Cloud Computing mit mathematischen Anwendungen

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1 Cloud Computing mit mathematischen Anwendungen Dr. habil. Marcel Kunze Engineering Mathematics and Computing Lab (EMCL) Institut für Angewandte und Numerische Mathematik IV Karlsruhe Institute of Technology (KIT) 1. Introduction KIT University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association

2 Amazon Compute Cluster Instances 2

3 Agenda Cloud Computing 1. Introduction " What is Cloud Computing? 2. Basics " Virtualization, Web Services, 3. Cloud Architecture " Infrastructure, Platform, Software,... as a Service 4. Professional Public Cloud Services " Amazon Web Services, Google App Engine, Windows Azure 5. Inside the Cloud: Private Cloud Services " OpenCirrus Project, Eucalyptus 6. Cloud Algorithms " MapReduce, Optimization, MatLab, " Hands-on based on Java " A Laptop is desirable 3 3

4 Literature C. Baun, M. Kunze, J. Nimis, S. Tai Cloud Computing: Web-basierte dynamische IT-Services Informatik im Fokus Springer-Verlag, 2.Auflage, Further reading: Articles (print and online) will be provided in each lecture 4

5 Cloud Computing? 5

6 Cloud Computing: Definition Building on compute and storage virtualization, cloud computing provides scalable, network-centric, abstracted IT infrastructure, platforms, and applications as on-demand services that are billed by consumption. C.Baun, M.Kunze, J.Nimis, S.Tai: Cloud Computing, Informatik im Fokus, Springer

7 Cloud Myths " Cloud computing infrastructure is just a web service interface to operating system virtualization. " I m running Xen in my data center I m running a private cloud. " Cloud needs more: Automation, SLAs, business model, " Cloud computing imposes a significant performance penalty over bare metal provisioning. " I won t be able to run a private cloud because my users will not tolerate the performance hit. " With modern hardware, virtualized services are sometimes even faster " Clouds and Grids are equivalent. " In the mid 1990s, the term grid was coined to describe technologies that would allow consumers to obtain computing power on demand. " Grids are not self-service, do not grant privileges to users, have a decentralized management and often are missing business models 7

8 History: Grid Computing " Idea 1998: Compute power as a utility " Federative approach: Ressource sharing " Resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations (Ian Foster, Carl Kesselman) 8

9 Conventional Layered Grid Architecture 9

10 Clouds vs. Grids Objective Cloud Computing Provide desired computing platform via network enabled services Grid Computing Resource sharing Job execution Functional Infrastructure Middleware One or few data centers, heterogeneous/homogeneous resource under central control, Industry and Business Proprietary, several reference implementations exist (e.g. Amazon) Geographically distributed, heterogeneous resource, no central control, VO Research and academic organization Well developed, maintained and documented Application Suited for generic applications Special application domains like High Energy Physics User interface Easy to use/deploy, no complex user interface required Difficult use and deployment Need new user interface, e.g., commands, APIs, SDKs, services Non-Functional Business Model Commercial: Pay-as-you-go Publicly funded: Use for free Operational Model Industrialization of IT Fully automated Services Mostly Manufacture Handcrafted Services QoS Possible Little support On-demand provisioning Yes No 10

11 Grid Computing vs. Cloud Computing " Grid Computing is not very popular anymore 11

12 Grid as a Service 12

13 What is cloud computing? Is it a technology? Is it a concept? Cloud computing is a transition Simon Wardley: Cloud Computing Why IT matters 13

14 The Industrial Revolution Attitude Concept Industrial Revolution Technology " Realization of concept needs " Environment (Suitability) " Skillset (Technology) " Mindset (Attitude) Suitability 14

15 Industrialization in the automotive sector 15

16 Cloud Computing: Industrialization of IT? Attitude Concept Cloud Computing Technology " Realization of concept needs " Environment (Suitability) " Skillset (Technology) " Mindset (Attitude) Suitability 16

17 From Innovation to Commodity " The adoption of innovation always follows a sigmoidal transition towards commodity: There is a rapid uptake at a certain point " Examples: Automobile, washing machines, telephone, television, " IT Examples: Personal Computer, World Wide Web, mobile communication, " It is the same with the transition of local IT to cloud computing Spread Usage 17

18 Cloud Computing Centers: IT-Factory Source: InformationWeek " Google, Yahoo, Microsoft: Gigantic data centers (Columbia River) " Growth: > servers per months 18

19 Trend: Containers as building blocks Source: Rackable Source: HP " HP, IBM, Sun, Rackable containers " Up to blade-cores or 15 PB disks per container " Microsoft Chicago and Dublin: Huge data centers " Million cores in container technology for Windows Live clients " Advantages of the containers " Excellent energy efficiency (PUE-value ~ 1.2) " Easy to place/re-locate: Alaska, ships, power plant 19

20 Cloud Computing = Industrialization of IT! " IT Service-centers do not necessarily have their own IT infrastructure " Main objective is to provide IT services " Value-add to commercial cloud services " HP: Vision of the fully automated Dark data center 20

21 So, what s new? " The illusion of infinite IT-resources which " are always available as on-demand services " do not require ownership, prior reservation, etc " Pay by use business model " No upfront commitment (Contract etc.) Further reading: Above the Clouds: A Berkeley View of Cloud Computing : 21

22 Good to know " All course info is on " 22

23 23

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