October 2, 2007
Big Long Term Impact of Virtualiztion
Analysis: In the short term there is the low handing fruit. Server consolidation and better schemes for load balancing and disaster recovery planning are some problems that this technology addresses. The implications for providers are that businesses will probably buy fewer, but larger servers. Maybe a few less operating systems licenses, but more virtualization software. Virtualization on the desktop will mean less PCs but more network devices (Wyse, Neoware…).
A lot of this is being made possible by the nearly omnipresent network. As long as you have an input/output device (terminal, laptop, cell-phone…) it does not matter how or where the content is coming from. So, network infrastructure providers and telecommunications carriers will benefit from virtualization.
Most importantly, once the network and virtualization technologies become more mature and more robust, an even greater impact will be realized. Since processing power (i.e. servers) can be recreated when needed, this will become a commodity. Imagine a mainframe-like computer that virtualizes a 1,000 windows servers. Let’s take a particular business that has applications for 200 servers that are needed from 7am-9pm Monday through Friday, and only need 35 servers overnight and on weekends. This business would rent those virtualized servers only for the time they are needed.
In this scenario, large computer manufacturers like IBM and HP would be selling a lot more big and expensive machines, along with maintenance and services. Data center operators like EDS and CSC would be providing these virtualized servers to the business users on a pay as you go basis.
Its kind-of funny how this looks like the old “time-sharing” model of the early days of computing. A significant portion of this equation that still needs a solution is the data storage piece because your servers are no longer pieces of hardware, but software and information saved on storage devices and they do not look any different that your real data. There is a lot of new innovation coming in that area as well and by the time we figure that out the model will change even more.
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