在过去，我使用微软Web应用程序压力测试工具和Pylot对Web应用程序进行压力测试。我写了一个简单的主页、登录脚本和站点演练(在一个电子商务网站中添加一些商品到购物车和结帐)。
只要让少数开发人员在主页上使劲敲一下，就几乎总能找到一个主要问题。更多的可伸缩性问题将在第二阶段浮出水面，甚至更多——在发布之后。
我使用的工具的URL是Microsoft Homer(又名Microsoft Web Application Stress Tool)和Pylot。
这些工具生成的报告对我来说没有多大意义，我花了很多时间试图弄清楚站点能够支持什么样的并发负载。这总是值得的，因为最愚蠢的错误和瓶颈总是会出现(例如，web服务器配置错误)。
你做了什么，你使用了什么工具，你的方法有什么成功?对我来说，最有趣的部分是提出某种有意义的公式，用于从压力测试应用程序报告的数字中计算应用程序可以支持的并发用户数。
当前回答
此外，还有一个很棒的开源纯python分布式和可伸缩的locust框架，它使用了greenlets。它很擅长模拟大量同时使用的用户。
其他回答
这是给JMeter的另一票。
JMeter是一个开源的负载测试工具，用Java编写。它能够测试许多不同的服务器类型(例如，web, web服务，数据库，基本上使用请求的任何东西)。
然而，一旦你开始面对复杂的测试，它确实有一个陡峭的学习曲线，但它是非常值得的。您可以非常快速地启动并运行，这取决于您想要进行哪种类型的压力测试，这可能没问题。
优点:
Open-Source/Free tool from the Apache project (helps with buy-in) Easy to get started with, and easy to use once you grasp the core concepts. (Ie, how to create a request, how to create an assertion, how to work with variables etc). Very scalable. I've run tests with 11 machines generating load on the server to the tune of almost a million hits/hour. It was much easier to setup than I was expecting. Has an active community and good resources to help you get up and running. Read the tutorials first and play with it for a while.
缺点:
The UI is written in Swing. (ugh!) JMeter works by parsing the response text returned by the server. So if you're looking to validate any sort of javascript behaviours, you're out of luck. Learning curve is steep for non-programmers. If you're familiar with regular expressions, you're already ahead of the game. There are large numbers of (insert expletive) idiots in the support forum asking stupid questions that could be easily solved if they'd give the documentation even a cursory glance. ('How do I use JMeter to stress-test my Windows GUI' shows up quite frequently). Reporting 'out of the box' leaves much to be desired, particularly for larger tests. In the test I mentioned above, I ended up having to write a quick console app to do some of the 'xml-logfile' to 'html' conversions. That was a few years ago though, so it's probable that this would no longer be required.
我们已经开发了一个流程，将负载和性能测量视为头等重要的问题——正如你所说，把它留到项目的最后往往会导致失望……
因此，在开发过程中，我们包括非常基本的多用户测试(使用selenium)，它检查基本的疯狂问题，如中断的会话管理、明显的并发问题和明显的资源争用问题。重要的项目在持续集成过程中包含了这一点，所以我们得到了非常定期的反馈。
对于没有极端性能要求的项目，我们在测试中包含基本性能测试;通常，我们使用BadBoy编写测试脚本，并将它们导入JMeter，替换登录细节和其他线程特定的东西。然后我们将这些数据提升到服务器每秒处理100个请求的水平;如果响应时间小于1秒，通常就足够了。我们出发，继续我们的生活。
For projects with extreme performance requirements, we still use BadBoy and JMeter, but put a lot of energy into understanding the bottlenecks on the servers on our test rig(web and database servers, usually). There's a good tool for analyzing Microsoft event logs which helps a lot with this. We typically find unexpected bottlenecks, which we optimize if possible; that gives us an application that is as fast as it can be on "1 web server, 1 database server". We then usually deploy to our target infrastructure, and use one of the "Jmeter in the cloud" services to re-run the tests at scale.
同样，PAL报告有助于分析测试期间发生了什么—您经常会在生产环境中看到非常不同的瓶颈。
关键是要确保不只是运行压力测试，还要收集了解应用程序性能所需的信息。
我发现IBM Page Detailer也是一个有趣的工具。
此外，还有一个很棒的开源纯python分布式和可伸缩的locust框架，它使用了greenlets。它很擅长模拟大量同时使用的用户。
You asked this question almost a year ago and I don't know if you still are looking for another way of benchmarking your website. However since this question is still not marked as solved I would like to suggest the free webservice LoadImpact (btw. not affiliated). Just got this link via twitter and would like to share this find. They create a reasonable good overview and for a few bucks more you get the "full impact mode". This probably sounds strange, but good luck pushing and braking your service :)
