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Prometheus 服务发现机制

· 阅读需 14 分钟

Prometheus 服务发现机制​

Prometheus 默认才用pull取拉取监控数据的，也就是定时去目标主机去抓取metrics数据。所以每一个被抓取目标需要暴露一个HTTP接口，通过这个借口获取对应指标数据。

这种方式需要由目标服务决定抓取的采集目标有哪些，通过配置在scrape_config中的各种job实现，无法动态感知新服务。如果后续添加新服务就要手动改prometheus的配置，所以要用动态服务发现，通过服务发现，prometheus能查询到需要监控的Target列表，然后轮询这个Target获取监控数据

获取数据源target的方式有很多种，静态配置和服务发现，实现服务发现的方式有：

  • kubernetes_sd_configs #k8s服务发现，让prome动态发现k8s中被监控的目标
  • static_configs #静态服务发现，基于prometheus配置文件指定的监控目标（默认使用的）
  • dns_sd_configs #DNS服务发现监控数据
  • consul_sd_configs. #Consul服务发现，基于consul动态发现监控目标
  • file_sd_configs #基于指定的文件实现服务发现

一、kubernetes_sd_configs​

promethues 的relabeling (重新修改标签)功能很强大,它能够在抓取到目标实例之前把目标实例的元数据标签动态重新修改,动态添加或者覆盖标签
prometheus 加载 target 成功之后,在Target 实例中,都包含一些 Metadata 标签信息,默认的标签有:
__address__:以<host>:<port>格式显示目标targets的地址
__scheme__:采集的目标服务地址的Scheme形式, HTTP 或者HTTPS
__metrics_path__:采集的目标服务的访问路径

基础功能-重新标记目的

relabel_configs: 在采集之前（比如在采集数据之前重新定义元标签），可以使用relabel_configs添加一些标签、也可以只采集特定目标或过滤目标。

metric_relabel_configs: 如果是已经抓取到指标数据时，可以使用metric_relabel_configs做最后的重新标记和过滤

配置 -> 重新标签（relabel_configs）-> 抓取 -> 重新标签（metric_relabel_configs） -> TSDB

    - job_name: 'kubernetes-apiserver'
      kubernetes_sd_configs:  #基于kubernetes_sd_configs 实现服务发现
      - role: endpoints  # 发现endpoints
      scheme: https  #当前job使用的发现协议
      tls_config:  #证书配置
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt #容器里的证书路径
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token #容器里的token路径
      relabel_configs:  #重新re修改标签label配置configs
      - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
        action: keep  #action定义里relabel的具体动作，action支持多种
        regex: default;kubernetes;https  #发现了default命名空间的kubernetes服务且时https协议
label 详解​
source_labels: 源标签，没有经过relabel处理之前的标签名字
target_label: 通过action处理之后的新的标签名字
regex: 正则表达式，匹配源标签
replacement: 通过分组替换后标签（target_label）对应的值
action 详解​

https://prometheus.io/docs/prometheus/latest/configuration/configuration/#kubernetes_sd_con

replace: 替换标签纸，根据regex正则匹配到源标签的值，使用replacement来引用表达式匹配的分组
keep: 满足regex正则条件的实例进行采集，把source_labels中没有匹配到regex正则内容的Target实例丢掉，即只采集匹配成功的实例

drop: 满足 regex 正则条件的实例不采集，把source_labels中匹配到regex正则内容的Target实例丢掉，即只采集没有匹配到的实例
---------------------------------------------------------
labelmap: 匹配 regex所有标签名称,然后复制匹配标签的值进行分组,通过replacement分组引用($[1),$[2),...)替代
labelkeep: 匹配 regex所有标签名称,其它不匹配的标签都将从标签集中删除
labeldrop: 匹配 regex所有标签名称,其它匹配的标签都将从标签集中删除

支持的发现目标类型

https://prometheus.io/docs/prometheus/latest/configuration/configuration/#kubernetes_sd_config

  • node
  • service
  • pod
  • endpoints
  • Endpointslice #对endpoint进行分片
  • ingress
api-server 指标数据​

监控 api-server 实现

可以直接通过k8s的service来获取

      - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
        action: keep
        regex: default;kubernetes;https  #含义为匹配default的namespace,svc名称时kubernetes并且协议时https，匹配成功后进行保留，并且把regex作为source_labels相对应的值。 即labels为key、regex为值
        
