---

前言

Alertmanager是一个独立的告警模块，接收Prometheus等客户端发来的警报，之后通过分组、删除重复等处理，并将它们通过路由发送给正确的接收器；告警方式可以按照不同的规则发送给不同的模块负责人，Alertmanager支持Email, Slack等告警方式, 也可以通过webhook接入钉钉等国内IM工具。
Github地址：https://github.com/prometheus/alertmanager
最新版本：0.23.0

一、安装AlertManager

1、下载

下载地址列表页：https://github.com/prometheus/alertmanager/releases
0.23.0版本下载地址：https://github.com/prometheus/alertmanager/releases/download/v0.23.0/alertmanager-0.23.0.linux-amd64.tar.gz

2、安装AlertManager

将上一步下载的包上传至服务器

tar zvxf alertmanager-0.23.0.linux-amd64.tar.gz
mv alertmanager-0.23.0.linux-amd64 /usr/local/alertmanager

vi /etc/systemd/system/alertmanager.service

添加：

[Unit]
Description=Alertmanager
After=network.target[Service]
Type=simple
#User=prometheus
#Group=prometheus
ExecStart=/usr/local/alertmanager/alertmanager \--config.file=/usr/local/alertmanager/alertmanager.yml \--storage.path=/usr/local/alertmanager/data \--web.listen-address=0.0.0.0:9093 \--cluster.listen-address=0.0.0.0:9094 \--log.level=info \--log.format=logfmt
Restart=always[Install]
WantedBy=multi-user.target

  systemctl daemon-reloadsystemctl enable alertmanager && systemctl start alertmanager

访问http://172.16.10.171:9093/metrics

二、配置AlertManager

1、配置Prometheus

修改prometheus.yml配置文件，修改alerting的配置。

vi /usr/local/prometheus/prometheus.yml

将刚启动的alertmanager配置进去

# 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: ["172.16.10.171:9093"]# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:# - "first_rules.yml"# - "second_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=<job_name>` to any timeseries scraped from this config.- job_name: "prometheus"# metrics_path defaults to '/metrics'# scheme defaults to 'http'.static_configs:- targets: ["localhost:9090"]- job_name: "spring"scrape_interval: 15sscrape_timeout: 10smetrics_path: "/demo/actuator/prometheus"static_configs:- targets: ["192.168.100.88:7901"]- job_name: "mysql8.x"static_configs:- targets: ["172.16.10.169:9104", "192.168.100.88:9104"]- job_name: "nginx"static_configs:- targets: ["172.16.10.171:9913"]- job_name: "node"static_configs:- targets: ["172.16.10.171:9100","172.16.10.160:9100","172.16.10.161:9100", "172.16.10.162:9100", "172.16.10.163:9100", "172.16.10.164:9100", "172.16.10.165:9100", "172.16.10.167:9100", "172.16.10.168:9100", "172.16.10.169:9100", "172.16.10.170:9100"]- job_name: "alertmanager"static_configs:- targets: ["172.16.10.171:9093"]

重启prometheus

systemctl restart prometheus

访问http://172.16.10.171:9090/targets

2、配置通知路由和接收器

alertmanager通过命令行标志和配置文件进行配置。命令行标志配置不可变的系统参数时，配置文件定义禁止规则，通知路由和通知接收器。
alertmanager.yml的配置信息包含以下几部分：

