optimize go applications [using simple example]
对于开发人员，性能分析是必备武器库，实际的性能分析并没有想象中那么困难。
会针对一些比较简单的例子，做CPU/ 内存，以及并发上的分析，目前还是仓库init阶段后续会有更多的例子补充
Go 内置的生态提供了大量的 API 及工具用于诊断程序的逻辑及性能问题。它们大致可以被分为以下几类：
Profiling：Profiling 工具（如 pprof）用于分析程序中的复杂度与开销，如内存使用及函数调用频率等，并通过它们来标识程序中开销最大的部分。
Tracing：Tracing 用于分析某次调用或用户请求的整个流程中的延迟。其支持跨进程，并展示整个系统中每个组件所花费的时间。
Debugging：Debugging 能够检验程序状态及执行流，能够暂停程序并检验其执行。
Runtime statistics and events：收集分析运行时统计及事件并提供程序健康状况的高级综述。尖峰/度的倾角能够帮助我们确定吞吐量，利用率和性能的变化。
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