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[38/57] [partial] incubator-servicecomb-website git commit: Generated
the static pages for asf-site
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+ <h1 class="page__title" itemprop="headline">使用maven管理复杂依赖关系的技巧
+</h1>
+
+ <p class="page__meta"><i class="fa fa-clock-o" aria-hidden="true"></i>
+
+
+
+
+ 少于 1 分钟 阅读
+
+</p>
+
+ </header>
+
+
+
+ <section class="page__content" itemprop="text">
+ <h2 id="依赖关系管理的核心问题">依赖关系管理的核心问题</h2>
+<p>依赖关系管理最让人头疼的问题是软件版本的选择。一个简化的例子：开发人员目前需要开发一个X项目，该项目需要同时引用项目A提供的组件，也需要引用项目B的组件，并且项目A和项目B同时依赖了项目C，但是版本号不同。</p>
+
+<ul>
+ <li>项目X的pom:</li>
+</ul>
+
+<div class="language-xml highlighter-rouge"><pre class="highlight"><code><span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>groupA<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>artifactA<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.1.0<span class="nt"></version></span>
+<span class="nt"></dependency></span>
+<span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>groupB<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>artifactB<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.1.0<span class="nt"></version></span>
+<span class="nt"></dependency></span>
+</code></pre>
+</div>
+
+<ul>
+ <li>项目A的pom:</li>
+</ul>
+
+<div class="language-xml highlighter-rouge"><pre class="highlight"><code><span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>groupC<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>artifactC<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.1.0<span class="nt"></version></span>
+<span class="nt"></dependency></span>
+</code></pre>
+</div>
+
+<ul>
+ <li>项目B的pom:</li>
+</ul>
+
+<div class="language-xml highlighter-rouge"><pre class="highlight"><code><span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>groupC<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>artifactC<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.2.0<span class="nt"></version></span>
+<span class="nt"></dependency></span>
+</code></pre>
+</div>
+
+<p>项目X在最终发布的时候，会出现如下几种情况：</p>
+
+<ol>
+ <li>使用项目C的0.1.0版本。由于项目B是使用0.2.0版本编译和测试的，那么组件B可能无法正常工作。比如项目B使用了0.2.0提供的新接口。</li>
+ <li>使用项目C的0.2.0版本。由于项目A是使用0.1.0版本编译和测试的，那么组件A可能无法正常工作。比如0.2.0版本和0.1.0不兼容，并且项目A恰好使用了这些不兼容的接口。</li>
+</ol>
+
+<p>可以看出，如果项目A和项目B使用的C组件存在接口不兼容的情况，无论怎么调整，项目X都无法正常工作，这个时候必须修改项目A的代码，使用和B同样的或者兼容的版本进行测试。进行依赖管理，能够做的事情，通常是保证对于公共组件的依赖，都使用较高的版本。尽管如此，我们通常还是会碰到一系列问题，特别是项目依赖关系非常复杂的情况。</p>
+
+<h2 id="最佳实践">最佳实践</h2>
+<p>很多项目都使用maven提供的dependencyManagement配置来管理依赖关系，保证不会因为引入了新的组件，导致基础组件的版本发生变更，出现漏测试的情况。该机制在Spring boot、ServiceComb等开源项目中广泛采用。对于需要提供额外三方软件使用清单的商用产品，这种管理方式可以增强认证信息的准确性。以ServiceComb为例，该项目引入的所有的三方件的版本都统一在:<br />
+ <a href="https://github.com/ServiceComb/ServiceComb-Java-Chassis/blob/master/java-chassis-dependencies/pom.xml">https://github.com/ServiceComb/ServiceComb-Java-Chassis/blob/master/java-chassis-dependencies/pom.xml</a> <br />
+管理，其他的子模块都不配置三方件的版本号，从而每个子模块依赖的三方件版本都是同一个版本，即使他们依赖的模块间接依赖了不同的三方件版本。<br />
+这种机制给使用者也带来了一定的好处，使用者可以采用dependencyManagement来定义自己的三方组件依赖关系，定义的时候，通过import方式继承。比如使用ServiceComb的微服务，可以采用如下方式管理依赖关系：</p>
+
+<div class="language-xml highlighter-rouge"><pre class="highlight"><code><span class="nt"><dependencyManagement></span>
+ <span class="nt"><dependencies></span>