# label替换方式如下：

本文深入探讨Prometheus服务发现机制的原理与实践，帮助你更好地理解和配置自动化监控。

K8s Prome常用监控部署

· 阅读需 5 分钟

K8s Prome常用监控部署​

使用K8s部署

Cadvisor 部署​

# 拉取镜像 
docker pull gcr.io/cadvisor/cadvisor:v0.39.2

# 做tag
docker tag gcr.io/cadvisor/cadvisor:v0.39.2 harbor.images.com/test/cadvisor:v0.39.2

# 推送镜像
docker push harbor.images.com/test/cadvisor:v0.39.2

# 创建命名空间
kubectl create ns monitoring

编写yaml

vim daemonset-deploy-cadvisor.yaml

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: cadvisor
  namespace: monitoring
spec:
  selector:
    matchLabels:
      app: cAdvisor
  template:
    metadata:
      labels:
        app: cAdvisor
    spec:
      tolerations:    #污点容忍,忽略master的NoSchedule
        - effect: NoSchedule
          key: node-role.kubernetes.io/master
      hostNetwork: true
      restartPolicy: Always   # 重启策略
      containers:
      - name: cadvisor
        image: harbor.images.com/test/cadvisor:v0.39.2
        imagePullPolicy: IfNotPresent  # 镜像策略
        ports:
        - containerPort: 8080
        volumeMounts:
          - name: root
            mountPath: /rootfs
          - name: run
            mountPath: /var/run
          - name: sys
            mountPath: /sys
          - name: docker
            mountPath: /var/lib/docker
      volumes:
      - name: root
        hostPath:
          path: /
      - name: run
        hostPath:
          path: /var/run
      - name: sys
        hostPath:
          path: /sys
      - name: docker
        hostPath:
          path: /var/lib/docker

应用并查看

kubectl create -f daemonset-deploy-cadvisor.yaml

# 查看状态
kubectl get pod -n monitoring -owide

node-exporter 部署​

# 拉取镜像
docker pull quay.io/prometheus/node-exporter:v1.3.1

# 打标签
docker tag quay.io/prometheus/node-exporter:v1.3.1 harbor.images.com/test/node-exporter:v1.3.1

# 推送镜像
docker push harbor.images.com/test/node-exporter:v1.3.1

编写 yaml

vim daemonset-deploy-node-exporter.yaml

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: node-exporter
  namespace: monitoring 
  labels:
    k8s-app: node-exporter
spec:
  selector:
    matchLabels:
        k8s-app: node-exporter
  template:
    metadata:
      labels:
        k8s-app: node-exporter
    spec:
      tolerations:
        - effect: NoSchedule
          key: node-role.kubernetes.io/master
      containers:
      - image: quay.io/prometheus/node-exporter:v1.3.1
      #- image: prom/node-exporter:v1.3.1 
        imagePullPolicy: IfNotPresent
        name: prometheus-node-exporter
        ports:
        - containerPort: 9100
          hostPort: 9100
          protocol: TCP
          name: metrics
        volumeMounts:
        - mountPath: /host/proc
          name: proc
        - mountPath: /host/sys
          name: sys
        - mountPath: /host
          name: rootfs
        args:
        - --path.procfs=/host/proc
        - --path.sysfs=/host/sys
        - --path.rootfs=/host
      volumes:
        - name: proc
          hostPath:
            path: /proc
        - name: sys
          hostPath:
            path: /sys
        - name: rootfs
          hostPath:
            path: /
      hostNetwork: true
      hostPID: true
---
apiVersion: v1
kind: Service
metadata:
  annotations:
    prometheus.io/scrape: "true"
  labels:
    k8s-app: node-exporter
  name: node-exporter
  namespace: monitoring 
spec:
  type: NodePort
  ports:
  - name: http
    port: 9100
    nodePort: 9100
    protocol: TCP
  selector:
    k8s-app: node-exporter

