kubernetes生态--交付prometheus监控及grafana炫酷dashboard到k8s集群

由于docker容器的特殊性，传统的zabbix无法对k8s集群内的docker状态进行监控，所以需要使用prometheus来进行监控：

什么是Prometheus?

Prometheus是由SoundCloud开发的开源监控报警系统和时序列数据库(TSDB)。Prometheus使用Go语言开发，是Google BorgMon监控系统的开源版本。
2016年由Google发起Linux基金会旗下的原生云基金会(Cloud Native Computing Foundation), 将Prometheus纳入其下第二大开源项目。
Prometheus目前在开源社区相当活跃。
Prometheus和Heapster(Heapster是K8S的一个子项目，用于获取集群的性能数据。)相比功能更完善、更全面。Prometheus性能也足够支撑上万台规模的集群。

Prometheus的特点

• 多维度数据模型。
• 灵活的查询语言。
• 不依赖分布式存储，单个服务器节点是自主的。
• 通过基于HTTP的pull方式采集时序数据。
• 可以通过中间网关进行时序列数据推送。
• 通过服务发现或者静态配置来发现目标服务对象。
• 支持多种多样的图表和界面展示，比如Grafana等。

基本原理

Prometheus的基本原理是通过HTTP协议周期性抓取被监控组件的状态，任意组件只要提供对应的HTTP接口就可以接入监控。不需要任何SDK或者其他的集成过程。这样做非常适合做虚拟化环境监控系统，比如VM、Docker、Kubernetes等。输出被监控组件信息的HTTP接口被叫做exporter 。目前互联网公司常用的组件大部分都有exporter可以直接使用，比如Varnish、Haproxy、Nginx、MySQL、Linux系统信息(包括磁盘、内存、CPU、网络等等)。

服务过程

• Prometheus Daemon负责定时去目标上抓取metrics(指标)数据，每个抓取目标需要暴露一个http服务的接口给它定时抓取。Prometheus支持通过配置文件、文本文件、Zookeeper、Consul、DNS SRV Lookup等方式指定抓取目标。Prometheus采用PULL的方式进行监控，即服务器可以直接通过目标PULL数据或者间接地通过中间网关来Push数据。
• Prometheus在本地存储抓取的所有数据，并通过一定规则进行清理和整理数据，并把得到的结果存储到新的时间序列中。
• Prometheus通过PromQL和其他API可视化地展示收集的数据。Prometheus支持很多方式的图表可视化，例如Grafana、自带的Promdash以及自身提供的模版引擎等等。Prometheus还提供HTTP API的查询方式，自定义所需要的输出。
• PushGateway支持Client主动推送metrics到PushGateway，而Prometheus只是定时去Gateway上抓取数据。
• Alertmanager是独立于Prometheus的一个组件，可以支持Prometheus的查询语句，提供十分灵活的报警方式。

三大套件

• Server 主要负责数据采集和存储，提供PromQL查询语言的支持。
• Alertmanager 警告管理器，用来进行报警。
• Push Gateway 支持临时性Job主动推送指标的中间网关。

prometheus不同于zabbix，没有agent，使用的是针对不同服务的exporter：

prometheus官网：官网地址

正常情况下，监控k8s集群及node，pod，常用的exporter有四个：

• kube-state-metrics -- 收集k8s集群master&etcd等基本状态信息
• node-exporter -- 收集k8s集群node信息
• cadvisor -- 收集k8s集群docker容器内部使用资源信息
• blackbox-exporte -- 收集k8s集群docker容器服务是否存活

接下来逐一创建以上exporter：

老套路，下载docker镜像，准备资源配置清单，应用资源配置清单：

一、kube-state-metrics

# docker pull quay.io/coreos/kube-state-metrics:v1.5.0

# docker tag 91599517197a harbor.od.com/public/kube-state-metrics:v1.5.0
# docker push harbor.od.com/public/kube-state-metrics:v1.5.0

