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How Composable Infrastructure Addresses IT’s Problem of Space and Time

Published November 6th, 2020. In this free Technical Insight report, Sr. Analyst Eric Slack provides a comparison of PCIe fabric and blade-server composable architectures. Download this free report now!

A Comparison of PCIe Fabric and Blade-Server Composable Architectures

IT infrastructure plays a critical role in a company’s success, and ultimately its survival, by enabling an enterprise to develop applications in the timeframe required to deliver what the market wants — before the competition does. To accomplish this, enterprise IT must solve a problem of space and time, where space is defined as infrastructure capacity and time as compute cycles. IT organizations have finite amounts of both resources and must maximize their use in order to assure they can deliver the compute environment the company needs when called upon.

Composable Infrastructure is designed to address this optimization problem by enabling valuable resources to be deployed through software in just the right amounts and with a minimum of time between jobs or workloads. This report will examine two architectural options for composable infrastructure — one created within a blade server chassis and the other across a PCIe fabric — and compare how each address IT’s fundamental problem.

Space and Time

In an idealized scenario, the IT resources required to support an enterprise’s applications would be deployed in exactly the right amount, at exactly the right time, and then redeployed to another application when no longer needed, with the same level of precision.

The total capacity (the space component) of the company’s IT estate would be fully utilized, and those resources would never be idle (the time component), due to set up, configuration changes, or expansion. While this scenario is never realized, its pursuit is more than just a goal.  In a world where the high-performance resources that drive innovation are always in short supply, and the next breakthrough can never come too soon, solving the space and time problem is essential.

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