作者：9位特权QQ号码连号 | 来源：互联网 | 2023-09-16 17:35
篇首语：本文由编程笔记#小编为大家整理，主要介绍了Azure China Application Gateway 性能监控相关的知识，希望对你有一定的参考价值。
目前中国区Azure Portal无法支持应用程序网关的日志诊断，显示和告警功能，之前在www.azure.cn网站的应用程序网关文档页面曾经出现过关于日志诊断的配置文章，但其实是直接翻译自Azure Global的，现在已经被删除。
这样意味着中国客户使用AppGW的网站或API，无法通过直接对AppGW的使用情况进行监控，以进行适当的性能扩展。如果一定要看，只能向21V开工单申请拉性能图表，但实时性差了很多，也不方便。这一问题已遭到客户的多次吐槽。
而微软后台研发在上周末由于客户的强烈需求，对中国区应用程序网关进行了hotfix，实现了部分的海外功能，即Diagnostic log生成和写入到Blob Storage的功能。下面对具体如何使用作出分享。
一．Application Gateway的诊断日志开启和检查
目前中国区对AppGW开启诊断日志只能通过以下Powershell命令行进行：Set-AzureRmDiagnosticSetting -ResourceId -StorageAccountId -Enabled
其中ResourceId代表需要被开启日志诊断功能的资源，在本文中具体指应用程序网关，StorageAccountId代表日志被写入的存储账号，由用户自定义。比如我再Powershell登录自己的Azure China测试订阅后，打开一个AppGW的日志诊断功能操作如下：
PS C:\\Users\\huxu> Set-AzureRmDiagnosticSetting -ResourceId /subscriptions/3fd8e8ff-2373-4d1c-8587-bddcd13a1ba0/resourceGroups/DWTEST01/providers/Microsoft.Network/applicationGateways/aapgwmon01 -StorageAccountId /subscriptions/3fd8e8ff-2373-4d1c-8587-bddcd13a1ba0/resourceGroups/dwtest01/providers/Microsoft.Storage/storageAccounts/appgwtest -Enabled $true
StorageAccountId : /subscriptions/3fd8e8ff-2373-4d1c-8587-bddcd13a1ba0/resourceGroups/dwtest01/providers/
Microsoft.Storage/storageAccounts/appgwtest
ServiceBusRuleId :
StorageAccountName :
Metrics
Enabled : True
Timegrain : PT1M
RetentionPolicy
Enabled : False
Days : 0
Logs
Enabled : True
Category : ApplicationGatewayAccessLog
RetentionPolicy
Enabled : False
Days : 0
Enabled : True
Category : ApplicationGatewayPerformanceLog
RetentionPolicy
Enabled : False
Days : 0
Enabled : True
Category : ApplicationGatewayFirewallLog
RetentionPolicy
Enabled : False
Days : 0
然后过了一段时间，在此存储账号内可以看到生成了日志文件。
日志文件为Json格式，其中accesslog文件格式如下：
{
"records":
[
{
"resourceId": "/SUBSCRIPTIONS/1D753E0D-7C47-4EC0-9FEC-EB512CD37742/RESOURCEGROUPS/KD-WEB-RG-PE/PROVIDERS/MICROSOFT.NETWORK/APPLICATIONGATEWAYS/APPGWKD",
"operationName": "ApplicationGatewayAccess",
"time": "2017-06-12T06:50:23Z",
"category": "ApplicationGatewayAccessLog",
"properties": {"instanceId":"ApplicationGatewayRole_IN_1","clientIP":"211.156.223.30","clientPort":44107,"httpMethod":"POST","requestUri":"/expressApi/ems/managePush","requestQuery":"X-AzureApplicationGateway-CACHE-HIT=0&SERVER-ROUTED=172.16.5.12&X-AzureApplicationGateway-LOG-ID=9e84951a-62ca-4903-b66a-86a8cff8eee8&SERVER-STATUS=200","userAgent":"Java/1.6.0_20","httpStatus":200,"httpVersion":"HTTP/1.1","receivedBytes":668,"sentBytes":335,"timeTaken":80,"sslEnabled":"off"}
}
,
{
"resourceId": "/SUBSCRIPTIONS/1D753E0D-7C47-4EC0-9FEC-EB512CD37742/RESOURCEGROUPS/KD-WEB-RG-PE/PROVIDERS/MICROSOFT.NETWORK/APPLICATIONGATEWAYS/APPGWKD",
"operationName": "ApplicationGatewayAccess",
"time": "2017-06-12T06:50:22Z",
"category": "ApplicationGatewayAccessLog",
"properties": {"instanceId":"ApplicationGatewayRole_IN_2","clientIP":"211.156.223.30","clientPort":43661,"httpMethod":"POST","requestUri":"/expressApi/ems/managePush","requestQuery":"X-AzureApplicationGateway-CACHE-HIT=0&SERVER-ROUTED=172.16.5.12&X-AzureApplicationGateway-LOG-ID=9b79883f-639a-45c1-aa26-4797295b62a0&SERVER-STATUS=200","userAgent":"Java/1.6.0_20","httpStatus":200,"httpVersion":"HTTP/1.1","receivedBytes":668,"sentBytes":335,"timeTaken":125,"sslEnabled":"off"}
}
]
}
Performance日志内容如下：
{
"records":
[
{
"resourceId": "/SUBSCRIPTIONS/1D753E0D-7C47-4EC0-9FEC-EB512CD37742/RESOURCEGROUPS/KD-WEB-RG-PE/PROVIDERS/MICROSOFT.NETWORK/APPLICATIONGATEWAYS/APPGWKD",