准备资源配置清单：

1、rbac.yaml

# mkdir /data/k8s-yaml/kube-state-metrics && cd /data/k8s-yaml/kube-state-metrics

apiVersion: v1
kind: ServiceAccount
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: kube-state-metrics
  namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: kube-state-metrics
rules:
- apiGroups:
  - ""
  resources:
  - configmaps
  - secrets
  - nodes
  - pods
  - services
  - resourcequotas
  - replicationcontrollers
  - limitranges
  - persistentvolumeclaims
  - persistentvolumes
  - namespaces
  - endpoints
  verbs:
  - list
  - watch
- apiGroups:
  - policy
  resources:
  - poddisruptionbudgets
  verbs:
  - list
  - watch
- apiGroups:
  - extensions
  resources:
  - daemonsets
  - deployments
  - replicasets
  verbs:
  - list
  - watch
- apiGroups:
  - apps
  resources:
  - statefulsets
  verbs:
  - list
  - watch
- apiGroups:
  - batch
  resources:
  - cronjobs
  - jobs
  verbs:
  - list
  - watch
- apiGroups:
  - autoscaling
  resources:
  - horizontalpodautoscalers
  verbs:
  - list
  - watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: kube-state-metrics
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: kube-state-metrics
subjects:
- kind: ServiceAccount
  name: kube-state-metrics
  namespace: kube-system

2、dp.yaml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  annotations:
    deployment.kubernetes.io/revision: "2"
  labels:
    grafanak8sapp: "true"
    app: kube-state-metrics
  name: kube-state-metrics
  namespace: kube-system
spec:
  selector:
    matchLabels:
      grafanak8sapp: "true"
      app: kube-state-metrics
  strategy:
    rollingUpdate:
      maxSurge: 25%
      maxUnavailable: 25%
    type: RollingUpdate
  template:
    metadata:
      labels:
        grafanak8sapp: "true"
        app: kube-state-metrics
    spec:
      containers:
      - name: kube-state-metrics
        image: harbor.od.com/public/kube-state-metrics:v1.5.0
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 8080
          name: http-metrics
          protocol: TCP
        readinessProbe:
          failureThreshold: 3
          httpGet:
            path: /healthz
            port: 8080
            scheme: HTTP
          initialDelaySeconds: 5
          periodSeconds: 10
          successThreshold: 1
          timeoutSeconds: 5
      serviceAccountName: kube-state-metrics

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/kube-state-metrics/rbac.yaml
# kubectl apply -f http://k8s-yaml.od.com/kube-state-metrics/dp.yaml

测试一下：

# kubectl get pod -n kube-system -o wide

# curl http://172.7.22.10:8080/healthz

 已经成功运行。

二、node-exporter

由于node-exporter是监控node的，所有需要每个节点启动一个，所以使用ds控制器

# docker pull prom/node-exporter:v0.15.0

# docker tag 12d51ffa2b22 harbor.od.com/public/node-exporter:v0.15.0
# docker push harbor.od.com/public/node-exporter:v0.15.0

准备资源配置清单：

1、ds.yaml

# mkdir node-exporter && cd node-exporter

kind: DaemonSet
apiVersion: extensions/v1beta1
metadata:
  name: node-exporter
  namespace: kube-system
  labels:
    daemon: "node-exporter"
    grafanak8sapp: "true"
spec:
  selector:
    matchLabels:
      daemon: "node-exporter"
      grafanak8sapp: "true"
  template:
    metadata:
      name: node-exporter
      labels:
        daemon: "node-exporter"
        grafanak8sapp: "true"
    spec:
      volumes:
      - name: proc
        hostPath: 
          path: /proc
          type: ""
      - name: sys
        hostPath:
          path: /sys
          type: ""
      containers:
      - name: node-exporter
        image: harbor.od.com/public/node-exporter:v0.15.0
        imagePullPolicy: IfNotPresent
        args:
        - --path.procfs=/host_proc
        - --path.sysfs=/host_sys
        ports:
        - name: node-exporter
          hostPort: 9100
          containerPort: 9100
          protocol: TCP
        volumeMounts:
        - name: sys
          readOnly: true
          mountPath: /host_sys
        - name: proc
          readOnly: true
          mountPath: /host_proc
      hostNetwork: true

