A Walk in the Clouds Comparing Google AppEngine , Amazon AWS and Sun Project Caroline

1. A Walk in the CloudsComparing Google AppEngine , Amazon AWS and Sun Project Caroline Niraj Juneja Blog: http://www.gandalf-lab.com

2. What are we talking about today • Really Quick Overview of Cloud Computing • Market Analysis – POV’s • Comparing three clouds • Amazon AWS • Google App Engine • Sun’s Project Caroline • Enterprise Adoption • Other Players • Hewlett Packard , SAP , Oracle , IBM • 3Tera , Enki , Enomaly • Niche Application Players (Vertica , Greenplum )

3. What is Cloud Computing • The Big Definition Wikipedia - Cloud computing is Internet ('Cloud') based development and use of computer technology ('Computing'). The cloud is a metaphor for the Internet (based on how it is depicted in computer network diagrams) and is an abstraction for the complex infrastructure it conceals[1]. It is a style of computing where IT-related capabilities are provided “as a service”[2], allowing users to access technology-enabled services from the Internet ("in the cloud")[3] without knowledge of, expertise with, or control over the technology infrastructure that supports them[4]. According to the IEEE Computer Society "It is a paradigm in which information is permanently stored in servers on the Internet and cached temporarily on clients that include desktops, entertainment centers, table computers, notebooks, wall computers, handhelds, etc."[5]. “ • No Consensus in the industry for a good definition of “Cloud computing” . Today anything and everything internet will come with a cloud computing logo • My Definition: If the time difference between - your application needs more capacityand gets more capacity is greater than instantly it is not cloud computing. i.e if there is no programmatic way to provision hardware ,no pooled capacity and even worst a purchase order to get new hardware. • The Bottom-line • Changes the economics of Computing from being a Capital investment to Utilities (You buy electricity you don’t buy generators ) • Changes the way software is developed – Hardware provisioning , Deployment and Scaling now part of developer lifecycle as a Program / script as compared to a Purchase order • Automates a whole bunch of infrastructure related tasks and activities leading efficiencies and cost savings

4. Some Myth’s and perceptions • Isn’t it all about hardware provisioning? • Not Really – It is also about changing of Software Development Lifecycle with scaling up , hardware provisioning and deployment all under the control of developer written programs • What about Security and Enterprise Adoption ? • Two answers • Private Clouds – You will start seeing the adoption of the cloud computing paradigm come into the corporate data center. Big iron vendors will start selling Private Cloud Products. • Refer link here http://goanimate.com/go/movie/0tTsEaeL-8o8?utm_source=emailshare&uid=0AhZ8_zfEIec • Just as Banks became a safe place to keep your money away from your safe-box in your grandfathers home , The Cloud will become the default place to keep your data in the future

5. Some Myth’s and perceptions • Isn’t this similar to Time Sharing? • Yes to some extent. • But it is not all about sharing of resources. It really boils down to cost savings as a result of automation and changing the SDLC • How is it different from ASP? • The ASP value-add was the typical value you get from an outsourcing company. Leverage Knowledge base , trained manpower and some shared infrastructure resources to guarantee reliability of operations and potential cost savings • Cloud Computing is like taking the ASP concept to the next level with zero to little amount of “People Services” and focus on the Computing as a Utility

6. Market Analysis SaaS – Software as a Service (Platform , Scaling and Hardware transparent) Gmail Google Apps Salesforce.com Force.com PaaS – Platform as a Service (Hardware Provisioning Hidden – Automatic Scaling) Sun Caroline Google app engine Amazon Simple DB Increasing Virtualization HaaS – Hardware as a Service Programmatic Interface for Hardware Provisioning Amazon EC2/S3 Bare Metal People Process based hardware provisioning In house hosted servers EDS (Infrastructure Outsourcing) Flexibility of Offering

7. Market Analysis (POV –Sun Microsystems) App Engine Source: http://www.projectcaroline.net

8. Market Analysis (POV –Sun Microsystems) Source: http://www.projectcaroline.net

9. Market Analysis (POV –Sun Microsystems) Source: http://www.projectcaroline.net

10. Market Analysis (POV – Red Monk) Source: http://www.redmonk.com

11. Comparing Three clouds • Discussion to focus on • Amazon Web Services • Google App Engine • Sun’s Project Caroline • Why these ? • Most talked about (except Caroline) • Gives a good overview around the breadth of offerings in the space

12. Amazon Web Services • Offerings • Hardware as a Service (HaaS) AWS-EC2 • Storage as a Service – AWS-S3 • Database as a Service – SimpleDB • Queuing as a Service – SQS • Aggregate Offerings • Pretty much anything you can think off • Oracle , Solaris , Hadoop Clusters (NY times), Specialized Applications (Vertica DB) , Animoto

13. AWS – Some Use Cases • AWS – Some Use Cases • Start up’s (low entry point and can get going with great infrastructure in a day) • SaaS vendors (Vertica ) – a logical marriage between SaaS and HaaS. AWS just becomes a component in the Supply Chain • Enterprise Use Cases • Testing –(Performance testing ,Compatibility Testing) • Massive Batch Jobs – Hadoop Image (NY Times example) , Animoto uses 3000 EC2 instances • Claim to Fame • Came from Bottom up in the market and took the low end of the market by storm • Low Entry point (10 cents an hour for a CPU) and can scale up to Terabytes of storage and thousands of server at the same price structure • Everything is Automated and has programmatic access (No calls to system admin’s to configure a parameter or restart a server)

