Flask+MySQL编写内存监控程序 用Python的Flask框架结合MySQL写一个内存监控程序
人气:0这里以监控内存使用率为例,写的一个简单demo性程序,具体操作根据51reboot提供的教程写如下。
一、建库建表
创建falcon数据库:
mysql> create database falcon character set utf8; Query OK, 1 row affected (0.00 sec)
创建内存监控使用的表stat,表结构如下:
CREATE TABLE `stat` ( `id` int(11) unsigned NOT NULL AUTO_INCREMENT, `host` varchar(256) DEFAULT NULL, `mem_free` int(11) DEFAULT NULL, `mem_usage` int(11) DEFAULT NULL, `mem_total` int(11) DEFAULT NULL, `load_avg` varchar(128) DEFAULT NULL, `time` bigint(11) DEFAULT NULL, PRIMARY KEY (`id`), KEY `host` (`host`(255)) ) ENGINE=InnoDB AUTO_INCREMENT=0 DEFAULT CHARSET=utf8;
二、flask web端设置
首先我们设计一个web服务,实现如下功能:
完成监控页面展示
接受POST提交上来的数据
提供json数据GET接口
具体框架结构图如下:
目录结构如下:
web ├── flask_web.py └── templates └── mon.html
flask_web代码如下:
import MySQLdb as mysql import json from flask import Flask, request, render_template app = Flask(__name__) db = mysql.connect(user="361way", passwd="123456", \ db="falcon", charset="utf8") db.autocommit(True) c = db.cursor() @app.route("/", methods=["GET", "POST"]) def hello(): sql = "" if request.method == "POST": data = request.json try: sql = "INSERT INTO `stat` (`host`,`mem_free`,`mem_usage`,`mem_total`,`load_avg`,`time`) VALUES('%s', '%d', '%d', '%d', '%s', '%d')" % (data['Host'], data['MemFree'], data['MemUsage'], data['MemTotal'], data['LoadAvg'], int(data['Time'])) ret = c.execute(sql) except mysql.IntegrityError: pass return "OK" else: return render_template("mon.html") @app.route("/data", methods=["GET"]) def getdata(): c.execute("SELECT `time`,`mem_usage` FROM `stat`") ones = [[i[0]*1000, i[1]] for i in c.fetchall()] return "%s(%s);" % (request.args.get('callback'), json.dumps(ones)) if __name__ == "__main__": app.run(host="0.0.0.0", port=8888, debug=True)
这里使用的汇图JS为highcharts、highstock ,具体模板页面内容如下:
[root@91it templates]# cat mon.html
<title>memory monitor</title> <!DOCTYPE HTML> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> <title>Highstock Example</title> <!-- <script type="text/javascript" src="{{ url_for('static', filename='jquery.min.js') }}"></script> --> <script type="text/javascript" src="http://ajax.useso.com/ajax/libs/jquery/1.8.2/jquery.min.js"></script> <style type="text/css"> ${demo.css} </style> <script type="text/javascript"> $(function () { $.getJSON('/data?callback=?', function (data) { // Create the chart $('#container').highcharts('StockChart', { rangeSelector: { inputEnabled: $('#container').width() > 480, selected: 1 }, title: { text: 'memory monitor' }, series: [{ name: 'memory monitor', data: data, type: 'spline', tooltip: { valueDecimals: 2 } }] }); }); }); </script> </head> <body> <!-- <script src="{{ url_for('static', filename='highstock.js') }}"></script> --> <script src="http://cdnjs.cloudflare.com/ajax/libs/highstock/2.0.4/highstock.js"></script> <!-- <script src="{{ url_for('static', filename='exporting.js') }}"></script> --> <script src="http://code.highcharts.com/modules/exporting.js"></script> <div id="container" style="height: 400px"></div> </body> </html>
注:这里的JS代码都直接使用互联网上的代码,如果主机无法连接互联网的,可以将上面的三段代取取下来,在templates 的同级目录创建static 目录,将下载下来的三个文件放到该目录,删除模板中三处引用javascript处的代码,使用当前注释的三段。
三、agent被监控端设置
web展示页面完成了,运行起来:python flask_web.py 监听在8888端口上。我们需要做一个agent来采集数据,并通过post方法请求flask_web页面,将数据上传写入数据库。这里以监控内存为例,具体监控代码如下:
#!/usr/bin/env python #coding=utf-8 import inspect import time import urllib, urllib2 import json import socket class mon: def __init__(self): self.data = {} def getTime(self): return str(int(time.time()) + 8 * 3600) def getHost(self): return socket.gethostname() def getLoadAvg(self): with open('/proc/loadavg') as load_open: a = load_open.read().split()[:3] return ','.join(a) def getMemTotal(self): with open('/proc/meminfo') as mem_open: a = int(mem_open.readline().split()[1]) return a / 1024 def getMemUsage(self, noBufferCache=True): if noBufferCache: with open('/proc/meminfo') as mem_open: T = int(mem_open.readline().split()[1]) F = int(mem_open.readline().split()[1]) B = int(mem_open.readline().split()[1]) C = int(mem_open.readline().split()[1]) return (T-F-B-C)/1024 else: with open('/proc/meminfo') as mem_open: a = int(mem_open.readline().split()[1]) - int(mem_open.readline().split()[1]) return a / 1024 def getMemFree(self, noBufferCache=True): if noBufferCache: with open('/proc/meminfo') as mem_open: T = int(mem_open.readline().split()[1]) F = int(mem_open.readline().split()[1]) B = int(mem_open.readline().split()[1]) C = int(mem_open.readline().split()[1]) return (F+B+C)/1024 else: with open('/proc/meminfo') as mem_open: mem_open.readline() a = int(mem_open.readline().split()[1]) return a / 1024 def runAllGet(self): #自动获取mon类里的所有getXXX方法,用XXX作为key,getXXX()的返回值作为value,构造字典 for fun in inspect.getmembers(self, predicate=inspect.ismethod): if fun[0][:3] == 'get': self.data[fun[0][3:]] = fun[1]() return self.data if __name__ == "__main__": while True: m = mon() data = m.runAllGet() print data req = urllib2.Request("http://test.361way.com:8888", json.dumps(data), {'Content-Type': 'application/json'}) f = urllib2.urlopen(req) response = f.read() print response f.close() time.sleep(60)
nohup python moniItems.py >/dev/null 2>&1 & 在被监控主机上运行,如果出于实验目的,想尽快的看到展示效果,可以将time.sleep(60) 改为time.sleep(2) ,这样每2秒就会取一次数据写入数据库。
访问 http://test.361way.com:8888 就可以看到我们的监控数据了:效果图如下
highcharts支持将按时间拖动,也支持按指定时间段查看。并且查看到的图片可以直接保存为png、jpg或pdf、csv等格式查看。
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