今日湛江新闻_怎么做公众号小程序_网站快速收录付费入口_免费推广的平台都有哪些

目录

一、Helm 包管理器

1.什么是 Helm

2.安装Helm

（3）Helm常用命令

（4）目录结构

（5）使用Helm完成redis主从搭建

二、Prometheus集群监控

1.监控方案

2.Prometheus监控k8s

三、ELK日志搜集

1.elk流程

2.配置elk

（1）配置es

（2）配置logstash

（3）配置filebeat，kibana

3.kibana使用和日志检索

四、k8s可视化管理

1. Dashboard安装

2.kubeSphere安装

五、感谢支持

---

一、Helm 包管理器

1.什么是 Helm

Helm是Kubernetes 包管理器，Helm 是查找、分享和使用软件构件 Kubernetes 的最优方式。

Helm 管理名为 chart 的 Kubernetes 包的工具。Helm 可以做以下的事情：

• 从头开始创建新的 chart
• 将 chart 打包成归档(tgz)文件
• 与存储 chart 的仓库进行交互
• 在现有的 Kubernetes 集群中安装和卸载 chart
• 管理与 Helm 一起安装的 chart 的发布周期

对于Helm，有三个重要的概念：

• chart ：创建Kubernetes应用程序所必需的一组信息，将pod、service、deploy放到一个里面。
• config ：包含了可以合并到打包的chart中的配置信息，用于创建一个可发布的对象。
• release ：是一个与特定配置相结合的chart的运行实例。

2.安装Helm

这里下载3.10.2，版本太老的话会有坑。

#下载、解压二进制文件
cd /opt/k8s/
mkdir helm
cd helm/
wget https://get.helm.sh/helm-v3.10.2-linux-amd64.tar.gz
tar -zxvf helm-v3.10.2-linux-amd64.tar.gzcd /opt/k8s/
chmod +x helm/#将配置文件拷贝到指定目录
cd linux-amd64/
cp helm /usr/local/bin/#查看helm
cd ~
helm version#添加helm仓库

注：使用helm下载安装包的时候可能会被墙，如果下载不下来就直接去官网下载也行，之前我们下载过ingress，可参考：3.k8s：服务发布：service，ingress；配置管理：configMap，secret，热更新；持久化存储：volumes，nfs，pv，pvc-CSDN博客

（3）Helm常用命令

#列出、增加、更新、删除 chart 仓库
helm repo#使用关键词搜索 chart
helm search#拉取远程仓库中的 chart 到本地
helm pull#在本地创建新的 chart
helm create#管理 chart 依赖
helm dependency#安装 chart
helm install#列出所有 release
helm list
helm list -n ingress-nginx#检查 chart 配置是否有误
helm lint#打包本地 chart
helm package#回滚 release 到历史版本
helm rollback#卸载 release
helm uninstall#升级 release
helm upgrade

（4）目录结构

mychart
├── Chart.yaml
├── charts # 该目录保存其他依赖的 chart（子 chart）
├── templates # chart 配置模板，用于渲染最终的 Kubernetes YAML 文件
│   ├── NOTES.txt # 用户运行 helm install 时候的提示信息
│   ├── _helpers.tpl # 用于创建模板时的帮助类
│   ├── deployment.yaml # Kubernetes deployment 配置
│   ├── ingress.yaml # Kubernetes ingress 配置
│   ├── service.yaml # Kubernetes service 配置
│   ├── serviceaccount.yaml # Kubernetes serviceaccount 配置
│   └── tests
│       └── test-connection.yaml
└── values.yaml # 定义 chart 模板中的自定义配置的默认值，可以在执行 helm install 或 helm update 的时候覆盖

（5）使用Helm完成redis主从搭建

#查看chart仓库
helm repo list#添加仓库
helm repo add bitnami https://charts.bitnami.com/bitnami
helm repo add aliyun https://kubernetes.oss-cn-hangzhou.aliyuncs.com/charts
helm repo add azure http://mirror.azure.cn/kubernetes/charts# 搜索 redis chart
helm search repo redis# 查看安装说明
helm show readme bitnami/redis# 先将 chart 拉到本地
cd /opt/k8s/
helm pull bitnami/redis#解压
tar -xvf redis-17.4.3.tgz 
cd redis/#修改配置
vim values.yaml 
##################################################24   storageClass: "managed-nfs-storage"25   redis:26     password: "123456"504     size: 1Gi
################################################### 安装操作
# 创建命名空间
kubectl create namespace redis# 安装redis
cd /opt/k8s/
helm install redis ./redis/ -n redis# 查看
kubectl get all -n redis# 升级
helm upgrade redis ./redis/ -n redis# 查看历史
helm history redis# 回退到上一版本
helm rollback redis# 回退到指定版本
helm rollback redis 3# 删除
helm delete redis -n redis

