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服务器之家 - 脚本之家 - Python - 使用Python对Syslog信息进行分析并绘图的实现

使用Python对Syslog信息进行分析并绘图的实现

2021-10-14 11:14格洛米爱学习 Python

这篇文章主要介绍了使用Python对Syslog信息进行分析并绘图的实现,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

实验目的:

  • 对设备syslong信息进行分析记录,并写入sqlite数据库中;后续读取数据库的信息,对syslog的严重级别分布、来源进行分析进行分析。
  • 同时监控ospf的状态信息,状态一旦改变,进行告警。

实验结果:

监控syslog的严重级别分布,和日志源分布,并绘图:

使用Python对Syslog信息进行分析并绘图的实现

使用Python对Syslog信息进行分析并绘图的实现

监控ospf状态信息:

使用Python对Syslog信息进行分析并绘图的实现

实验环境:

两台csr1000v,完成syslog(其中一台)和ospf的配置:

logging hosy x.x.x.x /将syslong日志信息发送给目的主机(运行python)进行处理。

logging trap debugging /监控所有级别的syslog信息。

ospf配置略。

 python脚本:

脚本一:监控csr1000v发送的syslog trap信息,并对信息进行分词处理,写入数据库。同时监控ospf邻居状态是否改变。

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import socketserver
import re
from dateutil import parser
import os
import sqlite3
 
# facility与id的对应关系的字典,方便后续分词时提取对应的信息
facility_dict = {0: 'kern',
                 1: 'user',
                 2: 'mail',
                 3: 'daemon',
                 4: 'auth',
                 5: 'syslog',
                 6: 'lpr',
                 7: 'news',
                 8: 'uucp',
                 9: 'cron',
                 10: 'authpriv',
                 11: 'ftp',
                 16: 'local0',
                 17: 'local1',
                 18: 'local2',
                 19: 'local3',
                 20: 'local4',
                 21: 'local5',
                 22: 'local6',
                 23: 'local7'}
 
# severity_level与id的对应关系的字典,方便后续分词时提取对应的信息
severity_level_dict = {0: 'emerg',
                       1: 'alert',
                       2: 'crit',
                       3: 'err',
                       4: 'warning',
                       5: 'notice',
                       6: 'info',
                       7: 'debug'}
 
