k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

2022-02-15 13:55:41

k8s监控实战-部署prometheus

目录

  • k8s监控实战-部署prometheus
    • 1 prometheus前言相关
      • 1.1 Prometheus的特点
      • 1.2 基本原理
        • 1.2.1 原理说明
        • 1.2.2 架构图:
        • 1.2.3 三大套件
        • 1.2.4 架构服务过程
        • 1.2.5 常用的exporter
    • 2 部署4个exporter
      • 2.1 部署kube-state-metrics
        • 2.1.1 准备docker镜像
        • 2.1.2 准备rbac资源清单
        • 2.1.3 准备Dp资源清单
        • 2.1.4 应用资源配置清单
      • 2.2 部署node-exporter
        • 2.2.1 准备docker镜像
        • 2.2.2 准备ds资源清单
        • 2.2.3 应用资源配置清单：
      • 2.3 部署cadvisor
        • 2.3.1 准备docker镜像
        • 2.3.2 准备ds资源清单
        • 2.3.3 应用资源配置清单：
      • 2.4 部署blackbox-exporter
        • 2.4.1 准备docker镜像
        • 2.4.2 准备cm资源清单
        • 2.4.3 准备dp资源清单
        • 2.4.4 准备svc资源清单
        • 2.4.5 准备ingress资源清单
        • 2.4.6 添加域名解析
        • 2.4.7 应用资源配置清单
        • 2.4.8 访问域名测试
    • 3 部署prometheus server
      • 3.1 准备prometheus server环境
        • 3.1.1 准备docker镜像
        • 3.1.2 准备rbac资源清单
        • 3.1.3 准备dp资源清单
        • 3.1.4 准备svc资源清单
        • 3.1.5 准备ingress资源清单
        • 3.1.6 添加域名解析
      • 3.2 部署prometheus server
        • 3.2.1 准备目录和证书
        • 3.2.2 创建prometheus配置文件
        • 3.2.3 应用资源配置清单
        • 3.2.4 浏览器验证
    • 4 使服务能被prometheus自动监控
      • 4.1 让traefik能被自动监控
        • 4.1.1 修改traefik的yaml
        • 4.1.2 应用配置查看
      • 4.2 用blackbox检测TCP/HTTP服务状态
        • 4.2.1 被检测服务准备
        • 4.2.2 添加tcp的annotation
        • 4.2.3 添加http的annotation
      • 4.3 添加监控jvm信息

1 prometheus前言相关

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

prometheus官网：官网地址

1.1 Prometheus的特点

  • 多维度数据模型,使用时间序列数据库TSDB而不使用mysql。
  • 灵活的查询语言PromQL。
  • 不依赖分布式存储，单个服务器节点是自主的。
  • 主要基于HTTP的pull方式主动采集时序数据
  • 也可通过pushgateway获取主动推送到网关的数据。
  • 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。

1.2 基本原理

1.2.1 原理说明

Prometheus的基本原理是通过各种exporter提供的HTTP协议接口

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,非常适合做虚拟化环境监控系统，比如VM、Docker、Kubernetes等。

互联网公司常用的组件大部分都有exporter可以直接使用，如Nginx、MySQL、Linux系统信息等。

1.2.2 架构图:

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

1.2.3 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。

1.2.4 架构服务过程

  1. 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。
    支持通过配置文件、文本文件、Zookeeper、DNS SRV Lookup等方式指定抓取目标。
  2. PushGateway用于Client主动推送metrics到PushGateway
    而Prometheus只是定时去Gateway上抓取数据。
    适合一次性、短生命周期的服务
  3. Prometheus在TSDB数据库存储抓取的所有数据
    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。
  4. Prometheus通过PromQL和其他API可视化地展示收集的数据。
    支持Grafana、Promdash等方式的图表数据可视化。
    Prometheus还提供HTTP API的查询方式，自定义所需要的输出。
  5. Alertmanager是独立于Prometheus的一个报警组件
    支持Prometheus的查询语句，提供十分灵活的报警方式。

1.2.5 常用的exporter

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

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

2 部署4个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：

2.1 部署kube-state-metrics

2.1.1 准备docker镜像

docker pull quay.io/coreos/kube-state-metrics:v1.5.0
docker tag  91599517197a harbor.zq.com/public/kube-state-metrics:v1.5.0
docker push harbor.zq.com/public/kube-state-metrics:v1.5.0

准备目录

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

2.1.2 准备rbac资源清单

cat >rbac.yaml <<'EOF'
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
EOF

2.1.3 准备Dp资源清单

cat >dp.yaml <<'EOF'
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.zq.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
EOF

2.1.4 应用资源配置清单

任意node节点执行

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

验证测试

kubectl get pod -n kube-system -o wide|grep kube-state-metrices
~]# curl http://172.7.21.4:8080/healthz
ok

返回OK表示已经成功运行。

2.2 部署node-exporter

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

2.2.1 准备docker镜像

docker pull prom/node-exporter:v0.15.0
docker tag 12d51ffa2b22 harbor.zq.com/public/node-exporter:v0.15.0
docker push harbor.zq.com/public/node-exporter:v0.15.0

