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WWW Conference 2012 - Web-Engineering - Cloudgenius
 

WWW Conference 2012 - Web-Engineering - Cloudgenius

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    WWW Conference 2012 - Web-Engineering - Cloudgenius WWW Conference 2012 - Web-Engineering - Cloudgenius Presentation Transcript

    • CloudGenius: Decision Support forWeb Server Migration to the Cloud Michael Menzel, Rajiv Ranjan KIT, UNSW WWW Conference – Web Engineering II Lyon, 2012
    • Agenda1. Motivation2. CloudGenius Framework3. CumulusGenius Tool4. Experiments & Evaluation5. Conclusion6. Future Work
    • MOTIVATION
    • 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)
    • 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
    • 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
    • CLOUDGENIUS FRAMEWORK
    • 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
    • CloudGenius Migration Process (condensed)Engineer Set Select Image & Deploy, Custom... Goals/Preferen ... Service ize ces Evaluate Images & Services CloudGenius Cloud Model
    • 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
    • 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.
    • 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.
    • 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.
    • Define Goals/PreferencesAssign weights in pairwise comparisons (per level)
    • Evaluate Combinations{ VM Image } x{ }= { VM Image } Weighted Evaluated set of combinationsNot all Combinations are viable! AMI
    • CUMULUSGENIUSIMPLEMENTATION
    • 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
    • EXPERIMENTS & EVALUATION
    • 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
    • AMI & Service Evaluation • Service evaluation has higher effort • AMI & Service evaluation not growing linearly
    • Experiment Results (avg. 20 runs)• Non-linearly growing computation time
    • Evaluation• Currently 10,000 AMIs on Amazon alone!• Filtering important• Fast evaluation algorithm – Parallelization – Heuristics such as Genetic Algorithms
    • Conclusion• Framework for Migration of Web servers – Cylcic Process – Model – Evaluation Methods• Implementation CumulusGenius – Java library• Experiments regarding computation time – Non-linear growing
    • 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
    • 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
    • Slides• Made available on http://www.slideshare.net/mugglmenzel next week• Made available on www2012 Website
    • Questions, Comments, DiscussionMERCI FOR YOUR ATTENTION!
    • DETAILS
    • Web server Migration Process (Guidance)
    • Web server Migration Process – ctd.
    • Process supports evolutionary MigrationIncorporate experience Select Set Target Preferences Setup Execute MigrationRSuccess!
    • Model
    • Evaluate VM Images VM Image
    • Evaluate Compute Services
    • Combining AMIs & Services
    • 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
    • Apache in the Cloud? Prepare & Plan!