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。
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}
- 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_name3、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
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
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
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：
代码语言：javascript复制sum by (pod_name)( rate(container_cpu_usage_seconds_total{image!="", pod_name!=""}[1m] ) )
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
修改hosts解析，访问测试
也可以直接访问nodeport端口
默认用户名和密码都是admin
配置数据源为prometheus
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
导入面板之后就可以看到对应的监控数据了。
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。
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。
