array(2) { ["docs"]=> array(10) { [0]=> array(10) { ["id"]=> string(3) "428" ["text"]=> string(77) "Visual Studio 2017 单独启动MSDN帮助(Microsoft Help Viewer)的方法" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(8) "DonetRen" ["tagsname"]=> string(55) "Visual Studio 2017|MSDN帮助|C#程序|.NET|Help Viewer" ["tagsid"]=> string(23) "[401,402,403,"300",404]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511400964" ["_id"]=> string(3) "428" } [1]=> array(10) { ["id"]=> string(3) "427" ["text"]=> string(42) "npm -v;报错 cannot find module "wrapp"" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(4) "zzty" ["tagsname"]=> string(50) "node.js|npm|cannot find module "wrapp“|node" ["tagsid"]=> string(19) "[398,"239",399,400]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511400760" ["_id"]=> string(3) "427" } [2]=> array(10) { ["id"]=> string(3) "426" ["text"]=> string(54) "说说css中pt、px、em、rem都扮演了什么角色" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(12) "zhengqiaoyin" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511400640" ["_id"]=> string(3) "426" } [3]=> array(10) { ["id"]=> string(3) "425" ["text"]=> string(83) "深入学习JS执行--创建执行上下文(变量对象,作用域链,this)" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(7) "Ry-yuan" ["tagsname"]=> string(33) "Javascript|Javascript执行过程" ["tagsid"]=> string(13) "["169","191"]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511399901" ["_id"]=> string(3) "425" } [4]=> array(10) { ["id"]=> string(3) "424" ["text"]=> string(30) "C# 排序技术研究与对比" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(9) "vveiliang" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(8) ".Net Dev" ["catesid"]=> string(5) "[199]" ["createtime"]=> string(10) "1511399150" ["_id"]=> string(3) "424" } [5]=> array(10) { ["id"]=> string(3) "423" ["text"]=> string(72) "【算法】小白的算法笔记:快速排序算法的编码和优化" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(9) "penghuwan" ["tagsname"]=> string(6) "算法" ["tagsid"]=> string(7) "["344"]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511398109" ["_id"]=> string(3) "423" } [6]=> array(10) { ["id"]=> string(3) "422" ["text"]=> string(64) "JavaScript数据可视化编程学习(二)Flotr2,雷达图" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(7) "chengxs" ["tagsname"]=> string(28) "数据可视化|前端学习" ["tagsid"]=> string(9) "[396,397]" ["catesname"]=> string(18) "前端基本知识" ["catesid"]=> string(5) "[198]" ["createtime"]=> string(10) "1511397800" ["_id"]=> string(3) "422" } [7]=> array(10) { ["id"]=> string(3) "421" ["text"]=> string(36) "C#表达式目录树(Expression)" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(4) "wwym" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(4) ".NET" ["catesid"]=> string(7) "["119"]" ["createtime"]=> string(10) "1511397474" ["_id"]=> string(3) "421" } [8]=> array(10) { ["id"]=> string(3) "420" ["text"]=> string(47) "数据结构 队列_队列实例:事件处理" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(7) "idreamo" ["tagsname"]=> string(40) "C语言|数据结构|队列|事件处理" ["tagsid"]=> string(23) "["246","247","248",395]" ["catesname"]=> string(12) "数据结构" ["catesid"]=> string(7) "["133"]" ["createtime"]=> string(10) "1511397279" ["_id"]=> string(3) "420" } [9]=> array(10) { ["id"]=> string(3) "419" ["text"]=> string(47) "久等了,博客园官方Android客户端发布" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(3) "cmt" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511396549" ["_id"]=> string(3) "419" } } ["count"]=> int(200) } 222 k8s 基于Kubeadm部署高可用集群 - 爱码网

Kubernetes的高可用

Kubernetes的高可用主要指的是控制平面的高可用,即有多套Master节点组件和Etcd组件,工作节点通过负载均衡连接到各Master。

HA的2中部署方式

一种是将etcd与Master节点组件混布在一起

k8s 基于Kubeadm部署高可用集群

另外一种方式是,使用独立的Etcd集群,不与Master节点混布

k8s 基于Kubeadm部署高可用集群

两种方式的相同之处在于都提供了控制平面的冗余,实现了集群高可以用,区别在于:

  • Etcd混布方式:
所需机器资源少
部署简单,利于管理
容易进行横向扩展
风险大,一台宿主机挂了,master和etcd就都少了一套,集群冗余度受到的影响比较大。
  • Etcd独立部署方式:
所需机器资源多(按照Etcd集群的奇数原则,这种拓扑的集群关控制平面最少就要6台宿主机了)。
部署相对复杂,要独立管理etcd集群和和master集群。
解耦了控制平面和Etcd,集群风险小健壮性强,单独挂了一台master或etcd对集群的影响很小。

