Dissecting The PaaS Landscape

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These are slides from the webinar Rishidot Research organized on March 25th 2013.

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Dissecting The PaaS Landscape

  1. 1. Dissecting The PaaS Landscape Rishidot Research Webinar
  2. 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. 3. Plan For The Talk Defining PaaS PaaS Ecosystem and Spectrum PaaS Differentiation PaaS and Big Data Conclusion
  4. 4. SPI Model
  5. 5. PaaS DefinitionPaaS is defined as an elastic on-demand platform for applicationsthat completely abstracts away theunderlying infrastructure with theapplication scaling seamlessly withthe platform.
  6. 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. 7. What is PaaS and What is NotPaaS definition has broadened butcertain characteristics hasn’t changedApplication scales with the platformthat offers “infinite” scalabilityNo human interventionNo hardware in the discussion
  8. 8. What is PaaS and What is NotApplication Scales With Legacy Applications onPlatform Elastic Infrastructure
  9. 9. Is PaaS Middleware for Cloud?
  10. 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. 11. Why PaaS?Organizations:  Platform for services world  Reduced and efficient operations  Cost effective IT  Agility
  12. 12. PaaS Evolution From Hosted to Private From Proprietary to Open Source From Startups to Enterprise
  13. 13. PaaS Ecosystem
  14. 14. PaaS Ecosystem
  15. 15. PaaS SpectrumHosted Private DevOps DevOps Infrastructure PaaS PaaS PaaS Tools ServicesAbstraction Control
  16. 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. 17. Hosted PaaS Vs Private PaaSHosted: • 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. 18. Hosted PaaS Vs Private PaaSPrivate 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. 19. Best Of Breed Vs PolyglotBest 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. 20. Best Of Breed Vs PolyglotPolyglot: • 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. 21. Proprietary Vs Open SourceProprietary 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. 22. Proprietary Vs Open SourceOpen 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. 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. 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. 25. Other PaaS Visual PaaS -> Force.com, Orangescape, WorkXpress, etc.. ALM Services -> CloudMunch, Electric Cloud, etc.. IDE Services -> Cloud9, Codeenvy, Neutron Drive, etc..
  26. 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. 27. PaaS  Platform Services rv ices Se latform P
  28. 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. 29. PaaS v1.0
  30. 30. Internet of things
  31. 31. Intelligent Applications
  32. 32. Intelligent Platforms (PaaS v2.0)
  33. 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. 34. Connect with meWork: Principal Analyst, Rishidot Researchand Editor, CloudAve.comEmail: krishnan@krishworld.comTwitter: @krishnanWebsite: www.rishidot.comBlog: www.cloudave.com/author/krishnan/Slides: www.slideshare.net/rishidot

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