Originating Author: Dave Vellante
The idea behind blade computing is a good one. Strip out, share and dramatically reduce the number of components like power, cooling, consoles and the like and squeeze more costs out of distributed computing. If every application workload fit well into blade environments, there would be no other computing approach.
Unfortunately that's not the case. Blade servers are perfect for applications that are parallelizable but more complex workloads with higher transaction and update activity are often not well-suited for blade architectures. The point is blade computing works best when organizations apply a 'one-size-fits-all' strategy, meaning all the blades in the chassis are as similar as possible and ideally identical (and of course from the same vendor). This makes blades more swappable, easier to manage, simpler to back up and cheaper to acquire and inventory spares. Greater diversity within a chassis defeats many of the benefits of blade computing.
Buyers must become more aware of the drawbacks of succumbing to the allure of blade computing without fully understanding its marginal costs and marginal benefits. Specifically, despite strong marketing pushes by blade vendors into small and medium sized businesses, these organizations often don't have the scale to exploit the economics of blade servers. Often, the marginal costs of chassis and the drawbacks of sole-sourcing outweigh the incremental benefits. Frequently, smaller customers find that the lack of critical mass in blade-friendly applications means they'd be better off buying traditional collocated servers and preserving their freedom to shop for the best server deal.
Action Item: IT must cut through the hype of blade computing and intelligently set expectations based on assessing the degree to which the critical mass of blade-friendly workloads can drive commonality and reduce costs. SMB customers will often not have this luxury and while larger customers can more easily scale, they must design commonality into blade computing infrastructures creating pods of simlar if not identical blade groups to support applications.
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