Analytical Evaluation of Resource Estimation in Web Application Services

Received: 7 July 2020 Accepted: 12 September 2020 Cloud computing for web application is ubiquitous in the global market and represents a generic pattern because rapid elasticity and infrastructure scaling naturally lends itself to the needs of a virtual data center. Server requirement analysis depending on the workload play a very important role in web app development and it leads to availability of service to customer at any cost and cost analysis to the application provider. To achieve proper infrastructure scaling the minimal number of servers are have to satisfy and determine SLO. Thus this paper evaluates an analytical model to formulate prediction or estimation of required servers has to satisfy the QoS performance metrics such as throughput, utilization of cloud datacenter, request loss and required number of servers. The experimental model is used to validate correctness of the analytical model that was hosted on AWS cloud platform. Finally results have presented and conclusions are drawn.