As Opsware Inc.—formerly Loudcloud Inc.—continues its transition from services company to software vendor, it is looking to stake a claim in the utility computing gold rush.
The Sunnyvale, Calif., company now offers server provisioning and change management software for data centers just two years after selling off its services business to Electronic Data Systems Corp., still its largest customer.
Founder Marc Andreessen recently spoke with eWEEK Senior Editor Paula Musich about the utility computing race and where most IT shops stand in automation.
How would you characterize data centers today and rate the level of automation theyve achieved?
Chaotic and out of control with very little automation. A lot of what were talking about dovetails with the history of computing over the last 30 years. In 1950, there were five mainframes in the world. By the mid-70s, there were a few hundred thousand servers. In the modern world, there are 28 million servers. You have this incredible proliferation. Most companies have been through their own version of that in the last 10 years. Even large companies that had a few hundred servers now have tens of thousands.
Companies know they are out of control. A new security hole opens up, and large organizations have 20,000 servers to be patched by hand. How do you get your arms around what you have, much less what you need to do? People are spending 70 to 80 percent of their budgets just maintaining what they have, which holds back spending on new applications.
In the promise of utility or autonomic computing, how far away from achieving that are most data centers? Is it more talk than substance?
I think autonomic computing is nonsense—mumbo jumbo hype pushed primarily by IBM. It means computers become artificially intelligent when they take care of themselves. And we are so far from that. Maybe 30 or 100 years from now when computers are smarter than we are, thatll happen.
The trends in the industry have been heading in the other direction. [Computers] are getting much harder to deal with. Its not like theyre about to start taking care of themselves. We focus on the pragmatic side. Starting from chaos, how do you organize, systematize—how do you try to build up to get as much automation as you possibly can? Where you still have human beings involved, you want a very small number of very smart architects. And then you want to have as much of the manual labor automated as possible. We think thats the practical point that delivers what people want, which is lower prices, faster rates of change and much higher quality levels.
What has to happen for users to get off the utility computing sidelines?
Theyll be waiting for autonomic computing for years. With utility computing, when youre fully automated, you can start to work in that model. I think most people are starting to approach this more pragmatically. They are saying, I have to deal with this patch problem today, or I have to deal with the fact that 70 or 80 percent of my budget is going towards maintenance and not towards new development, or My quality levels are unacceptable because every time I do a code push, everything crashes and I spend the next three days recovering.
Most everyone realizes they have some of these problems today, and even if they dont, theyll run into them in a year or two because you cant keep growing without fundamentally taking control of the situation.
Do you think the competing initiatives—on demand, Adaptive Enterprise, N1 etc.—are confusing enterprise IT shops?
Not the smart ones. Thats mostly marketing hype, which people understand. People are rolling out a lot of Linux and a lot of Microsoft [Corp.], Intel [Corp.] and AMD [Advanced Micro Devices Inc.] servers. They are rolling out a lot of Java and .Net. They are setting up new Web sites and dealing with a lot of patches. Our preference is to sidestep all the marketing hype and say if you want to pursue that, thats great. But there are real, actual problems you can bite off today.
As enterprises begin to adopt some level of utility computing, what measures should be used to gauge the success or failure of those projects?
Hard dollar measures. Real things like ratio of administrators to machines. If you dont have an operating model where youre running 80 or 100 machines to each person, youre inefficient. Most people are running at about 1 to 15 or 1 to 20.
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