想想您已经花了这么多时间来担心应用程序在负载下会怎样执行。
Just think about all the time you've spent worrying about how your application will perform under load.
它由一组测试和用于在负载下运行这些测试的属性组成。
It consists of a set of tests and the properties for running those tests under load.
将导致更小的JVM大小的物理内存的限制常常使您看到在负载下更高的收集率。
Physical memory restrictions leading to smaller JVM sizes typically see higher rates of collection under load.
一旦将Portlet部署到了门户中，就应该测试Portlet在负载下的行为。
Once your portlet has been deployed into a portal, you should test for the behavior of the portlet under load.
MessageListener线程池应该比任何侦听器端口最大会话值大。 具体多大将取决于系统在负载下的工作方式。
The MessageListener thread pool should be larger than any of the listener port Maximum Session values; how much larger depends on how you want the system to behave under load.
在第四个评估场景中，我们分析了不同工作负载下的磁盘输入/输出。
In our fourth evaluation, we analyzed the disk I/O for each of the workloads.
图7显示了测试期间，在负载和垃圾收集情况下的系统的结果。
Figure 7 shows a system under load and the garbage collection results during the test.
我们的系统没有苛刻的性能需求，但是我们想让系统在最大负载下是可用的。
Our system didn't have demanding performance requirements, but we wanted it to be usable under peak loads.
比起较早的迭代，这些组合的测试一般在较高的负载下执行，并且还至少执行二十四小时。
These combined tests were typically run under higher load than in earlier iterations and also run for at least twenty-four hours.
我们来考虑如何测试用户控制器和登录动作在极端负载下的表现。
Let's consider the user controller and the login action to be tested on extreme loads.
NAPI在高负载的情况下可以产生更好的性能，它避免了为每个传入的帧都产生中断。
NAPI can yield better performance under high loads by avoiding taking an interrupt for each incoming frame.
应用程序的性能是衡量应用程序在某些环境中以及特定负载下运行效率的一个度量。
Application performance is a measure of how efficient your application runs in certain environments and under specific loads.
在满负荷下执行广泛的负载测试，验证一段时间内没有系统和性能降低也很重要。
It's also important to perform extensive load testing under a full load to verify that there is no system or performance degradation over time.
幸运的是，除了启用完整记录功能，在负载较重的情况下，内存消耗没有大量增加。
Fortunately, memory consumption does not increase significantly with heavier loads unless full logging is enabled.
压力测试注重于产品在较大负载下的健壮性、可用性和错误处理效率。
Stress test refers to tests that put a greater emphasis on robustness, availability, and error handling under a heavy load on the product.
我们需要确保所有ASDI 项目的功能都被适当的执行过，并且在一定的负载下测试我们Web 应用的性能。
We needed to make sure all functions of the ASDI system were being performed properly and to test our Web application.s performance under load.
RationalQuantify能使我们查明瓶颈，Robot和SiteLoad能使我们在极高的负载下测试软件以确保系统能够对最坏的条件进行响应。
Rational Quantify enabled us to pinpoint bottlenecks, while Robot and SiteLoad enabled us to test software under peak loads to ensure that the system could respond to worst-case conditions.
这将显示出系统在测试时的内部情况，因为数据收集机制是在系统测试下进行的，而不是负载驱动的。
This shows the inside of the system under test, because the data collection mechanisms are on the systems under test, not the load drivers.
通过将负载测试作为预定的自动构建的一部分来运行，您可以更快地确定您的系统在某些负载条件下的执行情况，并快速适应变化。
By running load tests as part of a scheduled and automated build, you can more quickly determine how your system performs under certain load conditions and quickly adapt to changes.
其代价就是必须将两台机器都配置为处理双倍工作负载，尽管在常规操作下，仅仅使用了一半容量。
The cost is that both machines must be configured to handle double the workload, although under normal operation this capacity is used only by half.
图1显示了在不同用户负载水平下的应用程序特征，我们看到服务器容量和性能的交互。
In Figure 1, which shows application characteristics at different user load levels, we see the interaction between server capacity and performance.
在工作负载平衡的端点引用(epr)情况下，请求在集群中的服务器之间进行负载平衡。
In the case of workload balanced end point references (EPR), the request is load balanced across servers in the cluster.
在分派时，必须在可用的端点之间实现工作负载平衡，并且在可能的情况下将请求发送给活动频率最低的端点。
When dispatching, the workload must be balanced between the available endpoints and when possible the requests should be addressed to the endpoint with the lowest activity rate.
额外的CPU、二级缓存量和内存，在特定用户负载下可提供更好的容量和响应时间。
The additional CPUs, amount of level two cache, and memory provided better capacity and response time at specific user loads.
假设客户端代码不会比服务器缓慢很多，这个数据就是服务器在负载情况下的实际性能的最好表示。
Assuming the client code isn't significantly slower than the server, the figures are also good representations of actual server performance under load.
虽然此选项实现了软实时性能并且即使在负载条件下也可使操作系统顺利地运行，但这样做也付出了代价。
Although the option enables soft real-time performance and even under load makes the operating system execute more smoothly, it does so at a cost.
在第二个评估场景中，我们将查看系统在每个工作负载下的内存使用量。
In our second evaluation scenario, we looked at how much memory the system used at each of the workloads.
如果没有在峰值负载下积极测试和验证集群，那么在真正发生故障时，故障转移的一端可能受到资源限制，响应时间较长，甚至出现故障。
If you do not actively test and validate your clustering during peak loads, during an actual failure the failover side can become constrained and deliver poor response times or even fail.
如果需要执行显式的垃圾收集来降低应用程序内存使用，那么尝试在低负载情况下或在非繁忙时刻实现垃圾收集。
If you want to do explicit garbage collection to reduce your application footprint, attempt to implement it so that it is done under low-load conditions or at off-peak hours.
在这第一个评估场景中，我们将查看系统在每种工作负载下的CPU使用量。
In our first evaluation scenario, we looked at how much of the CPU the system used at each of the workloads.
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