- 前言
- 一、docker-compose安装
- 1.1 安装docker
- 1.2 安装docker-compose
- 二、路径准备
- 三、配置文件准备
- 3.1 prometheus.yml
- 3.2 alert-rules.yml
- 3.3 钉钉机器人告警配置config.yml
- 3.4 alertmanager.yml
- 四、docker-compose配置文件准备
- 五、启动容器
- 六、granafa配置数据源
- 七、service形式启动node-expoter
- 7.1 下载软件包
- 7.2 执行部署脚本
- 总结
前言
docker-compose 搭建prometheus+granafa+alertmanager+dingtalk;node-expoter使用service形式启动。
一、docker-compose安装
参考:https://blog.csdn.net/baidu_35848778/article/details/125082770
1.1 安装docker#获取yum源 sudo yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo; #安装服务 yum install docker-ce docker-ce-cli -y; systemctl restart docker ; systemctl enable docker ;1.2 安装docker-compose
#获取pip,python版本是2.7.5 wget https://bootstrap.pypa.io/pip/2.7/get-pip.py; python get-pip.py; #安装docker-compose pip install docker-compose二、路径准备
我这里使用的路径是/hdd-data/prom/,部署的时候按照各自机器的分布规划来安排即可。
mkdir -p /hdd-data/prom/{prometheus,prometheus/data,alertmanager,grafana}
#这一步务必要做
chmod 777 /hdd-data/prom/{prometheus/data,grafana}
cd /hdd-data/prom/
三、配置文件准备
3.1 prometheus.yml
/hdd-data/prom/prometheus/prometheus.yml
node-expoter由于使用的是service形式,所以没有使用域名加端口形式
global:
scrape_interval: 15s
evaluation_interval: 15s
alerting:
alertmanagers:
- static_configs:
- targets:
- alertmanager:9093
rule_files:
- "*rules.yml"
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['prometheus:9090']
- job_name: 'node'
static_configs:
- targets: ['xx.xx.xx.xx:9100']
- job_name: 'alertmanager'
static_configs:
- targets: ['alertmanager:9093']
3.2 alert-rules.yml
/hdd-data/prom/prometheus/alert-rules.yml
具体的硬件信息根据自己机器信息修改
groups:
- name: node-alert
rules:
- alert: NodeDown
expr: up{job="node"} == 0
for: 5m
labels:
severity: critical
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} down"
description: "Instance: {{ $labels.instance }} 已经宕机 5分钟"
value: "{{ $value }}"
- alert: NodeCpuHigh
expr: (1 - avg by (instance) (irate(node_cpu_seconds_total{job="node",mode="idle"}[5m]))) * 100 > 85
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} cpu使用率过高"
description: "CPU 使用率超过 80%"
value: "{{ $value }}"
- alert: NodeCpuIowaitHigh
expr: avg by (instance) (irate(node_cpu_seconds_total{job="node",mode="iowait"}[5m])) * 100 > 80
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} cpu iowait 使用率过高"
description: "CPU iowait 使用率超过 50%"
value: "{{ $value }}"
- alert: NodeLoad5High
expr: node_load5 > (count by (instance) (node_cpu_seconds_total{job="node",mode='system'})) * 1.2
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} load(5m) 过高"
description: "Load(5m) 过高,超出cpu核数 1.2倍"
value: "{{ $value }}"
- alert: NodeMemoryHigh
expr: (1 - node_memory_MemAvailable_bytes{job="node"} / node_memory_MemTotal_bytes{job="node"}) * 100 > 90
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} memory 使用率过高"
description: "Memory 使用率超过 90%"
value: "{{ $value }}"
- alert: NodeDiskRootHigh
expr: (1 - node_filesystem_avail_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/"} / node_filesystem_size_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/"}) * 100 > 90
for: 10m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk(/ 分区) 使用率过高"
description: "Disk(/ 分区) 使用率超过 90%"
value: "{{ $value }}"
- alert: NodeDiskBootHigh
expr: (1 - node_filesystem_avail_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/boot"} / node_filesystem_size_bytes{job="node",fstype=~"ext.*|xfs",mountpoint ="/boot"}) * 100 > 80
for: 10m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk(/boot 分区) 使用率过高"
description: "Disk(/boot 分区) 使用率超过 80%"
value: "{{ $value }}"
- alert: NodeDiskReadHigh
expr: irate(node_disk_read_bytes_total{job="node"}[5m]) > 20 * (1024 ^ 2)
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk 读取字节数 速率过高"
