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Paradoxical Economics of Enterprises ​

Use of Expensive Software Stacks ​

Mid-to-large scale enterprises typically operate many resource pools, with a range of software stacks and costs, that provide differentiated features and service levels to hosted applications. This results in pools with very different cost structures.

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The Paradox ​

When hardware cost is a fraction of a pool's total cost, right-sizing economics change and become paradoxical, such that:

As hardware's percentage of a pool's total cost decreases, its economic value increases with respect to software, power and space consumption when those costs are inversely correlated to hardware performance or efficiency.

The Counter-Intuitive Effect ​

The higher a pool's cost structure ratio (i.e., Kratio) the more important it is to shape hardware assignment; simply, there are more costs that can be displaced. The Kratio therefore acts as a coefficient to the relative gain in hardware performance when determining its economic value.

For example, a modest 20% gain in hardware performance for a pool with a Kratio of 10.0 is economically equivalent to a 50% gain for a pool with a Kratio of 2.0. The ideal uptake rate of better hardware, as well as its duration of use (i.e., hardware economic-life), will therefore vary over time and from one pool to another.

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Being able to prospectively differentiate economic value among different resource pools and hardware models — from newly available hardware versus existing inventory — is essential information in order to deploy hardware to its highest economic utility over its service life and thereby minimize total cost. Zypr enables this by:

  • Identifying and evaluating the many combinatorial ways by which a pool's resource compositional mix may evolve over time.
  • Distinguishing hardware retirements from inter-pool reassignments and pool recomposition (i.e., distinguishing hardware economic-life versus its service-life).
  • Accomplishing both at the lowest total cost with respect to the unique infrastructure economics of enterprise IT.

Ravello Analytics, LLC