准备目录

mkdir /data/k8s-yaml/node-exporter
cd /data/k8s-yaml/node-exporter

2.2.2 准备ds资源清单

cat >ds.yaml <<'EOF'
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.zq.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
EOF

主要用途就是将宿主机的/proc,sys目录挂载给容器,是容器能获取node节点宿主机信息

2.2.3 应用资源配置清单：

任意node节点

kubectl apply -f http://k8s-yaml.zq.com/node-exporter/ds.yaml
kubectl get pod -n kube-system -o wide|grep node-exporter

2.3 部署cadvisor

2.3.1 准备docker镜像

docker pull google/cadvisor:v0.28.3
docker tag 75f88e3ec333 harbor.zq.com/public/cadvisor:0.28.3
docker push harbor.zq.com/public/cadvisor:0.28.3

准备目录

mkdir /data/k8s-yaml/cadvisor
cd /data/k8s-yaml/cadvisor

2.3.2 准备ds资源清单

cadvisor由于要获取每个node上的pod信息,因此也需要使用daemonset方式运行

cat >ds.yaml <<'EOF'
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
#------pod的tolerations与node的Taints配合,做POD指定调度----
      tolerations:
      - key: node-role.kubernetes.io/master
        effect: NoSchedule
#-------------------------------------
      containers:
      - name: cadvisor
        image: harbor.zq.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
EOF

2.3.3 应用资源配置清单：

应用清单前,先在每个node上做以下软连接,否则服务可能报错

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

应用清单

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

检查：

kubectl -n kube-system get pod -o wide|grep cadvisor

2.4 部署blackbox-exporter

2.4.1 准备docker镜像

docker pull prom/blackbox-exporter:v0.15.1
docker tag  81b70b6158be  harbor.zq.com/public/blackbox-exporter:v0.15.1
docker push harbor.zq.com/public/blackbox-exporter:v0.15.1

准备目录

mkdir /data/k8s-yaml/blackbox-exporter
cd /data/k8s-yaml/blackbox-exporter

2.4.2 准备cm资源清单

cat >cm.yaml <<'EOF'
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
EOF

2.4.3 准备dp资源清单

cat >dp.yaml <<'EOF'
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.zq.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
EOF

2.4.4 准备svc资源清单

cat >svc.yaml <<'EOF'
kind: Service
apiVersion: v1
metadata:
  name: blackbox-exporter
  namespace: kube-system
spec:
  selector:
    app: blackbox-exporter
  ports:
    - name: blackbox-port
      protocol: TCP
      port: 9115
EOF

2.4.5 准备ingress资源清单

cat >ingress.yaml <<'EOF'
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  name: blackbox-exporter
  namespace: kube-system
spec:
  rules:
  - host: blackbox.zq.com
    http:
      paths:
      - path: /
        backend:
          serviceName: blackbox-exporter
          servicePort: blackbox-port
EOF

2.4.6 添加域名解析

这里用到了一个域名，添加解析

vi /var/named/zq.com.zone
blackbox       A    10.4.7.10
systemctl restart named

2.4.7 应用资源配置清单

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

2.4.8 访问域名测试

访问http://blackbox.zq.com，显示如下界面,表示blackbox已经运行成

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

3 部署prometheus server

3.1 准备prometheus server环境

3.1.1 准备docker镜像

docker pull prom/prometheus:v2.14.0
docker tag  7317640d555e harbor.zq.com/infra/prometheus:v2.14.0
docker push harbor.zq.com/infra/prometheus:v2.14.0

准备目录

mkdir /data/k8s-yaml/prometheus-server
cd /data/k8s-yaml/prometheus-server

3.1.2 准备rbac资源清单

cat >rbac.yaml <<'EOF'
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
EOF

3.1.3 准备dp资源清单

加上--web.enable-lifecycle启用远程热加载配置文件,配置文件改变后不用重启prometheus

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

cat >dp.yaml <<'EOF'
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.zq.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
EOF

3.1.4 准备svc资源清单

cat >svc.yaml <<'EOF'
apiVersion: v1
kind: Service
metadata:
  name: prometheus
  namespace: infra
spec:
  ports:
  - port: 9090
    protocol: TCP
    targetPort: 9090
  selector:
    app: prometheus
EOF

3.1.5 准备ingress资源清单

cat >ingress.yaml <<'EOF'
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  annotations:
    kubernetes.io/ingress.class: traefik
  name: prometheus
  namespace: infra
spec:
  rules:
  - host: prometheus.zq.com
    http:
      paths:
      - path: /
        backend:
          serviceName: prometheus
          servicePort: 9090
EOF

3.1.6 添加域名解析

这里用到一个域名prometheus.zq.com，添加解析：

vi /var/named/od.com.zone
prometheus         A    10.4.7.10
systemctl restart named

