Data Center Metrics - "It's The Economy, Stupid"

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Any article you read about data centers talks about some shade of "green," which, for the most part, is really just speak for "economy." Much like in economics, data center metrics are the language that describes the overall life cycle, health, as well as the day-to-day operations across all tiers - Facilities, IT, and Applications. Without metrics there is simply no way to communicate the essence of what a data center is, how it behaves, or how it is expected to behave.

Much like an economy, the complexities and interdependencies of the constantly moving and ever-shifting parts of the data center require persistent monitoring and tweaking just to keep it up and running. There are plenty of metrics out there to describe the economy of the data center, both macro and micro - all of them orthogonal views. There are many must reads. Two examples of the more well known ones are: Four Metrics Define Data Center “Greenness” from the Uptime Institute and PROXY PROPOSALS FOR MEASURING DATA CENTER PRODUCTIVITY from Green Grid.

Understanding all of the mechanics and motivations for these data center metrics can be a daunting task.

The metrics that describe an economy are probably some of the most successful in terms of familiarity. Why is that? Retail sales reports, unemployment figures, and GDP report on durable goods, inflation, etc.  One thing they all have in common is that they are presented relative to the previous measurement. Up is good, down is bad, or vice-versa depending on context. Simple. Looking at the actual value only means something to one with expertise in that area.

Systems that monitor, collect, and store the data that may be used to calculate metrics in the data center must help to present things in this light as well. Not only do they need to provide the data used in these constantly evolving orthogonal views that make up the data center economy, but they must also present these views to those who are not domain experts in terms of "up is good, down is bad." If we are to succeed in understanding the economy, we must make the economy understandable.

Michael Anthony