启动redis成功：

二、Prometheus集群监控

1.监控方案

Heapster、Weave Scope、Prometheus

我们选择Prometheus。Prometheus 是一套开源的监控系统、报警、时间序列的集合，最初由 SoundCloud 开发，后来随着越来越多公司的使用，于是便独立成开源项目。自此以后，许多公司和组织都采用了 Prometheus 作为监控告警工具。

2.Prometheus监控k8s

Prometheus有两种搭建方式，一种是自定义，一种是基于kube，我们使用第二种。

因为我们k8s是1.23的版本，因此需要选择Prometheus0.10,Prometheus0.11的版本其他的版本就不行。GitHub - prometheus-operator/kube-prometheus: Use Prometheus to monitor Kubernetes and applications running on Kubernetes

我们使用0.10版本：https://github.com/prometheus-operator/kube-prometheus/tree/v0.10.0

替换镜像
cd /opt/k8s/kube-prometheus/manifests
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' prometheusOperator-deployment.yaml
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' prometheus-prometheus.yaml
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' alertmanager-alertmanager.yaml
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' kubeStateMetrics-deployment.yaml
sed -i 's/k8s.gcr.io/lank8s.cn/g' kubeStateMetrics-deployment.yaml
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' nodeExporter-daemonset.yaml
sed -i 's/quay.io/quay.mirrors.ustc.edu.cn/g' prometheusAdapter-deployment.yaml
sed -i 's/k8s.gcr.io/lank8s.cn/g' prometheusAdapter-deployment.yaml# 启动并下载镜像
cd /opt/k8s/kube-prometheus/
kubectl create -f manifests/setup/
kubectl apply -f manifests/
kubectl get all -n monitoring
kubectl get po -n monitoring
kubectl get svc -n monitoring# 在主机配置域名映射
# 路径是C:\Windows\System32\drivers\etc\hosts
192.168.200.140 grafana.wolfcode.cn
192.168.200.140 prometheus.wolfcode.cn
192.168.200.140 alertmanager.wolfcode.cn# 添加ingress
cd manifests/
vim prometheus-ingress.yaml
####################################################################
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:namespace: monitoringname: prometheus-ingress
spec:ingressClassName: nginxrules:- host: grafana.wolfcode.cn  # 访问 Grafana 域名http:paths:- path: /pathType: Prefixbackend:service:name: grafanaport:number: 3000- host: prometheus.wolfcode.cn  # 访问 Prometheus 域名http:paths:- path: /pathType: Prefixbackend:service:name: prometheus-k8s port:number: 9090- host: alertmanager.wolfcode.cn  # 访问 alertmanager 域名http:paths:- path: /pathType: Prefixbackend:service:name: alertmanager-mainport:number: 9093
##################################################################### 启动ingress
kubectl apply -f prometheus-ingress.yaml# 一直监控节点有没有启动成功即可
kubectl get po -n monitoring## 卸载
kubectl delete --ignore-not-found=true -f manifests/ -f manifests/setup

注：如果需要删除命名空间monitioring，删除不掉，参考：记录一次namespace 处于Terminating状态的处理方法_mob604756ff20da的技术博客_51CTO博客



 

