Intelligent Management of Cloud Systems Through Machine Learning Approaches

Cloud computing environments are becoming more complex, and it is essential to have intelligent resource management to optimise performance, reduce costs, and achieve service- level agreements (SLAs). The purpose of this paper aims to explore the improvement of intelligent cloud management systems with the help of machine learning techniques. We survey the existing literature in a systematic way, compare the current systems, suggest a new system architecture, and outline what is expected based on the results, conclusions, and future work. The proposed system uses ML algorithms for workload prediction, resource allocation, anomaly detection, and automatic system recovery in proactive and adaptive cloud management.