部署prometheus、grafana、alertmanager
简介:由于资源有限,本实验用了两台机器
- 监控端:部署prometheus、grafana、alertmanager
- 被监控端:node_exporter、mysqld_exporter
一. 部署promethus
1. 下载
https://prometheus.io/download/
2. 解压
mkdir -p /data/prometheus
tar -zxvf /root/prometheus-2.42.0.linux-amd64.tar.gz -C /data/
cd /data
mv prometheus-2.42.0.linux-amd64/ prometheus
3. 部署
- 创建prometheus用户
useradd -s /sbin/nologin -M prometheus
mkdir -p /data/database/prometheus
chown -R prometheus:prometheus /data/database/prometheus/
- 配置systemctl启动项
vim /etc/systemd/system/prometheus.service
[Unit] Description=Prometheus Documentation=https://prometheus.io/ After=network.target [Service] Type=simple User=prometheus ExecStart=/data/prometheus/prometheus --web.enable-lifecycle --config.file=/data/prometheus/prometheus.yml --storage.tsdb.path=/data/database/prometheus Restart=on-failure [Install] WantedBy=multi-user.target
4. 加载配置&启动服务
systemctl daemon-reload
systemctl start prometheus
systemctl status prometheus
systemctl enable prometheus
-
访问web页面,IP:9090
-
查看到监控的数据,IP:9090/metrics
二. 监控linux主机
1. 下载node_exporter
wget https://github.com/prometheus/node_exporter/releases/download/v1.5.0/node_exporter-1.5.0.linux-amd64.tar.gz
2.解压
tar -zxvf node_exporter-1.5.0.linux-amd64.tar.gz -C /data/
mv /data/node_exporter-1.5.0.linux-amd64/ /data/node_exporter
3. 配置systemctl启动项
vim /etc/systemd/system/node_exporter.service
[Unit] Description=node_exporter [Service] ExecStart=/data/source.package/node_exporter-1.1.2.linux-amd64/node_exporter ExecReload=/bin/kill -HUP $MAINPID KillMode=process Restart=on-failure [Install] WantedBy=multi-user.target
4. 加载配置&启动服务
systemctl daemon-reload
systemctl start node_exporter.service
systemctl status node_exporter.service
systemctl enable node_exporter.service
- 查看到被监控的数据,IP:9100/metrics
5. 监控端配置
-
在主配置文件最后加上下面三行
vim /data/prometheus/prometheus.yml
- job_name: 'agent1' #取一个job名称来代表被监控的机器 static_configs: - targets: ['192.168.1.1:9100'] # 这里改成被监控机器的IP,后面端口接9100
- 测试prometheus.yaml文件有无报错
[root@VM-16-2-centos prometheus]# ./promtool check config prometheus.yml Checking prometheus.yml SUCCESS: prometheus.yml is valid prometheus config file syntax
6. 重新加载prometheus配置文件
-
curl -X POST http://127.0.0.1:9090/-/reload
,打开prometheus页面输入up查看是不是有对应的数据了 -
回到web管理界面 ——>点——>点Targets ——>可以看到多了一台监控目标
三. 监控mysql
1. 下载mysqld_exporter
wget https://github.com/prometheus/mysqld_exporter/releases/download/v0.14.0/mysqld_exporter-0.14.0.linux-amd64.tar.gz2
2. 解压
tar -zxvf mysqld_exporter-0.14.0.linux-amd64.tar.gz -C /data/
mv /data/mysqld_exporter-0.14.0.linux-amd64/ /data/mysqld_exporter
[root@VM-12-2-centos ~]# ls /data/mysqld_exporter/ LICENSE mysqld_exporter NOTICE
3. 安装mariadb数据库,并授权
yum -y install mariadb-server -y
systemctl start mariadb
[root@VM-12-2-centos ~]# mysql Welcome to the MariaDB monitor. Commands end with ; or \g. Your MariaDB connection id is 2 Server version: 5.5.68-MariaDB MariaDB Server Copyright (c) 2000, 2018, Oracle, MariaDB Corporation Ab and others. Type 'help;' or '\h' for help. Type '\c' to clear the current input statement. MariaDB [(none)]> MariaDB [(none)]> grant select,replication client,process ON *.* to 'mysql_monito'@'localhost' identified by '123'; Query OK, 0 rows affected (0.00 sec) MariaDB [(none)]> MariaDB [(none)]> flush privileges; Query OK, 0 rows affected (0.00 sec) MariaDB [(none)]> MariaDB [(none)]> exit Bye
4. 启动
nohup /usr/local/mysqld_exporter/mysqld_exporter --config.my-cnf=/usr/local/mysqld_exporter/.my.cnf &
5. 监控端配置
vim /data/prometheus/prometheus.yml
- job_name: 'mysql' #取一个job名称来代表被监控的机器 static_configs: - targets: ['192.168.1.1:9104'] # 这里改成被监控机器的IP,后面端口接9104
6. 重启prometheus
systemctl restart prometheus
- 回到web管理界面 ——>点——>点Targets ——>可以看到多了一台监控目标
