WWW Conference 2012 - Web-Engineering - Cloudgenius

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WWW Conference 2012 - Web-Engineering - Cloudgenius

  1. 1. CloudGenius: Decision Support forWeb Server Migration to the Cloud Michael Menzel, Rajiv Ranjan KIT, UNSW WWW Conference – Web Engineering II Lyon, 2012
  2. 2. Agenda1. Motivation2. CloudGenius Framework3. CumulusGenius Tool4. Experiments & Evaluation5. Conclusion6. Future Work
  3. 3. MOTIVATION
  4. 4. Web Servers in the Cloud• ... to gain Cloud features – Elasticity (slashdot) – Pay-per-use – Global distribution – ...• What to be done?• Where to go? (Cloud compute service)
  5. 5. Options for Realization• 3 Options to migrate a Web server – Convert it into a Cloud-compatible VM image – Rebuild on a basic VM image – Adopt prepared Web server VM image Converted Basic Prepared VM VM VM Image Image Image Less effort Higher Customizability
  6. 6. Web Server Migration Problem influences VM images Web server choose Image A Image ? Image B Image C evaluation Image decision Web serverrequirements Composite decisionWeb server goals Provider Service ? Cloud Provider A Cloud Provider B evaluation decision Service Service Servic A B eC Service evaluation
  7. 7. CLOUDGENIUS FRAMEWORK
  8. 8. Elements of the CloudGenius FrameworkEngineer requirements Set Select Image & Deploy, Customi + + Goals/Preferenc... Service ze ... es Evaluate Images Multi-Criteria Decision- & Services criteria Making Method (AHP) CloudGenius Cloud Model 1. Alternative 2 (0.8966) 2. Alternative 1 (0.1211) 3. ...Cyclic process Model Evaluation methods
  9. 9. CloudGenius Migration Process (condensed)Engineer Set Select Image & Deploy, Custom... Goals/Preferen ... Service ize ces Evaluate Images & Services CloudGenius Cloud Model
  10. 10. CloudGenius Model of Cloud Landscape Model holds Data• VM Images & Compute Services have attributes• Attributes are basis for criteria and requirements• VM Images and Services are related
  11. 11. Evaluation Methods Leverage (MC2)2 Framework [1] Alternative (MC2)2 allows to create evaluation 1 Alternative 2 methods with given criteria and Alternative n requirements requirements appropriate alternatives Resulting evaluation methods filter and evaluate alternatives Multi-Criteria Decision-Making criteria Method (AHP) We settle for AHP 1. Alternative 2 (0.8966) for normalized evaluations 2. 3. Alternative 1 (0.1211) ...[1] Menzel, M., Schönherr, M., Nimis, J., & Tai, S. (2010). (MC2)2: A Generic Decision-Making Framework and its Application to Cloud Computing. In Procs. InternationalConference on Cloud Computing and Virtualization (CCV 2010), Singapore.
  12. 12. Evaluate VM Images VM Image Attributes [2][2] S. Kalepu, S. Krishnaswamy, and S. Loke. Verity: A QoS Metric for Selecting Web Services and Providers. In Web InformationSystems Engineering Workshops, 2003. Proceedings. Fourth International Conference on, pages 131-139. IEEE, 2003.
  13. 13. Evaluate Compute Services Attributes [3][3] S. Kalepu, S. Krishnaswamy, and S. Loke. Verity: A QoS Metric for Selecting Web Services and Providers. In Web InformationSystems Engineering Workshops, 2003. Proceedings. Fourth International Conference on, pages 131-139. IEEE, 2003.
  14. 14. Define Goals/PreferencesAssign weights in pairwise comparisons (per level)
  15. 15. Evaluate Combinations{ VM Image } x{ }= { VM Image } Weighted Evaluated set of combinationsNot all Combinations are viable! AMI
  16. 16. CUMULUSGENIUSIMPLEMENTATION
  17. 17. CumulusGenius • Implementation of the model, evaluation methods in Java [2] • Basis for Experiments and future Tools • jClouds for deployments on EC2[4] available as java library: http://code.google.com/p/cumulusgenius
  18. 18. EXPERIMENTS & EVALUATION
  19. 19. Experimental Setup• Employed CumulusGenius Implementation• Generated Database of VM Images & Compute Services – Attribute values in plausible ranges – Every combination viable• All Criteria have same weight• 20 Runs with growing Database size
  20. 20. AMI & Service Evaluation • Service evaluation has higher effort • AMI & Service evaluation not growing linearly
  21. 21. Experiment Results (avg. 20 runs)• Non-linearly growing computation time
  22. 22. Evaluation• Currently 10,000 AMIs on Amazon alone!• Filtering important• Fast evaluation algorithm – Parallelization – Heuristics such as Genetic Algorithms
  23. 23. Conclusion• Framework for Migration of Web servers – Cylcic Process – Model – Evaluation Methods• Implementation CumulusGenius – Java library• Experiments regarding computation time – Non-linear growing
  24. 24. Future Work• Improve attribute list – Talk to experts (ongoing: German Telekom) – Public prototype, evaluate feedback• Apply & evaluate in real life migration scenarios (prototype w/ GUI)• Expand database of Cloud landscape – Scan existing VM images for data – Integrate existing databases (cloudmarket, bitnami)• Support more complex system setups
  25. 25. Contact MeFor Questions, Discussions,or Initiating Research Exchange:Michael MenzelResearch Center for Information Technology (FZI)Karlsruhe Institute of Technology (KIT)Englerstr. 1176131 KarlsruheEmail:menzel@fzi.de
  26. 26. Slides• Made available on http://www.slideshare.net/mugglmenzel next week• Made available on www2012 Website
  27. 27. Questions, Comments, DiscussionMERCI FOR YOUR ATTENTION!
  28. 28. DETAILS
  29. 29. Web server Migration Process (Guidance)
  30. 30. Web server Migration Process – ctd.
  31. 31. Process supports evolutionary MigrationIncorporate experience Select Set Target Preferences Setup Execute MigrationRSuccess!
  32. 32. Model
  33. 33. Evaluate VM Images VM Image
  34. 34. Evaluate Compute Services
  35. 35. Combining AMIs & Services
  36. 36. CumulusGenius: Web Frontend CumulusGenius Suggester GWT Aotearoa Evaluation Frontend Component User jClouds User CumulusGenius Preferences Deployments Logic User Data Collector Ratings Images Servicescurrentness of data? own benchmarks
  37. 37. Apache in the Cloud? Prepare & Plan!

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