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<!-- Title -->
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<h1>
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<i class="fa fa-circle-o-notch fa-spin"></i>
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<a href=".." >Docker</a>
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<h2 id="docker安装部署">Docker安装部署</h2>
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<p>这应该是部署应用的最方便也是最节省时间的方式了。在最近的一次版本更新<a href="https://github.com/tikazyq/crawlab/releases/tag/v0.2.3" target="_blank">v0.2.3</a>中，我们发布了Docker功能，让大家可以利用Docker来轻松部署Crawlab。下面将一步一步介绍如何使用Docker来部署Crawlab。</p>
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<p>对Docker不了解的开发者，可以参考一下这篇文章（<a href="https://juejin.im/post/5c2c69cee51d450d9707236e" target="_blank">9102 年了，学点 Docker 知识</a>）做进一步了解。简单来说，Docker可以利用已存在的镜像帮助构建一些常用的服务和应用，例如Nginx、MongoDB、Redis等等。用Docker运行一个MongoDB服务仅需<code>docker run -d --name mongo -p 27017:27017 mongo</code>一行命令。如何安装Docker跟操作系统有关，这里就不展开讲了，需要的同学自行百度一下相关教程。</p>
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<h3 id="下载镜像">下载镜像</h3>
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<p>我们已经在<a href="https://hub.docker.com/r/tikazyq/crawlab" target="_blank">DockerHub</a>上构建了Crawlab的镜像，开发者只需要将其pull下来使用。在pull 镜像之前，我们需要配置一下镜像源。因为我们在墙内，使用原有的镜像源速度非常感人，因此将使用DockerHub在国内的加速器。创建<code>/etc/docker/daemon.json</code>文件，在其中输入如下内容。</p>
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<pre><code class="lang-json">{
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<span class="hljs-string">"registry-mirrors"</span>: [<span class="hljs-string">"https://registry.docker-cn.com"</span>]
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}
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</code></pre>
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<p>这样的话，pull镜像的速度会比不改变镜像源的速度快很多。</p>
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<p>执行以下命令将Crawlab的镜像下载下来。镜像大小大概在几百兆，因此下载需要几分钟时间。</p>
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<pre><code class="lang-bash">docker pull tikazyq/crawlab:latest
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</code></pre>
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<h3 id="更改配置文件">更改配置文件</h3>
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<p>拷贝一份后端配置文件<code>./crawlab/config/config.py</code>以及前端配置文件<code>./frontend/.env.production</code>到某一个地方。例如我的例子，分别为<code>/home/yeqing/config.py</code>和<code>/home/yeqing/.env.production</code>。</p>
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<p>更改后端配置文件<code>config.py</code>，将MongoDB、Redis的指向IP更改为自己数据的值。注意，容器中对应的宿主机的IP地址不是<code>localhost</code>，而是<code>172.17.0.1</code>（当然也可以用network来做，只是稍微麻烦一些）。更改前端配置文件<code>.env.production</code>，将API地址<code>VUE_APP_BASE_URL</code>更改为宿主机所在的IP地址，例如<code>http://192.168.0.8:8000</code>，这将是前端调用API会用到的URL。</p>
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<h3 id="运行docker容器">运行Docker容器</h3>
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<p>更改好配置文件之后，接下来就是运行容器了。执行以下命令来启动容器。</p>
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<pre><code class="lang-bash">docker run <span class="hljs-_">-d</span> --rm --name crawlab \
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-p 8080:8080 \
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-p 8000:8000 \
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-v /home/yeqing/.env.production:/opt/crawlab/frontend/.env.production \
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-v /home/yeqing/config.py:/opt/crawlab/crawlab/config/config.py \
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tikazyq/crawlab master
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</code></pre>
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<p>其中，我们映射了8080端口（Nginx前端静态文件）以及8000端口（后端API）到宿主机。另外还将前端配置文件<code>/home/yeqing/.env.production</code>和后端配置文件<code>/home/yeqing/config.py</code>映射到了容器相应的目录下。传入参数<code>master</code>是代表该启动方式为主机启动模式，也就是所有服务（前端、Api、Flower、Worker）都会启动。另外一个模式是<code>worker</code>模式，只会启动必要的Api和Worker服务，这个对于分布式部署比较有用。等待大约20-30秒的时间来build前端静态文件，之后就可以打开Crawlab界面地址地址看到界面了。界面地址默认为<code>http://localhost:8080</code>。</p>
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<p><img src="https://user-gold-cdn.xitu.io/2019/6/12/16b4c3ed5dcd6cfc?w=2532&h=1300&f=png&s=146531" alt=""></p>
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<h3 id="docker-compose">Docker-Compose</h3>
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<p>当然，也可以用<code>docker-compose</code>的方式来部署。<code>docker-compose</code>是一个集群管理方式，可以利用名为<code>docker-compose.yml</code>的<code>yaml</code>文件来定义需要启动的容器，可以是单个，也可以（通常）是多个的。Crawlab的<code>docker-compose.yml</code>定义如下。</p>
