Dynamic deployment and auto-scaling enterprise applications on the heterogeneous cloud

Abstract

Over the past years, organizations have been moving their enterprise applications to the cloud with the aim of reducing infrastructure ownership and maintenance costs, and to take advantage of the elasticity and heterogeneity of the cloud. This paper joined the approaches of multi-cloud deployment using CloudML and identifying the ideal resource provisioning and deployment configuration using an optimization model, in order to dynamically scale an enterprise application across multiple clouds, without any user intervention. The approaches are discussed in detail along with the introduced extensions. Benchmark experiments were conducted on Amazon cloud infrastructure, based on one system with a single scalable component and two other systems with the basic workflow control structures, parallel and exclusive. The results of the experiments suggest that the approach is plausible for dynamic deployment and auto-scaling any web/services based enterprise workflow/application on the cloud.