注：如果pod一直下载不下来，可能是因为污点的问题，我们将污点去掉

kubectl taint nodes kubernete140 node-role.kubernetes.io/master-

http://grafana.wolfcode.cn/

http://prometheus.wolfcode.cn/

http://alertmanager.wolfcode.cn/

三、ELK日志搜集

1.elk流程

2.配置elk

（1）配置es

# 先给主机器打一个标签
kubectl label node kubernete140 es=data
cd /opt/k8s/elk#创建命名空间
vim namespace.yaml
############################
apiVersion: v1 
kind: Namespace 
metadata: name: kube-logging
############################# 创建es配置文件
vim es.yaml##################################################################
--- 
apiVersion: v1 
kind: Service 
metadata: name: elasticsearch-logging namespace: kube-logging labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile kubernetes.io/name: "Elasticsearch" 
spec: ports: - port: 9200 protocol: TCP targetPort: db selector: k8s-app: elasticsearch-logging 
--- 
apiVersion: v1 
kind: ServiceAccount 
metadata: name: elasticsearch-logging namespace: kube-logging labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile 
--- 
kind: ClusterRole 
apiVersion: rbac.authorization.k8s.io/v1 
metadata: name: elasticsearch-logging labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile 
rules: 
- apiGroups: - "" resources: - "services" - "namespaces" - "endpoints" verbs: - "get" 
--- 
kind: ClusterRoleBinding 
apiVersion: rbac.authorization.k8s.io/v1 
metadata: namespace: kube-logging name: elasticsearch-logging labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile 
subjects: 
- kind: ServiceAccount name: elasticsearch-logging namespace: kube-logging apiGroup: "" 
roleRef: kind: ClusterRole name: elasticsearch-logging apiGroup: "" 
--- 
apiVersion: apps/v1 
kind: StatefulSet #使用statefulset创建Pod 
metadata: name: elasticsearch-logging #pod名称,使用statefulSet创建的Pod是有序号有顺序的 namespace: kube-logging  #命名空间 labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile srv: srv-elasticsearch 
spec: serviceName: elasticsearch-logging #与svc相关联，这可以确保使用以下DNS地址访问Statefulset中的每个pod (es-cluster-[0,1,2].elasticsearch.elk.svc.cluster.local) replicas: 1 #副本数量,单节点 selector: matchLabels: k8s-app: elasticsearch-logging #和pod template配置的labels相匹配 template: metadata: labels: k8s-app: elasticsearch-logging kubernetes.io/cluster-service: "true" spec: serviceAccountName: elasticsearch-logging containers: - image: docker.io/library/elasticsearch:7.9.3 name: elasticsearch-logging resources: limits: cpu: 1000m memory: 2Gi requests: cpu: 100m memory: 500Mi ports: - containerPort: 9200 name: db protocol: TCP - containerPort: 9300 name: transport protocol: TCP volumeMounts: - name: elasticsearch-logging mountPath: /usr/share/elasticsearch/data/   #挂载点 env: - name: "NAMESPACE" valueFrom: fieldRef: fieldPath: metadata.namespace - name: "discovery.type"  #定义单节点类型 value: "single-node" - name: ES_JAVA_OPTS #设置Java的内存参数，可以适当进行加大调整 value: "-Xms512m -Xmx2g"  volumes: - name: elasticsearch-logging hostPath: path: /data/es/ nodeSelector: #如果需要匹配落盘节点可以添加 nodeSelect es: data tolerations: - effect: NoSchedule operator: Exists initContainers: #容器初始化前的操作 - name: elasticsearch-logging-init image: alpine:3.6 command: ["/sbin/sysctl", "-w", "vm.max_map_count=262144"] #添加mmap计数限制，太低可能造成内存不足的错误 securityContext:  #仅应用到指定的容器上，并且不会影响Volume privileged: true #运行特权容器 - name: increase-fd-ulimit image: busybox imagePullPolicy: IfNotPresent command: ["sh", "-c", "ulimit -n 65536"] #修改文件描述符最大数量 securityContext: privileged: true - name: elasticsearch-volume-init #es数据落盘初始化，加上777权限 image: alpine:3.6 command: - chmod - -R - "777" - /usr/share/elasticsearch/data/ volumeMounts: - name: elasticsearch-logging mountPath: /usr/share/elasticsearch/data/################################################################### 启动
kubectl apply -f namespace.yaml
kubectl apply -f es.yaml 
kubectl get po -n kube-logging
kubectl get svc -n kube-logging

