Method And Apparatus For Scalable ML-Based Frameworks For Resource Planning In Enterprise Networks

Method and apparatus for scalable machine learning (ML)-based frameworks for resource planning and recommendations for Enterprise Networks are disclosed. In some embodiments, a method for determining network health assessment and providing network planning and recommendations in wireless enterprise networks is provided. The method quantifies resource health of a plurality of network elements operating within the enterprise network by calculating a plurality of distance metrics between acceptable health parameters and observed network resource utilization values associated and corresponding to each selected network element. The method ranks each of the network elements based upon the distance metrics calculated for each network element. Factors that negatively impact the resource health of the network elements are ranked in accordance to how severely they impact the performance of the network elements. The method and apparatus provide suggestions and recommendations to improve network performance of the network elements. An apparatus for scalable machine-learning (ML)-based frameworks for resource planning in enterprise networks is also disclosed.