"You can't manage what you don't measure." This is especially true when it comes to energy consumption. In automobiles, miles per gallon (MPG) very clearly identifies fuel efficiency. In the data center environment, there are metrics that can be adopted to measure computational power efficiency in a similar way that MPG measures automotive fuel efficiency. The Green Grid has proposed the use of power usage effectiveness (PUE) and data...
center efficiency (DCE), or data center infrastructure efficiency (DCIE), to measure data center energy efficiency. But concerns about the effectiveness of PUE and DCE as true measures of efficiency highlight the need for a better metric.
PUE is a ratio of the total power a data center facility consumes versus how much of that power is consumed by IT equipment. An average data center should measure 2.0, meaning that only half of all the power consumed is used by non-IT equipment. A data center that measures greater than 2.0 needs to investigate its power inefficiencies. The Environmental Protection Agency recently stated that it will use PUE as an Energy Star rating for data centers. The EPA's endorsement should rapidly expand adoption of PUE.
But a data center manager could "game" the PUE metric by running inefficient servers and other IT equipment to raise the denominator. This is a major problem with using PUE and DCE as a measurements of effectiveness and efficiency. They ignore how efficiently the IT equipment components are being operated.
Therefore, it is necessary that we find a new metric -- one that is similar to the simplicity and elegance of MPG. What is needed is a simple and true measure of server efficiency, just as MPG can be used to compare cars. Watts per logical image (WPLI) is just such a metric.
Watts per logical image
Similar to MPG, WPLI measures performance on a granular, or per-unit, level. By looking at the efficiency of each server, focus can be placed on managing inefficiency, just as MPG identifies the need to replace gas-guzzling SUVs and trucks with light, more fuel-efficient vehicles.
For example, a popular dual quad-core blade server chassis operating at 3,535 W and running a single, preinstalled operating system has a WPLI of 3,535. Yet running 24 -32 virtual machines (3-4 production systems on each core, a realistic performance configuration for a virtual-to-host ratio) on the embedded hypervisor would result in a WPLI of 147 to 110.
Basically, in one scenario there is a server running at 3,535 W, and in the other scenario, the virtual servers run as efficiently as 110 W each. This example shows a power reduction of almost 98% per server.
This is why you need to measure power consumption at the logical image level, and this is why businesses must aggressively migrate to virtualized platforms.
WPLI equals the total individual server power consumption (plus related prorated chassis power requirements) divided by the number of operating system images running on that hardware. A composite WPLI can also be tracked by dividing all the power consumed by a data center's installed servers by the total number of operating system images running in a data center. This, however, only provides an average value and is not granular enough to make informed design decisions. It is a start and helps demonstrate that the IT organization is on the right track and is supporting overall enterprise sustainability activities of the corporation.
With all this information, a data center manager can now target the power-hungry environments and, where appropriate, the applications running on them for virtualization.
The blade and rack enclosure efficiency should also be considered when holistically architecting a more power-efficient data center. Not all racks or blade chassis handle power and cooling as efficiently and should be analyzed, and their placement and performance in the data center modeled and studied.
As we approach 2012, the date which IDC estimates that power costs will equal server capital costs, managing power consumption in the data center will become ever more critical.
By knowing the power consumption of a logical image, chargeback can accurately include the direct power consumption an application uses. This means that IT chargebacks can incorporate rising energy bills and start to increase cost transparency. An easy way to justify migrating to virtualization will be when the lines of business push IT to migrate its power-hungry, traditionally hosted applications to those with lower WPLI.
Using these metrics, data center managers will be able to craft more efficient business cases and financial justifications to help gain approval and accelerate capital acquisition requests.
Very few people purchase cars these days without considering MPG performance. No server purchase should be made without an understanding of the expected watts per logical image that the box will ultimately deliver.
ABOUT THE AUTHOR: Lucian Lipinsky de Orlov is Director of Business Strategy for VIRTERA, an independent IT professional services and consulting firm that delivers virtualization technologies and services to companies across the U.S. VIRTERA's proven vSpectrum consulting method helps clients in the successful and rapid adoption of virtualization and green IT technologies while delivering optimum ROI. For additional information on how to reduce power consumption and costs in a virtual environment, please visit http://www.virteratech.com/index.php/site/solutions_overview.
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