+ <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>io.servicecomb<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>java-chassis-dependencies<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.2.0<span class="nt"></version></span>
+ <span class="nt"><type></span>pom<span class="nt"></type></span>
+ <span class="nt"><scope></span>import<span class="nt"></scope></span>
+ <span class="nt"></dependency></span>
+ <span class="nt"></dependencies></span>
+<span class="nt"></dependencyManagement></span>
+</code></pre>
+</div>
+
+<h2 id="一个复杂的例子">一个复杂的例子</h2>
+<p>这个例子是在业务代码中使用Spring Boot、Spring Cloud、ServiceComb开源组件和ServiceComb商用组件的复杂场景。业务使用Spring Boot开发，并且启用了ServiceComb功能。可以通过下面的配置管理依赖关系。通过调整3个组件的顺序，决定优先使用哪些三方件。常见的业务场景有：</p>
+
+<ul>
+ <li>Spring Cloud依赖于Spring Boot，业务发现Spring Boot的bug，并升级了Spring boot，但是Spring Cloud没有配套对应版本的新版本。在Spring Boot接口兼容的情况下，可以将Spring Boot的依赖放到Spring Cloud前面，从而达到独立升级Spring Boot的目的。</li>
+ <li>Spring Cloud发现了bug，但是修复该bug的版本同时升级了Spring Boot，业务当前有其他原因不能使用Spring Boot的新版本，这个时候，可以将Spring Boot的依赖放到前面，保证了不会由于升级Spring Cloud，而引入Spring Boot新的版本。</li>
+</ul>
+
+<div class="language-xml highlighter-rouge"><pre class="highlight"><code> <span class="nt"><dependencyManagement></span>
+ <span class="nt"><dependencies></span>
+ <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>org.springframework.boot<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>spring-boot-dependencies<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>1.5.6.RELEASE<span class="nt"></version></span>
+ <span class="nt"><type></span>pom<span class="nt"></type></span>
+ <span class="nt"><scope></span>import<span class="nt"></scope></span>
+ <span class="nt"></dependency></span>
+ <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>org.springframework.cloud<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>spring-cloud-dependencies<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>Dalston.SR2<span class="nt"></version></span>
+ <span class="nt"><type></span>pom<span class="nt"></type></span>
+ <span class="nt"><scope></span>import<span class="nt"></scope></span>
+ <span class="nt"></dependency></span>
+ <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>io.servicecomb<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>java-chassis-dependencies<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.2.0<span class="nt"></version></span>
+ <span class="nt"><type></span>pom<span class="nt"></type></span>
+ <span class="nt"><scope></span>import<span class="nt"></scope></span>
+ <span class="nt"></dependency></span>
+ <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>com.huawei.paas.cse<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>cse-dependency<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>2.1.1<span class="nt"></version></span>
+ <span class="nt"><type></span>pom<span class="nt"></type></span>
+ <span class="nt"><scope></span>import<span class="nt"></scope></span>
+ <span class="nt"></dependency></span>
+ <span class="nt"></dependencies></span>
+ <span class="nt"></dependencyManagement></span>
+</code></pre>
+</div>
+
+<h2 id="总结">总结</h2>
