Balancing Fixed Number of Nodes Among Multiple Fixed Clusters

TL;DR

This paper introduces a dynamic node rebalancing system for fixed-node clusters in cloud environments, optimizing resource utilization without additional provisioning costs.

Contribution

It presents a novel system for real-time, threshold-based node reallocation among fixed clusters, ensuring efficiency and stability without extra resource costs.

Findings

Improved resource utilization across clusters.

Reduced operational costs through dynamic rebalancing.

Maintained cluster stability with threshold-based controls.

Abstract

Cloud infrastructure users often allocate a fixed number of nodes to individual container clusters (e.g., Kubernetes, OpenShift), resulting in underutilization of computing resources due to asynchronous and variable workload peaks across clusters. This research proposes a novel system and method for dynamic rebalancing of a fixed total number of nodes among multiple fixed clusters based on real-time resource utilization thresholds. By introducing a Node Balancing Cluster Group (NBCG), clusters are grouped and allowed to dynamically share nodes through a controlled reallocation mechanism, managed by a Node Balancing Cluster Balancer and a Resizing Rule Engine. The system identifies overutilized and underutilized clusters using threshold parameters, and reassigns nodes without incurring additional provisioning costs. If reallocation causes a violation of utilization thresholds, the system reverses the operation to maintain cluster stability. The proposed architecture not only optimizes resource utilization and operational cost but also introduces a strategic advantage for cloud service providers like IBM Cloud. Unlike existing solutions, this approach enables intra-account node sharing across clusters with strict adherence to user-defined constraints and ensures consistent cluster state management. This invention has the potential to significantly reduce computing resource waste and position IBM Cloud services as more efficient and competitive.