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PUE Reconsidered - AFCOM (MI), July 2009
 

PUE Reconsidered - AFCOM (MI), July 2009

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An exploration of the benefits and limitations of the popular Power Usage Effectiveness (PUE) metric, for gauging datacenter efficiency. ...

An exploration of the benefits and limitations of the popular Power Usage Effectiveness (PUE) metric, for gauging datacenter efficiency.

How to avoid the pitfalls inherent in the definition of PUE; and some suggested means by which the PUE concept can be enhanced in real-world applications.

CORPORATE PLUG: For more information about how Raritan helps solve this problem, I encourage you to see: http://www.raritan.com/resources/screenshots/power-iq/

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  • Market problems, landscape, trends, growth Power cost issue (and associated cooling issues) Data center growth chart Power cost growth chart Power cost vs. Industry chart Solution portfolio Yes, it costs more, BUT there is VALUE It’s not just about the bits and features Outlet metering, so what? Enter PowerIQ Distinctive product solutions The story resonates Today (“my a lot has changed since we last met”) PX single phase, 3 phase PM series RPC Power IQ Roadmap PX no switching High power for blades Inline meters High density BTO/ETO (show building blocks) Integration with 3 rd parties Key learnings Target customer Facilities vs. data center ops vs. IT Where we are currently at wrt product lifecycle and what that means Example deal, show PO from RA with strips, PIQ, sensors Great Opportunity of legacy customer base and new customer Show growth chart 2 instances at AFCOM, MCA Greater opportunity from new customers JPMC, AVCT shop still opportunity for power Cite all the data center build-out examples going on Gives you new beach-head for KVM Easier door opener b/c people want to talk about it.  It is the issue of the day. What next? Learn Leverage, We’ve got resources, don’t let stone unturned, I’ll get on a plane. Sell more power
  • Market problems, landscape, trends, growth Power cost issue (and associated cooling issues) Data center growth chart Power cost growth chart Power cost vs. Industry chart Solution portfolio Yes, it costs more, BUT there is VALUE It’s not just about the bits and features Outlet metering, so what? Enter PowerIQ Distinctive product solutions The story resonates Today (“my a lot has changed since we last met”) PX single phase, 3 phase PM series RPC Power IQ Roadmap PX no switching High power for blades Inline meters High density BTO/ETO (show building blocks) Integration with 3 rd parties Key learnings Target customer Facilities vs. data center ops vs. IT Where we are currently at wrt product lifecycle and what that means Example deal, show PO from RA with strips, PIQ, sensors Great Opportunity of legacy customer base and new customer Show growth chart 2 instances at AFCOM, MCA Greater opportunity from new customers JPMC, AVCT shop still opportunity for power Cite all the data center build-out examples going on Gives you new beach-head for KVM Easier door opener b/c people want to talk about it.  It is the issue of the day. What next? Learn Leverage, We’ve got resources, don’t let stone unturned, I’ll get on a plane. Sell more power

PUE Reconsidered - AFCOM (MI), July 2009 PUE Reconsidered - AFCOM (MI), July 2009 Presentation Transcript

