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Cloud Computing Karlsruhe Institute of Technology (KIT), Germany Institute for Applied Informatics (AIFB) Prof

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Cloud Computing Karlsruhe Institute of Technology (KIT), Germany Institute for Applied Informatics (AIFB) Prof About the Speaker: Stefan Tai Professor, Cloud Computing Karlsruhe Institute of Technology (KIT), Germany Institute for Applied Informatics (AIFB) Prof. Dr. Stefan Tai Karlsruhe Service Research Institute (KSRI) [email protected] Director, FZI Research Center for Information Technology in Karlsruhe, Germany From 1999-2007: Research Staff Member, IBM T.J. Watson Research Center, New York, USA Prior to 1999: Eurocontrol Experimental Center, Paris, France Fraunhofer ISST, Berlin, Germany TU Berlin, Germany 2 25 Sept 2009 S. Tai KIT – The cooperation of Forschungszentrum Karlsruhe GmbH and Universität Karlsruhe (TH) Karlsruhe, Germany www.eOrganiz ation. de 3 25 Sept 2009 S. Tai 4 25 Sept 2009 S. Tai Gartner‘s Hype Cycle of Emerging Technologies, What is Cloud Computing? July 2009 5 25 Sept 2009 S. Tai 6 25 Sept 2009 S. Tai Cloud Computing: Infrastructure, Platforms, First of all: What are Services? and Software as Services Figure Credit: Rackspace 7 25 Sept 2009 S. Tai 8 25 Sept 2009 S. Tai …set in multiple contexts Cloud Computing is about: Understanding business opportunities • Faster time-to-market, and cost-effective innovation processes • Di(tDynamic (trans-)forma tion o f open serv ice an d bus iness ne twor ks Enterprise Computing • Leveraging the participation Web and mass programming Web Computing Internet-scale service computing • Provide and consume sophisticated infrastructure, platforms and business applications as modular (Web) services • Disrupt traditional industries and offer rich, highly dynamic Cloud Economics experiences Enterprise-grade systems management • Under-utilized server resources waste computing power and energy • Over-utilized servers cause interruption or degradation of service levels 9 25 Sept 2009 S. Tai 10 25 Sept 2009 S. Tai Cloud Computing is about: Cloud Computing is about: Understanding business opportunities Understanding business opportunities • Faster time-to-market, and cost-effective innovation processes • Faster time-to-market, and cost-effective innovation processes • Di(tDynamic (trans-)forma tion o f open serv ice an d bus iness ne twor ks • Di(tDynamic (trans-)forma tion o f open serv ice an d bus iness ne twor ks • Leveraging the participation Web and mass programming • Leveraging the participation Web and mass programming Internet-scale service computing Internet-scale service computing • Provide and consume sophisticated infrastructure, platforms and • Provide and consume sophisticated infrastructure, platforms and business applications as modular (Web) services business applications as modular (Web) services • Disrupt traditional industries and offer rich, highly dynamic • Disrupt traditional industries and offer rich, highly dynamic experiences experiences Enterprise-grade systems management Enterprise-grade systems management • Under-utilized server resources waste computing power • Under-utilized server resources waste computing power and energy and energy • Over-utilized servers cause interruption or degradation of service • Over-utilized servers cause interruption or degradation of service levels levels 11 25 Sept 2009 S. Tai 12 25 Sept 2009 S. Tai Our Definition To keep in mind: Three Dimensions “Building on compute and storage virtualization , Cloud Service cloud computing provides scalable, network-centric, Engineering abstracted IT infrastructure, platforms, and applications as on-deman d serv ices t hat are bille d by consumpt ion. " Business opportunities “Cloud service engggineering leverages cloud Internet-scale service computing computing in the context of the Internet in its combined role as a platform for technical, economic, Enterprise-grade organizational and social networks.” systems management 13 25 Sept 2009 S. Tai 14 25 Sept 2009 S. Tai Clouds vs. Grids Cloud Architecture and Ecosystem Cloud Computing Grid Computing Objective Provide desired computing platform Resource sharing via network enabled services Job execution Infrastructure One or few data centers, Geographically distributed, heterogeneous/homogeneous heterogeneous resource, no central resource under central control, control, VO Industry and Business Research and academic organization nctional uu Middleware Proprietary, several reference Well developed, maintained and F implementations exist (e.g. Amazon) documented Application Suited for generic applications Special application domains like High Energy Physics User interface Easy to u se/deploy, no complex u ser Difficu lt u se and deploy ment interface required Need new user interface, e.g., commands, APIs, SDKs, services … Business Model Commercial: Pay-as-you-go Publicly funded: Use for free