Title
Cloudstep: A step-by-step decision process to support legacy application migration to the cloud
Abstract
Cloud computing is an emerging computing paradigm whose benefits (such as high scalability, reduced IT costs, self-service on demand, and pay-as-you-go price models) have increasingly attracted the interest of the corporate world. Nevertheless, many organizations have found it difficult to adopt cloud-based solutions, particularly regarding the migration of their existing legacy applications to this new environment. One of the main obstacles faced by those organizations is the lack of a general process to help application developers not only in selecting the cloud models and services best suited for their application, but also in carefully assessing the various risks and benefits involved. To fill this gap, this paper presents Cloudstep, a step-by-step decision process aimed at supporting legacy application migration to the cloud. The process relies on the creation of template-based profiles characterizing the organization, the target legacy application and candidate cloud providers, which are then cross-analyzed to help identify and possibly resolve critical constraints (either technical or non technical) that may hinder migration to the cloud. The use of the process is illustrated through an analysis of key factors influencing the migration of a commercial medical application to different infrastructure-as-a-service cloud providers.
Year
DOI
Venue
2012
10.1109/MESOCA.2012.6392602
Maintenance and Evolution of Service-Oriented and Cloud-Based Systems
Keywords
Field
DocType
cloud computing,decision making,Cloudstep,candidate cloud providers,cloud computing,cloud models,cloud services,cloud-based solutions,commercial medical application,critical constraints,infrastructure-as-a-service cloud providers,legacy application migration,pay-as-you-go price models,self-service on demand,step-by-step decision process,template-based profiles,cloud computing,cloud migration,decision support process,legacy application
Data science,On demand,Computer security,Cloud computing security,Decision process,Engineering,Legacy system,Cloud testing,Scalability,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-4673-3002-2
7
0.55
References 
Authors
0
5