首页> 外文会议>2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice >Safe Velocity: A Practical Guide to Software Deployment at Scale using Controlled Rollout
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Safe Velocity: A Practical Guide to Software Deployment at Scale using Controlled Rollout

机译:安全速度:使用受控部署大规模部署软件的实用指南

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Software companies are increasingly adopting novel approaches to ensure their products perform correctly, succeed in improving user experience and for increasing revenue. Two approaches that have significantly impacted product development are controlled experiments - concurrent experiments with different variations of the same product, and phased rollouts - deployments to smaller audiences (rings) before deploying broadly. Although powerful in isolation, product teams experience most benefits when the two approaches are integrated. Intuitively, combining them may seem trivial. However, in practice and at a large scale, this is difficult. For example, it requires careful data analysis to correctly handle exposed populations, determine the duration of exposure, and identify the differences between the populations. All of these are needed to optimize the likelihood of successful deployments, maximize learnings, and minimize potential harm to users of the products. In this paper, based on case study research at Microsoft, we introduce controlled rollout (CRL), which applies controlled experimentation to each ring of a traditional phased rollout. We describe its implementation on several products used by hundreds of millions of users along with the complexities encountered and overcome. In particular, we explain strategies for selecting the length of the rollout period and metrics of focus, and defining the pass criterion for each of the rings. Finally, we evaluate the effectiveness of CRL by examining hundreds of controlled rollouts at Microsoft Office. With our work, we hope to help other companies in optimizing their software deployment practices.
机译:软件公司越来越多地采用新颖的方法来确保其产品正确运行,成功改善用户体验并增加收入。两种对产品开发有重大影响的方法是受控实验-相同产品不同变体的并发实验,以及分阶段推出-在广泛部署之前先部署到较小的受众群体。尽管隔离功能强大,但是将这两种方法集成在一起时,产品团队将获得最大的收益。直观地,将它们组合起来似乎微不足道。然而,在实践中并且大规模地,这是困难的。例如,它需要仔细的数据分析,以正确处理暴露的种群,确定暴露的持续时间并确定种群之间的差异。所有这些都需要优化成功部署的可能性,最大程度地学习和最大程度地减少对产品用户的潜在危害。在本文中,基于Microsoft的案例研究,我们介绍了受控推出(CRL),它将受控实验应用于传统的分阶段推出的每个环。我们描述了它在数亿用户使用的几种产品上的实现以及遇到和克服的复杂性。特别是,我们解释了选择部署周期的长度和焦点度量以及定义每个环的通过标准的策略。最后,我们通过检查Microsoft Office上的数百个受控部署来评估CRL的有效性。通过我们的工作,我们希望能帮助其他公司优化其软件部署实践。

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