Towards self-managing cloud-scale computing platforms: Experiences and challenges

Jingren Zhou
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Abstract

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. More and more companies heavily rely on massive data analysis of many kinds to understand data insights and drive business decisions. To support this ever-increasing need, big data computing platforms have grown to an unprecedented scale, way beyond human manageability. In this talk, I'll share our experiences at Alibaba to enable our big data platforms to configure, optimize, monitor, and protect themselves automatically, including automatic version testing and deployment control, system health monitoring and alert, automatic physical design/data placement/storage optimization, etc. I'll also outline some outstanding research and engineering challenges.
迈向自我管理的云规模计算平台:经验与挑战
仅给出摘要形式,如下。完整的报告没有作为会议记录的一部分提供出版。越来越多的公司严重依赖于多种类型的海量数据分析来理解数据见解并推动业务决策。为了支持这种不断增长的需求,大数据计算平台已经发展到前所未有的规模,远远超出了人类的管理能力。在这次演讲中,我将分享我们在阿里巴巴的经验,使我们的大数据平台能够自动配置、优化、监控和保护自己,包括自动版本测试和部署控制、系统健康监测和警报、自动物理设计/数据放置/存储优化等。我还将概述一些突出的研究和工程挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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