kubenetes(k8s)自动化安装部署（自动化、二进制）

it2024-10-17 41

安装教程： http://www.rhce.cc/2182.html https://blog.csdn.net/wo18237095579/article/details/86630750 https://www.cnblogs.com/zhongle21/p/12220789.html#_lab2_0_2

一、所有节点

1、在所有节点上修改hostname hostnamectl set-hostname master hostnamectl set-hostname node

2、在所有节点上修改ip

vi /etc/sysconfig/network-scripts/ifcfg-ens33

注意事项：(1)BOOTPROTO=static (2)ONBOOT=yes (3)IPADDR=10.4.7.23

TYPE=Ethernet PROXY_METHOD=none BROWSER_ONLY=no BOOTPROTO=static DEFROUTE=yes IPV4_FAILURE_FATAL=no IPV6INIT=yes IPV6_AUTOCONF=yes IPV6_DEFROUTE=yes IPV6_FAILURE_FATAL=no IPV6_ADDR_GEN_MODE=stable-privacy NAME=ens33 UUID=cf12d995-ca97-4e6e-9f08-bdc547ee9478 DEVICE=ens33 ONBOOT=yes IPADDR=10.4.7.23 NETMASK=255.255.255.0 GATEWAY=10.4.7.1 DNS1=8.8.8.8 DNS2=114.114.114.114 ZONE=public service network restart

3、在所有节点上同步/etc/hosts vi /etc/hosts /etc/init.d/network restart

注意事项：(1)151.101.108.133 raw.githubusercontent.com，这一行是防止配置flannel时连接不上raw.githubusercontent.com

127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 ::1 localhost localhost.localdomain localhost6 localhost6.localdomain6 192.168.133.99 Centos dbserver 10.4.7.23 kubeadm1 10.4.7.24 kubeadm2 151.101.108.133 raw.githubusercontent.com

4、在所有节点上配置防火墙和关闭selinux

systemctl disable firewalld.service systemctl stop firewalld.service setenforce 0 swapoff -a vim /etc/selinux/config SELINUX=disabled

5、在所有节点上关闭swap swapoff -a

6、在所有节点上配置好yum源

vi /etc/yum.repos.d/kubernetes.repo [kubernetes] name=Kubernetes Repo baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64/ gpgcheck=0 gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg

7、在所有节点安装并启动docker，并设置docker自动启动

yum install docker -y systemctl enable docker --now

8、在所有节点设置相关属性

vi /etc/sysctl.d/k8s.conf net.bridge.bridge-nf-call-ip6tables = 1 net.bridge.bridge-nf-call-iptables = 1 net.ipv4.ip_forward = 1 vm.swappiness=0

9、在所有节点上安装软件包

yum install -y kubelet-1.18.2-0 kubeadm-1.18.2-0 kubectl-1.18.2-0 --disableexcludes=kubernetes

10、在所有节点上启动kubelet，并设置开机自动启动 systemctl restart kubelet systemctl enable kubelet

echo "export KUBECONFIG=/etc/kubernetes/admin.conf" >> /etc/profile source /etc/profile echo $KUBECONFIG scp /etc/kubernetes/admin.conf root@10.4.7.21:/etc/kubernetes/

11、修改阿里云的源

vi /etc/docker/daemon.json { "registry-mirrors": ["https://registry.docker-cn.com"] } systemctl daemon-reload systemctl restart docker

二、安装master

https://blog.csdn.net/chenxun_2010/article/details/107109311/

1、初始化集群 kubeadm init --image-repository registry.aliyuncs.com/google_containers --kubernetes-version=v1.18.2 --pod-network-cidr=10.244.0.0/16

2、添加配置

mkdir -p $HOME/.kube sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config sudo chown $(id -u):$(id -g) $HOME/.kube/config

3、添加flannel wget https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml kubectl apply -f kube-flannel.yml

4、等待5分钟左右验证节点 kubectl get pods --all-namespaces -o wide kubectl get nodes

三、安装node

1、主节点上获取token kubeadm token create --print-join-command

2、将从节点添加至集群 kubeadm join 10.4.7.23:6443 --token 133ugt.f9xaifwfbi9963th --discovery-token-ca-cert-hash sha256:14bc9da5c0e879882120a9a8332b12dba546b450ceee6805263fe2a8ee7567b6

注意事项： (1)报错Config not found: /etc/kubernetes/admin.conf 把master节点的对应文件复制到node节点的相应位置，请参照https://www.cnblogs.com/wind-zhou/p/12829079.html (2)报错：/etc/kubernetes/kubelet.conf already exists /etc/kubernetes/pki/ca.crt already exists 请参照https://www.cnblogs.com/liuyi778/p/12229416.html 或者加上 --ignore-preflight-errors=all (3)报错：[ERROR Port-10250]: Port 10250 is in use systemctl restart kubelet 还有一种可能是在master节点上部署node节点，该端口已经占用，请自行百度解决