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<pre><code class="lang-yaml"><span class="hljs-attr">version:</span> <span class="hljs-string">'3.3'</span>
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<span class="hljs-attr">services:</span>
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<span class="hljs-attr"> master:</span>
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<span class="hljs-attr"> image:</span> tikazyq/crawlab:latest
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<span class="hljs-attr"> container_name:</span> crawlab
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<span class="hljs-attr"> volumns:</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/config.py:/opt/crawlab/crawlab/config/config.py <span class="hljs-comment"># 后端配置文件</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/.env.production:/opt/crawlab/frontend/.env.production <span class="hljs-comment"># 前端配置文件</span>
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8080:8080"</span> <span class="hljs-comment"># nginx</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8000:8000"</span> <span class="hljs-comment"># app</span>
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<span class="hljs-attr"> depends_on:</span>
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<span class="hljs-bullet"> -</span> mongo
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<span class="hljs-bullet"> -</span> redis
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<span class="hljs-attr"> entrypoint:</span>
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<span class="hljs-bullet"> -</span> /bin/sh
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<span class="hljs-bullet"> -</span> /opt/crawlab/docker_init.sh
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<span class="hljs-bullet"> -</span> master
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<span class="hljs-attr"> mongo:</span>
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<span class="hljs-attr"> image:</span> mongo:latest
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<span class="hljs-attr"> restart:</span> always
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"27017:27017"</span>
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<span class="hljs-attr"> redis:</span>
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<span class="hljs-attr"> image:</span> redis:latest
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<span class="hljs-attr"> restart:</span> always
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"6379:6379"</span>
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</code></pre>
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<p>这里先定义了<code>master</code>节点，也就是Crawlab的主节点。<code>master</code>依赖于<code>mongo</code>和<code>redis</code>容器，因此在启动之前会同时启动<code>mongo</code>和<code>redis</code>容器。这样就不需要单独配置<code>mongo</code>和<code>redis</code>服务了，大大节省了环境配置的时间。</p>
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<p>安装<code>docker-compose</code>也很简单，大家去网上百度一下就可以了。</p>
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<p>安装完<code>docker-compose</code>和定义好<code>docker-compose.yml</code>后，只需要运行以下命令就可以启动Crawlab。</p>
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<pre><code class="lang-bash">docker-compose up
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</code></pre>
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<p>同样，在浏览器中输入<code>http://localhost:8080</code>就可以看到界面。</p>
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<h3 id="多节点模式">多节点模式</h3>
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<p><code>docker-compose</code>的方式很适合多节点部署，在原有的<code>master</code>基础上增加几个<code>worker</code>节点，达到多节点部署的目的。将<code>docker-compose.yml</code>更改为如下内容。</p>
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<pre><code class="lang-yaml"><span class="hljs-attr">version:</span> <span class="hljs-string">'3.3'</span>
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<span class="hljs-attr">services:</span>
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<span class="hljs-attr"> master:</span>
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<span class="hljs-attr"> image:</span> tikazyq/crawlab:latest
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<span class="hljs-attr"> container_name:</span> crawlab
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<span class="hljs-attr"> volumns:</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/config.master.py:/opt/crawlab/crawlab/config/config.py <span class="hljs-comment"># 后端配置文件</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/.env.production.master:/opt/crawlab/frontend/.env.production <span class="hljs-comment"># 前端配置文件</span>