四. 部署grafana
1. 下载
wget https://dl.grafana.com/enterprise/release/grafana-enterprise-9.3.6.linux-amd64.tar.gz
2. 解压
tar -zxvf grafana-enterprise-9.3.6.linux-amd64.tar.gz -C /data
mv grafana-9.3.6/ grafana
3. 修改初始化文件
- 备份
cp /data/grafana/conf/defaults.ini /data/grafana/conf/defaults.ini.bak
- 修改
vim /data/grafana/conf/defaults.ini
data = /data/database/grafana/data logs = /data/database/grafana/log plugins = /data/database/grafana/plugins provisioning = /data/grafana/conf/provisioning/
4. 配置systemctl启动项
vim /etc/systemd/system/grafana-server.service
[Unit] Description=Grafana After=network.target [Service] User=grafana Group=grafana Type=notify ExecStart=/data/grafana/bin/grafana-server -homepath /data/grafana/ Restart=on-failure [Install] WantedBy=multi-user.target
5. 加载配置&启动服务
systemctl daemon-reload
systemctl start grafana-server.service
systemctl status grafana-server.service
systemctl enable grafana-server.service
-
web页面:ip+3000
- 默认账号密码都是admin admin,登陆时需要修改密码。
6. 配置grafana
-
添加prometheus监控数据及模板,将grafana和prometheus关联起来,也就是在grafana中添加添加数据源
- 点击:设置->Data Source->Add data source->选择prometheus->url内填写http://IP:9090->save&test
-
点击:左边栏Dashboards“+”号内import->输入“8919”->load->更改name为“Prometheus Node”->victoriaMetrics选择刚创建的数据源“prometheus”
- 如要使用其他的模板,请到grafana的官网去查找 https://grafana.com/dashboards\
-
设置完成后,点击"Dashboards",->"victoriaMetrics"->"Prometheus Node"
五、部署alertmanager
1. 下载
https://prometheus.io/download/
2. 解压
tar -zxvf alertmanager-0.25.0.linux-amd64.tar.gz -C /data/
cd /data
mv alertmanager-0.25.0.linux-amd64/ alertmanager
chown -R prometheus:prometheus /data/alertmanager
mkdir -p /data/alertmanager/data
3. 配置报警系统altermanger服务
vim /data/alertmanager/alertmanager.yml
(最初配置)
global: resolve_timeout: 5m route: group_by: ['alertname'] group_wait: 10s group_interval: 10s repeat_interval: 1h receiver: 'web.hook' receivers: - name: 'web.hook' webhook_configs: - url: 'http://127.0.0.1:5001/' inhibit_rules: - source_match: severity: 'critical' target_match: severity: 'warning' equal: ['alertname', 'dev', 'instance']
4. 配置systemctl启动项
vim /etc/systemd/system/alertmanager.service
[Unit] Description=Alertmanager After=network.target [Service] Type=simple User=prometheus ExecStart=/data/alertmanager/alertmanager --config.file=/data/alertmanager/alertmanager.yml --storage.path=/data/alertmanager/data Restart=on-failure [Install] WantedBy=multi-user.target
5. 加载配置&启动服务
systemctl daemon-reload
systemctl start alertmanager.service
systemctl status alertmanager.service
systemctl enable alertmanager.service
6. 配置promethues.yaml
- 备份
cp /data/prometheus/prometheus.yml /data/prometheus/prometheus.yml.bak
- 编辑
vim /data/prometheus/prometheus.yml
(job_name中有几台监控的机器就写几行)
alerting: alertmanagers: - static_configs: - targets: - 192.168.1.1:9093 rule_files: - "/data/database/prometheus/rules/*.rules" 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: ['192.168.1.1:9090'] - job_name: 'node' static_configs: - targets: ['192.168.1.2:9100'] - targets: ['192.168.1.3:9100'] - targets: ['192.168.1.4:9100']
- 测试prometheus.yaml文件有无报错(可以检测出rules文件有无报错)
cd /data/prometheus
./promtool check config prometheus.yml
[root@VM-16-2-centos prometheus]# ./promtool check config prometheus.yml Checking prometheus.yml SUCCESS: 1 rule files found SUCCESS: prometheus.yml is valid prometheus config file syntax Checking /data/database/prometheus/rules/node.rules SUCCESS: 21 rules found
7. 创建prometheus的规则文件
mkdir /data/database/prometheus/rules
vim /data/database/prometheus/rules/node.rules