description: "Disk 读取字节数 速率超过 20 MB/s"
value: "{{ $value }}"
- alert: NodeDiskWriteHigh
expr: irate(node_disk_written_bytes_total{job="node"}[5m]) > 20 * (1024 ^ 2)
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk 写入字节数 速率过高"
description: "Disk 写入字节数 速率超过 20 MB/s"
value: "{{ $value }}"
- alert: NodeDiskReadRateCountHigh
expr: irate(node_disk_reads_completed_total{job="node"}[5m]) > 3000
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk iops 每秒读取速率过高"
description: "Disk iops 每秒读取速率超过 3000 iops"
value: "{{ $value }}"
- alert: NodeDiskWriteRateCountHigh
expr: irate(node_disk_writes_completed_total{job="node"}[5m]) > 3000
for: 5m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk iops 每秒写入速率过高"
description: "Disk iops 每秒写入速率超过 3000 iops"
value: "{{ $value }}"
- alert: NodeInodeRootUsedPercentHigh
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: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk(/ 分区) inode 使用率过高"
description: "Disk (/ 分区) inode 使用率超过 80%"
value: "{{ $value }}"
- alert: NodeInodeBootUsedPercentHigh
expr: (1 - node_filesystem_files_free{job="node",fstype=~"ext4|xfs",mountpoint="/boot"} / node_filesystem_files{job="node",fstype=~"ext4|xfs",mountpoint="/boot"}) * 100 > 80
for: 10m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} disk(/boot 分区) inode 使用率过高"
description: "Disk (/boot 分区) inode 使用率超过 80%"
value: "{{ $value }}"
- alert: NodeFilefdAllocatedPercentHigh
expr: node_filefd_allocated{job="node"} / node_filefd_maximum{job="node"} * 100 > 80
for: 10m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} filefd 打开百分比过高"
description: "Filefd 打开百分比 超过 80%"
value: "{{ $value }}"
- alert: NodeNetworkNetinBitRateHigh
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: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} network 接收比特数 速率过高"
description: "Network 接收比特数 速率超过 20MB/s"
value: "{{ $value }}"
- alert: NodeNetworkNetoutBitRateHigh
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: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} network 发送比特数 速率过高"
description: "Network 发送比特数 速率超过 20MB/s"
value: "{{ $value }}"
- alert: NodeNetworkNetinPacketErrorRateHigh
expr: avg by (instance) (irate(node_network_receive_errs_total{device=~"eth0|eth1|ens33|ens37"}[1m])) > 15
for: 3m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} 接收错误包 速率过高"
description: "Network 接收错误包 速率超过 15个/秒"
value: "{{ $value }}"
- alert: NodeNetworkNetoutPacketErrorRateHigh
expr: avg by (instance) (irate(node_network_transmit_packets_total{device=~"eth0|eth1|ens33|ens37"}[1m])) > 15
for: 3m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} 发送错误包 速率过高"
description: "Network 发送错误包 速率超过 15个/秒"
value: "{{ $value }}"
- alert: NodeProcessBlockedHigh
expr: node_procs_blocked{job="node"} > 10
for: 10m
labels:
severity: warning
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} 当前被阻塞的任务的数量过多"
description: "Process 当前被阻塞的任务的数量超过 10个"
value: "{{ $value }}"
- alert: NodeTimeOffsetHigh
expr: abs(node_timex_offset_seconds{job="node"}) > 3 * 60
for: 2m
labels:
severity: info
instance: "{{ $labels.instance }}"
annotations:
summary: "instance: {{ $labels.instance }} 时间偏差过大"
description: "Time 节点的时间偏差超过 3m"
value: "{{ $value }}"
3.3 钉钉机器人告警配置config.yml
/hdd-data/prom/alertmanager/config.yml
targets:
webhook:
url: https://oapi.dingtalk.com/robot/send?access_token=xxxxxxxxxxxx #修改为钉钉机器人的webhook
mention:
all: true
3.4 alertmanager.yml
/hdd-data/prom/alertmanager/alertmanager.yml
global:
resolve_timeout: 5m
smtp_smarthost: 'smtp.qiye.163.com:465' #邮箱smtp服务器代理,启用SSL发信, 端口一般是465
smtp_from: 'user@163.com' #发送邮箱名称
smtp_auth_username: 'user@163.com' #邮箱名称
smtp_auth_password: 'password' #邮箱密码或授权码
smtp_require_tls: false
route:
receiver: 'default'
