k8s原生的集群监控方案(Heapster+InfluxDB+Grafana)

  1. Heapster+InfluxDB+Grafana简介 heapster是一个监控计算、存储、网络等集群资源的工具,以k8s内置的cAdvisor作为数据源收集集群信息,并汇总出有价值的性能数据(Metrics):cpu、内存、network、filesystem等,然后将这些数据输出到外部存储(backend),如InfluxDB,最后再通过相应的UI界面进行可视化展示,如grafana。 另外heapster的数据源和外部存储都是可插拔的,所以可以很灵活的组建出很多监控方案,如:Heapster+ElasticSearch+Kibana等等。
  2. Heapster的整体架构图
  3. 创建InfluxDB资源对象
#下载influxdb.yaml
apiVersion: extensions/v1beta1
	kind: Deployment
	metadata:
		name: monitoring-influxdb
		namespace: kube-system
	spec:
		replicas: 1
		template:
			metadata:
				labels:
					task: monitoring
					k8s-app: influxdb
			spec:
				containers:
				- name: influxdb
					image: k8s.gcr.io/heapster-influxdb-amd64:v1.3.3
					volumeMounts:
					- mountPath: /data
						name: influxdb-storage
				volumes:
				- name: influxdb-storage
					emptyDir: {}
	---
	apiVersion: v1
	kind: Service
	metadata:
		labels:
			task: monitoring
			#For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
			#If you are NOT using this as an addon, you should comment out this line.
    kubernetes.io/cluster-service: 'true'
    kubernetes.io/name: monitoring-influxdb
		name: monitoring-influxdb
		namespace: kube-system
	spec:
		type: NodePort
		ports:
		- nodePort: 31001
			port: 8086
			targetPort: 8086
		selector:
			k8s-app: influxdb

所需的Heapster+InfluxDB+Grafana配置文件,请在Kubernetes Dashboard1.8.3部署中的yaml链接中下载使用。

#influxdb.yaml文件需更改的地方:
(1) image: k8s.gcr.io/heapster-influxdb-amd64:v1.3.3 (换成自己的images)
##说明:这里我在前文中提供的有images下载链接,直接下载使用不用更改!
(2)这里我们使用NotePort暴露monitoring-influxdb服务在主机的31001端口上,那么InfluxDB服务端的地址:http://[host-ip]:31001 ,记下这个地址,以便创建heapster和为grafana配置数据源时,可以直接使用。
spec:
		type: NodePort
		ports:
			- nodePort: 31001
				port: 8086
				targetPort: 8086
			selector:
				k8s-app: influxdb
  1. 创建Grafana资源对象
#下载grafana.yaml
apiVersion: extensions/v1beta1
	kind: Deployment
	metadata:
		name: monitoring-grafana
		namespace: kube-system
	spec:
		replicas: 1
		template:
			metadata:
				labels:
					task: monitoring
					k8s-app: grafana
			spec:
				containers:
				- name: grafana
					image: k8s.gcr.io/heapster-grafana-amd64:v4.4.3
					ports:
					- containerPort: 3000
						protocol: TCP
					volumeMounts:
					- mountPath: /etc/ssl/certs
						name: ca-certificates
						readOnly: true
					- mountPath: /var
						name: grafana-storage
					env:
					- name: INFLUXDB_HOST
						value: monitoring-influxdb
					- name: GF_SERVER_HTTP_PORT
						value: "3000"
						#The following env variables are required to make Grafana accessible via
						#the kubernetes api-server proxy. On production clusters, we recommend
						#removing these env variables, setup auth for grafana, and expose the grafana
						#service using a LoadBalancer or a public IP.
					- name: GF_AUTH_BASIC_ENABLED
						value: "false"
					- name: GF_AUTH_ANONYMOUS_ENABLED
						value: "true"
					- name: GF_AUTH_ANONYMOUS_ORG_ROLE
						value: Admin
					- name: GF_SERVER_ROOT_URL
						#If you're only using the API Server proxy, set this value instead:
						#value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
						value: /
				volumes:
				- name: ca-certificates
					hostPath:
						path: /etc/ssl/certs
				- name: grafana-storage
					emptyDir: {}
	---
	apiVersion: v1
	kind: Service
	metadata:
		labels:
			#For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
			#If you are NOT using this as an addon, you should comment out this line.
			kubernetes.io/cluster-service: 'true'
			kubernetes.io/name: monitoring-grafana
		name: monitoring-grafana
		namespace: kube-system
	spec:
		#In a production setup, we recommend accessing Grafana through an external Loadbalancer
		#or through a public IP.
		#type: LoadBalancer
		#You could also use NodePort to expose the service at a randomly-generated port
		#type: NodePort
		type: NodePort
		ports:
		- nodePort: 30108
			port: 80
			targetPort: 3000
		selector:
			k8s-app: grafana
##说明

