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.eOrganization . 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 of open servi ce and 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 of open servi ce and bus iness ne twor ks • Di(tDynamic (trans-)forma tion of open servi ce and 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 use/deplo y, 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 tua lize d resources p lus app lica tion framewor k Cloud application providers (SaaS) (e.g., RoR, Python, .NET) Clou d consumers – users ofthf the ab ove 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. , setu p, 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 SOAP request of sending a message
POST /MyQueue HTTP/1.1 CreateQueue: Create queues for use with your AWS account. Host: queue.amazonaws.com ListQueues: List your existing queues.
DeleteMessage: Remove a previously received message from a
35 25 Sept 2009 S. Tai 36 25 Sept 2009 S. Tai SQS Pricing Amazon Simple Storage Service (S3)
Source: aws.amazon.com
37 25 Sept 2009 S. Tai 38 25 Sept 2009 S. Tai
Amazon S3 S3 Design Principles
Write, read, and delete objects containing from 1 byte to 5 gigabytes of data each. The number of objects you can store is unlimited. Decentralization: Use fully decentralized techniques to remove Each objjq,pect is stored in a bucket and retrieved via a unique, developer- scaling bottlenecks and single points of failure. assigned key. A bucket can be located in the United States or in Europe. All objects Asynchrony: The system makes progress under all within the bucket will be stored in the bucket’s location, but the objects circumstances. can be accessed from anywhere. Autonomy: The system is designed such that individual Authentication mechanisms are provided to ensure that data is kept components can make decisions based on local information. secure from unauthorized access. Objects can be made private or public, and rights can be granted to specific users. Local responsibility: Each individual component is responsible UUtddses standards-base d REST and SOAP i nt erf aces d esi gned t o work for achieving its consistency; this is never the burden of its with any Internet-development toolkit. peers. Built to be flexible so that protocol or functional layers can easily be Controlled concurrency: Operations are designed such that no added. Default download protocol is HTTP. A BitTorrent™ protocol interface is provided to lower costs for high-scale distribution. or limited concurrency control is required. Additional interfaces will be added in the future. Failure tolerant: The system considers the failure of components Reliability backed with the Amazon S3 Service Level Agreement. to be a normal mode of operation, and continues operation with no or minimal interruption. Source: aws.amazon.com
39 25 Sept 2009 S. Tai 40 25 Sept 2009 S. Tai S3 Design Principles (cont.) Sample Code: Developer Community
Controlled parallelism: Abstractions used in the system are of such granularity that parallelism can be used to improve performance and robustness of recovery or the introduction of new nodes. Decompose illllinto small well-understoo d bu ilding bloc ks: Do not try to provide a single service that does everything for everyy,one, but instead build small comp onents that can be used as building blocks for other services. Symmetry: Nodes in the system are identical in terms of functionalit y, and requ ire no or minimal node-specific configuration to function. Simppylicity: The syypstem should be made as simple as possible (but no simpler).
41 25 Sept 2009 S. Tai 42 25 Sept 2009 S. Tai
Sample S3 REST Usage S3 Pricing
Use standard HTTP requests to create, fetch, and delete buckets and objects A typical REST operation consists of a sending a single HTTP request to Amazon S3, followed by waiting for an HTTP response. Like any HTTP request, a request to Amazon S3 contains a request methomethodd, a URI, request headers, and sometimes a query string and request body. The response contains a status code, response headers, and sometimes a response body. Following is an example that shows how to get an object named "Nelson" from the "quotes" bucket.
GET /Nelson HTTP/1.1 Host: quotes.s3.amazonaws.com Date: Wed, 01 Mar 2006 12:00:00 GMT Authorization: AWS 15B4D3461F177624206A:xQE0diMbLRepdf3YB+FIEXAMPLE=
HTTP/1.1 200 OK x-amz-id-2: qBmKRcEWBBhH6XAqsKU/eg24V3jf/kWKN9dJip1L/FpbYr9FDy7wWFurfdQOEMcY
x-amz-request-id: F2A8CCCA26B4B26D on.com Date: Wed, 01 Mar 2006 12:00:00 GMT zz Last-Modified: Sun, 1 Jan 2006 12:00:00 GMT ETag: "828ef3fdfa96f00ad9f27c383fc9ac7f“ Content-Type: text/plain Content-Length: 5 Data transfer “in” and “out” refers to transfer into and out of an Amazon S3 location (i.e., US or EU). Connection: close Data transferred within an Amazon S3 location via a COPY request is free of charge. rce: aws.ama
Server: AmazonS3 uu Data transferred via a COPY reqqgguest between locations is charged at regular rates. Data transferred between Amazon EC2 and Amazon S3 within the same region is free of charge (i.e., $0.00 per GB). Data transferred between So Amazon EC2 and Amazon S3 across regions (i.e. between US and EU), will be charged at Internet Data Transfer rates on both sides of the transfer. Source: aws.amazon.com ha-ha Storage and bandwidth size includes all file overhead.