（2）配置logstash

vim logstash.yaml

--- 
apiVersion: v1 
kind: Service 
metadata: name: logstash namespace: kube-logging 
spec: ports: - port: 5044 targetPort: beats selector: type: logstash clusterIP: None 
--- 
apiVersion: apps/v1 
kind: Deployment 
metadata: name: logstash namespace: kube-logging 
spec: selector: matchLabels: type: logstash template: metadata: labels: type: logstash srv: srv-logstash spec: containers: - image: docker.io/kubeimages/logstash:7.9.3 #该镜像支持arm64和amd64两种架构 name: logstash ports: - containerPort: 5044 name: beats command: - logstash - '-f' - '/etc/logstash_c/logstash.conf' env: - name: "XPACK_MONITORING_ELASTICSEARCH_HOSTS" value: "http://elasticsearch-logging:9200" volumeMounts: - name: config-volume mountPath: /etc/logstash_c/ - name: config-yml-volume mountPath: /usr/share/logstash/config/ - name: timezone mountPath: /etc/localtime resources: #logstash一定要加上资源限制，避免对其他业务造成资源抢占影响 limits: cpu: 1000m memory: 2048Mi requests: cpu: 512m memory: 512Mi volumes: - name: config-volume configMap: name: logstash-conf items: - key: logstash.conf path: logstash.conf - name: timezone hostPath: path: /etc/localtime - name: config-yml-volume configMap: name: logstash-yml items: - key: logstash.yml path: logstash.yml --- 
apiVersion: v1 
kind: ConfigMap 
metadata: name: logstash-conf namespace: kube-logging labels: type: logstash 
data: logstash.conf: |- input {beats { port => 5044 } } filter {  # 处理 ingress 日志 if [kubernetes][container][name] == "nginx-ingress-controller" {json {source => "message" target => "ingress_log" }if [ingress_log][requesttime] { mutate { convert => ["[ingress_log][requesttime]", "float"] }}if [ingress_log][upstremtime] { mutate { convert => ["[ingress_log][upstremtime]", "float"] }} if [ingress_log][status] { mutate { convert => ["[ingress_log][status]", "float"] }}if  [ingress_log][httphost] and [ingress_log][uri] {mutate { add_field => {"[ingress_log][entry]" => "%{[ingress_log][httphost]}%{[ingress_log][uri]}"} } mutate { split => ["[ingress_log][entry]","/"] } if [ingress_log][entry][1] { mutate { add_field => {"[ingress_log][entrypoint]" => "%{[ingress_log][entry][0]}/%{[ingress_log][entry][1]}"} remove_field => "[ingress_log][entry]" }} else { mutate { add_field => {"[ingress_log][entrypoint]" => "%{[ingress_log][entry][0]}/"} remove_field => "[ingress_log][entry]" }}}}if [kubernetes][container][name] =~ /^srv*/ {  # 处理以srv进行开头的业务服务日志json { source => "message" target => "tmp" } if [kubernetes][namespace] == "kube-logging" { drop{} } if [tmp][level] { mutate{ add_field => {"[applog][level]" => "%{[tmp][level]}"} } if [applog][level] == "debug"{ drop{} } } if [tmp][msg] { mutate { add_field => {"[applog][msg]" => "%{[tmp][msg]}"} } } if [tmp][func] { mutate { add_field => {"[applog][func]" => "%{[tmp][func]}"} } } if [tmp][cost]{ if "ms" in [tmp][cost] { mutate { split => ["[tmp][cost]","m"] add_field => {"[applog][cost]" => "%{[tmp][cost][0]}"} convert => ["[applog][cost]", "float"] } } else { mutate { add_field => {"[applog][cost]" => "%{[tmp][cost]}"} }}}if [tmp][method] { mutate { add_field => {"[applog][method]" => "%{[tmp][method]}"} }}if [tmp][request_url] { mutate { add_field => {"[applog][request_url]" => "%{[tmp][request_url]}"} } }if [tmp][meta._id] { mutate { add_field => {"[applog][traceId]" => "%{[tmp][meta._id]}"} } } if [tmp][project] { mutate { add_field => {"[applog][project]" => "%{[tmp][project]}"} }}if [tmp][time] { mutate { add_field => {"[applog][time]" => "%{[tmp][time]}"} }}if [tmp][status] { mutate { add_field => {"[applog][status]" => "%{[tmp][status]}"} convert => ["[applog][status]", "float"] }}}mutate { rename => ["kubernetes", "k8s"] remove_field => "beat" remove_field => "tmp" remove_field => "[k8s][labels][app]" }}output { elasticsearch { hosts => ["http://elasticsearch-logging:9200"] codec => json index => "logstash-%{+YYYY.MM.dd}" #索引名称以logstash+日志进行每日新建 } } 
---apiVersion: v1 
kind: ConfigMap 
metadata: name: logstash-yml namespace: kube-logging labels: type: logstash 
data: logstash.yml: |- http.host: "0.0.0.0" xpack.monitoring.elasticsearch.hosts: http://elasticsearch-logging:9200