3.2 部署prometheus server

3.2.1 准备目录和证书

mkdir -p /data/nfs-volume/prometheus/etc
mkdir -p /data/nfs-volume/prometheus/prom-db
cd /data/nfs-volume/prometheus/etc/
# 拷贝配置文件中用到的证书：
cp /opt/certs/ca.pem ./
cp /opt/certs/client.pem ./
cp /opt/certs/client-key.pem ./

3.2.2 创建prometheus配置文件

配置文件说明:

此配置为通用配置,除第一个jobetcd是做的静态配置外,其他8个job都是做的自动发现

因此只需要修改etcd的配置后,就可以直接用于生产环境

cat >/data/nfs-volume/prometheus/etc/prometheus.yml <<'EOF'
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
EOF

3.2.3 应用资源配置清单

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

3.2.4 浏览器验证

访问http://prometheus.zq.com,如果能成功访问的话,表示启动成功

点击status->configuration就是我们的配置文件

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

4 使服务能被prometheus自动监控

点击status->targets，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。

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

5个编号的job-name已经被发现并获取数据

接下来就需要将剩下的4个ob-name对应的服务纳入监控

纳入监控的方式是给需要收集数据的服务添加annotations

4.1 让traefik能被自动监控

4.1.1 修改traefik的yaml

修改fraefik的yaml文件,跟labels同级,添加annotations配置

vim /data/k8s-yaml/traefik/ds.yaml
........
spec:
  template:
    metadata:
      labels:
        k8s-app: traefik-ingress
        name: traefik-ingress
#--------增加内容--------
      annotations:
        prometheus_io_scheme: "traefik"
        prometheus_io_path: "/metrics"
        prometheus_io_port: "8080"
#--------增加结束--------
    spec:
      serviceAccountName: traefik-ingress-controller
........

任意节点重新应用配置

kubectl delete -f http://k8s-yaml.zq.com/traefik/ds.yaml
kubectl apply  -f http://k8s-yaml.zq.com/traefik/ds.yaml

4.1.2 应用配置查看

等待pod重启以后，再在prometheus上查看traefik是否能正常获取数据了

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

4.2 用blackbox检测TCP/HTTP服务状态

blackbox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两种方法

能用http的情况尽量用http,没有提供http接口的服务才用tcp

4.2.1 被检测服务准备

使用测试环境的dubbo服务来做演示,其他环境类似

  1. dashboard中开启apollo-portal和test空间中的apollo
  2. dubbo-demo-service使用tcp的annotation
  3. dubbo-demo-consumer使用HTTP的annotation

4.2.2 添加tcp的annotation

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

vim /data/k8s-yaml/test/dubbo-demo-server/dp.yaml
......
spec:
......
  template:
    metadata:
      labels:
        app: dubbo-demo-service
        name: dubbo-demo-service
#--------增加内容--------
      annotations:
        blackbox_port: "20880"
        blackbox_scheme: "tcp"
#--------增加结束--------
    spec:
      containers:
        image: harbor.zq.com/app/dubbo-demo-service:apollo_200512_0746

任意节点重新应用配置

kubectl delete -f http://k8s-yaml.zq.com/test/dubbo-demo-server/dp.yaml
kubectl apply  -f http://k8s-yaml.zq.com/test/dubbo-demo-server/dp.yaml

浏览器中查看http://blackbox.zq.com/和http://prometheus.zq.com/targets

我们运行的dubbo-demo-server服务,tcp端口20880已经被发现并在监控中

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

4.2.3 添加http的annotation

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

vim /data/k8s-yaml/test/dubbo-demo-consumer/dp.yaml 
spec:
......
  template:
    metadata:
      labels:
        app: dubbo-demo-consumer
        name: dubbo-demo-consumer
#--------增加内容--------
      annotations:
        blackbox_path: "/hello?name=health"
        blackbox_port: "8080"
        blackbox_scheme: "http"
#--------增加结束--------
    spec:
      containers:
      - name: dubbo-demo-consumer
......

任意节点重新应用配置

kubectl delete -f http://k8s-yaml.zq.com/test/dubbo-demo-consumer/dp.yaml
kubectl apply  -f http://k8s-yaml.zq.com/test/dubbo-demo-consumer/dp.yaml

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

4.3 添加监控jvm信息

dubbo-demo-service和dubbo-demo-consumer都添加下列annotation注解,以便监控pod中的jvm信息

vim /data/k8s-yaml/test/dubbo-demo-server/dp.yaml
vim /data/k8s-yaml/test/dubbo-demo-consumer/dp.yaml 
      annotations:
        #....已有略....
        prometheus_io_scrape: "true"
        prometheus_io_port: "12346"
        prometheus_io_path: "/"

12346是dubbo的POD启动命令中使用jmx_javaagent用到的端口,因此可以用来收集jvm信息

任意节点重新应用配置

kubectl apply  -f http://k8s-yaml.zq.com/test/dubbo-demo-server/dp.yaml
kubectl apply  -f http://k8s-yaml.zq.com/test/dubbo-demo-consumer/dp.yaml

k8s容器云架构之dubbo微服务—K8S(13)监控实战-部署prometheus

至此,所有9个服务,都获取了数据

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