本文介绍在k8s集群中使用node-exporter、prometheus、grafana对集群进行监控。
其实现原理有点类似ELK、EFK组合。node-exporter组件负责收集节点上的metrics监控数据，并将数据推送给prometheus, prometheus负责存储这些数据，grafana将这些数据通过网页以图形的形式展现给用户。

在开始之前有必要了解下Prometheus是什么?
Prometheus （中文名：普罗米修斯）是由 SoundCloud 开发的开源监控报警系统和时序列数据库(TSDB).自2012年起,许多公司及组织已经采用 Prometheus,并且该项目有着非常活跃的开发者和用户社区.现在已经成为一个独立的开源项目。Prometheus 在2016加入 CNCF ( Cloud Native Computing Foundation ), 作为在 kubernetes 之后的第二个由基金会主持的项目。 Prometheus 的实现参考了Google内部的监控实现，与源自Google的Kubernetes结合起来非常合适。另外相比influxdb的方案，性能更加突出，而且还内置了报警功能。它针对大规模的集群环境设计了拉取式的数据采集方式，只需要在应用里面实现一个metrics接口，然后把这个接口告诉Prometheus就可以完成数据采集了，下图为prometheus的架构图。
Kubernetes集群监控方案_第1张图片
Prometheus的特点：
1、多维数据模型（时序列数据由metric名和一组key/value组成）
2、在多维度上灵活的查询语言(PromQl)
3、不依赖分布式存储，单主节点工作.
4、通过基于HTTP的pull方式采集时序数据
5、可以通过中间网关进行时序列数据推送(pushing)
6、目标服务器可以通过发现服务或者静态配置实现
7、多种可视化和仪表盘支持

prometheus 相关组件，Prometheus生态系统由多个组件组成，其中许多是可选的：
1、Prometheus 主服务,用来抓取和存储时序数据
2、client library 用来构造应用或 exporter 代码 (go,java,python,ruby)
3、push 网关可用来支持短连接任务
4、可视化的dashboard (两种选择,promdash 和 grafana.目前主流选择是 grafana.)
4、一些特殊需求的数据出口(用于HAProxy, StatsD, Graphite等服务)
5、实验性的报警管理端(alartmanager,单独进行报警汇总,分发,屏蔽等 )

promethues 的各个组件基本都是用 golang 编写,对编译和部署十分友好.并且没有特殊依赖.基本都是独立工作。
上述文字来自网络！

现在我们正式开始部署工作。
一、环境介绍
操作系统环境：centos linux 7.2 64bit
K8S软件版本： 1.9.0（采用kubeadm方式部署）
Master节点IP： 192.168.115.5/24
Node节点IP： 192.168.115.6/24

二、在k8s集群的所有节点上下载所需要的image

# docker pull prom/node-exporter
# docker pull prom/prometheus:v2.0.0
# docker pull grafana/grafana:4.2.0

三、采用daemonset方式部署node-exporter组件

# cat node-exporter.yaml 
---
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
  name: node-exporter
  namespace: kube-system
  labels:
    k8s-app: node-exporter
spec:
  template:
    metadata:
      labels:
        k8s-app: node-exporter
    spec:
      containers:
      - image: prom/node-exporter
        name: node-exporter
        ports:
        - containerPort: 9100
          protocol: TCP
          name: http
---
apiVersion: v1
kind: Service
metadata:
  labels:
    k8s-app: node-exporter
  name: node-exporter
  namespace: kube-system
spec:
  ports:
  - name: http
    port: 9100
    nodePort: 31672
    protocol: TCP
  type: NodePort
  selector:
    k8s-app: node-exporter

通过上述文件创建pod和service

# kubectl create -f  node-exporter.yaml

四、部署prometheus组件
1、rbac文件

# cat rbac-setup.yaml 
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: prometheus
rules:
- apiGroups: [""]
  resources:
  - nodes
  - nodes/proxy
  - services
  - endpoints
  - pods
  verbs: ["get", "list", "watch"]
- apiGroups:
  - extensions
  resources:
  - ingresses
  verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics"]
  verbs: ["get"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: prometheus
  namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: prometheus
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: prometheus
subjects:
- kind: ServiceAccount
  name: prometheus
  namespace: kube-system

2、以configmap的形式管理prometheus组件的配置文件

# cat configmap.yaml 
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-config
  namespace: kube-system
data:
  prometheus.yml: |
    global:
      scrape_interval:     15s
      evaluation_interval: 15s
    scrape_configs:

    - job_name: 'kubernetes-apiservers'
      kubernetes_sd_configs:
      - role: endpoints
      scheme: https
      tls_config:
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      relabel_configs:
      - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
        action: keep
        regex: default;kubernetes;https

