背景
最近看着手里的几只树莓派在吃灰，心中不忍，遂想利用它们搭个小应用，并在新买的RPI4上监测他们的状态
以下过程参考了网上的文章，并使用了新版本的prometheus和Grafana搭配
过程
1、首先要在各监测点上安装node_exporter，由这个代理程序在各节点上采集设备信息
cd /home
curl -SL https://github.com/prometheus/node_exporter/releases/download/v0.16.0/node_exporter-0.16.0.linux-armv7.tar.gz > node_exporter.tar.gz && sudo tar -xvf node_exporter.tar.gz -C /usr/local/bin/ --strip-components=1
2、运行node_exporter
node_exporter
测试通过后可以配置supervisord或systemd等在后台运行，例如做为系统服务：
vim /etc/systemd/system/node_exporter.service
输入如下代码：
[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target
[Service]
User=root
ExecStart=/home/node_exporter
[Install]
WantedBy=default.target
开机启动
systemctl daemon-reload
systemctl status node_exporter
systemctl start node_exporter
systemctl enable node_exporter
3、在监测机上配置prometheus，将下面的配置保存到 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:
# - alertmanager: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: 'RPi_Mariadb'
static_configs:
- targets: ['192.168.10.10:9100']
- job_name: 'RPi_Redis'
static_configs:
- targets: ['192.168.10.11:9100']
- job_name: 'RPi_dotnet'
static_configs:
- targets: ['192.168.10.12:9100']
3、在树莓派上安装docker，通过脚本可以安装最新的docker
curl -sSL https://get.docker.com | sh
4、拉取prometheus镜象
docker pull prometheus
5、用上面的配置文件以及刚才拉取的镜象，创建一个新的镜象，这个镜象直接包含了我们的配置，当然，后面可以通过配置路径挂载，将配置文件保留在宿主机主，不用每次修改都要重新打包。
FROM prom/prometheus
COPY ./prometheus.yml /etc/prometheus/prometheus.yml
6、运行容器，prometheus通过9090端口提供一个WEB UI，UI上可以看到很多指标，但略丑。
docker run -p 9090:9090 --name prometheus-rpi -d prometheus/rpi-monitor
7、运行grafana
由于我这里安装的是32位的ARM，所以需要拉取32位的镜象，需要64位arm的朋友可以到hub.docker.com自行寻找相应的镜象
docker run -i -p 3000:3000 --name grafana6 grafana/grafana-arm32v7-linux:6.5.1
8、接下来就是配置datasource为prometheus，导入dashboard模板，模板ID为 8919，最终效果如下图
效果
