Moving the IT Infrastructure to the Cloud
DOI:
https://doi.org/10.29019/enfoqueute.v9n1.219Keywords:
cloud computing, cloud services, cloud framework, cloud adoptionAbstract
Cloud computing services are nowadays advertised as an emerging business model. Moreover, these services bring innovative solutions in a more sophisticated competitive market. But, the decision for their adoption could be significantly reduced due to organizations’ concerns related to security, privacy, and trust. The challenge involves such questions as where to start, which provider should the company choose or whether it is even worthwhile. Thus, this paper proposes an improved unified framework, based on a previous study where a 6 step process framework was introduced. This improved framework add one new step for security and control after the migration process. At the end, a 7 processes framework is proposed aimed to fulfill organizations’ concerns when decide to adopt cloud computing services with a follow-up step. This additional step intends to help IT directors to make sure everything is working properly in a methodological way, in order to achieve a successful cloud computing migration process. An effective solution that is gaining momentum and popularity for competitive organizations.
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References
AICIT. (2012). Relative weight Decision of Quality Attributes in Cloud Computing Service Using ANP. International Journal in Advance Computer Technology, 4, 240–248.
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., . . . Zaharia, M. (2010). A View of Cloud Computing. Communications of the ACM, 53(4), 50-58.
Bermúdez, G. T., García, V. H., & Giraldo, L. (2013). Implementation Models of Electronic Commerce Solutions. Revista Ingenierías.
Carroll, M., Merwe, A. V., & Kotze, P. (2011). Secure cloud computing: Benefits, risks and controls. Information Security for South Africa, (pp. 1-9). Johannesburg.
Coad, A., Segarra, A., & Teruel, M. (2016). Innovation and firm growth: Does firm age play a role? Research Policy, 45(3), 387-400.
Day, G. S., & Bens, K. J. (2005). Capitalizing on the internet opportunity. Journal of Business & Industrial Marketing, 20(160-168), 160-168.
Dillon, T., Wu, C., & Chang, E. (2010). Cloud Computing: Issues and Challenges. 24th IEEE International Conference on Advanced Information Networking and Applications (AINA) (pp. 27-33). Perth: IEEE.
Ezzat, E. M., Zanfaly, D. S., & Kota, M. M. (2011). Fly over clouds or drive through the crowd: A cloud adoption framework. International Conference and Workshop on Current Trends in Information Technology (CTIT), (pp. 6-11). Dubai.
Faroughiana, F. F., Kalafatis, S. P., Ledden, L., Samouel, P., & Tsogas, M. H. (2012). Value and Risk in Business-To-Business e-Banking. Industrial Marketing Management, 68-81.
Gorelik, E. (2013). Cloud Computing Models. Cambridge: Massachusetts Institute of Technology.
Hernandez Quintero, N. L., & Florez Fuente, A. S. (2014). Cloud Computing. Mundo FESC, 2(8), 46-51.
Kumar, K. B., Rajan, R. G., & Zingales, L. (1999, July). What Determines Firm Size? National Bureau of Economic Research, p. 54.
Leimeister, S., Böhm, M., Riedl, C., & Krcmar, H. (2010). The Business Perspective of Cloud Computing: Actors, Roles and Value Networks. ECIS, 56.
Leong, L., Bala, R., Lowery, C., & Smith, D. (2017). Magic Quadrant for Cloud Infraestructure as a Service, Worldwide. Gartner.
Low, C., Chen, Y., & Wu, M. (2011). Understaning the Determinants of Cloud Computing Adoption. 111(7).
Mell, P., & Grance, T. (2011, July 09). The NIST Definition of Cloud Computing: Recommendations of the National Intitute of Standars and Technology.
Moeller, S. B., Schlingemann, F. P., & MStulz, R. (2004). Firm size and the gains from acquisitions. Journal of Financial Economics, 73(2), 201-228.
Mokhtar, S. A., Al-Sharafi, A., Ali, S. H., & Al-Othami, A. Z. (2016). Identifying the determinants of cloud computing adoption in higher education institutions. International Conference on Information and Communication Technology (ICICTM), (pp. 115-119). Kuala Lumpur.
Moscoso-Zea, O. (2010). Megastore: structured storage for Big Data. 3.
Pantelić, O., Pajić, A., & Nikolic, A. (2016). Analysis of available cloud computing models to support cloud adoption decision process in an enterprise. 6th International Conference on Computers Communications and Control (ICCCC) (pp. 135-139). Oradea: International Conference on Computers Communications and Control.
Paredes-Gualtor, J., Moscoso-Zea, O., Saa, P., Sandoval, F., & Rodas, P. (2017). Unified Cloud Computing Adoption Framework. 2nd International Conference on Information Systems and Computer Science (INCISCOS).
Saa, P., Cueva-Costales, A., Moscoso-Zea, O., & Luján-Mora, S. (2017). Moving ERP Systems to the Cloud – Data Security Issues. Journal of Information Systems Engineering & Management, 1-9.
Saa, P., Moscoso-Zea, O., Cueva-Costales, A., & Lujan-Mora, S. (2017). Data Secutiry issues in Cloud-Bases Software-as-a-Service ERP. 12th Iberian Conference on Information Systems and Technologies (CISTI), 1-7.
Saedi, A. (2016). Cloud computing adoption framework: Innovation translation approach. 3rd International Conference on Computer and Information Sciences (ICCOINS), (pp. 153-157). Kuala Lumpur.
Taherizadeh, S., Jones, A. C., Taylor, I., Zhao, Z., & Stankovski, V. (2018). Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review. The Journal of Systems and Software, 19-38.
Teece, D. J. (2010). Business Models, Business Strategy and Innovation. Long Range Planning, 43(2-3), 172-194.
Varia, J. (2010). Migrating your Existing Applications to the AWS Cloud. Amazon Web Services.
Williams, M. I. (2010). A quick start guide to cloud computing: moving your business into the cloud. London: Paperback.
Youseff, L. B. (2008). Toward a Unified Ontology of Cloud Computing. Grid Computing Environments Workshop, 1-10.
Zeng, Q., Chen, W., & Huang, L. (2013). Trends in E-Business, E-Services, and E-Commerce: Impact of Technology on Goods, Services, and Business Transactions. Illinois: Western Illinois University.
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