    - job_name: 'kubernetes-nodes'
      kubernetes_sd_configs:
      - role: node
      scheme: https
      tls_config:
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      relabel_configs:
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
      - target_label: __address__
        replacement: kubernetes.default.svc:443
      - source_labels: [__meta_kubernetes_node_name]
        regex: (.+)
        target_label: __metrics_path__
        replacement: /api/v1/nodes/${1}/proxy/metrics

    - job_name: 'kubernetes-cadvisor'
      kubernetes_sd_configs:
      - role: node
      scheme: https
      tls_config:
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      relabel_configs:
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
      - target_label: __address__
        replacement: kubernetes.default.svc:443
      - source_labels: [__meta_kubernetes_node_name]
        regex: (.+)
        target_label: __metrics_path__
        replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor

    - job_name: 'kubernetes-service-endpoints'
      kubernetes_sd_configs:
      - role: endpoints
      relabel_configs:
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
        action: replace
        target_label: __scheme__
        regex: (https?)
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
      - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
        action: replace
        target_label: __address__
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
      - action: labelmap
        regex: __meta_kubernetes_service_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        action: replace
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_service_name]
        action: replace
        target_label: kubernetes_name

    - job_name: 'kubernetes-services'
      kubernetes_sd_configs:
      - role: service
      metrics_path: /probe
      params:
        module: [http_2xx]
      relabel_configs:
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_probe]
        action: keep
        regex: true
      - source_labels: [__address__]
        target_label: __param_target
      - target_label: __address__
        replacement: blackbox-exporter.example.com:9115
      - source_labels: [__param_target]
        target_label: instance
      - action: labelmap
        regex: __meta_kubernetes_service_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_service_name]
        target_label: kubernetes_name

    - job_name: 'kubernetes-ingresses'
      kubernetes_sd_configs:
      - role: ingress
      relabel_configs:
      - source_labels: [__meta_kubernetes_ingress_annotation_prometheus_io_probe]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_ingress_scheme,__address__,__meta_kubernetes_ingress_path]
        regex: (.+);(.+);(.+)
        replacement: ${1}://${2}${3}
        target_label: __param_target
      - target_label: __address__
        replacement: blackbox-exporter.example.com:9115
      - source_labels: [__param_target]
        target_label: instance
      - action: labelmap
        regex: __meta_kubernetes_ingress_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_ingress_name]
        target_label: kubernetes_name

    - job_name: 'kubernetes-pods'
      kubernetes_sd_configs:
      - role: pod
      relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
      - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
        action: replace
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
        target_label: __address__
      - action: labelmap
        regex: __meta_kubernetes_pod_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        action: replace
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_pod_name]
        action: replace
        target_label: kubernetes_pod_name

3、Prometheus deployment 文件

# cat prometheus.deploy.yml 
---
apiVersion: apps/v1beta2
kind: Deployment
metadata:
  labels:
    name: prometheus-deployment
  name: prometheus
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus
  template:
    metadata:
      labels:
        app: prometheus
    spec:
      containers:
      - image: prom/prometheus:v2.0.0
        name: prometheus
        command:
        - "/bin/prometheus"
        args:
        - "--config.file=/etc/prometheus/prometheus.yml"
        - "--storage.tsdb.path=/prometheus"
        - "--storage.tsdb.retention=24h"
        ports:
        - containerPort: 9090
          protocol: TCP
        volumeMounts:
        - mountPath: "/prometheus"
          name: data
        - mountPath: "/etc/prometheus"
          name: config-volume
        resources:
          requests:
            cpu: 100m
            memory: 100Mi
          limits:
            cpu: 500m
            memory: 2500Mi
      serviceAccountName: prometheus    
      volumes:
      - name: data
        emptyDir: {}
      - name: config-volume
        configMap:
          name: prometheus-config

4、Prometheus service文件

# cat prometheus.svc.yml 
---
kind: Service
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus
  namespace: kube-system
spec:
  type: NodePort
  ports:
  - port: 9090
    targetPort: 9090
    nodePort: 30003
  selector:
    app: prometheus

5、通过上述yaml文件创建相应的对象

# kubectl create -f  rbac-setup.yaml
# kubectl create -f  configmap.yaml 
# kubectl create -f  prometheus.deploy.yml 
# kubectl create -f  prometheus.svc.yml