43 25 Sept 2009 S. Tai 44 25 Sept 2009 S. Tai Amazon EC2 Amazon EC2
EC2 presents a true virtual computing environment, allowing you to use web service interfaces to launch instances with a variety of operating systems, load them with your custom application environment, manage your network’s access permissions, and run your image using as many or few systems as you desire.
Create an Amazon Machine Image (AMI) containing your applications, libraries, data and associated configuration settings. Or use pre- configured, templated images to get up and running immediately. Upload the AMI into Amazon S3. Amazon EC2 provides tools that make storingg the AMI simple. Amazon S3 provides a safe, reliable and fast repository to store your images. Use Amazon EC2 web service to configure security and network access. Choose which instance type(s) and operating system you want, then start, terminate, and monitor as many instances of your AMI as needed, using the web service APIs or the variety of management tools provided. Determine whether you want to run in multiple locations, utilize static IP endpoints, or attach persistent block storage to your instances. Pay only for the resources that you actually consume , like instance-hours or data transfer.
45 25 Sept 2009 S. Tai 46 25 Sept 2009 S. Tai
EC2 Instance Types EC2 Core Concepts
Amazon Machine Image (AMI): an encrypted file stored in Amazon S3, containing all the information necessary to boot instances of a customer’s software An AMI is like a bootable root disk, which can be pre-defined or user-built. Public AMIs: Pre-configured, template AMIs Private AMIs: User-built AMI containing private applications, libraries, data and associated configuration settings
Instance: The running system based on an AMI All instances based on the same AMI begin executing identically. An instance can be launched in very few minutes. Any information on them is lost when the instances are terminated or if they fail.
47 25 Sept 2009 S. Tai 48 25 Sept 2009 S. Tai EC2 Regions & Availability Zones EC2 Operating Systems
49 25 Sept 2009 S. Tai 50 25 Sept 2009 S. Tai
EC2 Software Appliances EC2 Pricing: On-demand Instance
51 25 Sept 2009 S. Tai 52 25 Sept 2009 S. Tai EC2 Pricing: Reserved Instance EC2 Data Transfer
No costs within availability zones $0.01/GB between regions $0.01/GB for public and elastic IP data transfer
53 25 Sept 2009 S. Tai 54 25 Sept 2009 S. Tai
Elastic Block Store (EBS) Elastic IP Adresses
Dynamic Mapping of IPs to virtual machines
For permanent data storage Uses S3
55 25 Sept 2009 S. Tai 56 25 Sept 2009 S. Tai Amazon Management Console (1): https://console.aws.amazon.com/ Amazon Management Console (2): AMIs
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Amazon Management Console (3): EBS Amazon Management Console (4): Elastic IPs
59 25 Sept 2009 S. Tai 60 25 Sept 2009 S. Tai Amazon Management Console (6): Security Amazon Management Console (5): Keys Groups/Firewall
61 25 Sept 2009 S. Tai 62 25 Sept 2009 S. Tai
AWS Management using ElasticFox Amazon Command Line Tools (FireFox plugin)
http://awsdocs.s3 . amazonaws.com/EC2/latest/ec2 -qrc. pdf http://docs.amazonwebservices.com/AWSEC2/latest/GettingStartedGuide/
63 25 Sept 2009 S. Tai 64 25 Sept 2009 S. Tai Go online! EC2 SOAP API
65 25 Sept 2009 S. Tai 66 25 Sept 2009 S. Tai
AWS Example: Grep the Web GrepThe Web – Zoom Level 1
Source: „Cloud Architectures“ by Jinesh Varia, Amazon, published online at http://jineshvaria. s3. amazonaws. com/public/cloudarchitectures-varia.pdf Source: amazon.com
67 25 Sept 2009 S. Tai 68 25 Sept 2009 S. Tai GrepThe Web – Zoom Level 2 Phases of GrepThe Web Architecture
Source: amazon.com Source: amazon.com
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GrepThe Web – Zoom Level 3 Using Queues for Loose coupling
Source: amazon.com Source: amazon.com
71 25 Sept 2009 S. Tai 72 25 Sept 2009 S. Tai Simple Controller Architecture MapReduce
Public Abstract BaseController (SQSMessageQueue fromQueue, SQSMessageQueue toQueue, SDBDomain domain)