global	全局配置
templates	通知模板
route	路由配置
receivers	接收器配置
inibit_rules	抑制配置

2.1、global

global指定在所有其他配置上下文中有效的参数。还用作其他配置部分的默认设置。

global:# 默认的SMTP头字段[ smtp_from: <tmpl_string> ]# 默认的SMTP smarthost用于发送电子邮件，包括端口号# 端口号通常是25，对于TLS上的SMTP，端口号为587# Example: smtp.example.org:587[ smtp_smarthost: <string> ]# 要标识给SMTP服务器的默认主机名[ smtp_hello: <string> | default = "localhost" ]# SMTP认证使用CRAM-MD5，登录和普通。如果为空，Alertmanager不会对SMTP服务器进行身份验证[ smtp_auth_username: <string> ]# SMTP Auth using LOGIN and PLAIN.[ smtp_auth_password: <secret> ]# SMTP Auth using PLAIN.[ smtp_auth_identity: <string> ]# SMTP Auth using CRAM-MD5.[ smtp_auth_secret: <secret> ]# 默认的SMTP TLS要求# 注意，Go不支持到远程SMTP端点的未加密连接[ smtp_require_tls: <bool> | default = true ]# 用于Slack通知的API URL[ slack_api_url: <secret> ][ victorops_api_key: <secret> ][ victorops_api_url: <string> | default = "https://alert.victorops.com/integrations/generic/20131114/alert/" ][ pagerduty_url: <string> | default = "https://events.pagerduty.com/v2/enqueue" ][ opsgenie_api_key: <secret> ][ opsgenie_api_url: <string> | default = "https://api.opsgenie.com/" ][ wechat_api_url: <string> | default = "https://qyapi.weixin.qq.com/cgi-bin/" ][ wechat_api_secret: <secret> ][ wechat_api_corp_id: <string> ]# 默认HTTP客户端配置[ http_config: <http_config> ]# 如果告警不包括EndsAt，则ResolveTimeout是alertmanager使用的默认值，在此时间过后，如果告警没有更新，则可以声明警报已解除# 这对Prometheus的告警没有影响，它们包括EndsAt[ resolve_timeout: <duration> | default = 5m ]

2.2、templates

templates指定了从其中读取自定义通知模板定义的文件，最后一个文件可以使用一个通配符匹配器，如templates/*.tmpl

templates:[ - <filepath> ... ]

2.3、route

route定义了路由树中的节点及其子节点。如果未设置，则其可选配置参数将从其父节点继承。
每个告警都会在已配置的顶级路由处进入路由树，该路由树必须与所有告警匹配（即没有任何已配置的匹配器），然后它会遍历子节点。如果continue设置为false，它将在第一个匹配的子项之后停止；如果continue设置为true，则告警将继续与后续的同级进行匹配。如果告警与节点的任何子节点都不匹配（不匹配的子节点或不存在子节点），则根据当前节点的配置参数来处理告警。

route:group_by: ['alertname']group_wait: 10sgroup_interval: 10srepeat_interval: 1hreceiver: 'web.hook'

2.4、receivers

receivers是一个或多个通知集成的命名配置。建议通过webhook接收器实现自定义通知集成。

receivers:
- name: 'web.hook'webhook_configs:- url: 'http://127.0.0.1:5001/'

2.5、inhibit_rules

当存在与另一组匹配器匹配的告警（源）时，抑制规则会使与一组匹配器匹配的告警（目标）“静音”。目标和源告警的equal列表中的标签名称都必须具有相同的标签值。
在语义上，缺少标签和带有空值的标签是相同的。因此，如果equal源告警和目标告警都缺少列出的所有标签名称，则将应用抑制规则。

inhibit_rules:- source_match:severity: 'critical'target_match:severity: 'warning'equal: ['alertname', 'dev', 'instance']

2.6、配置示例(邮件告警)

2.6.1配置alertmanager

vi /usr/local/alertmanager/alertmanager.yml

global:smtp_smarthost: "smtp.163.com:25"smtp_from: "18500971310@163.com"smtp_auth_username: "18500971310@163.com"smtp_auth_password: "12345678a"smtp_require_tls: falsesmtp_hello: "163.com"resolve_timeout: 5mroute:group_by: ['instance']group_wait: 10sgroup_interval: 10srepeat_interval: 1hreceiver: 'mail'
receivers:
- name: 'mail'email_configs:- send_resolved: trueto: '76775081@qq.com'
inhibit_rules:- source_match:severity: 'critical'target_match:severity: 'warning'equal: ['alertname', 'dev', 'instance']

systemctl restart alertmanager

2.6.2配置prometheus的rule_files

修改prometheus.yml，添加rule_files配置
vi /usr/local/prometheus/prometheus.yml

# 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: ["172.16.10.171:9093"]# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:- "*rule.yml"# - "first_rules.yml"# - "second_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=<job_name>` to any timeseries scraped from this config.- job_name: "prometheus"# metrics_path defaults to '/metrics'# scheme defaults to 'http'.static_configs:- targets: ["localhost:9090"]- job_name: "spring"scrape_interval: 15sscrape_timeout: 10smetrics_path: "/demo/actuator/prometheus"static_configs:- targets: ["192.168.100.88:7901"]- job_name: "mysql8.x"static_configs:- targets: ["172.16.10.169:9104", "192.168.100.88:9104"]- job_name: "nginx"static_configs:- targets: ["172.16.10.171:9913"]- job_name: "node"static_configs:- targets: ["172.16.10.171:9100","172.16.10.160:9100","172.16.10.161:9100", "172.16.10.162:9100", "172.16.10.163:9100", "172.16.10.164:9100", "172.16.10.165:9100", "172.16.10.167:9100", "172.16.10.168:9100", "172.16.10.169:9100", "172.16.10.170:9100"]- job_name: "alertmanager"static_configs:- targets: ["172.16.10.171:9093"]

