AIOps: Real-World Challenges and Research Innovations
AIOps is about empowering software and service engineers (e.g., developers, program managers, support engineers, site reliability engineers) to efficiently and effectively build and operate online services and applications at scale with artificial intelligence (AI) and machine learning (ML) techniques. AIOps can help improve service quality and customer satisfaction, boost engineering productivity, and reduce operational cost. In this technical briefing, we first summarize the real-world challenges in building AIOps solutions based on our practice and experience in Microsoft. We then propose a roadmap of AIOps related research directions, and share a few successful AIOps solutions we have built for Microsoft service products.
Yingnong Dang is a Principal Data Scientist Manager in Microsoft Azure. Yingnong is responsible of building innovative analytics and ML solutions for improving Azure Infrastructure availability and capacity, boosting engineering productivity, and increasing customer satisfaction. Yingnong’s team has close partnership with Microsoft Research and the academia. Before joining Azure in December 2013, Yingnong was a researcher in Microsoft Research Asia lab. His research areas include software analytics, data visualization, data mining, and human-compute interaction. As a researcher, he has transferred various technologies to Microsoft product teams including code clone analysis, crash dump analysis, performance trace analysis, etc. He owns 45+ U.S. patents and has published papers in top conferences including ICSE, FSE, VLDB, USNIX ATC, and NSDI.
Qingwei Lin Joined Microsoft Research in 2006, and is now a Lead Researcher in DKI (Data Knowledge Intelligence) area of Microsoft Research. Qingwei worked on data-driven technologies for service intelligence, using machine learning and data mining algorithms. In service intelligence area, Qingwei has multiple publications in the conferences of ICSE, FSE, ASE, DSN, SigKDD, USENIX ATC, ICDM, WWW, etc. The research technologies have been transferred into multiple Microsoft product divisions, such as Microsoft Azure, Office 365, Windows, etc. Qingwei hosted Microsoft company-wide "Service Intelligence" workshop as the Chair for 4 consecutive years.
Peng Huang is an Assistant Professor at the Johns Hopkins University Computer Science department (https://cs.jhu.edu/~huang). His research interests lie broadly in computer systems, programming language, and software engineering. He has published in top conferences including OSDI, SOSP, NSDI, MobiSys, EuroSys and ICSE. His co-authored paper received best paper award at OSDI '16. Dr. Huang received his MS and PhD from UC San Diego.
Thu 30 May Times are displayed in time zone: Eastern Time (US & Canada) change
11:00 - 12:30
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