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8080:8080"</span> <span class="hljs-comment"># nginx</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8000:8000"</span> <span class="hljs-comment"># app</span>
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<span class="hljs-attr"> depends_on:</span>
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<span class="hljs-bullet"> -</span> mongo
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<span class="hljs-bullet"> -</span> redis
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<span class="hljs-attr"> entrypoint:</span>
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<span class="hljs-bullet"> -</span> /bin/sh
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<span class="hljs-bullet"> -</span> /opt/crawlab/docker_init.sh
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<span class="hljs-bullet"> -</span> master
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<span class="hljs-attr"> worker1:</span>
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<span class="hljs-attr"> image:</span> tikazyq/crawlab:latest
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<span class="hljs-attr"> volumns:</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/config.worker.py:/opt/crawlab/crawlab/config/config.py <span class="hljs-comment"># 后端配置文件</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/.env.production.worker:/opt/crawlab/frontend/.env.production <span class="hljs-comment"># 前端配置文件</span>
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8001:8000"</span> <span class="hljs-comment"># app</span>
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<span class="hljs-attr"> depends_on:</span>
|
|
<span class="hljs-bullet"> -</span> mongo
|
|
<span class="hljs-bullet"> -</span> redis
|
|
<span class="hljs-attr"> entrypoint:</span>
|
|
<span class="hljs-bullet"> -</span> /bin/sh
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<span class="hljs-bullet"> -</span> /opt/crawlab/docker_init.sh
|
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<span class="hljs-bullet"> -</span> worker
|
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<span class="hljs-attr"> worker2:</span>
|
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<span class="hljs-attr"> image:</span> tikazyq/crawlab:latest
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<span class="hljs-attr"> volumns:</span>
|
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<span class="hljs-bullet"> -</span> /home/yeqing/config.worker.py:/opt/crawlab/crawlab/config/config.py <span class="hljs-comment"># 后端配置文件</span>
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<span class="hljs-bullet"> -</span> /home/yeqing/.env.production.worker:/opt/crawlab/frontend/.env.production <span class="hljs-comment"># 前端配置文件</span>
|
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<span class="hljs-attr"> ports:</span>
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"8002:8000"</span> <span class="hljs-comment"># app</span>
|
|
<span class="hljs-attr"> depends_on:</span>
|
|
<span class="hljs-bullet"> -</span> mongo
|
|
<span class="hljs-bullet"> -</span> redis
|
|
<span class="hljs-attr"> entrypoint:</span>
|
|
<span class="hljs-bullet"> -</span> /bin/sh
|
|
<span class="hljs-bullet"> -</span> /opt/crawlab/docker_init.sh
|
|
<span class="hljs-bullet"> -</span> worker
|
|
<span class="hljs-attr"> mongo:</span>
|
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<span class="hljs-attr"> image:</span> mongo:latest
|
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<span class="hljs-attr"> restart:</span> always
|
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<span class="hljs-attr"> ports:</span>
|
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"27017:27017"</span>
|
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<span class="hljs-attr"> redis:</span>
|
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<span class="hljs-attr"> image:</span> redis:latest
|
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<span class="hljs-attr"> restart:</span> always
|
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<span class="hljs-attr"> ports:</span>
|
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<span class="hljs-bullet"> -</span> <span class="hljs-string">"6379:6379"</span>
|
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</code></pre>
|
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<p>这里启动了多增加了两个<code>worker</code>节点，以<code>worker</code>模式启动。这样，多节点部署，也就是分布式部署就完成了。</p>
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