systemctl restart prometheus

2.6.3配置记录规则和报警规则

配置告警规则
在prometheus.yml同级目录下创建两个报警规则配置文件node-exporter-record-rule.yml，node-exporter-alert-rule.yml。第一个文件用于记录规则，第二个是报警规则。
由于之前在prometheus.yml中已经引用了所有已rule结尾的文件，所以我们不用在修改prometheus.yml配置文件。

vi /usr/local/Prometheus/node-exporter-record-rule.yml

添加内容如下：

groups:- name: node-exporter-recordrules:- expr: up{job=~"node"}record: node_exporter:uplabels:desc: "节点是否在线, 在线1,不在线0"unit: " "job: "node-exporter"- expr: time() - node_boot_time_seconds{}record: node_exporter:node_uptimelabels:desc: "节点的运行时间"unit: "s"job: "node-exporter"
##############################################################################################
#                              cpu                                                           #- expr: (1 - avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode="idle"}[5m])))  * 100record: node_exporter:cpu:total:percentlabels:desc: "节点的cpu总消耗百分比"unit: "%"job: "node"- expr: (avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode="idle"}[5m])))  * 100record: node_exporter:cpu:idle:percentlabels:desc: "节点的cpu idle百分比"unit: "%"job: "node"- expr: (avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode="iowait"}[5m])))  * 100record: node_exporter:cpu:iowait:percentlabels:desc: "节点的cpu iowait百分比"unit: "%"job: "node"- expr: (avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode="system"}[5m])))  * 100record: node_exporter:cpu:system:percentlabels:desc: "节点的cpu system百分比"unit: "%"job: "node"- expr: (avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode="user"}[5m])))  * 100record: node_exporter:cpu:user:percentlabels:desc: "节点的cpu user百分比"unit: "%"job: "node"- expr: (avg by (environment,instance) (irate(node_cpu_seconds_total{job="node-exporter",mode=~"softirq|nice|irq|steal"}[5m])))  * 100record: node_exporter:cpu:other:percentlabels:desc: "节点的cpu 其他的百分比"unit: "%"job: "node"
############################################################################################################################################################################################
#                                    memory                                                  #- expr: node_memory_MemTotal_bytes{job="node-exporter"}record: node_exporter:memory:totallabels:desc: "节点的内存总量"unit: bytejob: "node"- expr: node_memory_MemFree_bytes{job="node-exporter"}record: node_exporter:memory:freelabels:desc: "节点的剩余内存量"unit: bytejob: "node"- expr: node_memory_MemTotal_bytes{job="node-exporter"} - node_memory_MemFree_bytes{job="node-exporter"}record: node_exporter:memory:usedlabels:desc: "节点的已使用内存量"unit: bytejob: "node"- expr: node_memory_MemTotal_bytes{job="node-exporter"} - node_memory_MemAvailable_bytes{job="node-exporter"}record: node_exporter:memory:actualusedlabels:desc: "节点用户实际使用的内存量"unit: bytejob: "node"- expr: (1-(node_memory_MemAvailable_bytes{job="node-exporter"} / (node_memory_MemTotal_bytes{job="node-exporter"})))* 100record: node_exporter:memory:used:percentlabels:desc: "节点的内存使用百分比"unit: "%"job: "node"- expr: ((node_memory_MemAvailable_bytes{job="node-exporter"} / (node_memory_MemTotal_bytes{job="node-exporter"})))* 100record: node_exporter:memory:free:percentlabels:desc: "节点的内存剩余百分比"unit: "%"job: "node"
##############################################################################################
#                                   load                                                     #- expr: sum by (instance) (node_load1{job="node-exporter"})record: node_exporter:load:load1labels:desc: "系统1分钟负载"unit: " "job: "node"- expr: sum by (instance) (node_load5{job="node-exporter"})record: node_exporter:load:load5labels:desc: "系统5分钟负载"unit: " "job: "node"- expr: sum by (instance) (node_load15{job="node-exporter"})record: node_exporter:load:load15labels:desc: "系统15分钟负载"unit: " "job: "node"##############################################################################################
#                                 disk                                                       #- expr: node_filesystem_size_bytes{job="node-exporter" ,fstype=~"ext4|xfs"}record: node_exporter:disk:usage:totallabels:desc: "节点的磁盘总量"unit: bytejob: "node"- expr: node_filesystem_avail_bytes{job="node-exporter",fstype=~"ext4|xfs"}record: node_exporter:disk:usage:freelabels:desc: "节点的磁盘剩余空间"unit: bytejob: "node"- expr: node_filesystem_size_bytes{job="node-exporter",fstype=~"ext4|xfs"} - node_filesystem_avail_bytes{job="node-exporter",fstype=~"ext4|xfs"}record: node_exporter:disk:usage:usedlabels:desc: "节点的磁盘使用的空间"unit: bytejob: "node"- expr:  (1 - node_filesystem_avail_bytes{job="node-exporter",fstype=~"ext4|xfs"} / node_filesystem_size_bytes{job="node-exporter",fstype=~"ext4|xfs"}) * 100record: node_exporter:disk:used:percentlabels:desc: "节点的磁盘的使用百分比"unit: "%"job: "node"- expr: irate(node_disk_reads_completed_total{job="node-exporter"}[1m])record: node_exporter:disk:read:count:ratelabels:desc: "节点的磁盘读取速率"unit: "次/秒"job: "node"- expr: irate(node_disk_writes_completed_total{job="node-exporter"}[1m])record: node_exporter:disk:write:count:ratelabels:desc: "节点的磁盘写入速率"unit: "次/秒"job: "node"- expr: (irate(node_disk_written_bytes_total{job="node-exporter"}[1m]))/1024/1024record: node_exporter:disk:read:mb:ratelabels:desc: "节点的设备读取MB速率"unit: "MB/s"job: "node"- expr: (irate(node_disk_read_bytes_total{job="node-exporter"}[1m]))/1024/1024record: node_exporter:disk:write:mb:ratelabels:desc: "节点的设备写入MB速率"unit: "MB/s"job: "node"##############################################################################################
#                                filesystem                                                  #- expr:   (1 -node_filesystem_files_free{job="node-exporter",fstype=~"ext4|xfs"} / node_filesystem_files{job="node-exporter",fstype=~"ext4|xfs"}) * 100record: node_exporter:filesystem:used:percentlabels:desc: "节点的inode的剩余可用的百分比"unit: "%"job: "node"
#############################################################################################
#                                filefd                                                     #- expr: node_filefd_allocated{job="node-exporter"}record: node_exporter:filefd_allocated:countlabels:desc: "节点的文件描述符打开个数"unit: "%"job: "node"- expr: node_filefd_allocated{job="node-exporter"}/node_filefd_maximum{job="node-exporter"} * 100record: node_exporter:filefd_allocated:percentlabels:desc: "节点的文件描述符打开百分比"unit: "%"job: "node"#############################################################################################
#                                network                                                    #- expr: avg by (environment,instance,device) (irate(node_network_receive_bytes_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netin:bit:ratelabels:desc: "节点网卡eth0每秒接收的比特数"unit: "bit/s"job: "node"- expr: avg by (environment,instance,device) (irate(node_network_transmit_bytes_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netout:bit:ratelabels:desc: "节点网卡eth0每秒发送的比特数"unit: "bit/s"job: "node"- expr: avg by (environment,instance,device) (irate(node_network_receive_packets_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netin:packet:ratelabels:desc: "节点网卡每秒接收的数据包个数"unit: "个/秒"job: "node"- expr: avg by (environment,instance,device) (irate(node_network_transmit_packets_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netout:packet:ratelabels:desc: "节点网卡发送的数据包个数"unit: "个/秒"job: "node"- expr: avg by (environment,instance,device) (irate(node_network_receive_errs_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netin:error:ratelabels:desc: "节点设备驱动器检测到的接收错误包的数量"unit: "个/秒"job: "node"- expr: avg by (environment,instance,device) (irate(node_network_transmit_errs_total{device=~"eth0|eth1|ens33|ens37"}[1m]))record: node_exporter:network:netout:error:ratelabels:desc: "节点设备驱动器检测到的发送错误包的数量"unit: "个/秒"job: "node"- expr: node_tcp_connection_states{job="node-exporter", state="established"}record: node_exporter:network:tcp:established:countlabels:desc: "节点当前established的个数"unit: "个"job: "node"- expr: node_tcp_connection_states{job="node-exporter", state="time_wait"}record: node_exporter:network:tcp:timewait:countlabels:desc: "节点timewait的连接数"unit: "个"job: "node"- expr: sum by (environment,instance) (node_tcp_connection_states{job="node-exporter"})record: node_exporter:network:tcp:total:countlabels:desc: "节点tcp连接总数"unit: "个"job: "node"#############################################################################################
#                                process                                                    #- expr: node_processes_state{state="Z"}record: node_exporter:process:zoom:total:countlabels:desc: "节点当前状态为zoom的个数"unit: "个"job: "node"
#############################################################################################
#                                other                                                    #- expr: abs(node_timex_offset_seconds{job="node-exporter"})record: node_exporter:time:offsetlabels:desc: "节点的时间偏差"unit: "s"job: "node"#############################################################################################- expr: count by (instance) ( count by (instance,cpu) (node_cpu_seconds_total{ mode='system'}) )record: node_exporter:cpu:count