3、部署nginx https://blog.csdn.net/qq_43279371/article/details/107768713

四、部署kubeflow

docker pull istio/sidecar_injector:1.1.6 docker pull istio/proxyv2:1.1.6 docker pull istio/proxy_init:1.1.6 docker pull istio/pilot:1.1.6 docker pull istio/mixer:1.1.6 docker pull istio/galley:1.1.6 docker pull istio/citadel:1.1.6 docker pull sw1136562366/viewer-crd-controller:0.2.5 docker pull sw1136562366/api-server:0.2.5 docker pull sw1136562366/frontend:0.2.5 docker pull sw1136562366/visualization-server:0.2.5 docker pull sw1136562366/scheduledworkflow:0.2.5 docker pull sw1136562366/persistenceagent:0.2.5 docker pull sw1136562366/envoy:metadata-grpc docker pull sw1136562366/profile-controller:v1.0.0-ge50a8531 docker pull sw1136562366/notebook-controller:v1.0.0-gcd65ce25 docker pull sw1136562366/katib-ui:v0.8.0 docker pull sw1136562366/katib-controller:v0.8.0 docker pull sw1136562366/katib-db-manager:v0.8.0 docker pull sw1136562366/jupyter-web-app:v1.0.0-g2bd63238 docker pull sw1136562366/centraldashboard:v1.0.0-g3ec0de71 docker pull sw1136562366/tf_operator:v1.0.0-g92389064 docker pull sw1136562366/pytorch-operator:v1.0.0-g047cf0f docker pull sw1136562366/kfam:v1.0.0-gf3e09203 docker pull sw1136562366/admission-webhook:v1.0.0-gaf96e4e3 docker pull sw1136562366/metadata:v0.1.11 docker pull sw1136562366/metadata-frontend:v0.1.8 docker pull sw1136562366/application:1.0-beta docker pull sw1136562366/ingress-setup:latest docker pull sw1136562366/activator:latest docker pull sw1136562366/webhook:latest docker pull sw1136562366/controller:latest docker pull sw1136562366/istio:latest docker pull sw1136562366/autoscaler-hpa:latest docker pull sw1136562366/autoscaler:latest docker pull sw1136562366/kfserving-controller:0.2.2 docker pull sw1136562366/ml_metadata_store_server:v0.21.1 docker pull sw1136562366/spark-operator:v1beta2-1.0.0-2.4.4 docker pull sw1136562366/kube-rbac-proxy:v0.4.0 docker pull sw1136562366/spartakus-amd64:v1.1.0 docker pull argoproj/workflow-controller:v2.3.0 docker pull argoproj/argoui:v2.3.0 docker tag docker.io/sw1136562366/ingress-setup:latest k8s.gcr.io/kubeflow-images-public/ingress-setup:latest docker tag docker.io/sw1136562366/ingress-setup:latest gcr.io/kubeflow-images-public/ingress-setup:latest # tag ml-pipeline images docker tag docker.io/sw1136562366/viewer-crd-controller:0.2.5 k8s.gcr.io/ml-pipeline/viewer-crd-controller:0.2.5 docker tag docker.io/sw1136562366/api-server:0.2.5 k8s.gcr.io/ml-pipeline/api-server:0.2.5 docker tag docker.io/sw1136562366/frontend:0.2.5 k8s.gcr.io/ml-pipeline/frontend:0.2.5 docker tag docker.io/sw1136562366/visualization-server:0.2.5 k8s.gcr.io/ml-pipeline/visualization-server:0.2.5 docker tag docker.io/sw1136562366/scheduledworkflow:0.2.5 k8s.gcr.io/ml-pipeline/scheduledworkflow:0.2.5 docker tag docker.io/sw1136562366/persistenceagent:0.2.5 k8s.gcr.io/ml-pipeline/persistenceagent:0.2.5 docker tag docker.io/sw1136562366/envoy:metadata-grpc k8s.gcr.io/ml-pipeline/envoy:metadata-grpc # tag kubeflow-images-public images docker tag docker.io/sw1136562366/profile-controller:v1.0.0-ge50a8531 k8s.gcr.io/kubeflow-images-public/profile-controller:v1.0.0-ge50a8531 docker tag docker.io/sw1136562366/notebook-controller:v1.0.0-gcd65ce25 k8s.gcr.io/kubeflow-images-public/notebook-controller:v1.0.0-gcd65ce25 docker tag docker.io/sw1136562366/katib-ui:v0.8.0 k8s.gcr.io/kubeflow-images-public/katib/v1alpha3/katib-ui:v0.8.0 docker tag docker.io/sw1136562366/katib-controller:v0.8.0 k8s.gcr.io/kubeflow-images-public/katib/v1alpha3/katib-controller:v0.8.0 docker