Customer self-remediation of proactive network issue detection and notification

Abstract

Improving computer network availability has been a focus of researchers for the past 30 years and considerable investigation into the use of AI and Machine Learning, primarily in the operate space has been conducted. Previous efforts have been primarily reactive in nature, monitoring networks, developing base models, and trying to predict future failures based on those models. This approach has shown limited success due to the dynamic nature of network equipment and function. Cisco has been developing capabilities over the last decade to proactively analysis network devices and identify issues that could impact a networks availability. In the current approach issues are identified to the customer and it is the customer’s responsibility to identify the issues that they determine need to be fixed. The capability has been trialed over the last 2 years and the research discussed in this paper is focused on the analysis of their actions. Machine Learning is applied to the issue consumption data set and observations made on the features that can be used to predict which issues will be fixed.