IT] ional tt Operational Model Industrialization of IT Mostly Manufacture KK Fully automated Services Handcrafted Services QoS Possible Little support on-Func ks to M. Kunze, NN On-demand provisioning Yes No [Than 15 25 Sept 2009 S. Tai 16 25 Sept 2009 S. Tai Organizational Cloud Architecture: Technical Cloud Architecture: Public-/Hybrid-/Private-Cloud Cloud Computing Stack Generic Approach Layered architecture Everything as a Service concept Standard layers IfttInfrastructure as a S Siervice Platform as a Service Software as a Service Extra Layers Human as a Service Administration/Business Support 17 25 Sept 2009 S. Tai 18 25 Sept 2009 S. Tai Infrastructure as a Service Platform as a Service Infrastructure Services Progggramming Storage Environment Computational Programming Language, Network Libraries Database e.g. Django, Java e.g. Google Bigtable, GlFSGoogleFS, HdHadoop Execution Environment MapReduce, HadoopFS Runtime Environment RStResource Set e. g. Google App Engine, Java Virtual Machine Machine Images e.ggyp. EC2, Eucalyptus 19 25 Sept 2009 S. Tai 20 25 Sept 2009 S. Tai Software as a Service Human as a Service Applications User Interface CdCrowdsourc ing Frontend Application Enabling Collective e.g. Google Docs, Intelligence Yahoo Email e.g. Mechanical Turk Application Services Information Markets Webservices Interface Prediction of events Basic or Composite e.g. Iowa Electronic ege.g. Opensocial, Markets Google Maps 21 25 Sept 2009 S. Tai 22 25 Sept 2009 S. Tai Administration/Business Support Cloud Architecture Æ Cloud Players Available on all layers Administration High-value SPs Deppyloyment Configuration Intermediaries Monitoring Life cycle management Business support Metering Basic SPs Billing Authentication User management Infrastructure SPs 23 25 Sept 2009 S. Tai 25 Sept 2009 S. Tai Players Players: Providers Cloud infrastructure service providers – raw cloud Programmatic access via Web Services and/or Web APIs resources “Pure” virtualized resources IaaS (infrastructure-as-a-service) CPU, memory, storage, and bandwidth Cloud platform providers – resources + frameworks; PaaS Data store (platform-as-a-service) Cloud intermediaries – help broker some aspect of raw Versus resources and frameworks, e.g., server managers, application assemblers, application hosting Vir tuali ze d resources p lus app lica tion framewor k Cloud application providers (SaaS) (e.g., RoR, Python, .NET) Clou d consumers – users ofthf the a bove Imposes an application and data architecture Constrains how application is built [Thanks to M. Maximilien, IBM] [Thanks to M. Maximilien, IBM] 25 25 Sept 2009 S. Tai 26 25 Sept 2009 S. Tai Players: Cloud Intermediaries Players: Application Providers Resells (aspects of) raw cloud resources, with added value Software as a Service (SaaS): propositions Applications provided and consumed over the Web Packaging resources as bundles Infrastructure usage (mostly) hidden Facilitating cloud resource management, e.g., setup, up dates, backup, load balancing, etc. Providing tools and dashboards Enabler of the cloud ecosystem [Thanks to M. Maximilien, IBM] [Thanks to M. Maximilien, IBM] 27 25 Sept 2009 S. Tai 28 25 Sept 2009 S. Tai 28 Cloud Computing by example: AWS The Cloud Ecosystem 29 25 Sept 2009 S. Tai 30 25 Sept 2009 S. Tai Cloud computing by example: AWS Amazon Simple Queue Service (SQS) Amazon Web Services (AWS) Cloud Offerings: Amazon Elastic Compute Cloud (()Amazon EC2) Amazon Simple Storage Service (Amazon S3 Amazon Simple Queuing Service (Amazon SQS) Amazon SimpleDB Amazon Elas tic MMRdapReduce Amazon CloudFront Amazon DevPay AWS Import/Export 31 25 Sept 2009 S. Tai 32 25 Sept 2009 S. Tai Amazon Simple Queue Service (SQS) SQS Functionality “Message queuing in the Cloud” Developers can create an unlimited number of Amazon SQS queues, each of which can send and receive an unlimited Basic message queuing model, except: queues are hosted by number of messages . Amazon, and queues are accessed using Web service protocols New messages can be added to a queue at any time. The Simple API message body can contain up to 8 KB of text in any format. Platform agnostic A computer can check a queue at any time for messages waiting Basic support for access control and message locking to be read. A message is “locked” while a computer is processing it, keeping other computers from trying to process it simultaneously . If Reliability processing fails, the lock will expire and the message will again Runs within Amazon's high-availability data centers be available. Messages stored redundantly across multiple servers and locations Messages can be retained in queues for up to 4 days. Scalable to millions of messages a day Developers can access Amazon SQS through standards-based SOAP and Query interfaces designed to work with any Internet- development toolkit . Source: aws.amazon.com 33 25 Sept 2009 S. Tai 34 25 Sept 2009 S. Tai SQS API Sample
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