AWS EKS1.26+kubesphere3.4.1

1、前提准备

1台EC2服务器Amazon Linux2，设置admin的角色

安装 aws cli V2


curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"

unzip awscliv2.zip

sudo ./aws/install

export PATH=/usr/local/bin:$PATH

source ~/.bash_profile

安装kubectl 1.27


curl -O https://s3.us-west-2.amazonaws.com/amazon-eks/1.27.1/2023-04-19/bin/linux/amd64/kubectl

chmod +x ./kubectl

mkdir -p $HOME/bin && cp ./kubectl $HOME/bin/kubectl && export PATH=$PATH:$HOME/bin

echo 'export PATH=$PATH:$HOME/bin' >> ~/.bashrc

kubectl version --short --client

安装 eksctl 最新版本


使用以下命令下载并提取最新版本的 eksctl。

curl --silent --location "https://github.com/weaveworks/eksctl/releases/latest/download/eksctl_$(uname -s)_amd64.tar.gz" | tar xz -C /tmp

将提取的二进制文件移至 /usr/local/bin。

sudo mv /tmp/eksctl /usr/local/bin

使用以下命令测试您的安装是否成功。

eksctl version

安装helm


wget https://get.helm.sh/helm-v3.11.1-linux-amd64.tar.gz

tar -zxvf helm-v3.11.1-linux-amd64.tar.gz 

sudo mv linux-amd64/helm /usr/local/bin/helm

2、创建集群

使用eksctl安装EKS集群（这里自动新建了一个VPC，以及对应的子网。自动创建的子网，EKS 相关的标签已自动打好)

修改下面的集群名字

sudo yum install -y jq

export AWS_REGION=$(curl -s 169.254.169.254/latest/dynamic/instance-identity/document | jq -r '.region')

echo "export AWS_REGION=${AWS_REGION}" | tee -a ~/.bash_profile

aws configure set default.region ${AWS_REGION}

export ACCOUNT_ID=$(curl -s 169.254.169.254/latest/dynamic/instance-identity/document | jq -r '.accountId')

echo "export ACCOUNT_ID=${ACCOUNT_ID}" | tee -a ~/.bash_profile



export CLUSTER_NAME="eks-demo2"

需要根据实际场景修改下面的实例类型

cat << EOF > ${CLUSTER_NAME}-cluster.yaml

---

apiVersion: eksctl.io/v1alpha5

kind: ClusterConfig



metadata:

  name: ${CLUSTER_NAME} # EKS Cluster name

  region: ${AWS_REGION} # Region Code to place EKS Cluster

  version: "1.26"

  tags:

    karpenter.sh/discovery: ${CLUSTER_NAME}



vpc:

  cidr: "10.101.0.0/16" # CIDR of VPC for use in EKS Cluster

  nat:

    gateway: Disable # Disable NAT Gateway

karpenter:

  version: 'v0.30.0'

  createServiceAccount: true # default is false

  defaultInstanceProfile: 'KarpenterNodeInstanceProfile' # default is to use the IAM instance profile created by eksctl

  withSpotInterruptionQueue: true # adds all required policies and rules for supporting Spot Interruption Queue, default is false

iam:

  withOIDC: true # required



managedNodeGroups:

  - name: node-group # Name of node group in EKS Cluster

    instanceType: t3.xlarge # Instance type for node group

    desiredCapacity: 2 # The number of worker node in EKS Cluster

    volumeSize: 100  # EBS Volume for worker node (unit: GiB)

    volumeType: 'gp3'

    maxPodsPerNode: 100

    privateNetworking: false

    ssh:

      enableSsm: true

    iam:

      withAddonPolicies:

        imageBuilder: true # Add permission for Amazon ECR

        albIngress: true  # Add permission for ALB Ingress

        cloudWatch: true # Add permission for CloudWatch

        autoScaler: true # Add permission Auto Scaling

        ebs: true # Add permission EBS CSI driver

EOF



eksctl create cluster -f ${CLUSTER_NAME}-cluster.yaml

3、安装应的LB Controller

获取ID，确认 OIDC 是否已安装

aws eks describe-cluster --name ${CLUSTER_NAME} --query "cluster.identity.oidc.issuer" --output text

输出如下文本：

https://oidc.eks.cn-northwest-1.amazonaws.com.cn/id/36A3B4C5ED098358C3C724DA105EBC86

若没有安装，则执行：

安装OIDC

eksctl utils associate-iam-oidc-provider \

--region ${AWS_REGION} \

--cluster ${CLUSTER_NAME} \

--approve

创建一个 IAM policy。

下载 Amazon Load Balancer Controller 的 IAM policy，该策略允许负载均衡器代表您调用 Amazon API。

curl -O https://raw.githubusercontent.com/kubernetes-sigs/aws-load-balancer-controller/v2.5.4/docs/install/iam_policy.json

