ANALYSIS AND PREDICTION OF WORKLOADS IN CLOUD ENVIRONMENT - P. Akilandeswari; Panikkasseri, Medha Manoj; H. Srimathi (International Journal of Psychosocial Rehabilitation, 2020)
Cloud computing technologies over the years have helped meet the changing needs for resources and computing capabilities of different organizations globally. By migration of workloads to cloud platform, (public, private or hybrid) there have been significant increase in Data Analytics applications to gain valuable insights from data. The rising amounts of workload have led to the necessity of predicting the optimal choice of platform for performing analytics in cloud to achieve better results. The increases in popularity of containers have made them an efficient choice for computing and prediction over traditional Virtual machines. This paper tries to analyse the different workloads and the types of model to predict them with the prospect of running workloads in a containerised environment.