Cisco Systems, Inc.
Automatic configuration of software systems for optimal management and performance using machine learning

Abstract:

In one embodiment, information (workload, performance, and configuration) is obtained about identified sub-systems (a target component plus other components that influence its performance). The identified sub-systems are clustered into workload clusters and also into performance clusters, where identified sub-systems of particular workload clusters have similar workload measurements, and identified sub-systems of particular performance clusters have similar performance metrics. The techniques herein then determine a given mapped performance cluster for a given workload cluster that corresponds to a best set of performance metrics from among all performance clusters mapped to the given workload cluster. A configuration change recommendation is then generated for a given identified sub-system of the given workload cluster that is not within the given mapped performance cluster corresponding to the best set of performance metrics based on configuration information about each identified sub-system within the given mapped performance cluster that corresponds to the best set of performance metrics.