使用上一步中下载的策略创建一个 IAM policy。

aws iam create-policy \

--policy-name AWSLoadBalancerControllerIAMPolicy_${CLUSTER_NAME} \

--policy-document file://iam_policy.json

创建serviceaccount

eksctl create iamserviceaccount \

--cluster=${CLUSTER_NAME} \

--namespace=kube-system \

--name=aws-load-balancer-controller \

--role-name AmazonEKSLoadBalancerControllerRole_${CLUSTER_NAME} \

--attach-policy-arn=arn:aws:iam::${ACCOUNT_ID}:policy/AWSLoadBalancerControllerIAMPolicy_${CLUSTER_NAME} \

--approve

添加 eks-charts 存储库。

helm repo add eks https://aws.github.io/eks-charts

更新您的本地存储库，以确保您拥有最新的图表。

helm repo update

进行安装

helm install aws-load-balancer-controller eks/aws-load-balancer-controller \

  -n kube-system \

  --set clusterName=${CLUSTER_NAME} \

  --set serviceAccount.create=false \

  --set serviceAccount.name=aws-load-balancer-controller \

  --set enableShield=false \

  --set enableWaf=false \

  --set enableWafv2=false \

验证控制器是否已安装。

kubectl get deployment -n kube-system aws-load-balancer-controller

输出示例如下。

NAME READY UP-TO-DATE AVAILABLE AGE

aws-load-balancer-controller 2/2 2 2 84s

安装EBS CSI驱动

eksctl create iamserviceaccount \

    --name ebs-csi-controller-sa \

    --namespace kube-system \

    --cluster ${CLUSTER_NAME} \

    --role-name AmazonEKS_EBS_CSI_DriverRole_${CLUSTER_NAME} \

    --role-only \

    --attach-policy-arn arn:aws:iam::aws:policy/service-role/AmazonEBSCSIDriverPolicy \

    --approve



eksctl create addon --name aws-ebs-csi-driver --cluster ${CLUSTER_NAME} --service-account-role-arn  arn:aws:iam::${ACCOUNT_ID}:role/AmazonEKS_EBS_CSI_DriverRole_${CLUSTER_NAME} –force

4、安装kubesphere

4.1、最小化安装

使用 kubectl 安装 KubeSphere，

以下命令仅用于默认的最小安装。

kubectl apply -f https://github.com/kubesphere/ks-installer/releases/download/v3.4.1/kubesphere-installer.yaml

kubectl apply -f https://github.com/kubesphere/ks-installer/releases/download/v3.4.1/cluster-configuration.yaml

检查安装日志：

kubectl logs -n kubesphere-system $(kubectl get pod -n kubesphere-system -l 'app in (ks-install, ks-installer)' -o jsonpath='{.items[0].metadata.name}') -f

安装完成后，您会看到以下消息：

#####################################################
###              Welcome to KubeSphere!           ###
#####################################################
Account: admin
Password: P@88w0rd
NOTES：
  1. After logging into the console, please check the
    monitoring status of service components in
    the "Cluster Management". If any service is not
    ready, please wait patiently until all components
    are ready.
  2. Please modify the default password after login.
#####################################################
https://kubesphere.io             2020-xx-xx xx:xx:xx

访问 KubeSphere 控制台

现在已经安装了 KubeSphere，您可以按照以下步骤访问 KubeSphere 的 Web 控制台。

查看 ks-console 服务。

kubectl get svc -n kubesphere-system

但是这种内网 IP 无法直接用于外部访问，需要通过NodePort来暴露external-ip

执行kubectl edit ks-console将 service 类型NodePort 更改为LoadBalancer，并且增加三条注解，完成后保存文件。

kubectl edit svc ks-console -n kubesphere-system

    service.beta.kubernetes.io/aws-load-balancer-nlb-target-type: ip

    service.beta.kubernetes.io/aws-load-balancer-scheme: internet-facing

    service.beta.kubernetes.io/aws-load-balancer-type: external

#
......
spec:
  clusterIP: 10.100.160.240
  externalTrafficPolicy: Cluster
  ports:
  - name: nginx
    nodePort: 30880
    port: 80
    protocol: TCP
    targetPort: 8000
  selector:
    app: ks-console
    tier: frontend
    version: v3.0.0
  sessionAffinity: None
  type: LoadBalancer

执行kubectl get svc -n kubesphere-system获取您的 EXTERNAL-IP。

# kubectl get svc -n kubesphere-system
NAME                    TYPE           CLUSTER-IP       EXTERNAL-IP                                                               PORT(S)        AGE
ks-apiserver            ClusterIP      10.100.108.212   <none>                                                                    80/TCP         6m28s
ks-console              LoadBalancer   10.100.160.240   ad107c54ee456744c91c8da0b9321f2c-1235661477.ap-east-1.elb.amazonaws.com   80:30880/TCP   6m25s
ks-controller-manager   ClusterIP      10.100.126.96    <none>                                                                    443/TCP        6m28s
openldap                ClusterIP      None             <none>                                                                    389/TCP        6m54s
redis                   ClusterIP      10.100.218.34    <none>                                                                    6379/TCP       6m59s