部署环境

服务器

master1 192.168.0.101 (master节点1)
master2 192.168.0.102 (master节点2)
master3 192.168.0.103 (master节点3)
haproxy 192.168.0.100 (haproxy节点,做3个master节点的负载均衡器)
master-1 192.168.0.104 (node节点)
主机 IP 备注
master1 192.168.0.101 master节点1
master2 192.168.0.102 master节点2
master3 192.168.0.103 master节点3
haproxy 192.168.0.100 haproxy节点,做3个master节点的负载均衡器
node 192.168.0.104 node节点

环境

主机:CentOS Linux release 7.7.1908 (Core)
core:3.10.0-1062.el7.x86_64
docker:19.03.7
kubeadm:1.17.3
资源 配置
主机 CentOS Linux release 7.7.1908 (Core)
主机core 3.10.0-1062.el7.x86_64
docker 19.03.7
kubeadm 1.17.3

部署步骤

关闭防火墙,swap,设置内核等

在所有节点上操作

  • 关闭selinux,firewall
setenforce  0
sed -i 's/SELINUX=enforcing/SELINUX=permissive/' /etc/selinux/config 
systemctl stop firewalld
systemctl disable firewalld
  • 关闭swap,(1.8版本后的要求,目的应该是不想让swap干扰pod可使用的内存limit)
swapoff -a
vim /etc/fstab

# 注释掉swap行
  • 设置主机名
hostnamectl set-hostname [master|node]{X}
  • 设置域名解析(不设置可能会导致kubeadm init初始化超时)
vim /etc/hosts

192.168.0.101 master1
192.168.0.102 master2
192.168.0.103 master3
192.168.0.104 node
  • 修改下面内核参数,否则请求数据经过iptables的路由可能有问题
cat <<EOF >  /etc/sysctl.d/k8s.conf
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
EOF
sysctl --system

安装kubeadm、docker

在除了haproxy以外所有节点上操作

  • 将Kubernetes安装源改为阿里云,方便国内网络环境安装
cat << EOF > /etc/yum.repos.d/kubernetes.repo
[kubernetes]
name=Kubernetes
baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64/
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg
EOF
  • 安装docker-ce
wget -O /etc/yum.repos.d/docker-ce.repo https://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo

yum install -y docker-ce
systemctl start docker
systemctl enable docker
  • 安装kubelet kubeadm kubectl
yum install -y kubelet kubeadm kubectl

systemctl enable kubelet
systemctl start kubelet

安装配置负载均衡

在haproxy节点操作

安装haproxy

yum install haproxy -y 

修改haproxy配置

cat << EOF > /etc/haproxy/haproxy.cfg
global
    log         127.0.0.1 local2
    chroot      /var/lib/haproxy
    pidfile     /var/run/haproxy.pid
    maxconn     4000
    user        haproxy
    group       haproxy
    daemon

defaults
    mode                    tcp
    log                     global
    retries                 3
    timeout connect         10s
    timeout client          1m
    timeout server          1m

frontend kube-apiserver
    bind *:6443 # 指定前端端口
    mode tcp
    default_backend master

backend master # 指定后端机器及端口,负载方式为轮询
    balance roundrobin
    server master1  192.168.0.101:6443 check maxconn 2000
    server master2  192.168.0.102:6443 check maxconn 2000
    server master3  192.168.0.103:6443 check maxconn 2000
EOF

开机默认启动haproxy,开启服务

systemctl enable haproxy
systemctl start haproxy

检查服务端口情况

ss -tnlp | grep 6443
LISTEN     0      128          *:6443                     *:*                   users:(("haproxy",pid=1107,fd=4))

部署Kubernetes

在master1节点操作

生成init启动配置文件

kubeadm config print init-defaults > kubeadm-config.yaml

调整kubeadm-config.yaml文件,修改配置或新增配置

apiVersion: kubeadm.k8s.io/v1beta2
bootstrapTokens:
- groups:
  - system:bootstrappers:kubeadm:default-node-token
  token: abcdef.0123456789abcdef
  ttl: 24h0m0s
  usages:
  - signing
  - authentication
kind: InitConfiguration
localAPIEndpoint:
  advertiseAddress: 192.168.0.101    ##宿主机IP地址
  bindPort: 6443
nodeRegistration:
  criSocket: /var/run/dockershim.sock
  name: master1    ##当前节点在k8s集群中名称
  taints:
  - effect: NoSchedule
    key: node-role.kubernetes.io/master
---
apiServer:
  timeoutForControlPlane: 4m0s
apiVersion: kubeadm.k8s.io/v1beta2
certificatesDir: /etc/kubernetes/pki
clusterName: kubernetes
controlPlaneEndpoint: "192.168.0.100:6443"    ##前段haproxy负载均衡地址和端口
controllerManager: {}
dns:
  type: CoreDNS
etcd:
  local:
    dataDir: /var/lib/etcd
imageRepository: registry.cn-hangzhou.aliyuncs.com/google_containers    ##使用阿里的镜像地址,否则无法拉取镜像
kind: ClusterConfiguration
kubernetesVersion: v1.17.0
networking:
  dnsDomain: cluster.local
  podSubnet: "10.244.0.0/16"    ##此处填写后期要安装网络插件flannel的默认网络地址
  serviceSubnet: 10.96.0.0/12
scheduler: {}

执行节点初始化

# 通过阿里源预先拉镜像
kubeadm  config images pull  --config kubeadm-config.yaml  

kubeadm init --config=kubeadm-config.yaml --upload-certs | tee kubeadm-init.log

安装成功,可以看到输出

Your Kubernetes control-plane has initialized successfully!

