The document provides an overview of the Platform as a Service (PaaS) landscape, discussing key aspects of PaaS including definitions, hosted vs private models, single language vs polyglot platforms, and the evolution of PaaS towards supporting big data and becoming intelligent platforms. It also covers various PaaS vendors and differentiation factors.

1. Dissecting The PaaS Landscape
Rishidot Research Webinar

2. Bookkeeping and Disclaimers
 Speaker’s Twitter handle: @krishnan
 Webinar hashtag: #paasmkt
 This is not deep dive research rather a 30000 feet
overview on the market. Not all players covered.
 Deploycon 2013 100% off discount code sent to
webinar attendees
 Research report shared after Deploycon 2013
 Some of the vendors listed in this webinar are either
Rishidot Research clients or Deploycon sponsors

3. Plan For The Talk
 Defining PaaS
 PaaS Ecosystem and Spectrum
 PaaS Differentiation
 PaaS and Big Data
 Conclusion

4. SPI Model

5. PaaS Definition
PaaS is defined as an elastic on-
demand platform for applications
that completely abstracts away the
underlying infrastructure with the
application scaling seamlessly with
the platform.

6. P, ugh, aaS?
 The idea of PaaS has evolved
 Enterprise reluctance and diverse needs
has changed the aaS usage in PaaS
 PaaS  Platform Services where services
can be hosted or private
#ongoingdiscussion
 Let us stop thinking about the debate and
start talking about the usage

7. What is PaaS and What is Not
PaaS definition has broadened but
certain characteristics hasn’t changed
Application scales with the platform
that offers “infinite” scalability
No human intervention
No hardware in the discussion

8. What is PaaS and What is Not
Application Scales With Legacy Applications on
Platform Elastic Infrastructure

9. Is PaaS Middleware for Cloud?

10. Why PaaS?
Developers:
 Faster Development and Continuous
Deployment (Agile)
 Fewer Bugs (Similar environments in Dev,
Test and Production)
 Richer applications due to add-on services
 Easy seamless collaboration

11. Why PaaS?
Organizations:
 Platform for services world
 Reduced and efficient operations
 Cost effective IT
 Agility

12. PaaS Evolution
 From Hosted to Private
 From Proprietary to Open
Source
 From Startups to Enterprise

13. PaaS Ecosystem

14. PaaS Ecosystem

15. PaaS Spectrum
Hosted Private DevOps DevOps Infrastructure
PaaS PaaS PaaS Tools Services
Abstraction Control

16. PaaS: Axes Of Differentiation
 Hosted Vs Private PaaS
 Single Language (Best of Breed) Vs
Polyglot
 Proprietary Vs Open Source
 DevOps Vs NoOps
 Vertical PaaS

17. Hosted PaaS Vs Private PaaS
Hosted:
• On Demand
• Pay per use
• Economic benefits and agility
• Higher Levels of Abstraction
• Lose some control and “lock-in risks”
• GAE, Heroku, Engine Yard, Windows Azure,
Appfog, Tier 3, Dot Cloud, Force.com,
Orangescape, etc..

18. Hosted PaaS Vs Private PaaS
Private PaaS:
• Less agility
• More control and less lock-in risks
• Varying levels of abstraction
• Struck in CAPEX model
• Apprenda, ActiveState, CloudFoundry, WSO2,
Cloudsoft AMP, Cloudify, Cumulogic, etc..
Then there is Hybrid like OpenShift, CloudBees,
Oracle Java Service, etc..

19. Best Of Breed Vs Polyglot
Best of Breed:
 Single Language Platforms
 Best of breed evolution
 More depth than Polyglot platforms (Today)
 Support for legacy applications
 Enterprise target
 Apprenda, Engine Yard, WSO2, CloudBees,
Cumulogic, Oracle, etc..

20. Best Of Breed Vs Polyglot
Polyglot:
• Single platform supporting multiple languages
and frameworks
• Suitable for modern apps and orgs with multi-
language developer teams
• More adoption in startups but enterprises are
slowly embracing polyglot
• Heroku, CloudFoundry, OpenShift, Tier3,
ActiveState, AppFog, Google App Engine, etc..

21. Proprietary Vs Open Source
Proprietary Platforms:
• Non availability of source code. Less
flexibility in Platform customization
• Hosted or Private
• Higher Lock-in risks with hosted platforms
• Heroku, Engine Yard, Google App Engine,
Apprenda, HP, CloudBees, Cumulogic,
etc..

22. Proprietary Vs Open Source
Open Source:
• Usual moral reasons
• Source code available for easy customization
• Hosted or Private
• Lesser lock-in risks with hosted platforms
under certain conditions
• CloudFoundry, IronFoundry, OpenShift,
Brooklyn Project, Cloudify, etc..

23. DevOps Vs NoOps
 Convenience Vs Flexibility Question
 NoOps Platforms -> More Constraints
 Certain Applications like Marketing Apps
fits well with NoOps Platforms
 DevOps Platforms -> More Control
 Certain Big Data Applications need more
control

24. Vertical PaaS
 Focused on specific verticals like Financial,
Health Care, Media, Gaming, etc..
 Media PaaS: Azure, AWS, Google, Federated
Cloud Platforms
 Vertical PaaS for regulated industry
 Gaming PaaS on federated clouds could offer
high performance gaming based on real time
data

25. Other PaaS
 Visual PaaS -> Force.com,
Orangescape, WorkXpress, etc..
 ALM Services -> CloudMunch, Electric
Cloud, etc..
 IDE Services -> Cloud9, Codeenvy,
Neutron Drive, etc..

26. Beyond PaaS
 PaaS Market  Platform Services
Market
 Mobile Backend as a Service 
Platform Services
 Component Services like Identity,
Social, Real time streaming, etc.. 
Platform Services

27. PaaS  Platform Services
rv ices
Se
latform
P

28. PaaS and Big Data
 Current Generation of PaaS is built
for scaling users
 PaaS v2.0  PaaS for scaling data
a.k.a PaaS for Big Data
 The evolution has started already
but will accelerate in the coming
years

29. PaaS v1.0

30. Internet of things

31. Intelligent Applications

32. Intelligent Platforms (PaaS v2.0)

33. Conclusion
 Enterprise PaaS is real
 Platform Services are still evolving
 We need platforms for the internet of
things
 Platforms for big data
 Next 3-5 years is going to see emergence
of intelligent platforms

34. Connect with me
Work: Principal Analyst, Rishidot Research
and Editor, CloudAve.com
Email: krishnan@krishworld.com
Twitter: @krishnan
Website: www.rishidot.com
Blog: www.cloudave.com/author/krishnan/
Slides: www.slideshare.net/rishidot