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xinglu_zhang
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‎.gitignore‎

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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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.idea/

‎Dockerfile‎

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# 使用官方Python基础镜像
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FROM python:3.8-slim
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# 设置工作目录
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WORKDIR /app
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# 复制当前目录的内容到容器中
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COPY ../../PyProject/monitor /app
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# 安装依赖
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RUN pip install --index-url=https://mirrors.aliyun.com/pypi/simple/ --no-cache-dir -r requirements.txt
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# 安装supervisor
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RUN pip install --index-url=https://mirrors.aliyun.com/pypi/simple/ supervisor==4.2.5
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# 复制supervisor配置文件
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COPY supervisord.conf /etc/supervisor/conf.d/supervisord.conf
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# 设置环境变量
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ENV FLASK_APP=app.py
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ENV FLASK_RUN_HOST=0.0.0.0
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# 暴露端口
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EXPOSE 5000
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# 运行Flask应用
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#CMD ["flask", "run"]
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# 运行supervisord
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CMD ["/usr/local/bin/supervisord", "-n", "-c", "/etc/supervisor/conf.d/supervisord.conf"]

‎README.md‎

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# monitor
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cpu and memory monitor, can use docker
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# monitor监控
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可以监控linux服务器的CPU和内存占用情况，支持历史监控查询（个人自用，功能比较简陋）。
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使用docker部署，使用supervisord进行进程管理。
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### 本地启动
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```
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# 环境配置
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pip install --index-url=https://mirrors.aliyun.com/pypi/simple/ --no-cache-dir -r requirements.txt
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```
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### 打包部署（docker）
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```
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#打包镜像
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docker build -t monitor:0.0.3 . --progress=plain
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# 另存镜像
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docker save -o monitor003.tar monitor:0.0.3
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# 加载镜像
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docker load -i monitor-0.0.3.tar
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# 启动镜像
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docker run -d -p 5000:5000 --name monitor003 --mount type=bind,src=/proc,dst=/host/proc -dit --restart=always monitor:0.0.3
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```
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访问地址：http://localhost:5000/
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![img.png](img.png)

‎img.png‎

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‎monitor.db‎

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‎templates/__init__.py‎

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‎templates/index.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>Server Monitor</title>
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<script src="https://fastly.jsdelivr.net/npm/chart.js"></script>
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</head>
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<body>
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<div>
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<label for="start_time">Start Time:</label>
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<input type="datetime-local" id="start_time">
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<label for="end_time">End Time:</label>
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<input type="datetime-local" id="end_time">
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<button onclick="update()">Fetch Data</button>
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</div>
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<div>
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<canvas id="cpuChart" width="400" height="90"></canvas>
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<canvas id="memoryChart" width="400" height="90"></canvas>
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</div>
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<script>
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let cpuChart; // Global variable to store the CPU chart instance
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let memoryChart; // Global variable to store the Memory chart instance
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async function fetchData(url) {
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const response = await fetch(url + '?start_time=' + document.getElementById('start_time').value + '&end_time=' + document.getElementById('end_time').value);
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return await response.json();
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}
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async function updateChart(chartId, label, url) {
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// Destroy existing chart if it exists
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if (chartId === 'cpuChart' && cpuChart) {
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cpuChart.destroy();
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} else if (chartId === 'memoryChart' && memoryChart) {
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memoryChart.destroy();
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}
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const data = await fetchData(url);
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const labels = data.map(item => item.timestamp);
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const values = data.map(item => item[label]);
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const ctx = document.getElementById(chartId).getContext('2d');
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const chart = new Chart(ctx, {
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type: 'line',
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data: {
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labels: labels,
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datasets: [
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{
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label: label + ' Usage',
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data: values,
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backgroundColor: 'rgba(246,173,188,0.2)',
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borderColor: 'rgb(30,66,219)',
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borderWidth: 1
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}
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]
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},
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options: {
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scales: {
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y: {
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beginAtZero: true
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}
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}
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}
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});
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if (chartId === 'cpuChart') {
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cpuChart = chart;
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} else if (chartId === 'memoryChart') {
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memoryChart = chart;
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}
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}
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async function update() {
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await updateChart('cpuChart', 'cpu', '/data/cpu');
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await updateChart('memoryChart', 'memory', '/data/memory');
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}
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update();
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</script>
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</body>
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</html>

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