To start using your cluster, you need to run the following as a regular user:

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

You should now deploy a pod network to the cluster.
Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
  https://kubernetes.io/docs/concepts/cluster-administration/addons/

You can now join any number of the control-plane node running the following command on each as root:

# master节点用以下命令加入集群:
  kubeadm join 192.168.0.100:6443 --token abcdef.0123456789abcdef \
    --discovery-token-ca-cert-hash sha256:37041e2b8e0de7b17fdbf73f1c79714f2bddde2d6e96af2953c8b026d15000d8 \
    --control-plane --certificate-key 8d3f96830a1218b704cb2c24520186828ac6fe1d738dfb11199dcdb9a10579f8

Please note that the certificate-key gives access to cluster sensitive data, keep it secret!
As a safeguard, uploaded-certs will be deleted in two hours; If necessary, you can use
"kubeadm init phase upload-certs --upload-certs" to reload certs afterward.

Then you can join any number of worker nodes by running the following on each as root:

# 工作节点用以下命令加入集群
kubeadm join 192.168.0.100:6443 --token abcdef.0123456789abcdef \
    --discovery-token-ca-cert-hash sha256:37041e2b8e0de7b17fdbf73f1c79714f2bddde2d6e96af2953c8b026d15000d8 

原来的kubeadm版本,join命令只用于工作节点的加入,而新版本加入了 --contaol-plane 参数后,控制平面(master)节点也可以通过kubeadm join命令加入集群了。

启动flannel网络

kubectl apply -f "https://cloud.weave.works/k8s/net?k8s-version=$(kubectl version | base64 | tr -d '\n')"

master节点查看集群

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config

kubectl get no
NAME      STATUS   ROLES    AGE     VERSION
master1   Ready    master   4h12m   v1.17.3

加入另外两个master节点

# 在master(2|3)操作:
kubeadm join 192.168.0.100:6443 --token abcdef.0123456789abcdef \
    --discovery-token-ca-cert-hash sha256:37041e2b8e0de7b17fdbf73f1c79714f2bddde2d6e96af2953c8b026d15000d8 \
    --control-plane --certificate-key 8d3f96830a1218b704cb2c24520186828ac6fe1d738dfb11199dcdb9a10579f8

加入node节点

# 在node操作
kubeadm join 192.168.0.100:6443 --token abcdef.0123456789abcdef \
    --discovery-token-ca-cert-hash sha256:37041e2b8e0de7b17fdbf73f1c79714f2bddde2d6e96af2953c8b026d15000d8 

查看集群

kubectl get no
NAME      STATUS   ROLES    AGE     VERSION
node      Ready    <none>   3h37m   v1.17.3
master1   Ready    master   4h12m   v1.17.3
master2   Ready    master   4h3m    v1.17.3
master3   Ready    master   3h54m   v1.17.3

后记

查看haproxy日志

以便k8s集群启动有问题时排查问题

安装rsyslog服务

yum install rsyslog

配置rsyslog采集日志

vim /etc/rsyslog.conf

# 修改配置

$ModLoad imudp
$UDPServerRun 514

# 新增配置
local2.*                                                /var/log/haproxy.log

重启rsyslog

systemctl restart rsyslog
systemctl enable rsyslog

4层负载均衡使用nginx

安装nginx

yum install nginx
systemctl start nginx
systemctl enable nginx

配置nginx文件

vim /etc/nginx/nginx.conf

# 在http{}段外面添加

stream {
    server {
        listen 6443;
        proxy_pass kube_apiserver;
    }

    upstream kube_apiserver {
        server 192.168.0.101:6443 max_fails=3 fail_timeout=5s;
        server 192.168.0.102:6443 max_fails=3 fail_timeout=5s;
        server 192.168.0.103:6443 max_fails=3 fail_timeout=5s;
    }
    log_format proxy '$remote_addr [$time_local] '
                 '$protocol $status $bytes_sent $bytes_received '
                 '$session_time "$upstream_addr" '
                 '"$upstream_bytes_sent" "$upstream_bytes_received" "$upstream_connect_time"';
   access_log /var/log/nginx/proxy-access.log proxy;
}

重启nginx

systemctl restart nginx

参考文档

https://segmentfault.com/a/1190000018741112

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