Before cloud computing became all the rage, there was a concept made popular in the high-performance computing community called "grid computing." The basic idea was to build a database or application on top of shared IT infrastructure in a way that allowed it to dynamically scale.
If that sounds a lot like cloud computing to you, don't be all that surprised. The folks GridGain, a provider of an application development platform, like to point out that it's only a matter of time before cloud computing catches up to the data management principles that were first created for grid computing environments. In fact, GridGain CEO Nikita Ivanov says it's really only a matter of time before the two concepts merge.
As cloud computing evolves, IT organizations are discovering just how hard it is to make data truly elastic. The ability for data to be elastic is supposed to be one of the primary tenets of cloud computing. But in reality, most existing databases and enterprise applications were never designed to dynamically scale. As IT organizations become more familiar with cloud computing, Ivanov says that cloud and grid computing technologies will have to come together to truly meet the elastic requirements of cloud computing. Right now, Ivanov says that GridGain 3.0 is the only platform that provides both computational and data management capabilities under a common architecture.
We currently live in what might be called "The Stanley Steamer Age" of cloud computing. There are lots of different services, but most of them are not nearly as automated or dynamic as most people think, which results in a lot of manual intervention to crank up the system.
Grid computing, of course, is by no means simple to deploy or master. But as time passes, it's apparent that the next generation of cloud computing is going to be greatly influenced by grid computing practices that are already pretty well established.