应用并验证

kubectl create -f daemonset-deploy-node-exporter.yaml

# 验证
kubectl get pod -n monitoring -owide

Prometheus Server 部署​

vim prometheus-cfg.yaml

---
kind: ConfigMap
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus-config
  namespace: monitoring 
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s
      scrape_timeout: 10s
      evaluation_interval: 1m
    scrape_configs:
    - job_name: 'kubernetes-node'
      kubernetes_sd_configs:
      - role: node
      relabel_configs:
      - source_labels: [__address__]
        regex: '(.*):10250'
        replacement: '${1}:9100'
        target_label: __address__
        action: replace
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
    - job_name: 'kubernetes-node-cadvisor'
      kubernetes_sd_configs:
      - role:  node
      scheme: https
      tls_config:
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      relabel_configs:
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
      - target_label: __address__
        replacement: kubernetes.default.svc:443
      - source_labels: [__meta_kubernetes_node_name]
        regex: (.+)
        target_label: __metrics_path__
        replacement: /api/v1/nodes/${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-apiserver'
      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

拉取镜像并配置

# 选择在 node3 上安装 prome
mkdir -p /data/prometheusdata
chmod 777 /data/prometheusdata # 准备数据目录
docker pull prom/prometheus:v2.31.2

# 创建监控账号
kubectl create serviceaccount monitor -n monitoring

# 账号授权
kubectl create clusterrolebinding monitor-clusterrolebinding -n monitoring --clusterrole=cluster-admin --serviceaccount=monitoring:monitor

编写部署yaml

vim prometheus-deployment.yaml

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prometheus-server
  namespace: monitoring
  labels:
    app: prometheus
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus
      component: server
    #matchExpressions:
    #- {key: app, operator: In, values: [prometheus]}
    #- {key: component, operator: In, values: [server]}
  template:
    metadata:
      labels:
        app: prometheus
        component: server
      annotations:
        prometheus.io/scrape: 'false'
    spec:
      nodeName: k8s-slave3   # 写node3的hostname，master配置hosts
      serviceAccountName: monitor
      containers:
      - name: prometheus
        image: prom/prometheus:v2.31.2
        imagePullPolicy: IfNotPresent
        command:
          - prometheus
          - --config.file=/etc/prometheus/prometheus.yml
          - --storage.tsdb.path=/prometheus
          - --storage.tsdb.retention=720h
        ports:
        - containerPort: 9090
          protocol: TCP
        volumeMounts:
        - mountPath: /etc/prometheus/prometheus.yml
          name: prometheus-config
          subPath: prometheus.yml
        - mountPath: /prometheus/
          name: prometheus-storage-volume
      volumes:
        - name: prometheus-config
          configMap:
            name: prometheus-config
            items:
              - key: prometheus.yml
                path: prometheus.yml
                mode: 0644
        - name: prometheus-storage-volume
          hostPath:
           path: /data/prometheusdata
           type: Directory

应用并验证

kubectl create -f prometheus-deployment.yaml

# 验证
kubectl get pod -n monitoring

Prometheus svc​

vim prometheus-svc.yaml

---
apiVersion: v1
kind: Service
metadata:
  name: prometheus
  namespace: monitoring
  labels:
    app: prometheus
spec:
  type: NodePort
  ports:
    - port: 9090
      targetPort: 9090
      nodePort: 30090
      protocol: TCP
  selector:
    app: prometheus
    component: server

应用并验证

kubectl create -f prometheus-svc.yaml

# 验证
kubectl get svc -n monitoring

Mysql 主从复制原理

· 阅读需 2 分钟

Mysql 主从复制原理​

画一个图 ![在这里插入图片描述](/img/Mysql 主从复制原理/1.jpg)

用语言表述一下吧

  1. change master to 时，ip pot user password binlog position写入到master.info进行记录
  1. start slave 时，从库会启动IO线程和SQL线程
  2. IO_T，读取master.info信息，获取主库信息连接主库
  3. 主库会生成一个准备binlog DUMP线程，来响应从库
  4. IO_T根据master.info记录的binlog文件名和position号，请求主库DUMP最新日志
  5. DUMP线程检查主库的binlog日志，如果有新的，TP(传送)给从从库的IO_T
  6. IO_T将收到的日志存储到了TCP/IP 缓存，立即返回ACK给主库 ，主库工作完成
  7. IO_T将缓存中的数据，存储到relay-log日志文件,更新master.info文件binlog 文件名和postion，IO_T工作完成
  8. SQL_T读取relay-log.info文件，获取到上次执行到的relay-log的位置，作为起点，回放relay-log
  9. SQL_T回放完成之后，会更新relay-log.info文件。
  10. relay-log会有自动清理的功能。

Tips：

  1. 主库一旦有新的日志生成，会发送“信号”给binlog dump ，IO线程再请求