Source: amazon.com
73 25 Sept 2009 S. Tai 74 25 Sept 2009 S. Tai
MapReduce Programming Model Google’s MapReduce
Two functions: map (in_ key, in_ value) -> (out_ key, intermediate_ value) list reduce (out_key, intermediate_value list) -> out_value list
http://labs.google.com/papers/mapreduce.html
75 25 Sept 2009 S. Tai 76 25 Sept 2009 S. Tai MapReduce Hadoop
OpenSource Apache Software Foundation Project (Yahoo!) http://wiki.apache.org/hadoop/ProjectDescription
MapReduce programming model Distributed file system (HDFS) Parallel database http://en.wikipedia.org/wiki/Hadoop http://code.google.com/edu/parallel/mapreduce-tutorial.html
Source: amazon.com
77 25 Sept 2009 S. Tai 78 2578 Sept| Marcel 2009 KunzeS. Tai | KIT Delegation in Silicon Valley | January 2009
PaaS Example: Google App Engine Web Applications on Google Infrastructure
79 25 Sept 2009 S. Tai 80 25 Sept 2009 S. Tai Google App Engine: code.google.com/appengine/docs/ code.google.com/appengine/ whatisgoogleappengine.html
“Google App Engine lets you run your web applications on Google's infrastructure. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow. With App Engine, there are no servers to maintain: You just upload your application, and it's ready to serve your users.” “You can serve your app using a free domain name on the appspot.com domain, or use Google Apps to serve it from your own domain. You can share your application with the world, or limit access to members of your organization.” “App Engine costs nothing to get started. Sign up for a free account,,y and you can develop pp and publish yppyour application for the world to see, at no charge and with no obligation. A free account can use up to 500MB of persistent storage and enough CPU and bandwidth for about 5 million page views a month.”
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App Engine Components App Engine Developer Account
Dozens of examples in App Gallery Tools, Communication, Games, News, Finance, 1. Scalable Serving Infrastructure Sports, Lifestyle , Technology , Enterprise 2. Python and Java Runtime http://appgallery.appspot.com/ 3. Software Development Kit 4. Datastore Register as a developer 5. Web based Admin Console http://code.google.com/appengine
Free to get started 500 MB storage 2 GB bandwidth / day ~ 5 million page views / month
Pay-per-use if you need more
83 25 Sept 2009 S. Tai 84 25 Sept 2009 S. Tai Free Quota and Pricing HuaaS Example: On-demand Workforce
Resource Free Quota Additional
CPU Equivalent to 5M 10-12¢ / core-hour pageviews / month Storagefor a typical app 15-18¢ / GB-month
Bandwidth, Outgoing 11-13¢ / GB transferred
Bandwidth, Incoming 9-11¢ / GB transferred
85 25 Sept 2009 S. Tai 86 25 Sept 2009 S. Tai
Amazon Mturk: www.mturk.com MTurk Basic Idea
Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace that enables computer programs to co-ordinate the use of human intelligence to perform tasks which computers are unable to do.
Requesters, the human beings that write these programs, are able to pose tasks known as HITs (Human Intelligence Tasks), such as choosing the best among several photographs of a storefront, writing product descriptions, or identifying performers on music CDs. Workers (called Providers in Mechanical Turk's Terms of Service) can then browse among existing tasks and complete them for a monetary payment set by the Requester. To place HITs, the requesting programs use an open API, or the somewhat limited Mturk Requester site.
87 25 Sept 2009 S. Tai 88 25 Sept 2009 S. Tai Open Research Challenges and Opportunities, „Human(Intelligence)-as-a-Service“ Select Ongoing Research Activities
89 25 Sept 2009 S. Tai 90 25 Sept 2009 S. Tai
Gartner‘s Hype Cycle for Cloud Computing, July 2009 Cloud Computing Obstacles and Opportunities
Above the Clouds: A Berkeley View of Cloud Computing. Armbrust et al., Technical Report No. UCB/EECS-2009-28. Electrical Engggineering and Compp,yuter Sciences, University of California at Berkeley, USA, 2009.
