Power, Productivity and the Internet: Part 2 – All hands on deck

In part one, Power, Productivity and the Internet: Part 1 – The core of the problem, we looked at the issues inefficiencies of energy consumption in data centers here we look at what to do to address them.

A data center exists to support the data processing within it.  Data centers are rarely static and unchanging.  Data centers are seldom homogeneous in applications and data within them, or in the type and vintage of data processing equipment they contain.  As the business goes about its duty serving customers and earning money month after month, year after year, much changes in the server estate.  Servers are introduced to host new applications.  Servers are periodically swapped out with newer models.  Application configurations change, which also drive changes in server configurations.  Virtualization is applied to improve hardware utilization, but self-service provisioning and lack of good governance contributes to virtual sprawl.  As this transpires, it’s impossible to track what each of these servers are really doing, and especially to what extent these servers are delivering value to the business.

The result is that, at any point in time, we have a lot of investment in servers, some of which are very productive and returning value to the business, others somewhat productive, and some still that are not at all productive.  We’d like to know how we can best use the resources that are returning value to the business (those productively used), and especially to remove the resources that are costing energy and money but returning no value at all to the business.  As time goes on, a data center accumulates waste, and waste unnecessarily consumes energy.

Traditional methods of identifying server waste leave much on the table

Traditional methods of identifying server waste are based upon utilization measurements.  If the server’s CPU utilization is showing activity, then it’s probably doing something.  ‘Isn’t it?  Well, it may be doing something, but how do we know it is productive activity?

This is a problem recognized by data center managers across the industry.  In a recent survey commissioned by 1E, it was discovered that 83% of data center managers want a better view of server utilization though most still rely on simple CPU utilization as their primary metric.  Sixty five percent of those admit to migrating unused physical servers to virtual instances, thus simply propagating waste.

The simple fact is that utilization-based approaches simply do not lend the fidelity of information necessary to effectively minimize waste and to offer energy management at the server level.

Zeroing in on server waste

1E’s “Useful Work” technology is truly unique in its ability to provide clarity of data processing executing on the server.  With this Useful Work technology, each process is classified as either Useful or non-Useful.  This data is accumulated to provide a view of exactly where productive data processing is occurring over the server estate, when, and to what extent.  This provides an unparalleled opportunity to eliminate comatose servers or maximize consolidation, which directly translates into reduced data center energy consumption.

On another level, if the data processing is ultimately driving the power drawn by the server, and if we know that certain data processing is productive and useful to the Business while others is background activity (or non-useful to the Business), then what if we could reduce the power drawn by the server during non-useful activity, and restore it to normal for the productive and useful times?  This is an extension of the useful work technology and a feature that enables active power management of the server such that server power consumption is reduced when doing only non-useful work, and restored when doing useful data processing.  This is different than powering down a server overnight (after all, what business is not 24×7 these days?).  This is actively modulating power drawn based upon knowledge of the value of the data processing, with a view from inside the server itself.  This capability helped 1E win “Green IT Product of the Year” in 2011.




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