Performance Management in Cloud Computing

Abstract

Cloud service providers encounter a challenge in managing remote resources due to the dynamic nature of the cloud environment. The complexity of the process is increased by the requirement of maintaining service quality in line with customer expectations, as well as the extremely dynamic nature of cloud-hosted applications. As a result of developments in big data learning methodologies, traditional systems have given way to intricate systems. In the existing studies, it is shown that the resource adjustment decision-making process is intimately linked to the system's behavior, including resource utilization and application components. The most essential requirements and restrictions in cloud resource management, as well as workload and anomaly analysis approaches in the context of cloud performance management, are discussed in this paper. The related works are provided, with major methodologies in current studies ranging from data analysis to performance techniques. Finally, a list of open challenges is compiled, taking into account the identified gaps in the overall direction of the tasks under consideration.