91 25 Sept 2009 S. Tai 92 25 Sept 2009 S. Tai OpenCirrus™ Cloud Research in Karlsruhe Cloud Computing Research Testbed
Research, education, and innovation An open, internet-scale global testbed for cloud computing research Data center management & cloud services Systems level research Application level research Inter-disciplinary approach Structure: a loose federation Strong industry partnerships, projects, and strategic Sponsors: HP Labs, Intel Research, Yahoo! alliances Partners: UIUC, Singapore IDA, KIT, NSF Members: System and application development Great opportunity for cloud R&D European node in the OpenCirrusTM global, open Cloud Computing research testbed http://opencirrus.org
93 25 Sept 2009 S. Tai 94 25 Sept 2009 S. Tai
„Everything-as-a-Service (XaaS)“
Example 1: Landscape as a service (LaaS), or, Virtual Private Data Centers (VPDC)
95 25 Sept 2009 S. Tai 96 25 Sept 2009 S. Tai Migrating, resp. Provisioning, an entire (SAP-) Landscape as a Service LaaS-Architecture
97 25 Sept 2009 S. Tai 98 25 Sept 2009 S. Tai
LaaS Management and Monitoring Extending the VPDC to External Ressources
Pool- gateway S3 VM VM S3- JLAN
VM VM
Pool- VM gateway
VM S3- JLAN VM VM VM
99 25 Sept 2009 S. Tai 100 25 Sept 2009 S. Tai Composing XaaS
Howcanwemashup Example 2: an open, authenticated, Comppgosing Cloud Services ppyay-per-use Hadoop service?
101 25 Sept 2009 S. Tai 102 25 Sept 2009 S. Tai
Hadoop reality Basic Architecture
1. Reserve servers What‘s missing: 2. Install Hadoop on each server PttiPresentation Client 3. Configure one server as namenode, Web Client another one as jobtracker (all others are tasktrackers and will execute map-reduce) Multi-tenant 4. Log into namenode (SSH) support Mashup 5. Load data onto namenode 6. Load data onto HDFS Payment 7. Log into jobtracker (SSH)
8. Start program Authen- Hadoop as a Cloud Provider Storage Payment 9. Observe SSH shell output for tication Service Services progress independence 10. Load date from HDFS onto namenode … 11. Get results (SSH)
103 25 Sept 2009 S. Tai 104 25 Sept 2009 S. Tai Cloud Services Cloud Service-specific Modules
Authen- Hadoop as a Cloud StorageMySQL OpenID PaymentPaypal tication Service Services PttiPresentation Client
Jobs Budget Filesystem SSH SSH Mashup Authen- tication DB User Payment Hadoop
Jobtracker WS Namenode WS
MySQL / Hadoop as a Cloud HDFS OpenID Paypal Priority Budget SimpleDB Service Services Scheduler Tool
Filesystem Budget Filesystem
105 25 Sept 2009 S. Tai 106 25 Sept 2009 S. Tai
Animoto‘s Facebook Scale-up
Example 3: Understanding common Cloud Use Cases & Cost/Value Estimation …and Scale-down
107 25 Sept 2009 S. Tai 108 25 Sept 2009 S. Tai Cloud Computing TCO (single consumer viewpoint, IaaS focus) Estimating the Value of Cloud Computing
Collect real -world Examine key Understand and use cases and aspects from valuate benefits identify typical business and IT from cloud scenarios perspective computing business objectives Estimate costs • foster innovation • variable costs • rapid prototyping • fixed costs • leverage Web as platform • time to market
demand behavior • seasonal Estimate value • temporary spikes • Business value • unpredictable • Economic value
IT requirements Derive strategies • scalability • Decision processes • reliable and stable platform • Recommendations • high availability • Business transformation
109 25 Sept 2009 S. Tai 110 25 Sept 2009 S. Tai Source: „Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing“, M. Klems, J. Nimis, and S. Tai. Springer LNBIP, 2009.
Summary Summary and Discussion
Cloud Computing has the potential to fundamentally change the way we design the technical architecture and the business architecture of modern enterprises
Clou d CtiComputing isa disrupti ve thltechnology, ldileading to creative disruption
111 25 Sept 2009 S. Tai 112 25 Sept 2009 S. Tai Creative Disruption [Schumpeter] Conclusion
The opening up of new markets and the organizational development […] illustrate the process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one...
[The process] must be seen in its role in the perennial gale of creative destruction; it cannot be understood on the hypothesis that there is a perennial lull.
Business strategy can never assume an end-state or equilibrium The integrity and identity of any business is to some degree dependent on the external pressures exerted on it by the competitive environment; strategic success may be the greatest threat to future strategic success
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New Book on Cloud Computing (in German) More information: cloudwiki.fzi.de Springer-Verlag, September 2009
www.tinyurl.com/cloudbuch http:// mark uskl ems.word press.com/
115 25 Sept 2009 S. Tai 116 25 Sept 2009 S. Tai Thank You! Acknowledgments
Marcel Kunze, KIT Jens Nimis, FZI Alexander Lenk, FZI Markus Klems, FZI
Stefan Tai, [email protected] www.eOrganization.de
117 25 Sept 2009 S. Tai 118 25 Sept 2009 S. Tai