dashboard服务

1.上传镜像，并导入，打标签

2.创建dashboard的deployment和service

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: 10.0.0.11:5000/kubernetes-dashboard-amd64:v1.4.1
        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://10.0.0.11:8080
        livenessProbe:
          httpGet:
            path: /
            port: 9090
          initialDelaySeconds: 30
          timeoutSeconds: 30

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

3.通过http://10.0.0.11:8080/ui进行访问

4.资源类型

daemon sets ： 每个容器创建一个，特别适合做监控使用该资源类型 (无状态)

pet sets： 有状态，适合数据库之类的

jobs： 一次性容器，适用于定时任务

[root@k8s-master deamonset]# cat k8s_deamon.yml
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
  name: nginx
spec:
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: 10.0.0.11:5000/nginx:1.13
        ports:
        - containerPort: 80
        resources:
          limits:
            cpu: 100m
          requests:
            cpu: 100m