AI for System - Infusing AI into Cloud Computing Systems

Abstract

In the past fifteen years, the most significant paradigm shift in the computing industry is the migration to cloud computing, which brings unprecedented opportunities of digital transformation to business, society, and human life. The implication of this is profound. It means that cloud computing platforms have become part of the basic infrastructure of the world. Therefore, the non-functional properties of cloud computing platforms, including availability, reliability, performance, efficiency, security, sustainability, etc., become immensely important. The distributed nature, massive scale, and high complexity of cloud computing platforms ranging from storage to networking, computing and beyond present huge challenges to achieve effective and efficient building and operation of such software systems. There is huge wealth of various types of data available throughout the entire development lifecycle of software systems. This is manifested even stronger with the paradigm shift to cloud computing as much more data are available on system runtime and workloads. Leveraging the amount of data, AI for System is to utilize AI/ML technologies to design and build high-quality cloud systems at scale. In this talk, I will first introduce the concept of AI for System and its research landscape. Then using a few projects at Microsoft as examples [1-10], I will talk about the work from Microsoft Research on AI for System and its impact. I will also discuss the research challenges and opportunities in AI for System moving forward.