14. Google App Engine • Exposes the Google Infrastructure to the outside world • BigTable • Python Language runtime • Access to some google api’s (authentication , image manipulation) • APIs • The Python Runtime, The Python environment in which your app runs; CGI, sandbox features, application caching, logging • Datastore API, BigTable – Google’s Database • Images API, the image data manipulation service • Mail API, sending email from your app • Memcache API, the distributed memory cache • URL Fetch API, accessing other Internet hosts from your app • Users API, integrating your app with Google Accounts • You should expect to see more API’s exposed. More specifically the Google API’s for Docs , GWT , etc

15. App Engine - offering • Claim to Fame • Free (to start with) • BigTable ( a real winner) • Essentially a good way to get into the google world and potentially get acquired by google

16. Google App Engine • Use cases • Webscale Database needs (BigTable) – Map Reduce Programming model • Start up (who want to leverage google apis and sign on capability) • Enterprise Use Cases • None right now • But potentially Application’s requiring to link the web presence of customers (blogs , open social) to the Enterprise Applications (Example customer insight’s into CRM etc) could use AppEngine. • if you are a Google Apps Shop there Is a case of hosting on AppEngine

17. Comparing Amazon and Google Stacks Source: http://www.zdnet.com

18. Project Caroline – Sun Microsystems • Research project developing a platform for development and deployment of long-running Internet services • Utility scale: lots of customers and services on a single large shared grid, with secure isolation • Full programmatic control of distributed compute, storage, and network resources • Services can configure and flex their own resource usage up and down in real time • High level of resource abstraction • Will potentially end up in the “Private Cloud” for the Enterprise along Amazon like offerings for the Bottom market

19. Developer View

20. What is the API ? • Essentially a way to Provision and manage the system resources like • Network (IP Addresses) • Databases • Filesystem • Standard Configurations available for Tomcat / Glassfish / Ruby • Can create new configurations for new server types • Ant Based Environment also available for controlling the grid • Direct Access from netbeans to integrate the GRID workflow into SDLC

21. What is the API ? • File System Creation : myFS = grid.createBaseFileSystem(“myFS”,new BaseFileSystemConfiguration()); • Network Creation : myNet = grid.createNetwork(“myNet”, 16,new CustomerNetworkConfiguration()); • IP address allocation dbAddr = myNet.allocateAddress(“dbAddr”); intAddr = myNet.allocateAddress(“intAddr”); extAddr = grid.allocateExternalAddress(“extAddr”); • Database Creation myDB = grid.createPostgreSQLDatabase(“myDB”, new PostgreSQLConfiguration( dbAddr.getUUID(), null));

22. Impact of Project Caroline Model • Automate deployment & day-to-day operations • Faster response times • Capture knowledge in programs not process books • Services construct their environment instead of being inserted into an existing one • Simpler for operations and developers • Isolation between service instances • Multi-process components • Developer workflow

23. Other Players • Big Iron Vendors • Hewlett Packard.: A joint project between Yahoo , HP and Intel . Also watch out for EDS related Enterprise Offerings • IBM : On Demand Computing • Software Vendors • Microsoft – Project Reddog • Oracle – AWS Announcement’s plus more to come • SAP – Business by Design • Salesforce – force.com • Niche Players • 3Tera , Enki • Vertica • Dataware house appliances (Greenplum , Neoview) • A whole bunch others

24. “there will be small number of big players and a large numbers of small players in the cloud computing space ” – Dr. Eric Schmidt , CEO Google “we had enough complexity inside Amazon that we were finding we were spending too much time on fine-grained coordination between our network engineering groups and our applications programming groups. Basically what we decided to do is build a [set of APIs] between those two layers so that you could just do coarse-grained coordination between those two groups. Amazon is, you know, just a web-scale application. “ - Jeff Bezos , CEO Amazon on “how did Amazon end up creating AWS leaving the big iron vendors behind” The world needs only five computers. - Thomas Watson , CEO IBM (1943) - and then re-phrased by Greg Papadopoulos – CTO Sun Microsystems “there will be, more or less, five hyperscale, pan-global broadband computing services giants. There will be lots of regional players, of course; mostly, they will exist to meet national needs. That is, the network computing services business will look a lot like the energy business: a half-dozen global giants, a few dozen national and/or regional concerns, followed by wildcatters and specialists.”

25. Final Reflections • In my diagram below – There will be one layer added above the SaaS layer , which will be the device layer that will be realized as a result of everything moving to the cloud - Networked Refrigerators , Remote Controlled Vacuum Controllers or any and every device on the network were interesting discussions uptill now but will become a reality with the cloud. • The above is exactly what happened with the build-out of the last big grid – electricity in the 20th century. A hundred years ago, when Tesla, Westinghouse, Insull, and others were building the electric grid - companies viewed the effort in terms of the cost reduction to their business: in particular, the power they needed to run the machines that produced the goods they sold. But the real revolutionary aspect of the electric grid was not the way it reduced the cost structure, but the way it created new businesses altogether. We saw an avalanche of new products outfitted with electric cords, many of which were inconceivable before the grid's arrival Network Device Layer Growth Engine for the next generation

26. Demos • Project Caroline – animal guess example • Google App Engine – Guest Book • Amazon EC2 and S3 Console