Migrating to the Cloud: a Software Product Line Based Analysis

Abstract

Identifying which part of a local system should be migrated to a public Cloud environment is often a difficult and error prone process. With the significant (and increasing) number of commercial Cloud providers, choosing a provider whose capability best meets requirements is also often difficult. Most Cloud service providers offer large amounts of configurable resources, which can be combined in a number of different ways. in the case of small and medium companies, finding a suitable configuration with the minimum cost is often an essential requirement to migrate, or even to initiate the decision process for migration. We interpret this need as a problem associated with variability management and analysis. Variability techniques and models deal with large configuration spaces, and have been proposed previously to support configuration processes in industrial cases. Furthermore, this is a mature field which has a large catalog of analysis operations to extract valuable information in an automated way. Some of these operations can be used and tailored for Cloud environments. We focus in this work on Amazon Cloud services, primarily due to the large number of possible configurations available by this service provider and its popularity. Our approach can also be adapted to other providers offering similar capabilities.