+<p>上面列举了依赖关系管理的最佳实践。在配套不同组件进行业务代码开发时，如果碰到ClassNotFoundException、NoSuchMethodException等异常，可以通过IDE（比如eclipse）或者mvn dependency:tree命令来分析是否由于依赖关系错误，引入了某些三方件较老的版本，然后都可以利用dependencyManagement机制来强制约束三方件的版本号。正如最开始指出的，任何的三方件升级都可能存在风险，并且有些时候会出现无法解决，需要修改依赖组件代码的情况。一个好的实践是进行持续的集成，并增加适当的测试用例，尽早发现问题和解决依赖关系管理引入的接口不兼容问题。我们建议开发者能够结合上面的例子，适当调整下各个组件的顺序，观察一个项目实际使用的三方件版本的变化，深刻理解dependencyManagement的作用原理，这样能够帮助快速解决开发过程中碰到的ClassNotFoundExcep
tion、NoSuchMethodException等问题。</p>
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+</h1>
+
+ <p class="page__meta"><i class="fa fa-clock-o" aria-hidden="true"></i>
+
+
+
+
+ 少于 1 分钟 阅读
+
+</p>
+
+ </header>
+
+
+
+ <section class="page__content" itemprop="text">
+ <h2 id="背景">背景</h2>
+<p> <a href="https://github.com/ServiceComb/seckill">秒杀</a>是我们ServiceComb开源团队以领域驱动设计（<a href="https://en.wikipedia.org/wiki/Domain-driven_design">DDD</a>）为背景，从零开始构建一个微服务架构的示例项目；在《秒杀开发历程》系列博文中提到它作为一个高并发压力场景的应用，采用了<a href="https://docs.microsoft.com/en-us/azure/architecture/patterns/cqrs">CQRS</a>模式构建，因此我们将使用<a href="http://jmeter.apache.org/">JMeter</a>来对其进行性能评估。</p>
+
+<h2 id="制定用户行为模型">制定用户行为模型</h2>
+<p> 因为秒杀的场景在现实生活中非常常见，所以用户行为模型非常容易设计：</p>
+<ol>
+ <li>客户不停的刷秒杀活动，直到刷出一个正在进行的秒杀活动；</li>
+ <li>刷出了秒杀活动后，马上请求秒杀优惠券；</li>
+ <li>无论是否成功，客户会稍后查询一次自己已经拥有的优惠券确定优惠券是否进入自己的账号。</li>
+</ol>
+
+<p> 我们还需要一个管理员用户，隔一段时间就创建发布秒杀活动，当然活动包含的优惠券数量将会远少于客户的数量。
+
+ 用户行为模型在JMeter中体现为脚本逻辑，完成的脚本逻辑如下：</p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-script.png" alt="图1 脚本模型" class="align-center" /></p>
+
+<p> 脚本文件已经托管至秒杀项目中，可直接获取：</p>
+
+<div class="language-bash highlighter-rouge"><pre class="highlight"><code>git clone https://github.com/ServiceComb/seckill
+<span class="nb">cd </span>seckill/performance-test/script
+</code></pre>
+</div>
+
+<h2 id="性能测试环境">性能测试环境</h2>
+<p> 我们调来了两台云服务器进行性能测试，角色和配置如下：</p>
+<h3 id="秒杀服务器配置">秒杀服务器配置</h3>
+<p> 承载秒杀示例所有的微服务和中间件，包括四个微服务（Admin、Command、Event和Query）、两个数据库（ReadDB和WriteDB）和一个Message Broker（ActiveMQ）。</p>
+
+<table>
+ <thead>
+ <tr>
+ <th>配置项</th>
+ <th>配置值</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>CPU</td>
+ <td>Intel Xeon E5-2690 3.0GHz * 16</td>
+ </tr>
+ <tr>
+ <td>MEM</td>
+ <td>64GB</td>
+ </tr>
+ <tr>
+ <td>OS</td>
+ <td>Ubuntu 16.04.2 LTS</td>
+ </tr>
+ </tbody>
+</table>
+
+<p> 为了能够便于配置和启动示例系统，我们采用《秒杀开发历程（三）》中的一键启动模式拉起所有的服务，因此Docker升级为当前最新版17.06.2-ce，能够支持配置Container使用CPU和内存的大小限制，以Admin微服务为例：
+ </p>
+<div class="language-yaml highlighter-rouge"><pre class="highlight"><code> <span class="s">admin-service</span><span class="pi">:</span>
+ <span class="s">mem_limit</span><span class="pi">:</span> <span class="s">4096m</span>
+ <span class="s">cpu_count</span><span class="pi">:</span> <span class="s">4</span>
+ <span class="s">cpu_percent</span><span class="pi">:</span> <span class="s">50</span>
+ <span class="s">image</span><span class="pi">:</span> <span class="s2">"</span><span class="s">seckill-admin-service:0.2.0-SNAPSHOT"</span>
+ <span class="s">hostname</span><span class="pi">:</span> <span class="s">admin-service</span>
+ <span class="s">links</span><span class="pi">:</span>
+ <span class="pi">-</span> <span class="s2">"</span><span class="s">mysql-write-db:write_db.servicecomb.io"</span>
+ <span class="s">environment</span><span class="pi">:</span>
+ <span class="pi">-</span> <span class="s">JAVA_OPTS=-Dspring.profiles.active=prd -Dendpoints.shutdown.enabled=true</span>
+ <span class="s">ports</span><span class="pi">:</span>
+ <span class="pi">-</span> <span class="s2">"</span><span class="s">8081:8081"</span>