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/node-exporter/ds.yaml

# kubectl get pod -n kube-system -o wide

我们有两个node，每个node节点启动一个：

 三、cadvisor

# docker pull google/cadvisor:v0.28.3

# docker tag 75f88e3ec333 harbor.od.com/public/cadvisor:0.28.3

# docker push harbor.od.com/public/cadvisor:0.28.3

准备资源配置清单：

# mkdir cadvisor && cd cadvisor

1、ds.yaml  标红部分是k8s资源配置清单中一个重要的高级属性，下一篇博客着重介绍

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: cadvisor
  namespace: kube-system
  labels:
    app: cadvisor
spec:
  selector:
    matchLabels:
      name: cadvisor
  template:
    metadata:
      labels:
        name: cadvisor
    spec:
      hostNetwork: true
      tolerations:
      - key: node-role.kubernetes.io/master
        effect: NoSchedule
      containers:
      - name: cadvisor
        image: harbor.od.com/public/cadvisor:v0.28.3
        imagePullPolicy: IfNotPresent
        volumeMounts:
        - name: rootfs
          mountPath: /rootfs
          readOnly: true
        - name: var-run
          mountPath: /var/run
        - name: sys
          mountPath: /sys
          readOnly: true
        - name: docker
          mountPath: /var/lib/docker
          readOnly: true
        ports:
          - name: http
            containerPort: 4194
            protocol: TCP
        readinessProbe:
          tcpSocket:
            port: 4194
          initialDelaySeconds: 5
          periodSeconds: 10
        args:
          - --housekeeping_interval=10s
          - --port=4194
      terminationGracePeriodSeconds: 30
      volumes:
      - name: rootfs
        hostPath:
          path: /
      - name: var-run
        hostPath:
          path: /var/run
      - name: sys
        hostPath:
          path: /sys
      - name: docker
        hostPath:
          path: /data/docker

针对挂载资源，做一些调整：

# mount -o remount,rw /sys/fs/cgroup/
# ln -s /sys/fs/cgroup/cpu,cpuacct /sys/fs/cgroup/cpuacct,cpu

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/cadvisor/ds.yaml

检查：

四、blackbox-exporter

# docker pull prom/blackbox-exporter:v0.15.1

# docker tag 81b70b6158be  harbor.od.com/public/blackbox-exporter:v0.15.1
# docker push harbor.od.com/public/blackbox-exporter:v0.15.1

创建资源配置清单：

1、cm.yaml

apiVersion: v1
kind: ConfigMap
metadata:
  labels:
    app: blackbox-exporter
  name: blackbox-exporter
  namespace: kube-system
data:
  blackbox.yml: |-
    modules:
      http_2xx:
        prober: http
        timeout: 2s
        http:
          valid_http_versions: ["HTTP/1.1", "HTTP/2"]
          valid_status_codes: [200,301,302]
          method: GET
          preferred_ip_protocol: "ip4"
      tcp_connect:
        prober: tcp
        timeout: 2s

2、dp.yaml

kind: Deployment
apiVersion: extensions/v1beta1
metadata:
  name: blackbox-exporter
  namespace: kube-system
  labels:
    app: blackbox-exporter
  annotations:
    deployment.kubernetes.io/revision: 1
spec:
  replicas: 1
  selector:
    matchLabels:
      app: blackbox-exporter
  template:
    metadata:
      labels:
        app: blackbox-exporter
    spec:
      volumes:
      - name: config
        configMap:
          name: blackbox-exporter
          defaultMode: 420
      containers:
      - name: blackbox-exporter
        image: harbor.od.com/public/blackbox-exporter:v0.15.1
        imagePullPolicy: IfNotPresent
        args:
        - --config.file=/etc/blackbox_exporter/blackbox.yml
        - --log.level=info
        - --web.listen-address=:9115
        ports:
        - name: blackbox-port
          containerPort: 9115
          protocol: TCP
        resources:
          limits:
            cpu: 200m
            memory: 256Mi
          requests:
            cpu: 100m
            memory: 50Mi
        volumeMounts:
        - name: config
          mountPath: /etc/blackbox_exporter
        readinessProbe:
          tcpSocket:
            port: 9115
          initialDelaySeconds: 5
          timeoutSeconds: 5
          periodSeconds: 10
          successThreshold: 1
          failureThreshold: 3

3、svc.yaml

kind: Service
apiVersion: v1
metadata:
  name: blackbox-exporter
  namespace: kube-system
spec:
  selector:
    app: blackbox-exporter
  ports:
    - name: blackbox-port
      protocol: TCP
      port: 9115

4、ingress.yaml

apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  name: blackbox-exporter
  namespace: kube-system
spec:
  rules:
  - host: blackbox.od.com
    http:
      paths:
      - path: /
        backend:
          serviceName: blackbox-exporter
          servicePort: blackbox-port