# 启动
kubectl apply -f logstash.yaml 
kubectl get po -n kube-logging

（3）配置filebeat，kibana

vim filebeat.yaml

--- 
apiVersion: v1 
kind: ConfigMap 
metadata: name: filebeat-config namespace: kube-logging labels: k8s-app: filebeat 
data: filebeat.yml: |- filebeat.inputs: - type: container enable: truepaths: - /var/log/containers/*.log #这里是filebeat采集挂载到pod中的日志目录 processors: - add_kubernetes_metadata: #添加k8s的字段用于后续的数据清洗 host: ${NODE_NAME}matchers: - logs_path: logs_path: "/var/log/containers/" output.logstash: #因为还需要部署logstash进行数据的清洗，因此filebeat是把数据推到logstash中 hosts: ["logstash:5044"] enabled: true 
--- 
apiVersion: v1 
kind: ServiceAccount 
metadata: name: filebeat namespace: kube-logging labels: k8s-app: filebeat
--- 
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole 
metadata: name: filebeat labels: k8s-app: filebeat 
rules: 
- apiGroups: [""] # "" indicates the core API group resources: - namespaces - pods verbs: ["get", "watch", "list"] 
--- 
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding 
metadata: name: filebeat 
subjects: 
- kind: ServiceAccount name: filebeat namespace: kube-logging 
roleRef: kind: ClusterRole name: filebeat apiGroup: rbac.authorization.k8s.io 
--- 
apiVersion: apps/v1 
kind: DaemonSet 
metadata: name: filebeat namespace: kube-logging labels: k8s-app: filebeat 
spec: selector: matchLabels: k8s-app: filebeat template: metadata: labels: k8s-app: filebeat spec: serviceAccountName: filebeat terminationGracePeriodSeconds: 30 containers: - name: filebeat image: docker.io/kubeimages/filebeat:7.9.3 #该镜像支持arm64和amd64两种架构 args: [ "-c", "/etc/filebeat.yml", "-e","-httpprof","0.0.0.0:6060" ] env: - name: NODE_NAME valueFrom: fieldRef: fieldPath: spec.nodeName - name: ELASTICSEARCH_HOST value: elasticsearch-logging - name: ELASTICSEARCH_PORT value: "9200" securityContext: runAsUser: 0 resources: limits: memory: 1000Mi cpu: 1000m requests: memory: 100Mi cpu: 100m volumeMounts: - name: config #挂载的是filebeat的配置文件 mountPath: /etc/filebeat.yml readOnly: true subPath: filebeat.yml - name: data #持久化filebeat数据到宿主机上 mountPath: /usr/share/filebeat/data - name: varlibdockercontainers #这里主要是把宿主机上的源日志目录挂载到filebeat容器中,如果没有修改docker或者containerd的runtime进行了标准的日志落盘路径，可以把mountPath改为/var/lib mountPath: /var/libreadOnly: true - name: varlog #这里主要是把宿主机上/var/log/pods和/var/log/containers的软链接挂载到filebeat容器中 mountPath: /var/log/ readOnly: true - name: timezone mountPath: /etc/localtime volumes: - name: config configMap: defaultMode: 0600 name: filebeat-config - name: varlibdockercontainers hostPath: #如果没有修改docker或者containerd的runtime进行了标准的日志落盘路径，可以把path改为/var/lib path: /var/lib- name: varlog hostPath: path: /var/log/ - name: inputs configMap: defaultMode: 0600 name: filebeat-inputs - name: data hostPath: path: /data/filebeat-data type: DirectoryOrCreate - name: timezone hostPath: path: /etc/localtime tolerations: #加入容忍能够调度到每一个节点 - effect: NoExecute key: dedicated operator: Equal value: gpu - effect: NoSchedule operator: Exists

