node exporter完整版

标签：memfree   注意   sysfs   加载   curl   lob   def   ever   获取数据   

1）docker方式运行node exporter

docker run -d     --name node-exporter  -p 9100:9100   -v "/proc:/host/proc:ro"   -v "/sys:/host/sys:ro"   -v "/:/rootfs:ro"   --restart=always   --net="host"   prom/node-exporter --path.procfs /host/proc --path.sysfs /host/sys --collector.filesystem.ignored-mount-points "^/(sys|proc|dev|host|etc)($|/)" 

2）验证, 可以通过对外暴露的api接口获取数据

curl http://192.168.1.42:9100/metrics

#（2）安装consul
consul作用： 服务注册中心,向外提供服务的增删api接口, prometheus可以向consul动态获取节点信息以及自动加载配置

1）docker安装consul

 docker run  --restart=always --name consul -d -p 8500:8500 consul

2）向consul的api接口添加服务

curl -X PUT -d ‘{"id": "node03","name": "node03","address": "192.168.1.42","port": 9100,"tags": ["test"],"checks": [{"http": "http://192.168.1.42:9100/","interval": "5s"}]}‘ http://localhost:8500/v1/agent/service/register

扩展： 删除服务节点

 curl -X PUT  http://localhost:8500/v1/agent/service/deregister/node02

3）服务注册成功

#（3）安装和配置altermanger

altermanager作用： 接收prometheus发送的告警信息, 通过相关方式例如邮件和微信等方式发送给接收者;
0）准备目录

test -d /etc/alertmanager || mkdir -pv /etc/alertmanager

1）准备配置文件

# cat /etc/alertmanager/alertmanager.yml 
global:
        resolve_timeout: 5m

templates:
- ‘/etc/alertmanager/wechat.tmpl‘

route:
        group_by: [‘alertname‘]
        group_wait: 10s
        group_interval: 10s
        repeat_interval: 1h
        receiver: ‘wechat‘
receivers:
- name: ‘wechat‘
        wechat_configs:
        - corp_id: ‘wwc08fcb42fc6fe93c‘
                to_party: ‘2‘
                agent_id: ‘1000002‘
                api_secret: ‘cLG91Xgcd3o3zPJp6NbOJV9m7SBIlhtCScxov3Hp-XQ‘
                send_resolved: true

2）准备模板文件

# cat /etc/alertmanager/wechat.tmpl 
{{ define "wechat.default.message" }}
{{ range .Alerts }}
========start==========
告警程序：prometheus_alert
告警级别：{{ .Labels.severity }}
告警类型：{{ .Labels.alertname }}
故障主机: {{ .Labels.instance }}
告警主题: {{ .Annotations.summary }}
告警详情: {{ .Annotations.description }}
触发时间: {{ .StartsAt.Format "2006-01-02 15:04:05" }}
========end==========
{{ end }}
{{ end }}

3)启动容器

docker run --restart=always   -d -p 9093:9093 -v /etc/alertmanager/alertmanager.yml:/etc/alertmanager/alertmanager.yml -v /etc/alertmanager/wechat.tmpl:/etc/alertmanager/wechat.tmpl --name alertmanager prom/alertmanager

4）验证容器是否有报错

docker logs -f alertmanager

#（4）安装和配置prometheus
prometheus作用： 用于向exporter获取数据并保存数据, 同时可以设置规则和触发器, 向报警器发送信息;

1）准备目录

test -d /etc/prometheus || mkdir /etc/prometheus -pv

2）准备prometheus配置文件

rule_files ： 报警规则文件
alerting: 当触发报警, 把报警相关发送给altermanager, 由altermanager接收告警信息在发送给接收人;
job_name: consul : prometheus 向consul注册;

# cat /etc/prometheus/prometheus.yml 
global:
        scrape_interval:     15s
        evaluation_interval: 15s
rule_files:
        - "/etc/prometheus/*.rules"
alerting:
        alertmanagers:
        - static_configs:
                - targets:
                        - "192.168.1.82:9093"
scrape_configs:
        - job_name: prometheus
                static_configs:
                        - targets: [‘localhost:9090‘]
                                labels:
                                        instance: prometheus
        - job_name: ‘consul‘
                consul_sd_configs:
                        - server: ‘192.168.1.82:8500‘
                                services: []

                relabel_configs:
                        - source_labels: [__meta_consul_tags]
                                regex: .*test.*
                                action: keep

3）准备告警规则文件 , 注意该文件不能有tag键， 同时key和value之间必须要有空格

# cat /etc/prometheus/prometheus.rules 
groups:
- name: alert-rule
    rules:
    - alert: NodeFilesystemUsage-high
        expr: (1-  (node_filesystem_free_bytes{fstype=~"ext3|ext4|xfs"} / node_filesystem_size_bytes{fstype=~"ext3|ext4|xfs"}) ) * 100 > 80
        for: 2m
        labels:
            severity: warning
        annotations:
            summary: "{{$labels.instance}}: High Node Filesystem usage detected"
            description: "{{$labels.instance}}: Node Filesystem usage is above 80% ,(current value is: {{ $value }})"
    - alert: NodeMemoryUsage
        expr: (100 - (((node_memory_MemFree_bytes+node_memory_Buffers_bytes+node_memory_Cached_bytes)/node_memory_MemTotal_bytes) * 100))  > 80
        for: 2m
        labels:
            severity: warning
        annotations:
            summary: "{{$labels.instance}}: High Node Memory usage detected"
            description: "{{$labels.instance}}: Node Memory usage is above 80% ,(current value is: {{ $value }})"
    - alert: NodeCPUUsage
        expr: (100 - (avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m])) * 100))  > 80
        for: 2m
        labels:
            severity: warning
        annotations:
            summary: "{{$labels.instance}}: Node High CPU usage detected"
            description: "{{$labels.instance}}: Node CPU usage is above 80% ,(current value is: {{ $value }})"

4）docker方式启动prometheus

docker run  --restart=always --name prometheus -d -p 9090:9090 -v /etc/prometheus:/etc/prometheus  prom/prometheus 

5）登录到prometheus验证

rule这里能看到相关规则

#（4）下载安装和配置grafana

1）下载和启动grafana

 wget https://dl.grafana.com/oss/release/grafana-6.0.2-1.x86_64.rpm
 yum  install grafana-6.0.2-1.x86_64.rpm -y 
 systemctl start grafana-server 
 systemctl enable grafana-server 
 ss -anltup |grep 3000 

2)添加图形

https://grafana.com/dashboards 页面搜索node exporter 根据id导入模板 id 为8919

3）查看图形

9）安装饼图插件

grafana-cli plugins install grafana-piechart-panel
systemctl restart grafana-server

node exporter完整版

标签：memfree   注意   sysfs   加载   curl   lob   def   ever   获取数据   

原文地址：https://blog.51cto.com/1000682/2374406