这里用到了一个域名，添加解析：

# vi /var/named/od.com.zone

blackbox       A    10.4.7.10

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/blackbox-exporter/cm.yaml
# kubectl apply -f http://k8s-yaml.od.com/blackbox-exporter/dp.yaml
# kubectl apply -f http://k8s-yaml.od.com/blackbox-exporter/svc.yaml
# kubectl apply -f http://k8s-yaml.od.com/blackbox-exporter/ingress.yaml

访问域名测试：

访问到以下界面，表示blackbox已经运行成功

 接下来部署prometheus server：

# docker pull prom/prometheus:v2.14.0

# docker tag 7317640d555e harbor.od.com/infra/prometheus:v2.14.0
# docker push harbor.od.com/infra/prometheus:v2.14.0

准备资源配置清单：

1、rbac.yaml

apiVersion: v1
kind: ServiceAccount
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: prometheus
  namespace: infra
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: prometheus
rules:
- apiGroups:
  - ""
  resources:
  - nodes
  - nodes/metrics
  - services
  - endpoints
  - pods
  verbs:
  - get
  - list
  - watch
- apiGroups:
  - ""
  resources:
  - configmaps
  verbs:
  - get
- nonResourceURLs:
  - /metrics
  verbs:
  - get
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: prometheus
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: prometheus
subjects:
- kind: ServiceAccount
  name: prometheus
  namespace: infra

2、dp.yaml

加上--web.enable-lifecycle启用远程热加载配置文件
调用指令是curl -X POST http://localhost:9090/-/reload

storage.tsdb.min-block-duration=10m #只加载10分钟数据到内

storage.tsdb.retention=72h #保留72小时数据

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  annotations:
    deployment.kubernetes.io/revision: "5"
  labels:
    name: prometheus
  name: prometheus
  namespace: infra
spec:
  progressDeadlineSeconds: 600
  replicas: 1
  revisionHistoryLimit: 7
  selector:
    matchLabels:
      app: prometheus
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        app: prometheus
    spec:
      containers:
      - name: prometheus
        image: harbor.od.com/infra/prometheus:v2.14.0
        imagePullPolicy: IfNotPresent
        command:
        - /bin/prometheus
        args:
        - --config.file=/data/etc/prometheus.yml
        - --storage.tsdb.path=/data/prom-db
        - --storage.tsdb.min-block-duration=10m
        - --storage.tsdb.retention=72h
        - --web.enable-lifecycle
        ports:
        - containerPort: 9090
          protocol: TCP
        volumeMounts:
        - mountPath: /data
          name: data
        resources:
          requests:
            cpu: "1000m"
            memory: "1.5Gi"
          limits:
            cpu: "2000m"
            memory: "3Gi"
      imagePullSecrets:
      - name: harbor
      securityContext:
        runAsUser: 0
      serviceAccountName: prometheus
      volumes:
      - name: data
        nfs:
          server: hdss7-200
          path: /data/nfs-volume/prometheus

3、svc.yaml

apiVersion: v1
kind: Service
metadata:
  name: prometheus
  namespace: infra
spec:
  ports:
  - port: 9090
    protocol: TCP
    targetPort: 9090
  selector:
    app: prometheus

4、ingress.yaml

apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  annotations:
    kubernetes.io/ingress.class: traefik
  name: prometheus
  namespace: infra
spec:
  rules:
  - host: prometheus.od.com
    http:
      paths:
      - path: /
        backend:
          serviceName: prometheus
          servicePort: 9090