# 分词处理的类
class syslogudphandler(socketserver.baserequesthandler):
    def handle(self):
        data = bytes.decode(self.request[0].strip())  # 读取数据
        # print(data)
        syslog_info_dict = {'device_ip': self.client_address[0]}
        try:
            # syslog信息如下:<187>83: *apr  4 00:03:12.969: %link-3-updown: interface gigabitethernet2,
            # changed state to up,我们需要对此进行提炼分词,并将分词结果记入到一个字典里面;具体的分词过程简单了解即可
            syslog_info = re.match(r'^<(\d*)>(\d*): \*(.*): %(\w+)-(\d)-(\w+): (.*)', str(data)).groups()
            # print(syslog_info[0]) 提取为整数 例如 185
            # 185 二进制为 1011 1001
            # 前5位为facility  >> 3 获取前5位
            # 后3位为severity_level  & 0b111 获取后3位
            syslog_info_dict['facility'] = (int(syslog_info[0]) >> 3)
            syslog_info_dict['facility_name'] = facility_dict[int(syslog_info[0]) >> 3]
            syslog_info_dict['logid'] = int(syslog_info[1])
            syslog_info_dict['time'] = parser.parse(syslog_info[2])
            syslog_info_dict['log_source'] = syslog_info[3]
            syslog_info_dict['severity_level'] = int(syslog_info[4])
            syslog_info_dict['severity_level_name'] = severity_level_dict[int(syslog_info[4])]
            syslog_info_dict['description'] = syslog_info[5]
            syslog_info_dict['text'] = syslog_info[6]
        except attributeerror:
            # 有些日志会缺失%sys-5-config_i, 造成第一个正则表达式无法匹配 , 也无法提取severity_level
            # 下面的icmp的debug就是示例
            # <191>91: *apr  4 00:12:29.616: icmp: echo reply rcvd, src 10.1.1.80, dst 10.1.1.253, topology base, dscp 0 topoid 0
            syslog_info = re.match(r'^<(\d*)>(\d*): \*(.*): (\w+): (.*)', str(data)).groups()
            print(syslog_info[0])
            syslog_info_dict['facility'] = (int(syslog_info[0]) >> 3)
            syslog_info_dict['facility_name'] = facility_dict[int(syslog_info[0]) >> 3]
            syslog_info_dict['logid'] = int(syslog_info[1])
            syslog_info_dict['time'] = parser.parse(syslog_info[2])
            syslog_info_dict['log_source'] = syslog_info[3]
            # 如果在文本部分解析不了severity_level, 切换到syslog_info[0]去获取
            # 185 二进制为 1011 1001
            # 前5位为facility  >> 3 获取前5位
            # 后3位为severity_level  & 0b111 获取后3位
            syslog_info_dict['severity_level'] = (int(syslog_info[0]) & 0b111)
            syslog_info_dict['severity_level_name'] = severity_level_dict[(int(syslog_info[0]) & 0b111)]
            syslog_info_dict['description'] = 'n/a'
            syslog_info_dict['text'] = syslog_info[4]
        # print(syslog_info_dict)
        # 根据分词后的字典进行分析,如果用正则表达式匹配到了ospf状态有了改变,则打印告警信息
        if syslog_info_dict['log_source'] == 'ospf':
            result_ospf = re.findall('(process \d+), nbr ([0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}).+to (\w+)', syslog_info_dict['text'])[0]
            if result_ospf:
                print('ospf '+result_ospf[0]+' neighbor '+result_ospf[1]+' status '+result_ospf[2])
        # 将字典信息写入sqlite数据库中
        conn = sqlite3.connect(gl_dbname)
        cursor = conn.cursor()
        cursor.execute("insert into syslogdb (time, \
                                              device_ip, \
                                              facility, \
                                              facility_name, \
                                              severity_level, \
                                              severity_level_name, \
                                              logid, \
                                              log_source, \
                                              description, \
                                              text) values ('%s', '%s', %d, '%s', %d, '%s', %d, '%s', '%s', '%s')" % (
        syslog_info_dict['time'].strftime("%y-%m-%d %h:%m:%s"),
        syslog_info_dict['device_ip'],
        syslog_info_dict['facility'],
        syslog_info_dict['facility_name'],
        syslog_info_dict['severity_level'],
        syslog_info_dict['severity_level_name'],
        syslog_info_dict['logid'],
        syslog_info_dict['log_source'],
        syslog_info_dict['description'],
        syslog_info_dict['text'],
        ))
        conn.commit()
 
 
if __name__ == "__main__":
    # 使用linux解释器 & win解释器
    global gl_dbname
    gl_dbname = 'syslog.sqlite'
    if os.path.exists(gl_dbname):
        os.remove(gl_dbname)
    # 连接数据库
    conn = sqlite3.connect(gl_dbname)
    cursor = conn.cursor()
    # 创建数据库
 
    cursor.execute("create table syslogdb(id integer primary key autoincrement,\
                                         time varchar(64), \
                                         device_ip varchar(32),\
                                         facility int,\
                                         facility_name varchar(32),\
                                         severity_level int,\
                                         severity_level_name varchar(32),\
                                         logid int,\
                                         log_source varchar(32), \
                                         description varchar(128), \
                                         text varchar(1024)\
                                         )")
    conn.commit()
    try:
        host, port = "0.0.0.0", 514  # 本地地址与端口
        server = socketserver.udpserver((host, port), syslogudphandler)  # 绑定本地地址,端口和syslog处理方法
        print("syslog 服务已启用, 写入日志到数据库!!!")
        server.serve_forever(poll_interval=0.5# 运行服务器,和轮询间隔
 
    except (ioerror, systemexit):
        raise
    except keyboardinterrupt:  # 捕获ctrl+c,打印信息并退出
        print("crtl+c pressed. shutting down.")
    finally:
        conn.commit()

