Cloud Computing Overview And Predictions May 2009


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A summary of Cloud Computing concepts, advantages, and common sense predictions.

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Cloud Computing Overview And Predictions May 2009

  1. 1. Cloud Computing Overview and Predictions May 2009 Brent Jackson
  2. 2. Agenda  Understanding and Managing the Hype  Defining Cloud Computing  Exploring Types of Cloud Computing  Advantages and Disadvantages  Impact and Predictions  Resources
  3. 3. Managing Cloud Computing Hype  “Cloud” as Present Buzzword  Vendors Adding “Cloud” to Product Lines “Cloud is what we do/sell.” Trademark Attempt  Distinguish Hype from Reality  Manage Expectations  Leverage Interest
  4. 4. Defining Cloud Computing  Network Delivery Service Model for IT Services Virtualization, Utility, Grid Orientation Services SLA Implied/Explicit Internet Standards On-Demand Pay-Per-Use Multi-Customer Cloud Computing Internet Delivery Web Hosting MSPs ??? Elastic Scalability ASPs Cloud  Not an Architecture Computing
  5. 5. Types of Cloud Computing  Several Different Software as Platform as a Types of CC Have a Service Service (SaaS) (PaaS) Emerged, Each Delivered as a Service Infrastructure Cloud  XaaS : Everything as a as a Service Service (IaaS) Brokers Service Web 2.0 Portals & Mashups
  6. 6. Software as a Service (SaaS)  Whole Applications or  Examples App Ecosystems  Delivered via Internet NetSuite  Multi-tennancy Ariba  Some App Zoho Customization RightNow Google Apps  Offline Usage Models SAP Business ByDesign Emerging ~FaceBook et al
  7. 7. Infrastructure as a Service (IaaS)  Virtual Hardware  Examples Delivered as a Service  Amazon Web Services  EC2, S3, SimpleDB, SQS, VMs / Compute Power MapReduce Storage  GoGrid Network (f/w, nlbs)  Flexiscale  Google  Virtual Software  App Engine, Gdata Infrastructure  Rackspace / Mosso Databases  Cloudera  Hadoop Messaging (MOM)  Eucapyptus f/w Data Processing  Nimbus f/w
  8. 8. Platform as a Service (PaaS)  Internet Platforms to  Examples: Develop, Test, Deploy  and Run Your Own Google App Engine Applications Bungee IDE LongJump Standard or Proprietary Intuit Quickbase Languages Coghead† (SAP) Higher Level Etelos Abstractions (Many Run on IaaS)
  9. 9. Cloud Service Brokers (CSB)  Cloud “Middleware”  Examples: Intermediation Rearden Commerce  Enhances a Service Boomi AtomSphere  Performance, Security, Dashboards, etc. Cast Iron Aggregation  May be Deployed at  Combines Services Service, Cloud, or Arbitrage Consumer  Flexible Aggregation  Higher Availability  Prevent Lock-in (a.k.a. Integration as a Service)
  10. 10. Is Hadoop Cloud Computing?  Except as a Service Offered by Cloudera, Hadoop / MapReduce Frameworks Do Not Strictly Satisfy Definition of Cloud Computing  Doug Cutting Does Not Consider Hadoop to be Cloud Computing  However, Hadoop is Popularly Cited as an Example of Cloud Computing  Massively Distributed and Scalable  Computation Near Data  Leverages IaaS  Hadoop Best Classified as Software IaaS (Data Processing)
  11. 11. Pros and Cons of Cloud Computing Advantages Challenges  Lower Startup Costs  Security  Software  Trust Model Weak  Infrastructure  Confidentiality  Scale on Demand  Stability / Reliability  “Unlimited” Capacity  Reduced Feature Set  Less Maintenance  Performance Not  Patching Guaranteed  Updates  Maturity  Refesh  Legal Ambiguities  Technology Abstraction
  12. 12. Democratization  Cloud Computing Tears Down Traditional Barriers to Entry  Infrastructure Costs  Software Licensing Costs  Development Tools  Distribution and Publishing  Geographic Advantage  Anyone with an Idea, Tenacity, Skills and an Internet Connection Can Compete with Traditional Software Giants  Dynamic Scaling to Success
  13. 13. Cloud Computing and Government  President Obama as Technology Proponent  Several Cloud Pilot Programs in 2010 Budget Request  Federal CIO Vivek Kundra is a Cloud Proponent  Washington DC use of Google Apps, Wikipedia, YouTube, Twitter  Stated Objectives toward Shared Government IT Infrastructures  “Cloud Czar” Patrick Stingley Appointed  GSA CTO for Cloud Computing  Federal Cloud Computing Summits  Official NIST Definition of Cloud Computing  Peter Mell, Tim Grace
  14. 14. Cloud Computing Predictions  Rapid Growth Driven by Economics and Government  Dominant DC Model for All but Largest Enterprises  Cloud Computing Won’t Be a Panacea  Major Shift in Software Market and Distribution Model  Threat to Dominance of Present Vendors  Consolidation of IaaS, PaaS Vendors  Mega DCs May Drive Future Hardware Directions  Proliferation of Cloud (Especially SaaS) Startups, Followed by Acquisition  Democratization of IT and Media  Cloud Integration as an Emergent Service  Hybrid Solutions Commonplace
  15. 15. Cloud Computing Predictions (2)  PaaS Battle Over Languages: Familiarity vs. Abstraction  Java and DSLs Likely Winners  Most Small/Medium Businesses will be Serverless  No IT other than Desktops and ISP  Outages Continued but Reduced Impact  Significant and Public Data Security Incidents with Subsequent Lawsuits  Limited Critical Mass of Private Clouds Will Limit Viability  Killer Apps: Media, Mass Collaboration, and Gaming Will Continue to Drive Cloud Computing  PaaS More Fundamentally Changes Computing Paradigm than Other Types of Cloud Computing
  16. 16. A Few Cloud Computing Resources  Gartner Cloud Page uting.jsp  Burton Group Cloud Page mp=cloudhmbnr  Business Cloud 9  Proposed 2010 Budget, section 9 (pg. 155)  Government Cloud Computing Summit  NIST Cloud Computing Definition computing-standards_ISPAB-Dec2008_P-Mell.pdf