这里用到一个域名，添加解析：

prometheus         A    10.4.7.10

记得重启named服务

创建需要的目录：

# mkdir -p /data/nfs-volume/prometheus/{etc,prom-db}

修改prometheus配置文件：别问为啥这么写，问就是不懂~

# vi /data/nfs-volume/prometheus/etc/prometheus.yml

global:
  scrape_interval:     15s
  evaluation_interval: 15s
scrape_configs:
- job_name: 'etcd'
  tls_config:
    ca_file: /data/etc/ca.pem
    cert_file: /data/etc/client.pem
    key_file: /data/etc/client-key.pem
  scheme: https
  static_configs:
  - targets:
    - '10.4.7.12:2379'
    - '10.4.7.21:2379'
    - '10.4.7.22:2379'
- 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-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
- job_name: 'kubernetes-kubelet'
  kubernetes_sd_configs:
  - role: node
  relabel_configs:
  - action: labelmap
    regex: __meta_kubernetes_node_label_(.+)
  - source_labels: [__meta_kubernetes_node_name]
    regex: (.+)
    target_label: __address__
    replacement: ${1}:10255
- job_name: 'kubernetes-cadvisor'
  kubernetes_sd_configs:
  - role: node
  relabel_configs:
  - action: labelmap
    regex: __meta_kubernetes_node_label_(.+)
  - source_labels: [__meta_kubernetes_node_name]
    regex: (.+)
    target_label: __address__
    replacement: ${1}:4194
- job_name: 'kubernetes-kube-state'
  kubernetes_sd_configs:
  - role: pod
  relabel_configs:
  - 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
  - source_labels: [__meta_kubernetes_pod_label_grafanak8sapp]
    regex: .*true.*
    action: keep
  - source_labels: ['__meta_kubernetes_pod_label_daemon', '__meta_kubernetes_pod_node_name']
    regex: 'node-exporter;(.*)'
    action: replace
    target_label: nodename
- job_name: 'blackbox_http_pod_probe'
  metrics_path: /probe
  kubernetes_sd_configs:
  - role: pod
  params:
    module: [http_2xx]
  relabel_configs:
  - source_labels: [__meta_kubernetes_pod_annotation_blackbox_scheme]
    action: keep
    regex: http
  - source_labels: [__address__, __meta_kubernetes_pod_annotation_blackbox_port,  __meta_kubernetes_pod_annotation_blackbox_path]
    action: replace
    regex: ([^:]+)(?::d+)?;(d+);(.+)
    replacement: $1:$2$3
    target_label: __param_target
  - action: replace
    target_label: __address__
    replacement: blackbox-exporter.kube-system:9115
  - source_labels: [__param_target]
    target_label: instance
  - 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
- job_name: 'blackbox_tcp_pod_probe'
  metrics_path: /probe
  kubernetes_sd_configs:
  - role: pod
  params:
    module: [tcp_connect]
  relabel_configs:
  - source_labels: [__meta_kubernetes_pod_annotation_blackbox_scheme]
    action: keep
    regex: tcp
  - source_labels: [__address__, __meta_kubernetes_pod_annotation_blackbox_port]
    action: replace
    regex: ([^:]+)(?::d+)?;(d+)
    replacement: $1:$2
    target_label: __param_target
  - action: replace
    target_label: __address__
    replacement: blackbox-exporter.kube-system:9115
  - source_labels: [__param_target]
    target_label: instance
  - 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
- job_name: 'traefik'
  kubernetes_sd_configs:
  - role: pod
  relabel_configs:
  - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scheme]
    action: keep
    regex: traefik
  - 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

拷贝配置文件中用到的证书：

# cd /data/nfs-volume/prometheus/etc/
# cp /opt/certs/ca.pem ./
# cp /opt/certs/client.pem ./
# cp /opt/certs/client-key.pem ./

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/prometheus-server/rbac.yaml
# kubectl apply -f http://k8s-yaml.od.com/prometheus-server/dp.yaml
# kubectl apply -f http://k8s-yaml.od.com/prometheus-server/svc.yaml
# kubectl apply -f http://k8s-yaml.od.com/prometheus-server/ingress.yaml

浏览器验证：prometheus.od.com

这里点击status-targets，这里展示的就是我们在prometheus.yml中配置的job-name，这些targets基本可以满足我们收集数据的需求。

点击status-configuration就是我们的配置文件

 我们在配置文件中，除了etcd使用的静态配置以外，其他job都是使用的自动发现。

 静态配置：

global:
  scrape_interval:     15s
  evaluation_interval: 15s
scrape_configs:
- job_name: 'etcd'
  tls_config:
    ca_file: /data/etc/ca.pem
    cert_file: /data/etc/client.pem
    key_file: /data/etc/client-key.pem
  scheme: https
  static_configs:
  - targets:
    - '10.4.7.12:2379'
    - '10.4.7.21:2379'
    - '10.4.7.22:2379'

自动发现：自动发现资源是pod

- job_name: 'blackbox_http_pod_probe'
  metrics_path: /probe
  kubernetes_sd_configs:
  - role: pod
  params:
    module: [http_2xx]
  relabel_configs:

