Excess capacity in a computing environment is as bad as excess inventory in the manufacturing world. When architecting OneView360° from a clean sheet of paper, we implemented a grid-based computing approach that enables capacity on demand. Rather than a traditional mainframe approach, we have created a cluster of small servers that are consolidated to form the data processing grid - a high-performance and scalable architecture.

We provide the flexibility to enable just-in-time computing throughput, which allows you to optimize your assets, reducing IT overhead and enabling you to manage variable demand. This solves two difficult challenges: data management and capacity. Our approach to dynamic data management was built to run on a grid from the outset.

Aside from the benefit of empowering capacity on demand so your environment grows as your business does, one of the largest benefits to this approach is cost savings. A grid-based computing environment can be as a little as 50% of the cost or less of a similar mainframe environment. The savings can and likely will run into the millions of dollars when processing, managing and storing large amounts of data. Further, it is likely that this environment will allow your organization to save on software costs, as you shift from mainframe deployments to the smaller processors found in our grid-computing model.

This solution was built to run on low-cost, high-volume processor-based servers, and Linux has provided a cost-effective and enterprise-ready operating system for OneView360°. This grid implementation applies to all tiers (servers, applications, integration) and is based on open standards.

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