+</code></pre>
+</div>
+
+<h3 id="加压机配置">加压机配置</h3>
+<p> 加压机与秒杀服务器处于同一网络环境中，配置如下：
+
+| 配置项 | 配置值 |
+| —- | —————————— |
+| CPU | Intel Xeon E5-2690 3.0GHz * 16 |
+| MEM | 32GB |
+| OS | Ubuntu 16.04.2 LTS |</p>
+
+<h2 id="启动测试">启动测试</h2>
+<p> 我们设定测试场景为200客户，每隔1秒启动一个新客户；1个管理员每隔10秒发布1个秒杀活动，一共发布160次，每个秒杀活动包含50张优惠券，即一共投放8000张优惠券。整个测试持续半个小时。
+
+ 现在，我们切换到性能测试脚本目录下，执行下面的命令启动测试：
+ </p>
+<div class="language-bash highlighter-rouge"><pre class="highlight"><code>jmeter -n -t seckill.jmx -l log.jtl
+</code></pre>
+</div>
+
+<h2 id="测试结果">测试结果</h2>
+<p> 测试完毕后通过下面的命令分析测试结果日志数据，请将<report folder="">替换为你的本地目录：</report></p>
+
+<div class="language-bash highlighter-rouge"><pre class="highlight"><code>jmeter -g log.jtl -o <report folder>
+</code></pre>
+</div>
+
+<p> 我们需要先验证测试结果的正确性，查看数据统计图：</p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-statistics.png" alt="图2 事务统计" class="align-center" /></p>
+
+<p> 其中秒杀的失败率在96.45%，原因是Query对于活动的秒杀活动采用的是0.5秒刷新缓存的策略，在活动中的优惠券被秒杀一空下架前，短暂的时间内仍然能够查询到这个活动；架构中采用的<a href="https://docs.microsoft.com/en-us/azure/architecture/patterns/cqrs">CQRS</a>模式只能保证最终一致性，并不能保证实时一致性。
+
+ 成功秒杀的次数为225264 - 217264 = 8000，正好等于我们设定的优惠券投放量，其他事务的失败率均为0%，因此测试结果正确。</p>
+
+<h3 id="吞吐能力">吞吐能力</h3>
+<p> 秒杀整体吞吐能力如下图：</p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-tps-all.png" alt="图3 整体吞吐能力" class="align-center" /></p>
+
+<p> 可以看到查询活跃的秒杀活动（刷券）事务处理量最高，稳定在4000左右，其他因为业务比例的原因较低，去掉查询活跃的秒杀活动事务后如下图：</p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-tps-less.png" alt="图4 秒杀和优惠券查询" class="align-center" /></p>
+
+<p> 秒杀和优惠券查询之间的差值是由于存在秒杀失败造成的，我们的用户行为模型是无论秒杀成功与否都会进行一次优惠券查询。</p>
+
+<h3 id="响应时间">响应时间</h3>
+<p> 事务的响应时间我们可以看下面两个图：</p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-latencies.png" alt="图5 响应时间" class="align-center" /></p>
+
+<p><img src="/assets/images/performance-test-on-seckill-with-jmeter-time-percentiles.png" alt="图6 响应时间分布" class="align-center" /></p>
+
+<p> 75%的事务处理时间都在10ms以下，整体平均响应时间处于50ms以下。</p>
+
+<h2 id="瓶颈分析">瓶颈分析</h2>
+<p> 依据执行过程中对于测试资源的观察，加压机CPU使用率基本已满（200线程并发），服务器CPU使用率低于20%，其他资源使用率很低。</p>
+
+<h2 id="总结">总结</h2>
+<p> 通过这次性能测试，我们得知秒杀示例在使用一台普通服务器配置能够达到总体5000以上的TPS还能够保持较低的资源使用率，表现出良好的性能；未来我们会将秒杀示例部署在K8S群集中并配置弹性伸缩进行压力测试，您可以阅读我们<a href="http://servicecomb.io/cn/docs/stress-test-on-company-with-jmeter-in-k8s/">《在Kubernetes集群中使用JMeter对Company示例进行压力测试》</a>这篇文章展望。</p>
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+ <article class="page" itemscope itemtype="http://schema.org/CreativeWork">
+ <meta itemprop="headline" content="分布式调用链追踪">
+ <meta itemprop="description" content="介绍如何在体质指数应用中使用ServiceComb提供的分布式追踪能力">
+
+ <meta itemprop="dateModified" content="September 03, 2017">
+
+ <div class="page__inner-wrap">
+
+
+ <header>
+ <h1 class="page__title" itemprop="headline">分布式调用链追踪
+</h1>
+
+ </header>
+
+
+
+ <section class="page__content" itemprop="text">
+ <aside class="sidebar__right">
+<nav class="toc">
+ <!-- <header><h4 class="nav__title"><i class="fa fa-file-text"></i> 在本页上</h4></header> -->
+<ul class="toc__menu" id="markdown-toc">
+ <li><a href="#前言" id="markdown-toc-前言">前言</a></li>
+ <li><a href="#启用" id="markdown-toc-启用">启用</a></li>
+ <li><a href="#验证" id="markdown-toc-验证">验证</a></li>
+ <li><a href="#下一步" id="markdown-toc-下一步">下一步</a></li>
+</ul>
+
+ </nav>
+</aside>
