dashboard的特点主要如下:
1、能够直观的看到rc、deployment、pod、services等k8s组件的运行情况和日志信息。
2、结合heapster和influxdb后,dashboard的监控图表上可以看到pod的cpu和内存消耗情况。
部署dashboard需要两个费劲的镜像 注:正常来讲只需要配置好yaml文件,不需要事先下载好镜像到节点当中,也就是如果yaml配置文件内所使用的镜像在node中不存在就会自动从docker源下载,但是我们现在使用的镜像是没有国内源的,所以先下载下来导入到每个node内。
准备镜像:国外下载,国内导入
核心操作:从海外的服务器上pull下来对应的镜像,之后通过docker save保存成tar包,将tar包传回国内,在每个node上执行docker load将镜像导入(在master上也要倒入)。
镜像1:
在dashboard.yaml中定义了dashboard所用的镜像:
daocloud.io/daocloud/google_containers_kubernetes-dashboard-amd64:v1.6.1
也可以选择其他的版本
注:这个镜像每个节点都下载
# docker pull daocloud.io/daocloud/google_containers_kubernetes-dashboard-amd64:v1.6.1
镜像2:
启动k8s的pod还需要一个额外的镜像:
registry.access.redhat.com/rhel7/pod-infrastructure:latest
(node中,/etc/kubernetes/kubelet的配置),由于一些众所周知的原因,这个镜像在国内是下载不下来的
美国服务器:
# yum install docker -y
# systemctl start docker
# docker search pod-infrastructure //从找到的结果中下载了一个其他版本的镜像,原装的不能下载
# docker pull docker.io/tianyebj/pod-infrastructure
# docker save -o podinfrastructure.tar docker.io/tianyebj/pod-infrastructure
本地机器node1:
# scp 美国服务器IP:/podinfrastructure.tar /
  下载下来之后拷贝给所有node节点,然后导入:
# docker load < podinfrastructure.tar
查看导入之后的镜像
# docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
daocloud.io/daocloud/google_containers_kubernetes-dashboard-amd64 v1.6.1 71dfe833ce74 10 months ago 134 MB
docker.io/tianyebj/pod-infrastructure latest 34d3450d733b 14 months ago 205 MB
修改配置文件(每个节点都修改):
# vim /etc/kubernetes/kubelet //修改下行内的镜像名称image=之后的内容
KUBELET_POD_INFRA_CONTAINER="--pod-infra-container-image=docker.io/tianyebj/pod-infrastructure:latest"
重启服务(每个节点都重启):
# systemctl restart kubelet
master上编辑dashboard.yaml:
任何目录下都可以,注意或更改以下带**部分
[root@k8s-master /]# vim dashboard.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
# Keep the name in sync with image version and
# gce/coreos/kube-manifests/addons/dashboard counterparts
name: kubernetes-dashboard-latest
namespace: kube-system
spec:
replicas: 1
template:
metadata:
labels:
k8s-app: kubernetes-dashboard
version: latest
kubernetes.io/cluster-service: "true"
spec:
containers:
- name: kubernetes-dashboard
**image: daocloud.io/daocloud/google_containers_kubernetes-dashboard-amd64:v1.6.1
resources:
# keep request = limit to keep this container in guaranteed class
limits:
cpu: 100m
memory: 50Mi
requests:
cpu: 100m
memory: 50Mi
ports:
- containerPort: 9090
args:
**- --apiserver-host=http://192.168.245.250:8080 #注意这里因没部署DNS服务,现在必须写IP
livenessProbe:
httpGet:
path: /
port: 9090
initialDelaySeconds: 30
timeoutSeconds: 30
master上编辑dashboardsvc.yaml文件
任何目录下都可以:
[root@k8s-master /]# vim dashboardsvc.yaml
apiVersion: v1
kind: Service
metadata:
name: kubernetes-dashboard
namespace: kube-system
labels:
k8s-app: kubernetes-dashboard
kubernetes.io/cluster-service: "true"
spec:
selector:
k8s-app: kubernetes-dashboard
ports:
- port: 80
targetPort: 9090
启动
在master执行如下命令:
# kubectl create -f dashboard.yaml
# kubectl create -f dashboardsvc.yaml  
dashboard搭建完成。
验证
命令验证,master上执行如下命令:
[root@k8s-master /]# kubectl get deployment --all-namespaces
NAMESPACE NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
kube-system kubernetes-dashboard-latest 1 1 1 1 19s
[root@k8s-master /]# kubectl get svc --all-namespaces
NAMESPACE NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE
default kubernetes 10.254.0.1 <none> 443/TCP 4d
kube-system kubernetes-dashboard 10.254.231.52 <none> 80/TCP 32s
[root@k8s-master /]# kubectl get pod -o wide --all-namespaces
NAMESPACE NAME READY STATUS RESTARTS AGE IP NODE
kube-system kubernetes-dashboard-latest-1231782504-t79t7 1/1 Running 0 1m 10.0.27.2 k8s-node-2
界面验证,浏览器访问:http://192.168.245.250:8080/ui
销毁应用(注意不想用的时候才销毁)
在master上执行:
# kubectl delete deployment kubernetes-dashboard-latest --namespace=kube-system
# kubectl delete svc kubernetes-dashboard --namespace=kube-system
补充
浏览器访问dashboard页面报错如下:
Error: 'dial tcp 172.17.34.2:9090: getsockopt: connection refused'
Trying to reach: 'http://172.17.34.2:9090/'
1.所有节点执行下面命令重置flannel网络
[root@k8s-node1 ~]# systemctl daemon-reload
[root@k8s-node1 ~]# systemctl restart flanneld
2.master上重新创建dashboard应用
[root@k8s-master yaml]# kubectl delete deployment kubernetes-dashboard-latest --namespace=kube-system
deployment "kubernetes-dashboard-latest" deleted
[root@k8s-master yaml]# kubectl delete svc kubernetes-dashboard --namespace=kube-system
service "kubernetes-dashboard" deleted
[root@k8s-master yaml]# kubectl create -f dashboard.yaml
deployment "kubernetes-dashboard-latest" created
[root@k8s-master yaml]# kubectl create -f dashboardsvc.yaml
service "kubernetes-dashboard" created
[root@k8s-master yaml]# kubectl get deployment --all-namespaces
NAMESPACE NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
default mynginx 2 2 2 2 26d
kube-system kubernetes-dashboard-latest 1 1 1 1 12s