tag docker.io/sw1136562366/katib-db-manager:v0.8.0 k8s.gcr.io/kubeflow-images-public/katib/v1alpha3/katib-db-manager:v0.8.0 docker tag docker.io/sw1136562366/jupyter-web-app:v1.0.0-g2bd63238 k8s.gcr.io/kubeflow-images-public/jupyter-web-app:v1.0.0-g2bd63238 docker tag docker.io/sw1136562366/centraldashboard:v1.0.0-g3ec0de71 k8s.gcr.io/kubeflow-images-public/centraldashboard:v1.0.0-g3ec0de71 docker tag docker.io/sw1136562366/tf_operator:v1.0.0-g92389064 k8s.gcr.io/kubeflow-images-public/tf_operator:v1.0.0-g92389064 docker tag docker.io/sw1136562366/pytorch-operator:v1.0.0-g047cf0f k8s.gcr.io/kubeflow-images-public/pytorch-operator:v1.0.0-g047cf0f docker tag docker.io/sw1136562366/kfam:v1.0.0-gf3e09203 k8s.gcr.io/kubeflow-images-public/kfam:v1.0.0-gf3e09203 docker tag docker.io/sw1136562366/admission-webhook:v1.0.0-gaf96e4e3 k8s.gcr.io/kubeflow-images-public/admission-webhook:v1.0.0-gaf96e4e3 docker tag docker.io/sw1136562366/metadata:v0.1.11 k8s.gcr.io/kubeflow-images-public/metadata:v0.1.11 docker tag docker.io/sw1136562366/metadata-frontend:v0.1.8 k8s.gcr.io/kubeflow-images-public/metadata-frontend:v0.1.8 docker tag docker.io/sw1136562366/application:1.0-beta k8s.gcr.io/kubeflow-images-public/kubernetes-sigs/application:1.0-beta docker tag docker.io/sw1136562366/ingress-setup:latest k8s.gcr.io/kubeflow-images-public/ingress-setup:latest # tag kubeflow-images-public images docker tag docker.io/sw1136562366/activator:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/activator:latest docker tag docker.io/sw1136562366/webhook:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/webhook:latest docker tag docker.io/sw1136562366/controller:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/controller:latest docker tag docker.io/sw1136562366/istio:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/networking/istio:latest docker tag docker.io/sw1136562366/autoscaler-hpa:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/autoscaler-hpa:latest docker tag docker.io/sw1136562366/autoscaler:latest k8s.gcr.io/knative-releases/knative.dev/serving/cmd/autoscaler:latest # tag knative-releases images docker tag docker.io/sw1136562366/kfserving-controller:0.2.2 k8s.gcr.io/kfserving/kfserving-controller:0.2.2 docker tag docker.io/sw1136562366/ml_metadata_store_server:v0.21.1 k8s.gcr.io/tfx-oss-public/ml_metadata_store_server:v0.21.1 docker tag docker.io/sw1136562366/spark-operator:v1beta2-1.0.0-2.4.4 k8s.gcr.io/spark-operator/spark-operator:v1beta2-1.0.0-2.4.4 docker tag docker.io/sw1136562366/kube-rbac-proxy:v0.4.0 k8s.gcr.io/kubebuilder/kube-rbac-proxy:v0.4.0 docker tag docker.io/sw1136562366/spartakus-amd64:v1.1.0 k8s.gcr.io/google_containers/spartakus-amd64:v1.1.0

五、kubenetes运维基础

#查看名字的命令是： kubectl get deploy -n kubeflow kubectl get sts -n kubeflow #xxx是对应的deploy和statefulset的名字，因为有很多个，所以要一个一个去改 kubectl edit deploy -n kubeflow xxx kubectl edit sts -n kubeflow xxx ***kubectl edit deploy -n kubeflow controller --namespace knative-serving*** #看一下容器什么状态 kubectl get pods -n kubeflow #看一下这个容器的状态 kubectl describe pods -n kubeflow xxxxx #把它删了，会自动重启的 kubectl delete pods -n kubeflow xxx #statefulset和pod应该要对应起来的，改了statefulset之后对应的pod会变 #看服务报错,看着改,这已经和k8没啥关系了 kubectl logs -n kubeflow xxx #删除Evicted的pod kubectl delete pods -n kubeflow $(kubectl get pods -n kubeflow |grep Evicted|awk '{print $1}') systemctl stop kubelet systemctl stop docker systemctl restart network systemctl restart docker systemctl restart kubelet ifconfig kubectl get node

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