Kubernetes集群监控方案_第2张图片
Kubernetes集群监控方案_第3张图片
Node-exporter对应的nodeport端口为31672，通过访问http://192.168.115.5:31672/metrics 可以看到对应的metrics
Kubernetes集群监控方案_第4张图片
prometheus对应的nodeport端口为30003，通过访问http://192.168.115.5:30003/target 可以看到prometheus已经成功连接上了k8s的apiserver
Kubernetes集群监控方案_第5张图片
可以在prometheus的WEB界面上提供了基本的查询K8S集群中每个POD的CPU使用情况，查询条件如下：

sum by (pod_name)( rate(container_cpu_usage_seconds_total{image!="", pod_name!=""}[1m] ) )

Kubernetes集群监控方案_第6张图片
上述的查询有出现数据，说明node-exporter往prometheus中写入数据正常，接下来我们就可以部署grafana组件，实现更友好的webui展示数据了。

五、部署grafana组件
1、grafana deployment配置文件

# cat grafana-deploy.yaml 
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: grafana-core
  namespace: kube-system
  labels:
    app: grafana
    component: core
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: grafana
        component: core
    spec:
      containers:
      - image: grafana/grafana:4.2.0
        name: grafana-core
        imagePullPolicy: IfNotPresent
        # env:
        resources:
          # keep request = limit to keep this container in guaranteed class
          limits:
            cpu: 100m
            memory: 100Mi
          requests:
            cpu: 100m
            memory: 100Mi
        env:
          # The following env variables set up basic auth twith the default admin user and admin password.
          - name: GF_AUTH_BASIC_ENABLED
            value: "true"
          - name: GF_AUTH_ANONYMOUS_ENABLED
            value: "false"
          # - name: GF_AUTH_ANONYMOUS_ORG_ROLE
          #   value: Admin
          # does not really work, because of template variables in exported dashboards:
          # - name: GF_DASHBOARDS_JSON_ENABLED
          #   value: "true"
        readinessProbe:
          httpGet:
            path: /login
            port: 3000
          # initialDelaySeconds: 30
          # timeoutSeconds: 1
        volumeMounts:
        - name: grafana-persistent-storage
          mountPath: /var
      volumes:
      - name: grafana-persistent-storage
        emptyDir: {}

2、grafana service配置文件

# cat grafana-svc.yaml 
apiVersion: v1
kind: Service
metadata:
  name: grafana
  namespace: kube-system
  labels:
    app: grafana
    component: core
spec:
  type: NodePort
  ports:
    - port: 3000
  selector:
    app: grafana
component: core

3、grafana ingress配置文件

# cat grafana-ing.yaml 
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
   name: grafana
   namespace: kube-system
spec:
   rules:
   - host: k8s.grafana
     http:
       paths:
       - path: /
         backend:
          serviceName: grafana
          servicePort: 3000

通过访问traefik的webui可以看到k8s.grafana服务发布成功
Kubernetes集群监控方案_第7张图片
修改hosts解析，访问测试
Kubernetes集群监控方案_第8张图片
Kubernetes集群监控方案_第9张图片
也可以直接访问nodeport端口
Kubernetes集群监控方案_第10张图片
默认用户名和密码都是admin
Kubernetes集群监控方案_第11张图片
配置数据源为prometheus
Kubernetes集群监控方案_第12张图片
导入面板，可以直接输入模板编号315在线导入，或者下载好对应的json模板文件本地导入，面板模板下载地址https://grafana.com/dashboards/315
Kubernetes集群监控方案_第13张图片
导入面板之后就可以看到对应的监控数据了。
Kubernetes集群监控方案_第14张图片
Kubernetes集群监控方案_第15张图片
Kubernetes集群监控方案_第16张图片
这里要说明一下，在测试过程中，导入编号为162的模板，发现只有部分数据，且pod的名称显示不友好。模板地址https://grafana.com/dashboards/162，详见下图。
Kubernetes集群监控方案_第17张图片
六、后记
这里存在一些问题后续要继续研究解决。
1、prometheus的数据存储采用emptydir。如果Pod被删除，或者Pod发生迁移，emptyDir也会被删除，并且永久丢失。后续可以在K8S集群外部再配置一个Prometheus系统来永久保存监控数据， 两个prometheus系统之间通过配置job自动进行数据拉取。
2、Grafana的配置数据存储采用emptydir。如果Pod被删除，或者Pod发生迁移，emptyDir也会被删除，并且永久丢失。我们也可以选择将grafana配置在k8s外部，数据源选择K8S集群外部的prometheus即可。
3、关于监控项的报警（alertmanager）尚未配置。

参考文档，感谢作者分享！
https://www.kubernetes.org.cn/3418.html
https://blog.qikqiak.com/post/kubernetes-monitor-prometheus-grafana/
https://github.com/giantswarm/kubernetes-prometheus/tree/master/manifests
https://segmentfault.com/a/1190000013245394