这里还有很多数据没有收集到，是因为我们在启动服务的时候，没有添加annotations，下面给需要收集数据的服务添加annotations

 1、traefik：

修改traefik的yaml：

从dashboard里找到traefik的yaml，跟labels同级添加annotations

"annotations": {
  "prometheus_io_scheme": "traefik",
  "prometheus_io_path": "/metrics",
  "prometheus_io_port": "8080"
}

 等待pod重启以后，在去prometheus上去看

 2、blackbox：

这个是检测容器内服务存活性的，也就是端口健康状态检查，分为tcp和http

首先准备两个服务，将dubbo-demo-service和dubbo-demo-consumer都调整为使用master镜像，不依赖apollo的（节省资源）

等两个服务起来以后，首先在dubbo-demo-service资源中添加一个TCP的annotation：

"annotations": {
  "blackbox_port": "20880",
  "blackbox_scheme": "tcp"
}

 

这里会自动发现我们服务中，运行tcp port端口为20880的服务，并监控其状态

接下来在dubbo-demo-consumer资源中添加一个HTTP的annotation：

"annotations": {
  "blackbox_path": "/hello?name=health",
  "blackbox_port": "8080",
  "blackbox_scheme": "http"
}

 

 去检查blackbox.od.com

http://blackbox.od.com/

 接下来添加监控jvm信息的annotation：

"annotations": {
  "prometheus_io_scrape": "true",
  "prometheus_io_port": "12346",
  "prometheus_io_path": "/"
}

dubbo-demo-service和dubbo-demo-consumer都添加：

 

 匹配规则，要去prometheus.yml中去看。

 

 接下来部署炫酷的dashboard工具grafana：

 下载镜像：

# docker pull grafana/grafana:5.4.2

# docker tag 6f18ddf9e552 harbor.od.com/infra/grafana:v5.4.2

# docker push harbor.od.com/infra/grafana:v5.4.2

准备资源配置清单：

1、rbac.yaml

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: grafana
rules:
- apiGroups:
  - "*"
  resources:
  - namespaces
  - deployments
  - pods
  verbs:
  - get
  - list
  - watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: grafana
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: grafana
subjects:
- kind: User
  name: k8s-node

2、dp.yaml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  labels:
    app: grafana
    name: grafana
  name: grafana
  namespace: infra
spec:
  progressDeadlineSeconds: 600
  replicas: 1
  revisionHistoryLimit: 7
  selector:
    matchLabels:
      name: grafana
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        app: grafana
        name: grafana
    spec:
      containers:
      - name: grafana
        image: harbor.od.com/infra/grafana:v5.4.2
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 3000
          protocol: TCP
        volumeMounts:
        - mountPath: /var/lib/grafana
          name: data
      imagePullSecrets:
      - name: harbor
      securityContext:
        runAsUser: 0
      volumes:
      - nfs:
          server: hdss7-200
          path: /data/nfs-volume/grafana
        name: data

# mkdir /data/nfs-volume/grafana

3、svc.yaml

apiVersion: v1
kind: Service
metadata:
  name: grafana
  namespace: infra
spec:
  ports:
  - port: 3000
    protocol: TCP
    targetPort: 3000
  selector:
    app: grafana

4、ingress.yaml

apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  name: grafana
  namespace: infra
spec:
  rules:
  - host: grafana.od.com
    http:
      paths:
      - path: /
        backend:
          serviceName: grafana
          servicePort: 3000

域名解析：

grafana            A    10.4.7.10

应用资源配置清单：

# kubectl apply -f http://k8s-yaml.od.com/grafana/rbac.yaml
# kubectl apply -f http://k8s-yaml.od.com/grafana/dp.yaml
# kubectl apply -f http://k8s-yaml.od.com/grafana/svc.yaml
# kubectl apply -f http://k8s-yaml.od.com/grafana/ingress.yaml

 浏览器访问验证：

grafana.od.com

默认用户名密码admin

进入容器安装插件：

# kubectl exec  -it grafana-d6588db94-xr4s6 /bin/bash -n infra

grafana-cli plugins install grafana-kubernetes-app
grafana-cli plugins install grafana-clock-panel
grafana-cli plugins install grafana-piechart-panel
grafana-cli plugins install briangann-gauge-panel
grafana-cli plugins install natel-discrete-panel

配置数据源：选择prometheus，把三个证书添加进来

 重启grafana

找到我们刚才安装的插件里面的kubernetes,启用，然后新建cluster

 添加完需要稍等几分钟，在没有取到数据之前，会报http forbidden，没关系，等一会就好。大概2-5分钟。

 

