Computer Performance

In computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved:

Short response time for a given piece of work.
High throughput (rate of processing work).
Low utilization of computing resource(s).
Fast (or highly compact) data compression and decompression.
High availability of the computing system or application.
High bandwidth.
Short data transmission time.

Performance Metrics/Indicators

Refer to https://swsmile.info/post/performance-indicator/.

Benchmark

In computing, a benchmark is the act of running a computer program, a set of programs, or other operations, in order to assess the relative performance of an object, normally by running a number of standard tests and trials against it.[1] The term benchmark is also commonly utilized for the purposes of elaborately designed benchmarking programs themselves.

Benchmarking is usually associated with assessing performance characteristics of computer hardware, for example, the floating point operation performance of a CPU, but there are circumstances when the technique is also applicable to software. Software benchmarks are, for example, run against compilers or database management systems (DBMS).

Benchmarks provide a method of comparing the performance of various subsystems across different chip/system architectures.

Profiling (performance analysis)

In software engineering, profiling (“program profiling”, “software profiling”) is a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or frequency and duration of function calls. The most common use of profiling information is to aid program optimization.

Profiling is achieved by instrumenting either the program source code or its binary executable form using a tool called a profiler (or code profiler). A number of different techniques may be used by profilers, such as event-based, statistical, instrumented, and simulation methods.

Performance Tuning

Performance tuning is the improvement of system performance. This is typically a computer application, but the same methods can be applied to economic markets, bureaucracies or other complex systems. The motivation for such activity is called a performance problem, which can be real or anticipated. Most systems will respond to increased load with some degree of decreasing performance. A system’s ability to accept a higher load is called scalability, and modifying a system to handle a higher load is synonymous to performance tuning.

Systematic tuning follows these steps:

Assess the problem and establish numeric values that categorize acceptable behavior.
Measure the performance of the system before modification.
Identify the part of the system that is critical for improving the performance. This is called the bottleneck.
Modify that part of the system to remove the bottleneck.
Measure the performance of the system after modification.
If the modification makes the performance better, adopt it. If the modification makes the performance worse, put it back to the way it was.

Analysis

一般来说，一个系统的性能受到这两个条件的约束，缺一不可。比如，我的系统可以顶得住一百万的并发，但是系统的延迟是2分钟以上，那么，这个一百万的负载毫无意义。系统延迟很短，但是吞吐量很低，同样没有意义。所以，一个好的系统的性能测试必然受到这两个条件的同时作用。有经验的朋友一定知道，这两个东西的一些关系：

**Throughput越大，Latency会越差。**因为请求量过大，系统太繁忙，所以响应速度自然会低。
**Latency越好，能支持的Throughput就会越高。**因为Latency短说明处理速度快，于是就可以处理更多的请求。

系统性能测试

经过上述的说明，我们知道要测试系统的性能，需要我们收集系统的Throughput和Latency这两个值。

首先，需要定义Latency这个值，比如说，对于网站系统响应时间必需是5秒以内（对于某些实时系统可能需要定义的更短，比如5ms以内，这个更根据不同的业务来定义）
其次，开发性能测试工具，一个工具用来制造高强度的Throughput，另一个工具用来测量Latency。对于第一个工具，你可以参考一下“十个免费的Web压力测试工具”，关于如何测量Latency，你可以在代码中测量，但是这样会影响程序的执行，而且只能测试到程序内部的Latency，真正的Latency是整个系统都算上，包括操作系统和网络的延时，你可以使用Wireshark来抓网络包来测量。这两个工具具体怎么做，这个还请大家自己思考去了。
最后，开始性能测试。你需要不断地提升测试的Throughput，然后观察系统的负载情况，如果系统顶得住，那就观察Latency的值。这样，你就可以找到系统的最大负载，并且你可以知道系统的响应延时是多少。

再多说一些，

关于Latency，如果吞吐量很少，这个值估计会非常稳定，当吞吐量越来越大时，系统的Latency会出现非常剧烈的抖动，所以，我们在测量Latency的时候，我们需要注意到Latency的分布，也就是说，有百分之几的在我们允许的范围，有百分之几的超出了，有百分之几的完全不可接受。也许，平均下来的Latency达标了，但是其中仅有50%的达到了我们可接受的范围。那也没有意义。
关于性能测试，我们还需要定义一个时间段。比如：在某个吞吐量上持续15分钟。因为当负载到达的时候，系统会变得不稳定，当过了一两分钟后，系统才会稳定。另外，也有可能是，你的系统在这个负载下前几分钟还表现正常，然后就不稳定了，甚至垮了。所以，需要这么一段时间。这个值，我们叫做峰值极限。
性能测试还需要做Soak Test，也就是在某个吞吐量下，系统可以持续跑一周甚至更长。这个值，我们叫做系统的正常运行的负载极限。

性能测试有很多很复要的东西，比如：burst test等。这里不能一一详述，这里只说了一些和性能调优相关的东西。总之，性能测试是一细活和累活。

【Performance】性能