vim kibana.yaml

---
apiVersion: v1
kind: ConfigMap
metadata:namespace: kube-loggingname: kibana-configlabels:k8s-app: kibana
data:kibana.yml: |-server.name: kibanaserver.host: "0"i18n.locale: zh-CN                      #设置默认语言为中文elasticsearch:hosts: ${ELASTICSEARCH_HOSTS}         #es集群连接地址，由于我这都都是k8s部署且在一个ns下，可以直接使用service name连接
--- 
apiVersion: v1 
kind: Service 
metadata: name: kibana namespace: kube-logging labels: k8s-app: kibana kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile kubernetes.io/name: "Kibana" srv: srv-kibana 
spec: type: NodePortports: - port: 5601 protocol: TCP targetPort: ui selector: k8s-app: kibana 
--- 
apiVersion: apps/v1 
kind: Deployment 
metadata: name: kibana namespace: kube-logging labels: k8s-app: kibana kubernetes.io/cluster-service: "true" addonmanager.kubernetes.io/mode: Reconcile srv: srv-kibana 
spec: replicas: 1 selector: matchLabels: k8s-app: kibana template: metadata: labels: k8s-app: kibana spec: containers: - name: kibana image: docker.io/kubeimages/kibana:7.9.3 #该镜像支持arm64和amd64两种架构 resources: limits: cpu: 1000m requests: cpu: 100m env: - name: ELASTICSEARCH_HOSTS value: http://elasticsearch-logging:9200 ports: - containerPort: 5601 name: ui protocol: TCP volumeMounts:- name: configmountPath: /usr/share/kibana/config/kibana.ymlreadOnly: truesubPath: kibana.ymlvolumes:- name: configconfigMap:name: kibana-config
--- 
apiVersion: networking.k8s.io/v1
kind: Ingress 
metadata: name: kibana namespace: kube-logging 
spec: ingressClassName: nginxrules: - host: kibana.wolfcode.cnhttp: paths: - path: / pathType: Prefixbackend: service:name: kibana port:number: 5601

# 启动
kubectl apply -f filebeat.yaml -f kibana.yaml 
kubectl get po -n kube-logging
kubectl get svc -n kube-logging# 在svc中可以看到端口，直接访问即可

3.kibana使用和日志检索

先找到Stack Management：

四、k8s可视化管理

国内比较多的有：Kubernetes Dashboard，kubesphere，Rancher，Kuboard。

1. Dashboard安装

# 下载recommended.yaml
cd /opt/k8s/dashboard
wget https://raw.githubusercontent.com/kubernetes/dashboard/v2.7.0/aio/deploy/recommended.yaml# 修改一下配置文件
#########################################
#第40行新增type: NodePort
########################################## 运行
kubectl apply -f recommended.yaml 
kubectl get po -n kubernetes-dashboard
kubectl get svc -n  kubernetes-dashboard#svc中会有端口，可以访问页面，得用https访问

注：你直接apply这个yaml很大概率下载不下来，因为用的是外国的镜像，我们替换镜像地址：

#194行的kubernetesui/dashboard:v2.7.0镜像地址变更为
image: registry.cn-hangzhou.aliyuncs.com/google_containers/dashboard:v2.7.0#280行的kubernetesui/metrics-scraper:v1.0.8镜像地址变更为
image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-scraper:v1.0.8

我们选择token方式。

获取token

# 配置所有权限的账号
cd /opt/k8s/dashboard
vim dashboard-admin.yaml#################################################
apiVersion: v1 
kind: ServiceAccount 
metadata: labels: k8s-app: kubernetes-dashboard name: dashboard-admin namespace: kubernetes-dashboard 
--- 
apiVersion: rbac.authorization.k8s.io/v1 
kind: ClusterRoleBinding 
metadata: name: dashboard-admin-cluster-role 
roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: cluster-admin 
subjects: - kind: ServiceAccountname: dashboard-adminnamespace: kubernetes-dashboard
################################################## 启动
kubectl apply -f dashboard-admin.yaml 
kubectl get sa -n kubernetes-dashboard
kubectl describe sa dashboard-admin -n  kubernetes-dashboard# 通过账户详情可以看到有一个属性叫Mountable secrets,这里的secret就是对应的值
kubectl describe secrets dashboard-admin-token-248cr -n  kubernetes-dashboard

我们将token复制进去，就可以登录了：

改成简体中文：

左侧可以查看，右上角加号可以添加：

2.kubeSphere安装

官网地址：面向云原生应用的容器混合云，支持 Kubernetes 多集群管理的 PaaS 容器云平台解决方案 | KubeSphere

# 先把dashboard删掉
cd /opt/k8s/
kubectl delete -f dashboard/# 一键安装
helm upgrade --install -n kubesphere-system --create-namespace ks-core https://charts.kubesphere.io/main/ks-core-1.1.2.tgz --debug --wait --set global.imageRegistry=swr.cn-southwest-2.myhuaweicloud.com/ks  --set extension.imageRegistry=swr.cn-southwest-2.myhuaweicloud.com/ks# 登录
http://192.168.200.140:30880/
账号：admin
密码：P@88w0rd

首次登录修改完密码后如下： 

 

五、感谢支持

感谢各位大佬支持，如果觉得满意可以请喝一杯咖啡吗：