配置告警规则
vi /usr/local/prometheus/node-exporter-alert-rule.yml
配置内容如下：

groups:- name: node-exporter-alertrules:- alert: node-exporter-downexpr: node_exporter:up == 0for: 1mlabels:severity: 'critical'annotations:summary: "instance: {{ $labels.instance }} 宕机了"description: "instance: {{ $labels.instance }} \n- job: {{ $labels.job }} 关机了， 时间已经1分钟了。"value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-cpu-highexpr:  node_exporter:cpu:total:percent > 80for: 3mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} cpu 使用率高于 {{ $value }}"description: "instance: {{ $labels.instance }} \n- job: {{ $labels.job }} CPU使用率已经持续三分钟高过80% 。"value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-cpu-iowait-highexpr:  node_exporter:cpu:iowait:percent >= 12for: 3mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} cpu iowait 使用率高于 {{ $value }}"description: "instance: {{ $labels.instance }} \n- job: {{ $labels.job }} cpu iowait使用率已经持续三分钟高过12%"value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-load-load1-highexpr:  (node_exporter:load:load1) > (node_exporter:cpu:count) * 1.2for: 3mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} load1 使用率高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-memory-highexpr:  node_exporter:memory:used:percent > 85for: 3mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} memory 使用率高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-disk-highexpr:  node_exporter:disk:used:percent > 88for: 10mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} disk 使用率高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-disk-read:count-highexpr:  node_exporter:disk:read:count:rate > 3000for: 2mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} iops read 使用率高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-disk-write-count-highexpr:  node_exporter:disk:write:count:rate > 3000for: 2mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} iops write 使用率高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-disk-read-mb-highexpr:  node_exporter:disk:read:mb:rate > 60for: 2mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 读取字节数 高于 {{ $value }}"description: ""instance: "{{ $labels.instance }}"value: "{{ $value }}"- alert: node-exporter-disk-write-mb-highexpr:  node_exporter:disk:write:mb:rate > 60for: 2mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 写入字节数 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-filefd-allocated-percent-highexpr:  node_exporter:filefd_allocated:percent > 80for: 10mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 打开文件描述符 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-network-netin-error-rate-highexpr:  node_exporter:network:netin:error:rate > 4for: 1mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 包进入的错误速率 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-network-netin-packet-rate-highexpr:  node_exporter:network:netin:packet:rate > 35000for: 1mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 包进入速率 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-network-netout-packet-rate-highexpr:  node_exporter:network:netout:packet:rate > 35000for: 1mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 包流出速率 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-network-tcp-total-count-highexpr:  node_exporter:network:tcp:total:count > 40000for: 1mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} tcp连接数量 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-process-zoom-total-count-highexpr:  node_exporter:process:zoom:total:count > 10for: 10mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} 僵死进程数量 高于 {{ $value }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"- alert: node-exporter-time-offset-highexpr:  node_exporter:time:offset > 0.03for: 2mlabels:severity: infoannotations:summary: "instance: {{ $labels.instance }} {{ $labels.desc }}  {{ $value }} {{ $labels.unit }}"description: ""value: "{{ $value }}"instance: "{{ $labels.instance }}"

重启prometheus

Systemctl restart prometheus

访问http://172.16.10.171:9090/alerts

这说明配置成功了。
测试关掉一个node_exporter
systemctl stop node_exporter
等待1分钟左右，
先变成pending,再变成firing


过一会收到邮件

当重启后

systemctl restart node_exporter

会收到恢复邮件