Kubernetes集群监控方案

半世苍凉 提交于 2019-11-25 20:20:48

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}${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 



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:
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。

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

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