脚本二:读取数据库中的信息,并根据信息进行饼图绘制。

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import sqlite3
from matplotlib import pyplot as plt
from syslog_server_to_db import severity_level_dict
 
# 绘制严重等级的饼图
def syslog_show_error_level_pie(dbname):
    # 连接数据库
    conn = sqlite3.connect(dbname)
    cursor = conn.cursor()
    # 提取安全级别和数量信息
    cursor.execute("select severity_level as level,count(*) as count from syslogdb group by severity_level")
    yourresults = cursor.fetchall()
 
    level_list = []
    count_list = []
 
    # 把结果写入leve_list和count_list的列表
    for level_info in yourresults:
        level_list.append(severity_level_dict[level_info[0]])
        count_list.append(level_info[1])
 
    print(level_list)
    print([float(count) for count in count_list])
 
    plt.rcparams['font.sans-serif'] = ['simhei'# 设置中文
    # 调节图形大小,宽,高
    plt.figure(figsize=(6, 6))
 
    # 使用count_list的比例来绘制饼图
    # 使用level_list作为注释
    patches, l_text, p_text = plt.pie(count_list,
                                      labels=level_list,
                                      labeldistance=1.1,
                                      autopct='%3.1f%%',
                                      shadow=false,
                                      startangle=90,
                                      pctdistance=0.6)
 
    # 改变文本的大小
    # 方法是把每一个text遍历。调用set_size方法设置它的属性
    for t in l_text:
        t.set_size = 30
    for t in p_text:
        t.set_size = 20
    # 设置x,y轴刻度一致,这样饼图才能是圆的
    plt.axis('equal')
    plt.title('syslog严重级别分布图'# 主题
    plt.legend()
    plt.show()
 
# 绘制syslog来源的饼图
def syslog_show_source_pie(dbname):
    # 连接数据库
    conn = sqlite3.connect(dbname)
    cursor = conn.cursor()
    # 提取log源与其对应的数量
    cursor.execute("select log_source,count(*) as count from syslogdb group by log_source")
    yourresults = cursor.fetchall()
 
    source_list = []
    count_list = []
 
    # 将数据库的信息,依次写入两个列表
    for source_info in yourresults:
        source_list.append(source_info[0])
        count_list.append(source_info[1])
 
    print(source_list)
    print([float(count) for count in count_list])
 
    plt.rcparams['font.sans-serif'] = ['simhei'# 设置中文
    # 调节图形大小,宽,高
    plt.figure(figsize=(6, 6))
 
    # 使用count_list的比例来绘制饼图
    # 使用level_list作为注释
    patches, l_text, p_text = plt.pie(count_list,
                                      labels=source_list,
                                      labeldistance=1.1,
                                      autopct='%3.1f%%',
                                      shadow=false,
                                      startangle=90,
                                      pctdistance=0.6)
 
    # 改变文本的大小
    # 方法是把每一个text遍历。调用set_size方法设置它的属性
    for t in l_text:
        t.set_size = 30
    for t in p_text:
        t.set_size = 20
    # 设置x,y轴刻度一致,这样饼图才能是圆的
    plt.axis('equal')
    plt.title('日志源分布图'# 主题
    plt.legend()
    plt.show()
 
 
if __name__ == '__main__':
    syslog_show_error_level_pie("syslog.sqlite")
    syslog_show_source_pie("syslog.sqlite")

参考资料来源:现任明教教主

到此这篇关于使用python对syslog信息进行分析并绘图的实现的文章就介绍到这了,更多相关python syslog分析 内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家!

原文链接:https://blog.csdn.net/tushanpeipei/article/details/115823325

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