Decision support for multicloud deployment of a modeling environment

Nowadays, many companies are moving their activities to the cloud. They are using advantages such as collaboration, disaster recovery, and cost savings as the drive for this change. Nonetheless, many cloud providers have different offerings, some more appealing than others. This article describes decisive factors for the deployment of modeling environments using a multicloud deployment platform. This is conceived for users who are specialists in modeling, but not in cloud computing, but who intend to take advantage of cloud environments’ capabilities. The automate decisions are made by leveraging the decision trees and providing a decisional algorithm that helps one decide the deployment details. Furthermore, the paper evaluates the algorithm from the perspective of the most valuable outcome of it.

I. Introduction

Moving to cloud is an important trend nowadays [1], as more and more companies tend to move their activities entirely to cloud. They are keen to use the advantages that come with a cloud solution, such as collaboration, disaster recovery, cost savings, and, in many cases, the ease of implementation of complex solutions - generated by the abundance of tools that are already made available by cloud providers and are compatible with the other offerings of cloud providers. On top of this trend, we approach the problem of a multicloud deployment decision that leverages the cloud advantages [2], by giving users the choice of the most suited service, offered by different cloud providers.