虽然Heapster已经预先配置好了Grafana的Datasource和Dashboard,但是为了方便访问,这里我们使用NotePort暴露monitoring-grafana服务在主机的30108上,那么Grafana服务端的地址:http://192.168.245.16:30108 ,通过浏览器访问,为Grafana修改数据源,如下: 标红的地方,为上一步记录下的InfluxDB服务端的地址。

  1. 创建Heapster资源对象
#下载heapster-rbac.yaml  
```

kind: ClusterRoleBinding apiVersion: rbac.authorization.k8s.io/v1beta1 metadata: name: heapster roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: system:heapster subjects: - kind: ServiceAccount name: heapster namespace: kube-system

#下载heapster.yaml

apiVersion: v1
kind: ServiceAccount
metadata:
	name: heapster
	namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
	name: heapster
	namespace: kube-system
spec:
	replicas: 1
	template:
		metadata:
			labels:
				task: monitoring
				k8s-app: heapster
		spec:
			serviceAccountName: heapster
			containers:
			- name: heapster
				image: k8s.gcr.io/heapster-amd64:v1.5.3
				imagePullPolicy: IfNotPresent
				command:
				- /heapster
				- --source=kubernetes:https://kubernetes.default
			#- --sink=influxdb:http://monitoring-influxdb.kube-system.svc:8086
				- --sink=influxdb:http://192.168.246.167:31001 #influxdb服务端地址
---
apiVersion: v1
kind: Service
metadata:
	labels:
		task: monitoring
		#For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
		#If you are NOT using this as an addon, you should comment out this line.
		kubernetes.io/cluster-service: 'true'
		kubernetes.io/name: Heapster
	name: heapster
	namespace: kube-system
spec:
	ports:
	- port: 80
		targetPort: 8082
	selector:
		k8s-app: heapster

##说明

(1)
--source 为heapster指定获取集群信息的数据源。参考:https://github.com/kubernetes/heapster/blob/master/docs/source-configuration.md
--sink 为heaster指定后端存储,这里我们使用InfluxDB,其他的,请参考:https://github.com/kubernetes/heapster/blob/master/docs/sink-owners.md
(2)heapster-rbac.yaml  文件作用
如没有heapster-rbac.yaml  将导致权限的问题,heaster默认使用一个令×××(Token)与ApiServer进行认证,通过查看heapster.yml发现 serviceAccountName: heapster ,现在明白了吧,就是heaster没有权限,那么如何授权呢-----给heaster绑定一个有权限的角色就行了,即heapster-rbac.yaml配置的那样!
1. 通过dashboard查看集群概况
![](http://i2.51cto.com/images/blog/201805/27/73485c29e42a4f79ac7ef0b0be6190a4.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_30,g_se,x_10,y_10,shadow_20,type_ZmFuZ3poZW5naGVpdGk=)
![](http://i2.51cto.com/images/blog/201805/27/615471a67d07d5f392f23bc046f9a23a.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_30,g_se,x_10,y_10,shadow_20,type_ZmFuZ3poZW5naGVpdGk=)
1. 通过Grafana查看集群详情(cpu、memory、filesystem、network)
![](http://i2.51cto.com/images/blog/201805/27/cf665a65a1a335ff687731b6a79cc8f4.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_30,g_se,x_10,y_10,shadow_20,type_ZmFuZ3poZW5naGVpdGk=)![](http://i2.51cto.com/images/blog/201805/27/69664be92f6ca6e119e52e195ea3fe7f.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_30,g_se,x_10,y_10,shadow_20,type_ZmFuZ3poZW5naGVpdGk=)

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