groups: - name: Node-rules rules: - alert: Node-Down expr: up{job="node1"} == 0 for: 1m labels: severity: 严重警告 instance: "{{ $labels.instance }}" annotations: summary: "{{$labels.instance }} 节点已经宕机 1分钟" description: "节点宕机" - alert: Node-CpuHigh expr: (1 - avg by (instance) (irate(node_cpu_seconds_total{job="node",mode="idle"}[5m]))) * 100 > 80 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} cpu使用率超 80%" description: "CPU 使用率为 {{ $value }}%" - alert: Node-CpuIowaitHigh expr: avg by (instance) (irate(node_cpu_seconds_total{job="node",mode="iowait"}[5m])) * 100 > 80 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} CPU iowait 使用率超过 80%" description: "CPU iowait 使用率为 {{ $value }}%" - alert: Node-MemoryHigh expr: (1 - node_memory_MemAvailable_bytes{job="node"} / node_memory_MemTotal_bytes{job="node"}) * 100 > 80 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Memory使用率超过 80%" description: "Memory 使用率为 {{ $value }}%" - alert: Node-Load5High expr: node_load5 > (count by (instance) (node_cpu_seconds_total{job="node",mode='system'})) * 1.2 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Load(5m)过高,超出cpu核数1.2倍" description: "Load(5m)过高,超出cpu核数 1.2倍" - alert: Node-DiskRootHigh expr: (1 - node_filesystem_avail_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/"} / node_filesystem_size_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/"}) * 100 > 80 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk(/ 分区) 使用率超过 80%" description: "Disk(/ 分区) 使用率为 {{ $value }}%" - alert: Node-DiskDataHigh expr: (1 - node_filesystem_avail_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/data"} / node_filesystem_size_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/data"}) * 100 > 80 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk(/data 分区) 使用率超过 80%" description: "Disk(/data 分区) 使用率为 {{ $value }}%" - alert: Node-DiskReadHigh expr: irate(node_disk_read_bytes_total{job="node"}[5m]) > 20 * (1024 ^ 2) for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk 读取字节数速率超过 20 MB/s" description: "Disk 读取字节数速率为 {{ $value }}MB/s" - alert: Node-DiskWriteHigh expr: irate(node_disk_written_bytes_total{job="node"}[5m]) > 20 * (1024 ^ 2) for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk 写入字节数速率超过 20 MB/s" description: "Disk 写入字节数速率为 {{ $value }}MB/s" - alert: Node-DiskReadRateCountHigh expr: irate(node_disk_reads_completed_total{job="node"}[5m]) > 3000 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk iops 每秒读取速率超过 3000 iops" description: "Disk iops 每秒读取速率为 {{ $value }}" - alert: Node-DiskWriteRateCountHigh expr: irate(node_disk_writes_completed_total{job="node"}[5m]) > 3000 for: 1m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk iops 每秒写入速率超过 3000 iops" description: "Disk iops 每秒写入速率为 {{ $value }}" - alert: Node-InodeRootUsedPercentHigh expr: (1 - node_filesystem_files_free{job="node",fstype=~"ext4|xfs",mountpoint="/"} / node_filesystem_files{job="node",fstype=~"ext4|xfs",mountpoint="/"}) * 100 > 80 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk (/ 分区) inode 使用率超过 80%" description: "Disk (/ 分区) inode 使用率为 {{ $value }}%" - alert: Node-InodeBootUsedPercentHigh expr: (1 - node_filesystem_files_free{job="node",fstype=~"ext4|xfs",mountpoint="/data"} / node_filesystem_files{job="node",fstype=~"ext4|xfs",mountpoint="/data"}) * 100 > 80 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Disk (/data 分区) inode 使用率超过 80%" description: "Disk (/data 分区) inode 使用率为 {{ $value }}%" - alert: Node-FilefdAllocatedPercentHigh expr: node_filefd_allocated{job="node"} / node_filefd_maximum{job="node"} * 100 > 80 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Filefd 打开百分比超过 80%" description: "Filefd 打开百分比为 {{ $value }}%" - alert: Node-NetworkNetinBitRateHigh expr: avg by (instance) (irate(node_network_receive_bytes_total{device=~"eth0|eth1|ens33|ens37"}[1m]) * 8) > 20 * (1024 ^ 2) * 8 for: 