Performance Estimation of Scalable e-Learning Systems in the Cloud

Performance estimation of large scale cloud deployments of web servers is an ongoing challenge for researchers and operations engineers all over the globe. In this paper we propose an approach for performance estimation of cloud environment based on performance metrics and scalable coefficient between number of backend nodes and number of load balancers. An example performance estimation using this methodology is provided for a large automated environment in a public cloud.