• prometheus安装和使用记录


    Getting started | Prometheus

     
    复制代码
    # prometheus
    mkdir
    -m=777 -p /data/{download,app_logs,app/prometheus} cd /data/download wget https://github.com/prometheus/prometheus/releases/download/v2.45.0-rc.0/prometheus-2.45.0-rc.0.linux-amd64.tar.gz tar xvfz prometheus-*.tar.gz
    ln -s /data/download/prometheus-2.45.0-rc.0.linux-amd64/prometheus /usr/bin/prometheus
    cp
    /data/download/prometheus-2.45.0-rc.0.linux-amd64/prometheus.yml /data/app/prometheus/prometheus.yml
    prometheus --config.file=/data/app/prometheus/prometheus.yml --web.listen-address=:9090 --web.enable-lifecycle --storage.tsdb.path=/data/app/prometheus/data >>/data/app_logs/prometheus.log 2>&1 &

    # node_exporter 在需要监控的服务器里安装
    mkdir -m=777 -p /data/{download,app_logs,app/prometheus}
    cd /data/download
    wget https://github.com/prometheus/node_exporter/releases/download/v1.6.0/node_exporter-1.6.0.linux-amd64.tar.gz
    tar xvfz node_exporter*
    ln -s /data/download/node_exporter-1.6.0.linux-amd64/node_exporter /usr/bin/node_exporter
    # 启动node_exporter,服务器暴露的端口是8080,同时服务器里有其他服务占用了8080端口,可以使用nginx将node_exporter获取指标的api暴露出去
    # location /metrics {
    # proxy_pass http://127.0.0.1:9000/metrics;
    # }
    node_exporter --web.listen-address 127.0.0.1:9000 >>/data/app_logs/node_exporter.log 2>&1 &
    # 添加node_exporter之后,需要更新prometheus.xml添加targets,然后运行:curl -X PUT http://server_address:port/-/reload重新加载配置文件

    #
    alert_manager可以和prometheus安装到同一台服务器
    cd /data/download
    wget https://github.com/prometheus/alertmanager/releases/download/v0.25.0/alertmanager-0.25.0.linux-amd64.tar.gz
    tar xvfz alertmanager*
    ln -s /data/download/alertmanager-0.25.0.linux-amd64/alertmanager /usr/bin/alertmanager
    cp /data/download/alertmanager-0.25.0.linux-amd64/alertmanager.yml /data/app/prometheus/alertmanager.yml
    alertmanager --config.file=/data/app/prometheus/alertmanager.yml --web.listen-address 127.0.0.1:9001 >>/data/app_logs/node_exporter.log 2>&1 &
    # 将alert_manager的地址添加到prometheus.yml里的alertmanagers的targets里,然后运行:curl -X PUT http://server_address:port/-/reload重新加载配置文件
    复制代码

    测试报警邮件功能:设置如果安装exporter的服务器内存占用率超过50%或者tcp timewait超过10的时候就发邮件(在实际工作中需要设置一个合适的条件):

    prometheus.yml里添加rule_files的路径:

    复制代码
    # my global config
    global:
      scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
      evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
      # scrape_timeout is set to the global default (10s).
    # Alertmanager configuration
    alerting:
      alertmanagers:
        - static_configs:
            - targets:
              - 127.0.0.1:9001
    
    # Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
    rule_files:
      # - "first_rules.yml"
      # - "second_rules.yml"
      - "/data/app/prometheus/alert.rules.yml"
    
    # A scrape configuration containing exactly one endpoint to scrape:
    # Here it's Prometheus itself.
    scrape_configs:
      # The job name is added as a label `job=` to any timeseries scraped from this config.
      - job_name: "prometheus"
    
        # metrics_path defaults to '/metrics'
        # scheme defaults to 'http'.
        scrape_interval: 5s
    
        static_configs:
                - targets: ["node1_ip:8080"]
                - targets: ["node2_ip:8080"]
                  labels:
                    groups: 'container'
    复制代码

    alert.rules.yml里添加具体的rule,node_socket_TCP_tw这些具体的指标通过http://node_exporter_ip:port/metrics可以获取到

    复制代码
    groups:
    - name: tcp-alert-group
      rules:
      - alert: TcpTimeWait
        expr: node_sockstat_TCP_tw > 10
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: tcp time wait more than 10
          description: please check node_sockstat_TCP_tw metric
      - alert: MemoryUse
        expr: (node_memory_MemTotal_bytes-node_memory_MemFree_bytes-node_memory_Buffers_bytes-node_memory_Cached_bytes)/node_memory_MemTotal_bytes > 0.5
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: memory use more than 50% for 10 min
          description: please check memory use
    复制代码

    alertmanager.yml里配置告警邮件的信息:

    复制代码
    global:
      resolve_timeout: 5m
      smtp_smarthost: your_smpt_host:port
      smtp_from: alertmanager@your_email_domain
      smtp_require_tls: false
    route:
      group_by: ['alertname']
      group_wait: 30s
      group_interval: 5m
      repeat_interval: 10m
      receiver: 'email'
    receivers:
      - name: 'email'
        email_configs:
        - to: 'receiver_email'
          send_resolved: true
    复制代码

    yml文件一旦更新,需要重新加载配置:curl -X PUT http://server_address:port/-/reload

    在Prometheus的界面可以看到添加的alert:

     当alert的条件满足后,alertmanager就会发邮件

     

    grafana的安装和启动:

    复制代码
    # grafana可以和prometheus里安装到同一台服务器
    yum install -y https://dl.grafana.com/enterprise/release/grafana-enterprise-10.0.0-1.x86_64.rpm
    # grafana默认启动的端口号是3000,如果服务器没有暴露3000端口的话,需要修改grafana的配置文件
    sed -i 's/3000/8080/g' /usr/share/grafana/conf/defaults.ini
    grafana server >> /data/app_logs/grafana.log 2>&1 &
    # grafana数据保存地址:/var/lib/grafana.db
    复制代码

    grafana启动之后就可以在浏览器上打开对应的地址,初次登录用户名和密码:admin/admin

    Data sources里添加prometheus,grafana和prometheus启动在同一台服务器里的话,地址就可以用localhost

     添加dashboard,在Explore里可以查询指标并且添加到dashboard

    cpu使用率:avg(1-irate(node_cpu_seconds_total{mode="idle"}[1m])) by(instance)

    内存使用率:(node_memory_MemTotal_bytes-node_memory_MemFree_bytes-node_memory_Buffers_bytes-node_memory_Cached_bytes)/node_memory_MemTotal_bytes

    tcp连接数:node_sockstat_TCP_alloc

     dashboard:

     

     

    注意点:

    1.prometheus启动的时候添加--web.enable-lifecycle才允许通过调用/-/reload接口重新加载配置文件
    2.prometheus启动的时候指定一个固定的数据存放位置--storage.tsdb.path=/data/app/prometheus/data,如果数据存放位置不一致,启动后查不到历史数据,历史数据做备份的话,prometheus启动的服务器还可以变更
    3.grafana的数据保存地址:/var/lib/grafana.db,定期做备份,服务器发生系统错误无法使用的时候,在新的服务器里同步/var/lib/grafana.db文件之后,启动grafana之前的配置不会丢失
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  • 原文地址:https://www.cnblogs.com/huizit1/p/17492003.html