"operationName": "ApplicationGatewayPerformance",
"time": "2017-06-12T06:54:00Z",
"category": "ApplicationGatewayPerformanceLog",
"properties": {"instanceId":"ApplicationGatewayRole_IN_2","healthyHostCount":2,"unHealthyHostCount":0,"requestCount":0,"latency":22,"failedRequestCount":0,"throughput":0}
}
,
{
"resourceId": "/SUBSCRIPTIONS/1D753E0D-7C47-4EC0-9FEC-EB512CD37742/RESOURCEGROUPS/KD-WEB-RG-PE/PROVIDERS/MICROSOFT.NETWORK/APPLICATIONGATEWAYS/APPGWKD",
"operationName": "ApplicationGatewayPerformance",
"time": "2017-06-12T06:54:00Z",
"category": "ApplicationGatewayPerformanceLog",
"properties": {"instanceId":"ApplicationGatewayRole_IN_0","healthyHostCount":2,"unHealthyHostCount":0,"requestCount":0,"latency":6,"failedRequestCount":0,"throughput":0}
}
]
}
目前中国区的功能属于被阉割版，无法在portal上对应用程序网关的日志进行操作和显示，也无法自定义度量值，比如实例的CPU,MEMORY，只能看到上面日志中默认生成的度量值。监控日志每分钟分别对所有实例生成一次，requestCount和throughput都是过去1分钟每秒的平均值，latency表示后端server的响应平均延迟。
二．利用Python对Application Gateway的诊断日志进行可视化
感谢研发的努力才能拿到这样的结果，但更多的功能还需要漫长的等待。然而客户的吐槽仍然没有停止，难道在系统性能测试时需要用肉眼去看json吗？
对日志文件实现可视化的方法很多，比如官网介绍了将json转成表格然后用powerbi进行酷炫的展示。这里为各位介绍利用python数据处理和画图相关的包进行可视化的方式，个人觉得比较简单灵活。
首先当然是通过python从blob storage取得日志文件，官网有详细操作说明，这里不再赘述。
然后对取得的json文件进行图表展示，比如这里对第二个实例的延迟和存活的后端server数量进行展示，代码如下：
import pandas as pd
import matplotlib.ticker as tic
import matplotlib.pyplot as plt
import matplotlib.dates as dat
import datetime as dt
import os
import json
from matplotlib.font_manager import FontProperties
#载入文件
os.chdir(‘C:\\\\Work\\\\AppGW0613‘)
with open(‘PerformanceLog.json‘,‘r‘) as f:
data = json.load(f)
#赋值
ss=data[‘records‘][0][‘time‘]
list1 = [dt.datetime.strptime(ss,‘%Y-%m-%dT%H:%M:%SZ‘)]
list2 = [data[‘records‘][0][‘properties‘][‘latency‘]]
list3 = [data[‘records‘][0][‘properties‘][‘healthyHostCount‘]]
#遍历监控数据
for i in range (1,data[‘records‘].__len__()):
if data[‘records‘][i][‘properties‘][‘instanceId‘] == ‘ApplicationGatewayRole_IN_2‘:
s=data[‘records‘][i][‘time‘]
timeTuple = dt.datetime.strptime(s,‘%Y-%m-%dT%H:%M:%SZ‘)
list1.append(timeTuple)
list2.append(data[‘records‘][i][‘properties‘][‘latency‘])
list3.append(data[‘records‘][i][‘properties‘][‘healthyHostCount‘])
plt.figure(figsize=(8,20))
#延迟图
ax = plt.subplot(211)
plt.xlabel("Time")
plt.ylabel("Latency")
ax.set_ylim(ymin=0,ymax=25)
ymajor = tic.MultipleLocator(5)
ax.yaxis.set_major_locator(ymajor)
tittle = ‘ApplicationGatewayRole_IN_2‘
font = FontProperties(size=14)
ax.set_title(tittle,fontproperties=font)
ax.xaxis.set_major_formatter(dat.DateFormatter(‘%Y-%m-%d %H:%M:%S‘))
plt.xticks(pd.date_range(list1[0],list1[-1],freq=‘1min‘))
plt.plot(list1,list2,"g")
ax.xaxis_date()
for label in ax.get_xticklabels():
label.set_rotation(20)
label.set_horizontalalignment(‘right‘)
#存活服务器数量图
ax2 = plt.subplot(212)
ax2.set_ylim(ymin=0,ymax=10)
plt.xlabel("Time")
plt.ylabel("HealthyHost")
ymajor = tic.MultipleLocator(1)
ax2.yaxis.set_major_locator(ymajor)
ax2.xaxis.set_major_formatter(dat.DateFormatter(‘%Y-%m-%d %H:%M:%S‘))
plt.xticks(pd.date_range(list1[0],list1[-1],freq=‘1min‘))
plt.plot(list1,list3,"r")
ax2.xaxis_date()
for label in ax2.get_xticklabels():
label.set_rotation(20)
label.set_horizontalalignment(‘right‘)
plt.show()
显示效果如下：
Python的画图方便易用，但我画的有点丑。希望能够有帮助：）
![python有什么应用领域[python常见问题]](https://img1.php1.cn/3cd4a/24c6f/78c/659dcb4c0e67b0fe.jpeg)
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