group_wait: 10s
group_interval: 1m
repeat_interval: 1h
group_by: ['alertname']
inhibit_rules:
- source_match:
severity: 'critical'
target_match:
severity: 'warning'
equal: ['alertname', 'instance']
receivers:
- name: 'default'
email_configs:
- to: 'receiver@163.com'
send_resolved: true
webhook_configs:
- url: 'http://dingtalk:8060/dingtalk/webhook/send'
send_resolved: true
四、docker-compose配置文件准备
/hdd-data/prom/prom.yml
version: '3.7'
services:
dingtalk:
image: timonwong/prometheus-webhook-dingtalk:latest
container_name: prom_dingtalk
volumes:
- type: bind
source: ./alertmanager/config.yml
target: /etc/prometheus-webhook-dingtalk/config.yml
read_only: true
ports:
- "8060:8060"
networks:
- prom
alertmanager:
depends_on:
- dingtalk
image: prom/alertmanager:latest
container_name: alertmanager
volumes:
- type: bind
source: ./alertmanager/alertmanager.yml
target: /etc/alertmanager/alertmanager.yml
read_only: true
ports:
- "9093:9093"
- "9094:9094"
networks:
- prom
prometheus:
depends_on:
- alertmanager
image: prom/prometheus:latest
container_name: prometheus
volumes:
- type: bind
source: ./prometheus/prometheus.yml
target: /etc/prometheus/prometheus.yml
read_only: true
- type: bind
source: ./prometheus/alert-rules.yml
target: /etc/prometheus/alert-rules.yml
read_only: true
- type: volume
source: prometheus
target: /prometheus
ports:
- "9090:9090"
networks:
- prom
grafana:
depends_on:
- prometheus
image: grafana/grafana:latest
container_name: grafana
volumes:
- type: volume
source: grafana
target: /var/lib/grafana
ports:
- "3000:3000"
networks:
- prom
volumes:
prometheus:
driver: local
driver_opts:
type: none
o: bind
device: /hdd-data/prom/prometheus/data #数据存储配置
grafana:
driver: local
driver_opts:
type: none
o: bind
device: /hdd-data/prom/grafana #数据存储配置
networks:
prom:
driver: bridge
五、启动容器
docker-compose -f /hdd-data/prom/prom.yml up -d
启动完成后检查启动结果
docker-compose -f /hdd-data/prom/jiankong.yml ps
#输出
Name Command State Ports
-------------------------------------------------------------------------------------------------------------------------------------------
alertmanager /bin/alertmanager --config ... Up 0.0.0.0:9093->9093/tcp,:::9093->9093/tcp, 0.0.0.0:9094->9094/tcp,:::9094->9094/tcp
granafa /run.sh Up 0.0.0.0:3000->3000/tcp,:::3000->3000/tcp
prom_dingtalk /bin/prometheus-webhook-di ... Up 0.0.0.0:8060->8060/tcp,:::8060->8060/tcp
prometheus /bin/prometheus --config.f ... Up 0.0.0.0:9090->9090/tcp,:::9090->9090/tcp
六、granafa配置数据源
七、service形式启动node-expoter数据源处url可以配置为http://ip:9090
也可以配置为http://prometheus:9090
7.1 下载软件包直接使用service形式启动感觉收集数据更准确,也不用特殊配置映射,简单一点。
如果使用docker容器形式,docker服务死了就没数据了,和物理机监控的目的背离了。
wget https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz7.2 执行部署脚本
#!/bin/bash set -e tar -xvf ./node_exporter-1.3.1.linux-amd64.tar.gz if [ -d ./node_exporter-1.3.1.linux-amd64/ ];then sudo cp ./node_exporter-1.3.1.linux-amd64/node_exporter /usr/local/bin/ else echo "请检查 node_exporter 所在文件目录" exit 1 fi sudo touch /usr/lib/systemd/system/node_exporter.service sudo chmod o+w /usr/lib/systemd/system/node_exporter.service sudo chmod o+x /usr/local/bin/node_exporter cat << EOF > /usr/lib/systemd/system/node_exporter.service [Service] User=$USER Group=$USER ExecStart=/usr/local/bin/node_exporter [Install] WantedBy=multi-user.target [Unit] Description=node_exporter After=network.target EOF sudo systemctl daemon-reload sudo systemctl start node_exporter sudo systemctl enable node_exporter sudo systemctl status node_exporter echo 'end success'
总结
好使,prometheus的轻度使用可以直接满足,重度使用的话还是要多增加一些配置,或是使用自己构建的镜像。
参考:https://blog.csdn.net/weixin_42900170/article/details/122886745
参考:https://blog.csdn.net/qq_33326449/article/details/120203438



