有哪些用于性能测试 SharePoint Web 部件和控件的好技术? [英] What are some good techniques for performance testing SharePoint web parts and controls?

问题描述

这是一个关于特定于 SharePoint Web 部件和控件的性能测试的问题(尽管标准 ASP.NET 方法也适用).我想知道有哪些好的技术，考虑到以下因素:

This is a question about performance testing specific to SharePoint web parts and controls (although standard ASP.NET methods would be applicable as well). I'm wondering what are some good techniques, considering factors such as:

• 缓存(你应该缓存什么以及什么时候缓存?)
• 负载均衡服务器(存储状态)
• 与页面其他部分的交互(例如多个 JavaScript 执行)
• 测量特定控件的 CPU 使用率
• 渲染页面大小

推荐答案

我推荐 Visual Studio Test Suite 2008 SP1.我们在索引服务器上使用了一个测试代理，测试控制器在安装了 Visual Studio 的开发人员桌面上运行.

I recommend Visual Studio Test Suite 2008 with SP1. We have used a test agent on our indexing server with the test controller running on the developers desktop with Visual Studio installed.

可以模拟浏览器缓存，并且我们发现我们自己的服务器缓存存在错误，而缓存实际上并没有发挥作用.

It is possible to simulate browser caching and we have found errors with our own server caching where the caching was not actually working.

负载平衡服务器易于使用，因为您可以模拟一系列 IP 地址.您确实需要能够为运行测试的机器分配一系列 ip 地址，并且只能调整 ip 地址的最后一个八位字节.可以将每个 Web 前端的统计信息添加到测试生成的 perfmon 统计信息中.

Load balanced servers are easy to work with as you can simulate a range of ip addresses. You do need to be able to assign a range of ip addresses to the machine running the tests and only the last octet of the ip address is able to be adjusted. The stats on each web front end can be added to the perfmon stats generated by the test.

如果需要，您可以模拟对页面不同部分的点击，但场景越复杂，就越难做到完美.

You can simulate clicks on different parts of the page if required, but the more complex the scenario the harder it is to get perfect.

CPU 和其他统计数据测量很棒.所有的测试结果都可以添加到数据库中，负载测试期间和之后的测试图表非常好.

The CPU and other stats measuring is great. All the test results can be added to a database and the charting of the tests during and after the load test is really good.

可以在每次测试运行中添加注释，以便您在需要查看之前运行的测试结果时轻松识别它们.

Comments can be added to each test run so you can identify them easily when you need to view the results of tests that have been run before.

请注意，随着时间的推移，结果可能会迅速增加.

Be warned that the results can quickly add up in size over time.

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