3m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Network 接收比特数速率超过 20MB/s" description: "Network 接收比特数速率为 {{ $value }}MB/s" - alert: Node-NetworkNetoutBitRateHigh expr: avg by (instance) (irate(node_network_transmit_bytes_total{device=~"eth0|eth1|ens33|ens37"}[1m]) * 8) > 20 * (1024 ^ 2) * 8 for: 3m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Network 接收比特数速率超过 20MB/s" description: "Network 发送比特数速率为 {{ $value }}MB/s" - alert: Node-NetworkNetinPacketErrorRateHigh expr: avg by (instance) (irate(node_network_receive_errs_total{device=~"eth0|eth1|ens33|ens37"}[1m])) > 15 for: 3m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Network 接收错误包速率超过 15个/秒" description: "Network 接收错误包速率为 {{ $value }}个/秒" - alert: Node-NetworkNetoutPacketErrorRateHigh expr: avg by (instance) (irate(node_network_transmit_packets_total{device=~"eth0|eth1|ens33|ens37"}[1m])) > 15 for: 3m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Network 发送错误包速率超过 15个/秒" description: "Network 发送错误包速率为 {{ $value }}个/秒" - alert: Node-ProcessBlockedHigh expr: node_procs_blocked{job="node"} > 10 for: 10m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} Process 当前被阻塞的任务的数量超过 10个" description: "Process 当前被阻塞的任务的数量为 {{ $value }}个" - alert: Node-TimeOffsetHigh expr: abs(node_timex_offset_seconds{job="node"}) > 3 * 60 for: 2m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} 节点的时间偏差超过 3m" description: "节点的时间偏差为 {{ $value }}m" - alert: Node-TCPconnection expr: node_sockstat_TCP_tw{job="node"} > 15000 for: 2m labels: severity: 警告 instance: "{{ $labels.instance }}" annotations: summary: "{{ $labels.instance }} TCP 等待关闭的TCP连接数TIME_WAIT过高大于15000" description: "TCP 等待关闭的TCP连接数为 {{ $value }}"
8. 配置alertmanager邮件报警
vim /data/alertmanager/alertmanager.yml
# 全局配置项 global: resolve_timeout: 5m #处理超时时间,默认为5min smtp_smarthost: 'smtp.qq.com:465' #邮箱smtp服务器代理 smtp_from: '111111112@qq.com' #发送邮箱名称 smtp_auth_username: '111111112@qq.com' #邮箱名称 smtp_auth_password: 'asdklfjwiehrqc' #邮箱授权码 smtp_require_tls: false smtp_hello: 'qq.com'
# 定义报警模板
templates:
- '/data/alertmanager/email.tmpl'
# 定义路由树信息
route:
group_by: ['alertname'] #报警分组依据
group_wait: 10s #最初即第一次等待多久时间发送一组警报的通知
group_interval: 10s #在发送新警报前的等待时间
repeat_interval: 10m #发送重复警报的周期 对于email配置中,此项不可以设置过低,否则将会由于邮件发送太多频繁,被smtp服务器拒绝
receiver: 'email' #发送警报的接收者的名称,以下receivers name的名称
# 定义警报接收者信息
receivers:
- name: 'email' # 警报
email_configs: # 邮箱配置
- to: '1111111112@qq.com, hello@163.com' #添加多个邮箱中间用,+空格分开
html: '{{ template "email.html" . }}'
send_resolved: true
# 一个inhibition规则是在与另一组匹配器匹配的警报存在的条件下,使匹配一组匹配器的警报失效的规则。两个警报必须具有一组相同的标签。
inhibit_rules:
- source_match:
severity: 'critical'
target_match:
severity: 'warning'
equal: ['alertname', 'dev', 'instance']
9. 创建自定义报警模板
vim /data/alertmanager/email.tmpl
{{ define "email.html" }} {{- if gt (len .Alerts.Firing) 0 -}} {{- range $index, $alert := .Alerts -}} <pre> ======== 异常告警 ======== 告警类型:{{ $alert.Labels.alertname }} 告警级别:{{ $alert.Labels.severity }} 告警实例:{{ $alert.Labels.instance }} 告警应用: {{ $alert.Labels.name }} 告警信息:{{ $alert.Annotations.summary }} 告警详情:{{ $alert.Annotations.description }} 告警时间:{{ $alert.StartsAt.Local }} ========== END ========== </pre> {{- end }} {{- end }} {{- if gt (len .Alerts.Resolved) 0 -}} {{- range $index, $alert := .Alerts -}} <pre> ======== 告警恢复 ======== 告警类型:{{ $alert.Labels.alertname }} 告警级别:{{ $alert.Labels.severity }} 告警实例:{{ $alert.Labels.instance }} 告警详情:{{ $alert.Annotations.description }} 告警应用: {{ $alert.Labels.name }} 当前状态: OK 告警时间:{{ $alert.StartsAt.Local }} 恢复时间:{:{ $alert.EndsAt.Local }} ========== END ========== </pre> {{- end }} {{- end }} {{- end }}
10. 重启服务
systemctl restart prometheus.service
systemctl restart alertmanager.service