用Python两个小时徒手撸了一个简易的监控系统，给大家分享一下，希望能对大家有所启发

首先数据库建表

建立一个数据库“falcon”，建表语句如下：

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;

首先我们设计一个web服务，实现如下功能：

1.完成监控页面展示
2.接受POST提交上来的数据
3.提供json数据GET接口

目录结构如下：

web
├── flask_web.py
└── templates
 └── mon.html
[/code]
flask_web.py
[code]
import MySQLdb as mysql
import json
from flask import Flask, request, render_template
app = Flask(__name__)
db = mysql.connect(user="reboot", passwd="reboot123", 
 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)

这个template页面是我抄的highstock的示例，mon.html

简单起见我们只展示mem_usage信息到页面上

 
 
 

 
 
 
$(function () {
 $.getJSON('/data?callback=?', function (data) {

 // Create the chart
 $('#container').highcharts('StockChart', {

 rangeSelector: {
 inputEnabled: $('#container').width() > 480,
 selected: 1
 },

 title: {
 text: 'jb51.net'
 },

 series: [{
 name: 'jb51.net',
 data: data,
 type: 'spline',
 tooltip: {
 valueDecimals: 2
 }
 }]
 });
 });
});
 
 
 

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，并上传数据库

moniItems.py

#!/usr/bin/env python
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://jb51.net: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 & 运行起来

访问 http://jb51.net:8888 就可以看到我们的监控数据了：效果图如下