分析 WebMethods 服务？
哪些技术可用于配置 WebMethods Integration Server 中运行的服务？
也就是说，获取表明哪些部分将从优化中受益最多的数据。
What techniques are available to profile services running in WebMethods Integration Server?
That is, to obtain data which would indicate which parts would benefit most from optimisation.
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从 http://www.wrightia.com/serviceprofiler.html 检查“webMethods 集成服务器的服务分析器”
Check the 'Service Profiler for webMethods Integration Server' from http://www.wrightia.com/serviceprofiler.html
您是否想过尝试webMUnit？
您可以在某些方法调用周围添加时间记录，以了解执行过程需要多长时间。 然而，时间记录本身也会增加开销，所以请记住这一点。
或者可能是内存分析器，例如 YourKit Profiler、JProfiler、JProbe 等？ 我不确定这些，因为我自己从未使用过它们，但它们可能会帮助您知道什么占用了大量内存等
Have you thought of trying webMUnit?
You could add time logging around certain method calls to get an idea of how long things are taking to execute. However, the time logging itself will add overhead too, so just keep that in mind.
Or possibly memory profilers such as YourKit Profiler, JProfiler, JProbe etc? Im not sure about these, as I've never used them myself, but they might help by letting you know what's taking up a lot of memory etc
另一个可以做到这一点的工具是 Green Hat tester，它是一个用于测试 webMethods 的商业工具。 如果您在运行测试时使用其报告功能，则会生成生成的分析信息。
António Abreu 的链接工具是一个更专用的分析工具，并且是最简单的解决方案。
如果您想要一个“开箱即用”的解决方案，您可以为被调用的服务打开服务审核并自己进行跑腿工作，但这需要一些手动工作。
Another tool which will do it is Green Hat tester which is a commercial tool used for testing webMethods. If you use the reporting capabilities of that when running tests you get profiling information generated..
António Abreu's linked tool is a more dedicated profiling tool however and would be the simplest solution.
If you want an "out of the box" solution you could turn on service auditing for the called services and do the legwork yourself, but that's a bit of manual effort.
您可以在这里找到一个新的 IS 服务监控工具：丰富的统计信息
You can find here a new monitoring tool for IS services: Rich Statistics
我只参与了开发阶段，所以我不知道细节，但我们的系统经过了重负载测试，并且在此过程中对硬件进行了监控，它实际上给出了一些有关瓶颈的反馈。 使用了JMeter和sar。
I was involved only in development phase so i dont know details but our system was tested with heavy load-testing and hardware was monitored during the process, it actually gave some feedback about bottlenecks. JMeter and sar were used.