PaaS on OpenStack - Run Applications on Any Cloud, Any Time Using Any Thing

Yesterday, I had a session during the OpenStack Summit where I tried to present a more general view on how we should be thinking about PaaS in the context of OpenStack.

The key takeaway :

The main goal of PaaS is to drive productivity into the process by which we can deliver new applications.

Most of the existing PaaS solutions take a fairly extreme approach with their abstraction of the underlying infrastructure and therefore fit a fairly small number of extremely simple applications and thus miss the real promise of PaaS.

Amazon's Elastic Beanstalk took a more bottom up approach giving us better set of tradeoffs between the abstraction and control which makes it more broadly applicable to a larger set of applications.

The fact that OpenStack is opensource allows us to think differently on the things we can do at the platform layer. We can create a tighter integration between the PaaS and IaaS layers and thus come up with better set of tradeoffs into the way we drive productivity without giving up control. Specifically that means that:

• Anyone should be able to:
  • Build their own PaaS in a snap
  • Run on any cloud (public/private)
  • Gain multi-tenancy, elasticity… Without code changes.
• Provide a significantly higher degree of control without adding substantial complexity over our:
  • Language choice
  • Operating System
  • Middleware stack
• Should come pre-integrated with a popular stack:
  • Spring,Tomcat, DevOps, NoSQL, Hadoop...
  • Designed to run the most demanding mission-critical app

You can read the full story and see the demo here

Productivity vs. Control tradeoffs in PaaS

Gartner published recently an interesting paper: Productivity vs. Control: Cloud Application Platforms Must Split to Win. (The paper requires registration.)

The paper does a pretty good job covering the evolution that is taking place in the PaaS market toward a more open platform and compares between the two main categories: aPaaS (essentially a PaaS running as a service) and CEAP (Cloud Enabled Application Platform) which is the  *P* out of PaaS that gives you the platform to build your own PaaS in private or public cloud.

While I was reading through the paper I felt that something continued to bother me with this definition, even though I tend to agree with the overall observation. If I follow the logic of this paper than I have to give away productivity to gain control, hmm…  that’s a hard choice.

The issue seem to be with the way we define productivity. Read the full detailes here

Designing applications for cloud deployment

During the last two years, I was involved in several projects deployed on the Amazon cloud. Being a relatively early adopter was a fantastic experience that provided lots of opportunities to burn my fingers and learn from mistakes. It also seriously challenged my view of scalable software architectures. I spoke about key lessons learned at CloudCamp London last week – here is the summary of that presentation.

http://gojko.net/2010/01/25/designing-applications-for-cloud-deployment/

Big Data on Grids or on Clouds?

 Contributed by Wolfgang Gentzsch:

Now that we have a new computing paradigm, Cloud Computing, how can Clouds help our data? Replace our internal data vaults as we hoped Grids would? Are Grids dead now that we have Clouds? Despite all the promising developments in the Grid and Cloud computing space, and the avalanche of publications and talks on this subject, many people still seem to be confused about internal data and compute resources, versus Grids versus Clouds, and they are hesitant to take the next step. I think there are a number of issues driving this uncertainty.

read more at: BigDataMatters.com