大型实验平台的解剖

Somit Gupta, Lucy Ulanova, Sumit Bhardwaj, Pavel A. Dmitriev, Paul Raff, Aleksander Fabijan
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引用次数: 51

摘要

在线控制实验(例如,A/B测试)是成功的数据驱动型公司不可或缺的一部分。在微软,支持实验是一个独特的挑战,因为正在开发的产品种类繁多,而且实验功能必须添加到现有的成熟产品中,这些产品的代码库可以追溯到几十年前。本文描述了Microsoft ExP平台(简称ExP),该平台为微软的产品(从web属性(如bing.com)到移动应用程序到Windows操作系统中的设备驱动程序)提供了可信赖的大规模A/B实验。该平台的两个核心原则是可信赖性(实验只有在结果可信的情况下才有意义)和可扩展性(我们渴望通过A/B实验暴露任何产品的每一个变化)。目前,每年进行的实验超过一万次。本文描述了A/B实验系统的四个核心组件:实验门户、实验执行服务、日志处理服务和分析服务,并解释了设计选择背后的原因。这四个组成部分共同提供了一个系统,在这个系统中,想法可以在几分钟内转化为实验,而这些实验可以在几小时内提供初步的可靠结果。
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The Anatomy of a Large-Scale Experimentation Platform
Online controlled experiments (e.g., A/B tests) are an integral part of successful data-driven companies. At Microsoft, supporting experimentation poses a unique challenge due to the wide variety of products being developed, along with the fact that experimentation capabilities had to be added to existing, mature products with codebases that go back decades. This paper describes the Microsoft ExP Platform (ExP for short) which enables trustworthy A/B experimentation at scale for products across Microsoft, from web properties (such as bing.com) to mobile apps to device drivers within the Windows operating system. The two core tenets of the platform are trustworthiness (an experiment is meaningful only if its results can be trusted) and scalability (we aspire to expose every single change in any product through an A/B experiment). Currently, over ten thousand experiments are run annually. In this paper, we describe the four core components of an A/B experimentation system: experimentation portal, experiment execution service, log processing service and analysis service, and explain the reasoning behind the design choices made. These four components work together to provide a system where ideas can turn into experiments within minutes and those experiments can provide initial trustworthy results within hours.
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