster successfully if no nodes are available. For example, if you specify desiredCapacity to be 2 but there are no available 2 nodes, your cluster creation will fail due to timeout even though there are no errors. The easiest way to avoid this is to create the cluster with 1 node and increase the number of nodes later in the EKS console. After you increase number of nodes in your node groups, make sure GPU nodes are in the same subnet. This is required for EFA to work.

c. Create the EKS cluster#

eksctl create cluster -f eks_cluster_config.yaml

3. Create an EFS file system#

To enable multiple pods deployed to multiple nodes to load shards of the same model so that they can used in coordination to serve inference request too large to loaded by a single GPU, we’ll need a common, shared storage location. In Kubernetes, these common, shared storage locations are referred to as persistent volumes. Persistent volumes can be volume mapped in to any number of pods and then accessed by processes running inside of said pods as if they were part of the pod’s file system. We will be using EFS as persistent volume.

Additionally, we will need to create a persistent-volume claim which can use to assign the persistent volume to a pod.

a. Create an IAM role#

Follow the steps to create an IAM role for your EFS file system: https://docs.aws.amazon.com/eks/latest/userguide/efs-csi.html#efs-create-iam-resources. This role will be used later when you install the EFS CSI Driver.

b. Install EFS CSI driver#

Install the EFS CSI Driver through the Amazon EKS add-on in AWS console: https://docs.aws.amazon.com/eks/latest/userguide/efs-csi.html#efs-install-driver. Once it’s done, check the Add-ons section in EKS console, you should see the driver is showing Active under Status.

c. Create EFS file system#

Follow the steps to create an EFS file system: https://github.com/kubernetes-sigs/aws-efs-csi-driver/blob/master/docs/efs-create-filesystem.md. Make sure you mount subnets in the last step correctly. This will affect whether your nodes are able to access the created EFS file system.

4. Test#

Follow the steps to check if your EFS file system is working properly with your nodes: https://github.com/kubernetes-sigs/aws-efs-csi-driver/tree/master/examples/kubernetes/multiple_pods. This test is going to mount your EFS file system on all of your available nodes and write a text file to the file system.

5. Create an PVC for the created EFS file system#

We have provided an example in here: pvc. This folder contains three files: pv.yaml, claim.yaml, and storageclass.yaml. Make sure you modify the pv.yaml file and change the volumeHandle value to your own EFS file system ID.

pv.yaml

apiVersion: v1
kind: PersistentVolume
metadata:
  name: efs-pv
spec:
  capacity:
    storage: 200Gi
  volumeMode: Filesystem
  accessModes:
    - ReadWriteMany
  persistentVolumeReclaimPolicy: Retain
  storageClassName: efs-sc
  csi:
    driver: efs.csi.aws.com
    volumeHandle: fs-0cf1f987d6f5af59c # Change to your own ID

claim.yaml

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: efs-claim
spec:
  accessModes:
    - ReadWriteMany
  storageClassName: efs-sc
  resources:
    requests:
      storage: 200Gi

storageclass.yaml

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: efs-sc
provisioner: efs.csi.aws.com

Run the below command to deploy:

kubectl apply -f pvc/
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