AI for Cloud Ops
Join the first Research Days event of 2022 featuring ‘AI for Cloud Ops’ on February 16, 2022 between 11:00AM and 12:30PM EST (5:00PM CET, 6:00PM IST). Boston University faculty members Ayse Coskun, Alan Liu, and Gianluca Stringhini, and Red Hat’s Marcel Hild, Senior Manager, AIOps, AI CoE, Office of the CTO, will discuss this collaborative work at the intersection of artificial intelligence (AI) and cloud systems. Michael Clifford, Associate Manager, Data Science, Red Hat, will lead a discussion with the project team.
Today’s Continuous Integration/Continuous Development (CI/CD) trends encourage rapid design of software using a wide range of customized, off-the-shelf, and legacy software components, followed by frequent updates that are immediately deployed on the cloud. Altogether, this component diversity and breakneck pace of development amplify the difficulty in identifying, localizing, or fixing problems related to performance, resilience, and security. Existing approaches that rely on human experts have limited applicability to modern CI/CD processes, as they are fragile, costly, and often not scalable. This project aims to address this gap in effective cloud management and operations with a concerted, systematic approach to building and integrating AI-driven software analytics into production systems. We aim to provide a rich selection of heavily-automated “ops” functionality as well as intuitive, easily-accessible analytics to users, developers, and administrators. In this way, our longer-term aim is to improve performance, resilience, and security in the cloud without incurring high operation costs.
Ayse Coskun, Professor, Electrical and Computer Engineering at Boston University
Alan Liu, Assistant Professor, Electrical and Computer Engineering at Boston University
Gianluca Stringhini Assistant Professor, Electrical and Computer Engineering at Boston University
Marcel Hild, Senior Manager, AIOps, AI CoE, Office of the CTO at Red Hat
Michael Clifford, Associate Manager, Data Science at Red Hat
Session Recording and Materials