Monitoring Performance Computing Environments and Autoscaling Using AI
International Research Journal of Modernization in Engineering Technology and Science · 2023
Modern organizations face unpredictable demands and dynamic workloads, necessitating effective management of computing resources.Autoscaling in cloud computing offers a solution by enabling applications to autonomously adjust their capacity in response to changing demand.This paper explores the utilization of AI-powered algorithms to address the challenges encountered in monitoring and autoscaling, considering factors such as memory requirements, network traffic, CPU utilization, and custom metrics.AI-driven models offer numerous advantages, including enhanced resource utilization, scalability, reliability, reduced maintenance overheads, continuous availability, cost-effectiveness, and simplified management of the computing environment.However, complexities in configuration, potential performance degradation, inconsistent performance, security concerns, and increased costs are notable drawbacks.By comparing AIpowered techniques with other traditional methods, this research evaluates the role of AI in overcoming challenges faced by alternative approaches.Through experimental evaluation and comprehensive analysis, this study demonstrates the superiority of AI-driven techniques in diverse aspects such as CPU utilization, memory utilization, throughput, and response time.Moreover, the paper identifies multiple areas for further improvement, aiming to enhance efficiency and reduce computing costs.