1. Cloud computing (and Google AppEngine) material adapted from slides by Indranil Gupta, Jimmy Lim, Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet, Google Distributed Computing Seminar, 2007 (licensed under Creation Commons Attribution 3.0 License)

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3. Source: http://www.free-pictures-photos.com/ What is Cloud Computing?

4. 4  A new consumption and delivery model inspired by consumer Internet services.  Private, Public and Hybrid  Workload and/or Programming Model Specific  The Industrialization of Delivery for IT supported Services Cloud Services Cloud Computing Model  Self-service  Sourcing options  Economies-of-scale Multiple Types of Clouds will co-exist: “Cloud” represents: Cloud enables:“Cloud” is:

5. Different ‘Could’ Delivery Models  Infrastructure as a service (IaaS)  Utility computing  Why buy machines when you can rent cycles?  Examples: Amazon’s EC2, GoGrid, AppNexus  Platform as a Service (PaaS)  Provides an specialized API. App developer takes care of the implementation  Example: Google App Engine  Software as a Service (SaaS)  Provides the whole application  Example: Gmail, GoogleDocs, SalesForce

6. Key Enabling Technology: Virtualization Hardware Operating System App Traditional Stack Hardware OS App Hypervisor OS Virtualized Stack Hardware JVM App OS/JVM Managent JVM Virtualized Stack

7. 7 Steady CAPEX spend Global Annual Server Spending (IDC) Source: IBM Corporate Strategy analysis of IDC data Uncontrolled management and energy costs To make progress, delivery organizations must address the server, storage and network operating cost problem, not just CAPEX $0B 50 100 150 200 250 300 1996 1997 1998 1999 2000 2001 20022003 2004 200520062007200820092010 New system spend Management and admin costs Power and cooling costs

8. To Cloud or Not to Cloud?

9. Push factors  Fluctuating demand  Highly standardized applications  Modular, independent applications  Unacceptably high costs Barriers  Data privacy or regulatory and compliance issues  High level of Internal control required  Accessibility and reliability are a concern  Cost is not a concern Source: IBM Market Insights, Cloud Computing Research, July 2009. n=1,090 Trade-off: value vs. risk of migration

11. “The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do. […] The computer industry is the only industry that is more fashion-driven than women’s fashion. Maybe I’m an idiot, but I have no idea what anyone is talking about. What is it? It’s complete gibberish. It’s insane. When is this idiocy going to stop?” “The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do. […] The computer industry is the only industry that is more fashion-driven than women’s fashion. Maybe I’m an idiot, but I have no idea what anyone is talking about. What is it? It’s complete gibberish. It’s insane. When is this idiocy going to stop?” Larry Ellison During Oracle’s Analyst Day From http://blogs.wsj.com/biztech/2008/09/25/larry-ellisons-brilliant-anti-cloud-computing-rant/http://blogs.wsj.com/biztech/2008/09/25/larry-ellisons-brilliant-anti-cloud-computing-rant/ 11

12. Cloud computing is a new consumption and delivery model inspired by consumer Internet services. Cloud computing exhibits the following 5 key characteristics: On-demand self-service Ubiquitous network access Location independent resource pooling Elasticity Pay per use While the technology is not new, the end user focus of self-service, self- management leveraging these technologies is new. Virtualization Service Automation & SOA Usage Tracking Web 2.0 End User Focused

13. Three-tier architectures and Google AppEngine

14.  Separation of concerns: Presentation, business and data handling logic are clearly partitioned in different tiers.  Synchronous communication: Communications between tiers is synchronous request-reply. Each tier waits for a response from the other tier before proceeding.  Flexible deployment: There are no restrictions on how a multi-tier application is deployed. All tiers could run on the same machine, or each tier may be deployed on its own machine. Databases Application Logic Web Server / Presentation Logic Web Client Web Client Web Client Tier Web Server Tier Business Logic Tier Data Management Tier

15. BigTable (your) Java / Python hosted application (your) Presentation Logic Web Client Web Client Web Client Tier Web Server Tier Business Logic Tier Data Management Tier Hosting Server

16.  Simplified (Web Application) development  Scalability  Reliability ▪ (by leveraging Google infrastructure )

17.  Simplified (Web Application) development  Implementation ▪ Simplified/integrated application monitoring and logging ▪ Simplified user authentication ▪ Tooling  Deployment / maintenance / and use ▪ No servers to setup – Apache, EJB containers, database ▪ No server management / monitoring / upgrade ▪ Billing model: Pay per use ▪ Reduced upfront investment ▪ Scalability ▪ Monitoring and statistics ▪ User authentication

20.  Runs your code (e.g., servlet)  Restricted JVM environment ▪ Threads, security manager, file-access read only, new connections, reflection  Enforces Isolation  Keeps apps safe from each other  Many applications, many concurrent requests  Smaller footprint  Stateless!  Allows for scheduling flexibility  Time bound!  Service API requests to access to other services

21.  Across requests  Session  Memcache  Datastore No relational model! New API. (compared to databases) What consistency model?

22. C-A-P choose two C AP Fox&Brewer “CAP Theorem” consistency AvailabilityPartition-resilience Claim: every distributed system is on one side of the triangle. CA: available, and consistent, unless there is a partition. AP: a reachable replica provides service even in a partition, but may be inconsistent. CP: always consistent, even in a partition, but a reachable replica may deny service without agreement of the others (e.g., quorum).