PaaSing Comments – Data and PaaS

I’ve been looking at the PaaS space for some time now.  I spent some time with the good folks at CloudBees (naturally), and have had many conversations on CloudFoundry, Azure, and more with vendors, customers and other cloudy folks.

Krishnan posted a very good article over on CloudAve, and at one level I fully agree that PaaS will be come more of a data-centric (vs. code-centric) animal over the next few years.  To some degree that’s generally true of all areas of IT – data, intelligence and action from data, etc.  But there is a lot more to this.

Most PaaS frameworks have very few actual services – other than code logic containers, maybe one messaging framework, and some data services (structured and unstructured persistence and query).  You get some scale out, load balancing, and rudimentary IAM and operations services.  Over time as the enterprise PaaS market really starts to take off, we may find that these solutions are sorely lacking.

In the data and analytics space alone there are many types of services that PaaS frameworks could benefit from:  data capture, transformation, persistence (have), integration, analytics and intelligence.  But this is too one-dimensional.  Is it batch or realtime, or high-frequency/low-latency?  What is the volume of data, how does it arrive and in what format? What is the use-case of the data services?  Is it structured or unstructured? Realtime optimization of an individual users’ e-commerce experience or month-end financial reporting and trend analysis?

Many enterprises have multiple needs and different technologies to service them.  Many applications have the same – multiple data and analytical topologies and requirements.  Today’s complex applications are really compositions of multiple workload models, each with its own set of needs.  You can’t build a trading system with just one type of workload model assumption.  You need multiple.

A truly useful PaaS environment is going to need a “specialty engine” app store model that enables developers to mix and match and assemble these services without needing to break out of the core PaaS programming model. They need to be seamlessly integrated into a core services data model so the interfaces are consumed in a consistent manner and behave predictably.

Data-centricity is one of the anchor points.  But so is integration.  And messaging.  And security in all it’s richness and diversity of need.

This gets back to the question of scale.  Salesforce has the lead, but they also have a very limiting computational model which will keep them out of the more challenging applications.  Microsoft is making strides with Azure, and Amazon continues to add components but in a not-very-integrated way.  But will a lot of other companies be able to compete?  Will enterprises be able to build and operate such complex solutions (they already do, but…)?

This is a great opportunity and challenge, and I have great expectations that we will be seeing some exciting innovations in the PaaS market this year.

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