+
+<p>分布式调用链追踪用于有效地监控微服务的网络延时并可视化微服务中的数据流转。本指南将展示如何在 <em>体质指数</em> 应用中使用 <strong>ServiceComb</strong> 提供的分布式调用链追踪能力。</p>
+
+<h2 id="前言">前言</h2>
+
+<p>在您进一步阅读之前，请确保您已阅读了<a href="/cn/docs/quick-start-bmi/">微服务应用快速开发指南</a>，并已成功运行体质指数微服务。</p>
+
+<h2 id="启用">启用</h2>
+
+<ol>
+ <li>
+ <p>在 <em>体质指数计算器</em> 的 <code class="highlighter-rouge">pom.xml</code> 文件中添加依赖项：</p>
+
+ <div class="language-xml highlighter-rouge"><pre class="highlight"><code> <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>io.servicecomb<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>handler-tracing-zipkin<span class="nt"></artifactId></span>
+ <span class="nt"></dependency></span>
+</code></pre>
+ </div>
+ </li>
+ <li>
+ <p>在 <em>体质指数计算器</em> 的 <code class="highlighter-rouge">microservice.yaml</code> 文件中添加分布式追踪的处理链：</p>
+
+ <div class="language-yaml highlighter-rouge"><pre class="highlight"><code><span class="s">cse</span><span class="pi">:</span>
+ <span class="s">handler</span><span class="pi">:</span>
+ <span class="s">chain</span><span class="pi">:</span>
+ <span class="s">Provider</span><span class="pi">:</span>
+ <span class="s">default</span><span class="pi">:</span> <span class="s">tracing-provider</span>
+</code></pre>
+ </div>
+ </li>
+ <li>
+ <p>在 <em>体质指数界面</em> 的 <code class="highlighter-rouge">pom.xml</code> 文件中添加依赖项：</p>
+
+ <div class="language-xml highlighter-rouge"><pre class="highlight"><code> <span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>io.servicecomb<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>spring-cloud-zuul-zipkin<span class="nt"></artifactId></span>
+ <span class="nt"></dependency></span>
+</code></pre>
+ </div>
+ </li>
+</ol>
+
+<p>体质指数应用中已配置好了上述配置项，您只需执行以下几步即可：</p>
+
+<ol>
+ <li>
+ <p>使用 Docker 运行 <em>Zipkin</em> 分布式追踪服务：</p>
+
+ <div class="language-bash highlighter-rouge"><pre class="highlight"><code>docker run -d -p 9411:9411 openzipkin/zipkin
+</code></pre>
+ </div>
+ </li>
+ <li>
+ <p>重启 <em>体质指数计算器</em> 微服务：</p>
+
+ <div class="language-bash highlighter-rouge"><pre class="highlight"><code>mvn spring-boot:run -Drun.jvmArguments<span class="o">=</span><span class="s2">"-Dcse.handler.chain.Provider.default=tracing-provider"</span>
+</code></pre>
+ </div>
+ </li>
+ <li>
+ <p>重启 <em>体质指数界面</em> 微服务：</p>
+
+ <div class="language-bash highlighter-rouge"><pre class="highlight"><code>mvn spring-boot:run -Drun.jvmArguments<span class="o">=</span><span class="s2">"-Dservicecomb.tracing.enabled=true"</span>
+</code></pre>
+ </div>
+ </li>
+</ol>
+
+<h2 id="验证">验证</h2>
+
+<ol>
+ <li>
+ <p>访问 <a>http://localhost:8889</a> ，在身高和体重栏处输入正数，并点击 <em>Submit</em> 按钮。</p>
+ </li>
+ <li>
+ <p>访问 <a>http://localhost:9411</a> ，查看分布式调用追踪情况，可得下方界面。</p>
+ </li>
+</ol>
+
+<p><img src="/assets/images/distributed-tracing-result.png" alt="分布式追踪效果" class="align-center" /></p>
+
+<h2 id="下一步">下一步</h2>
+
+<ul>
+ <li>
+ <p>了解更多<a href="/cn/users/distributed-tracing/">分布式调用链追踪</a></p>
+ </li>
+ <li>
+ <p>阅读<a href="/cn/docs/tracing-with-servicecomb/">基于 ServiceComb 和 Zipkin 的分布式调用链追踪</a>来进一步了解分布式追踪</p>
+ </li>
+ <li>
+ <p>认识 <a href="/cn/users/"><strong>ServiceComb</strong> 微服务开发框架</a></p>
+ </li>
+ <li>
+ <p>通过 <a href="/cn/docs/linuxcon-workshop-demo/">Company应用</a> 更深入地了解微服务开发</p>
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