配置alert告警插件：

# docker pull docker.io/prom/alertmanager:v0.14.0
# docker tag 30594e96cbe8 harbor.od.com/infra/alertmanager:v0.14.0
# docker push harbor.od.com/infra/alertmanager:v0.14.0

资源配置清单：

1、cm.yaml

apiVersion: v1
kind: ConfigMap
metadata:
  name: alertmanager-config
  namespace: infra
data:
  config.yml: |-
    global:
      # 在没有报警的情况下声明为已解决的时间
      resolve_timeout: 5m
      # 配置邮件发送信息
      smtp_smarthost: 'smtp.163.com:25'
      smtp_from: 'xxx@163.com'
      smtp_auth_username: 'xxx@163.com'
      smtp_auth_password: 'xxxxxx'
      smtp_require_tls: false
    # 所有报警信息进入后的根路由，用来设置报警的分发策略
    route:
      # 这里的标签列表是接收到报警信息后的重新分组标签，例如，接收到的报警信息里面有许多具有 cluster=A 和 alertname=LatncyHigh 这样的标签的报警信息将会批量被聚合到一个分组里面
      group_by: ['alertname', 'cluster']
      # 当一个新的报警分组被创建后，需要等待至少group_wait时间来初始化通知，这种方式可以确保您能有足够的时间为同一分组来获取多个警报，然后一起触发这个报警信息。
      group_wait: 30s

      # 当第一个报警发送后，等待'group_interval'时间来发送新的一组报警信息。
      group_interval: 5m

      # 如果一个报警信息已经发送成功了，等待'repeat_interval'时间来重新发送他们
      repeat_interval: 5m

      # 默认的receiver：如果一个报警没有被一个route匹配，则发送给默认的接收器
      receiver: default

    receivers:
    - name: 'default'
      email_configs:
      - to: 'xxxx@qq.com'
        send_resolved: true

2、dp.yaml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: alertmanager
  namespace: infra
spec:
  replicas: 1
  selector:
    matchLabels:
      app: alertmanager
  template:
    metadata:
      labels:
        app: alertmanager
    spec:
      containers:
      - name: alertmanager
        image: harbor.od.com/infra/alertmanager:v0.14.0
        args:
          - "--config.file=/etc/alertmanager/config.yml"
          - "--storage.path=/alertmanager"
        ports:
        - name: alertmanager
          containerPort: 9093
        volumeMounts:
        - name: alertmanager-cm
          mountPath: /etc/alertmanager
      volumes:
      - name: alertmanager-cm
        configMap:
          name: alertmanager-config
      imagePullSecrets:
      - name: harbor

3、svc.yaml

apiVersion: v1
kind: Service
metadata:
  name: alertmanager
  namespace: infra
spec:
  selector: 
    app: alertmanager
  ports:
    - port: 80
      targetPort: 9093

