Migrating Application Data to the Cloud using Cloud Data Patterns

Steve Strauch, Vasilios Andrikopoulos, Thomas Bachmann, Frank Leymann

Abstract

Taking advantage of the capabilities offered by Cloud computing requires either an application to be built specifically for it, or for existing applications to be migrated to it. In this work we focus on the latter case, and in particular on migrating the application data. Migrating data to the Cloud creates a series of technical, architectural and legal challenges that the State of the Art attempts to address. We organize such efforts into a set of migration scenarios and connect them with a list of reusable solutions for the application data migration in the form of patterns. From there we define an application data migration methodology and we demonstrate how it can be used in practice.

References

  1. Adler, B. (2011). Building Scalable Applications In the Cloud: Reference Architecture & Best Practices, RightScale Inc.
  2. Amazon.com, Inc. (2011). AWS Case Study: Alexa.
  3. Anand, S. (2010). Netflix's Transition to High-Availability Storage Systems.
  4. Andrikopoulos, V., Binz, T., Leymann, F., and Strauch, S. (2012). How to Adapt Applications for the Cloud Environment. Springer Computing.
  5. Armbrust, M. et al. (2009). Above the Clouds: A Berkeley View of Cloud Computing. Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley.
  6. Badger, L., Grance, T., R., P.-C., and Voas, J. (2012). Cloud Computing Synopsis and Recommendations - Recommendations of the National Institute of Standards and Technology. NIST Special Publication 800-146.
  7. Buretta, M. (1997). Data Replication: Tools and Techniques for Managing Distributed Information. John Wiley & Sons, Inc.
  8. Consultative Committee for Space Data Systems (2002). Reference Model for an Open Archival Information System (OAIS).
  9. Conway, G. and Curry, E. (2012). Managing Cloud Computing: A Life Cycle Approach. In Proceedings of CLOSER'12. SciTePress.
  10. Cunningham, S. R. (2010). Windows Azure Application Profile Guidance. Custom E-Commerce (Elasticity Focus) Application Migration Scenario.
  11. Fowler, M. et al. (2002). Patterns of Enterprise Application Architecture. Addison-Wesley Professional.
  12. Hohpe, G. and Woolf, B. (2003). Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA.
  13. Khajeh-Hosseini, A., Greenwood, D., Smith, J. W., and Sommerville, I. (2012). The Cloud Adoption Toolkit: Supporting Cloud Adoption Decisions in the Enterprise. Software: Practice and Experience, 42(4):447- 465.
  14. Laszewski, T. and Nauduri, P. (2011). Migrating to the Cloud: Oracle Client / Server Modernization. Elsevier Science.
  15. Lee, J., Malcolm, G., and Matthews, A. (2009). Overview of Microsoft SQL Azure Database.
  16. Mell, P. and Grance, T. (2009). Cloud Computing Definition. National Institute of Standards and Technology, Version 15.
  17. Menzel, M. and Ranjan, R. (2012). CloudGenius: Decision Support for Web Server Cloud Migration. In Proceedings of WWW 7812, New York, NY, USA. ACM.
  18. Microsoft Azure (2012). Generic Migration Scenarios and Case Studies.
  19. Pritchett, D. (2008). BASE: An ACID Alternative. Queue, 6(3):48-55.
  20. Redkar, T. and Guidici, T. (2011). Windows Azure Platform. Apress.
  21. Strauch, S., Andrikopoulos, V., Breitenb├╝cher, U., Kopp, O., and Leymann, F. (2012a). Non-Functional Data Layer Patterns for Cloud Applications. In Proceedings of CloudCom'12. IEEE Computer Society Press.
  22. Strauch, S., Breitenb├╝cher, U., Kopp, O., Leymann, F., and Unger, T. (2012b). Cloud Data Patterns for Confidentiality. In Proceedings of CLOSER'12. SciTePress.
  23. Tak, B. C., Urgaonkar, B., and Sivasubramaniam, A. (2011). To Move or Not to Move: The Economics of Cloud Computing. In Proceedings of HotCloud'11, Berkeley, CA, USA. USENIX Association.
  24. United States Congress (2002). Sarbanes-Oxley Act (SOX).
  25. Varia, J. (2010). Migrating your Existing Applications to the AWS Cloud. A Phase-driven Approach to Cloud Migration.
  26. Vogels, W. (2009). Eventually consistent. Communications of the ACM, 52(1):40-44.
  27. Zawodny, J. and Balling, D. (2004). High Performance MySQL: Optimization, Backups, Replication, Loadbalancing, and More. O'Reilly & Associates, Inc. Sebastopol, CA, USA.
  28. All links were last followed on February 5, 2013.
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Paper Citation


in Harvard Style

Strauch S., Andrikopoulos V., Bachmann T. and Leymann F. (2013). Migrating Application Data to the Cloud using Cloud Data Patterns . In Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8565-52-5, pages 36-46. DOI: 10.5220/0004376300360046


in Bibtex Style

@conference{closer13,
author={Steve Strauch and Vasilios Andrikopoulos and Thomas Bachmann and Frank Leymann},
title={Migrating Application Data to the Cloud using Cloud Data Patterns},
booktitle={Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2013},
pages={36-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004376300360046},
isbn={978-989-8565-52-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Migrating Application Data to the Cloud using Cloud Data Patterns
SN - 978-989-8565-52-5
AU - Strauch S.
AU - Andrikopoulos V.
AU - Bachmann T.
AU - Leymann F.
PY - 2013
SP - 36
EP - 46
DO - 10.5220/0004376300360046