{"componentChunkName":"component---src-templates-blog-detail-tsx","path":"/blog/2018-03-09-serverless-by-the-numbers-2018-data-report","result":{"data":{"currentBlog":{"id":"73576d26-e0ce-5f26-9330-64b4f3889157","frontmatter":{"thumbnail":"https://main.qcloudimg.com/raw/3cb7b20955d78ced738e0279bb3f6f41.jpg","authors":["AndreaPasswater"],"categories":["news","engineering-culture"],"date":"2018-03-09T00:00:00.000Z","title":"Serverless 数据解读：2018 报告","description":"Serverless Framework 使用统计数据：事件源、服务结构、运行时长等等。","authorslink":["https://serverless.com/author/andreapasswater/"],"translators":["Aceyclee"],"translatorslink":["https://www.zhihu.com/people/Aceyclee"],"tags":["事件源","服务结构"],"keywords":"Serverless 统计数据,Serverless 事件源,Serverless 服务结构","outdated":null},"wordCount":{"words":212,"sentences":45,"paragraphs":45},"fileAbsolutePath":"/opt/build/repo/content/blog/2018-03-09-serverless-by-the-numbers-2018-data-report.md","fields":{"slug":"/blog/2018-03-09-serverless-by-the-numbers-2018-data-report/","keywords":["go","serverless","无服务器","云函数","服务","使用率","Go","部署"]},"html":"

说起如何使用 Serverless Framework，大家都有很多想分享的。

\n

“我将所有的 API 整合到了单个无服务 GraphQL 端点中。”\n“我使用 Serverless Framework 来支持我的机器学习实例。”\n“再请问下，服务器是什么？我完全不知道。我倒是知道云函数，Serverless Framework 和云函数差不多吗？”

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（免责声明：最后一条是我自己编的。）

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那么话说回来，Serverless Framework 的实际统计数据是怎样的呢？

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我们一起来看下：

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事件源

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先来看今天最大的问题：开发者正在部署的所有服务中都包含了什么？

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API 占据主导地位

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答案就是 http。

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在我们深入讨论前，先了解一点有用的背景知识。仅包含一种事件类型的服务占所有服务的 79%。所有服务中的 16% 使用两种事件类型，4% 包含三种或更多事件类型。

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为了使这些数据更易于理解，我们将从几个不同的方面来剖析。\n首先，请看下面这张仅显示单事件源服务的数据图（记住，单事件源服务占所有服务的 79%）：

\n

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含一种事件类型的所有服务（按事件类型）

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大多数包含两种事件类型的服务（所有服务的 16%）中都包含 http，例如 http + cron 和 http + sns。「其他」部分占据较大比例，主要原因在于其中有很多种排列方式，因此我们将其作为一种最受欢迎的类型：

\n

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含两种事件类型的所有服务（按事件类型）

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包含三种及更多事件类型的服务如要划分所有排列不太现实，但此类服务在所有部署的服务中仅占 4% 多一点。

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每个服务有多少个函数？

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我们来看看开发者在每个服务中部署了多少个函数。请注意，本图仅包含在三个不同日期存在部署活动的服务，以便排除「Hello, World」应用。

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服务（按函数个数）

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热门语言

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Serverless 开发者倾向于使用哪些 runtime？

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概况

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Node.js 使用比例遥遥领先，其次是 Python。

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所部署服务的百分比（按语言）

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增长最迅速

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我们来看看各个语言在不同时间段的使用率（不含占据绝对主导地位的 Node 6.10）。

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AWS 上使用的语言（排除 Node 6.10；以服务百分比表示）

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Python 3.6 是过去 8 个月内使用率整体增长最稳定的语言，今年的增长尤为突出。

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但是，从相对较长的时间范围来看，Go 仅在上图中右下角呈现暂时性的趋势。这是因为 Lambda 从一月开始才支持 Go（绘制此图时，受支持时间约 2 个月）。

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Golang 采用率曲线

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Golang 支持是 re:Invent 2017 大会上备受关注的公告之一（Serverless Aurora 也是）。但直到 2018 年 1 月，Golang 支持才提供正式可用版本。

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那么，Go 的使用率增长有多快呢？

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下面这张编程语言（包含各个版本）图表直接比较了 2017 年 8 月和 2018 年 2 月各语言的使用率。

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AWS 上使用的语言（以服务百分比表示）

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在短短的六周内，Go 的使用率已经达到 Java 的一半左右。同样值得注意的是，从 8 月到 2 月，Node.js 的使用率下降了三个百分点。

\n

我们不妨再来看看试验曲线是怎样的。为此，我们以周为时间单位来看看自 1 月 15 日起采用 Go 语言编写的服务的部署次数。（注意，是部署次数而不是服务数量；换而言之，人们使用 Go 的频率有多高。）

\n

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Golang 在 AWS 上的使用率（以占所有部署的百分比表示）

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如图所示，Golang 使用率稳定增长，已经增长了两倍。

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明年的服务统计图一定非常有意思。

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开发人员在什么时间段进行部署？

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早上 7 点？实际并非如此。

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事实证明，服务部署的高峰时段是在午餐时间到下班时间之间：

\n

\n

总结

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