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Using Bayesian Networks to Reduce SLO Violations in a Dynamic Cloud-based Environment

Authors:
Aspen Olmsted
Agam Dua

Keywords: Bayesian network, Machine Learning, Cloud Computing, Auto scaling, Service Level Objective, Availability

Abstract:
Abstract—As more organizations move critical infrastructure to the cloud and leverage features like auto-scaling to grow according to the customer demand, we see a new set of challenges specific to this class of dynamic, distributed systems. In this paper, we propose a model leveraging Bayesian networks to help in the diagnostics of these systems during failures to considerably shorten the time to localize the cause of Service Level Objectives violations. The model subsequently reduces the violation duration by reducing the Mean Time To Resolution.

Pages: 14 to 16

Copyright: Copyright (c) IARIA, 2020

Publication date: April 26, 2020

Published in: conference

ISSN: 2308-4294

ISBN: 978-1-61208-778-8

Location: Nice, France

Dates: from October 25, 2020 to October 29, 2020