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.
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
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
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
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
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
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