PUE Modeling

The cost of operating a data center is directly related to the cost of power.  New equipment is continuing to offer improvements in performance and space but these assets are requiring more and more operational and cooling power to operate.  This reality, combined with the growing cost of power and the effects on global climate are challenging enterprises to operate with higher efficiency and greater conservation.

Before a company begins the process of getting “greener”, it is paramount that current power consumption rates are measured to accurately establish a benchmark for efficiency.  Metrics like Power Usage Effectiveness (PUE) and Data Center Infrastructure efficiency (DCiE) are often used to measure the efficiency of the data center’s power usage before and after these “green” initiatives have been implemented.  But a better approach to this “change and hope” strategy for improving power efficiency utilizes extensive modeling to assess the impact of these changes on power consumption, cooling and space before the change is made, not after the fact.

In order to see significant improvements in the PUE value you may need to physically move hardware to optimize space, power, and cooling characteristics.  You can make changes and hope, or you can use a Data Center Infrastructure Management (DCIM) solution like nlyte to model these changes and measure the effect on PUE before starting the process.  Without modeling, you are only guessing that the changes you are spending expensive man-hours implementing will reduce the PUE value for your data center.

After modeling these moves in nlyte, you will know exactly if the changes have helped or hurt your PUE value.  After you have optimized asset placement for maximum cooling and power utilization, nlyte will help facilitate the physical move by coordinating resources, recognizing dependencies and enforcing best practices through its built-in workflow.

Using PUE to measure the effectiveness of data center power usage in terms of the computing power it contains, allows you to see how optimizing space, power and cooling can save money while reducing your carbon footprint.  Using the nlyte DCIM solution further extends these savings by modeling these changes virtually to measure their effect on PUE.  Simply a better way to a lower PUE!