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<a class="post-title-link" href="/2020/05/08/白话中台番外篇：DDD、EventStorming与业务中台（转载）/" itemprop="url">白话中台番外篇：DDD、EventStorming与业务中台（转载）</a></h1>
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<p>本文转载自（<a href="https://zhuanlan.zhihu.com/p/120896743" target="_blank" rel="noopener">https://zhuanlan.zhihu.com/p/120896743</a>）</p>
<p>提到中台（尤其是业务中台）的构建方法论，就不得不提另两个同样伴随着微服务和中台概念兴起的工具：Domain-Driven Design（DDD，领域驱动设计）和EventStorming（事件风暴）。在各种讲中台落地规划，尤其是业务中台的共性能力识别和微服务划分的时候，总是能看到这两位的身影。不过相信好多朋友对于这两个相对陌生的面孔还是感觉云里雾里，搞不清楚到底是什么，以及与中台的关系。</p>
<p>本篇就以我个人的经历和视角，为大家讲述一下我对这二位的理解。</p>
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<a class="post-title-link" href="/2020/01/12/对架构的理解（手稿）/" itemprop="url">对架构的理解（手稿）（未完待续...）</a></h1>
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<h3 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h3><p>在网络上关于架构的文章有许多，能看到的19年火热的”中台”概念，以及又开始流行的 “DDD”，但对这些知识的理解总是容易混淆，以及为什么需要这些架构方法论，它们能解决的哪些问题，区别在哪等存在着疑惑。就拿之前实习碰到的“域”概念来说，我依然没能想明白设计者是从哪方面去考虑设计的。这篇文章主要是来记录自己对架构设计的笔记和理解。</p>
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<a class="post-title-link" href="/2019/10/21/全链路压测那点事/" itemprop="url">全链路压测那点事（转载）</a></h1>
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<h3 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h3><p>文章转载自 <a href="https://blog.csdn.net/Testfan_zhou/article/details/91955829" target="_blank" rel="noopener">全链路压测那点事(一)</a> </p>
<p>全链路压测一直是测试领域的一顶皇冠。全链路压测对测试人员要求极高，不仅需要有性能测试知识，还要有一定的组织能力与工程能力。全链路压测不仅是一个测试任务，而是一个公司级别的超大型项目，全链路压测涉及到公司所有技术人员与职能部门，从压测准备到实施，直至压测完成后的改进与优化，通常需要涉及公司开发、测试、运维等多个部门协同合作，因此全链路压测更合理的组织方式是以项目形式展开，协同部门负责人进行牵头，集全公司之力以线上性能最优为目标进行的一次技术改进过程。</p>
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<a class="post-title-link" href="/2019/09/09/基础架构-notes/" itemprop="url">基础架构 notes</a></h1>
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<h3 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h3><p>记录基础架构的一些知识点 待续….</p>
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<a class="post-title-link" href="/2019/07/28/阿尔萨斯-原理探究-仿写arthas-TimeTunnel/" itemprop="url">阿尔萨斯 原理探究 仿写arthas-TimeTunnel 流量采集</a></h1>
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<h3 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h3><p>对于TimeTunnel功能块的编写真的可以用心累来形容，总结一句话就是太想当然了！！在开始做这块功能的时候，原本大体的思路就是在watch方法的基础上请求参数进行序列化的操作，但是这个序列化的过程就没有那么容易了！考虑一下下面这种情况：</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">public</span> <span class="keyword">int</span> <span class="title">doAdd</span><span class="params">(<span class="keyword">int</span> x,String s,<span class="keyword">long</span> l ,Job j,Main n,<span class="keyword">double</span> d)</span> </span>{}</span><br></pre></td></tr></table></figure>
<p>考虑到我们将使用反射来完成回放功能，那么你需要将当前的类、方法名、方法参数类型、请求参数都保留下来，前面三个是好做的，但是如果你需要保留的参数并没有实现 Serializable 接口，那么该类就不能被序列化，<strong>并且就算该类实现了Serializable接口，也不能保证该类成员对象都能被序列化的</strong>！！（与深拷贝有点相似，需要考虑到整个对象的引用情况）</p>
<p>于是我换了一种思路，采用FastJson将对象以字符串的形式进行序列化，要回调的时候再通过JSON.parseObject实现对象的转换！！</p>
<p>先看看我的做的TimeTunnel效果图：<font color="#FF0000">对正在运行的函数doAdd和doDelet实现方法级别的流量录制</font>.</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line">2</span><br><span class="line">1</span><br><span class="line">-------------------</span><br><span class="line">开始采集方法：doAdd</span><br><span class="line"></span><br><span class="line">2</span><br><span class="line">开始采集方法：doDelet</span><br><span class="line"></span><br><span class="line">1</span><br><span class="line">-------------------</span><br></pre></td></tr></table></figure>
<p>对类、方法、方法参数以元数据存储一份，每一次的请求参数以当前时间轴进行保存：</p>
<p><img src="/2019/07/28/阿尔萨斯-原理探究-仿写arthas-TimeTunnel/1.png" alt="你想输入的替代文字"></p>
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