Update: Updated link to Hoff's terminology map and related image to his latest version.
I was privileged to be a part of the Enterprise Cloud Summit that took place at the beginning of Interop in Las Vegas a few weeks ago. The program was excellent, with an all-star list of cloud experts and a surprisingly large number of attendees who were new to cloud computing and trying to get a sense of what it was all about.
What was different from prior cloud-related conferences, however, at least for me, were the types of questions this inquisitive audience was asking. Almost nobody asked around defining cloud computing, but many took advantage of the show to ask panelists and speakers to describe how they could put the cloud to use in their own businesses.
The cloud conversation is moving from "what is it?" to "how would I use it for my business or institution?"
I find this very exciting--and, quite frankly, very refreshing. The amount of energy spent on presenting and defending terminology and taxonomy has become a huge time-sink for those trying to advance the cloud discussion. It's not that I mind walking people through the differences between cloud computing and virtualization, but I'd rather focus my efforts on business cases and customer success stories (or even failures).
It's not that the industry has arrived at a common cloud definition--though the NIST definition has some legs, and I'm a huge fan of Chris Hoff's terminology map (pictured here). Rather, the market seems to have come to the conclusion that cloud computing has a lot in common with obscenity--you may not be able to define it, but you'll know it when you see it.
Perhaps the most beneficial aspect of this shift is the fact that we should start seeing some real business cases, use cases, and best-practice discussions appear in the cloud-computing discussion.
Best Buy running on Google App Engine; stories about impressive gains by the venerable New York Times and Animoto when they used Amazon Web Services; and Eli Lilly's tale of redefining research projects: all these serve as examples of cloud's value in the right contexts. We know from these examples that "batch jobs" are great cloud fodder (such as grid computing and image processing), as are applications with unpredictable scale.
We need to see more such examples publicized, however. Where are the financials with their complex models and data mining? Biotech with its constant data processing demand? Manufacturing with its "just in time" supply chain management?
Perhaps the examples will continue to be more of the same, but that's OK to me. Then we know where cloud's strengths and weaknesses are, and we can move the conversation forward from there.