基础报警规则：

# vi /data/nfs-volume/prometheus/etc/rules.yml

groups:
- name: hostStatsAlert
  rules:
  - alert: hostCpuUsageAlert
    expr: sum(avg without (cpu)(irate(node_cpu{mode!='idle'}[5m]))) by (instance) > 0.85
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "{{ $labels.instance }} CPU usage above 85% (current value: {{ $value }}%)"
  - alert: hostMemUsageAlert
    expr: (node_memory_MemTotal - node_memory_MemAvailable)/node_memory_MemTotal > 0.85
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "{{ $labels.instance }} MEM usage above 85% (current value: {{ $value }}%)"
  - alert: OutOfInodes
    expr: node_filesystem_free{fstype="overlay",mountpoint ="/"} / node_filesystem_size{fstype="overlay",mountpoint ="/"} * 100 < 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Out of inodes (instance {{ $labels.instance }})"
      description: "Disk is almost running out of available inodes (< 10% left) (current value: {{ $value }})"
  - alert: OutOfDiskSpace
    expr: node_filesystem_free{fstype="overlay",mountpoint ="/rootfs"} / node_filesystem_size{fstype="overlay",mountpoint ="/rootfs"} * 100 < 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Out of disk space (instance {{ $labels.instance }})"
      description: "Disk is almost full (< 10% left) (current value: {{ $value }})"
  - alert: UnusualNetworkThroughputIn
    expr: sum by (instance) (irate(node_network_receive_bytes[2m])) / 1024 / 1024 > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual network throughput in (instance {{ $labels.instance }})"
      description: "Host network interfaces are probably receiving too much data (> 100 MB/s) (current value: {{ $value }})"
  - alert: UnusualNetworkThroughputOut
    expr: sum by (instance) (irate(node_network_transmit_bytes[2m])) / 1024 / 1024 > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual network throughput out (instance {{ $labels.instance }})"
      description: "Host network interfaces are probably sending too much data (> 100 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskReadRate
    expr: sum by (instance) (irate(node_disk_bytes_read[2m])) / 1024 / 1024 > 50
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk read rate (instance {{ $labels.instance }})"
      description: "Disk is probably reading too much data (> 50 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskWriteRate
    expr: sum by (instance) (irate(node_disk_bytes_written[2m])) / 1024 / 1024 > 50
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk write rate (instance {{ $labels.instance }})"
      description: "Disk is probably writing too much data (> 50 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskReadLatency
    expr: rate(node_disk_read_time_ms[1m]) / rate(node_disk_reads_completed[1m]) > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk read latency (instance {{ $labels.instance }})"
      description: "Disk latency is growing (read operations > 100ms) (current value: {{ $value }})"
  - alert: UnusualDiskWriteLatency
    expr: rate(node_disk_write_time_ms[1m]) / rate(node_disk_writes_completedl[1m]) > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk write latency (instance {{ $labels.instance }})"
      description: "Disk latency is growing (write operations > 100ms) (current value: {{ $value }})"
- name: http_status
  rules:
  - alert: ProbeFailed
    expr: probe_success == 0
    for: 1m
    labels:
      severity: error
    annotations:
      summary: "Probe failed (instance {{ $labels.instance }})"
      description: "Probe failed (current value: {{ $value }})"
  - alert: StatusCode
    expr: probe_http_status_code <= 199 OR probe_http_status_code >= 400
    for: 1m
    labels:
      severity: error
    annotations:
      summary: "Status Code (instance {{ $labels.instance }})"
      description: "HTTP status code is not 200-399 (current value: {{ $value }})"
  - alert: SslCertificateWillExpireSoon
    expr: probe_ssl_earliest_cert_expiry - time() < 86400 * 30
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "SSL certificate will expire soon (instance {{ $labels.instance }})"
      description: "SSL certificate expires in 30 days (current value: {{ $value }})"
  - alert: SslCertificateHasExpired
    expr: probe_ssl_earliest_cert_expiry - time()  <= 0
    for: 5m
    labels:
      severity: error
    annotations:
      summary: "SSL certificate has expired (instance {{ $labels.instance }})"
      description: "SSL certificate has expired already (current value: {{ $value }})"
  - alert: BlackboxSlowPing
    expr: probe_icmp_duration_seconds > 2
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Blackbox slow ping (instance {{ $labels.instance }})"
      description: "Blackbox ping took more than 2s (current value: {{ $value }})"
  - alert: BlackboxSlowRequests
    expr: probe_http_duration_seconds > 2 
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Blackbox slow requests (instance {{ $labels.instance }})"
      description: "Blackbox request took more than 2s (current value: {{ $value }})"
  - alert: PodCpuUsagePercent
    expr: sum(sum(label_replace(irate(container_cpu_usage_seconds_total[1m]),"pod","$1","container_label_io_kubernetes_pod_name", "(.*)"))by(pod) / on(pod) group_right kube_pod_container_resource_limits_cpu_cores *100 )by(container,namespace,node,pod,severity) > 80
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Pod cpu usage percent has exceeded 80% (current value: {{ $value }}%)"

在prometheus.yml中添加配置：

# vi prometheus.yml

alerting:
  alertmanagers:
    - static_configs:
        - targets: ["alertmanager"]
rule_files:
 - "/data/etc/rules.yml"

重载配置：

# curl -X POST http://prometheus.od.com/-/reload

 以上这些就是我们的告警规则

测试告警：

把app命名空间里的dubbo-demo-service给停掉：

 看下blackbox里的信息：

看下alert：

 红色的时候就开会发邮件告警：

 已经收到告警了，后续上生产，还会更新如何添加微信、钉钉、短信告警

 如果需要自己定制告警规则和告警内容，需要研究一下promql，自己修改配置文件。