  • PUE Reconsidered Utility + Limitations of PUE / DCiE as a Datacenter Efficiency Metric 29 July 2009
  • PUE Reconsidered
    • Historical Basis for PUE – what is the problem?
    • Strengths of PUE Metric – what does it measure?
    • Weaknesses of PUE Metric – what does it omit?
    • Bottom Line: How to be Strategic About Datacenter Efficiency
    Utility + Limitations of PUE / DCiE as a Datacenter Efficiency Metric Henry Hsu • Raritan, Inc. Solutions Consulting, Datacenter Efficiency Henry.Hsu@raritan.com • (732) 764-8886 x1273
  • Open Secret: Datacenter electrical costs are skyrocketing… $ B I L L I O N S M I L L I O N S O F S E R V E R S
  • … fueled by an explosion in power / heat densities
  • Industry groups + vendors propose a wide range of solutions IT equipment Cooling & moving air
    • virtualization
    • power save mode
    • consolidation
    • upgrade technology
    • decommission servers
    • move apps/jobs to virtualized servers and shut down servers
    • batch processing during off-peak
    • avoid overcooling
    • minimize humidification
    • reduce air mixing via hot/cold air separation
    • blanking plates to minimize recirculation
    • raised floor grommets to reduce bypass airflow
    • optimize floor layout (CFD)
    • closely couple supply and returns to the load
  • But first, we need to understand the problem… Source: EYP Mission Critical Facilities Inc., New York Typical Real-World Energy Allocation in Today’s Datacenter
  • … so The Green Grid proposed PUE as a benchmark in Feb’07 “ Green Grid Data Center Power Efficiency Metrics: PUE and DCiE”; by Christian Belady, et. al.; www.thegreengrid.org PUE = Power Usage Effectiveness = Total Facility Power IT Equipment Power DCiE is the exact same thing , but expressed as an inverse: DCiE = Datacenter Infrastructure Efficiency Total Facility Power IT Equipment Power = 1 PUE =
  • PUE is extremely valuable as a broad efficiency ratio… PUE = Power Usage Effectiveness = Total Facility Power IT Equipment Power PUE = 1 MW 0.5 MW = 2.0 “ My total facility consumes 2x the power of the IT equipment load.” DCiE = PUE 1 = 0.5 “ Roughly 50% of the power in my facility is used to power IT equipment.” EXAMPLE: Typical 1MW Facility
  • … and has become a de facto standard metric
    • Dueling Press Releases (e.g. Google and Microsoft)
    • EPA Datacenter “Energy Star” Program
    • Department of Energy (DOE) “DCPro” Tool and Survey
    Sun Microsystems Microsoft Google
  • It’s critical to understand what PUE is, and what it is not !
    • A relative measure of your plant versus your IT equipment
    PUE = 1 MW 0.5 MW = 2.0
    • Resilience : Tier I / II / III / IV architecture?
    • Trending: How does my efficiency change as IT load changes?
    • Diversity : Heterogeneous versus homogenous IT load?
    • Utility : Are the servers themselves being used well?
    Does not (in and of itself) address: In short, it does not benchmark the efficiency of the IT component.
  • Example: Henry’s Super Awesome Datacenter TM (SAD)
    • 1000 servers
    • Equipment from every AFCOM sponsor ever
    • Located in Reykjavik, Iceland (max temp = 55)
    • Placed outdoors under a tented roof
    • 24/7/365 operation
    • Servers completely underutilized
    • No critical resilience whatsoever
    • No business value or practicality
    • Real-world evaluation = complete waste of energy
    PERFECT PUE OF 1.0 !! Every kilowatt is used to power servers. No energy “wasted”.
    • All servers dedicated full-time to HenryAndHisCat.com (Video site featuring footage of me playing with my cat.)
  • None of the proposed IT initiatives (on left, below) improve PUE PUE = Power Usage Effectiveness = Total Facility Power IT Equipment Power IT equipment Cooling & moving air
    • virtualization
    • power save mode
    • consolidation
    • upgrade technology
    • decommission servers
      • extra savings on cooling
    • move apps/jobs to virtualized servers and shut down servers
    • batch processing during off-peak
    • avoid overcooling
    • minimize humidification
    • reduce air mixing via hot/cold air separation
    • blanking plates to minimize recirculation
    • raised floor grommets to reduce bypass airflow
    • optimize floor layout (CFD)
    • closely couple supply and returns to the load
  • Green Grid recognizes that PUE is not a panacea Proposed: In the long-term, create a business-oriented metric Proposed : Three “levels” of PUE sophistication DCP = Datacenter Productivity = “ Useful Work” Total Facility Power
  • To solve the real problem, we need to measure it… Uptime Institute, “4 Metrics That Define Data Center Greenness”
  • … including environmental information Source: ASHRAE, “Thermal Guidelines for Data Processing Environments”
  • Real-world user examples where better info = energy savings
    • World’s Largest Networking Company
        • Goal: reduce 25% carbon emissions by 2012
        • Problem: test labs account for more than 80% of corporate energy consumption
        • Solution: automate shutdown of test equipment when not in use; provide detailed, comprehensive energy savings data for all labs in enterprise.
    • Largest European Bank
        • Goal: quantify exact power costs for each business application in datacenters
        • Problem: no reliable, real-time energy data exists for individual servers
        • Solution: rack PDU’s that provide detailed power + environmental data for each receptacle in the cabinet.
    • World’s Largest Software Company
        • Goal: Provide state-of-the-art data center for customers to perform live integration testing of application suites.
        • Problem: Need to reboot servers remotely; and understand real-time power consumption of each customer’s test configurations
        • Solution: high-security rack PDU’s with remote switching and energy metering.
  • Gather data beyond PUE to enable tangible efficiency actions
    • Important Solution Attributes:
    • Open standards / vendor agnostic
    • Trended information over time
    • Energy data (kwh), not just current (amps)
    • Energy data per IT device (not just for rack)
    • Product configs to fit all rack densities
    • Make sure facilities is happy (UL489)
    • Use what you have!
  • Gather data beyond PUE to enable tangible efficiency actions
    • Important Solution Attributes:
    • Open standards / vendor agnostic
    • Trended information over time
    • Energy data (kwh), not just current (amps)
    • Energy data per IT device (not just for rack)
    • Product configs to fit all rack densities
    • Make sure facilities is happy (UL489)
    • Use what you have!
  • Summary
    • PUE is valuable (and widespread) as a high-level metric
    • You must understand the pros / cons of PUE to properly evaluate industry, vendor, and press claims
    • PUE is not sufficient to improve efficiency tactically
    • Datacenters can only be optimized when the energy chain is fully understood / instrumented:
        • the appropriate measurements;
        • at a sufficient level of detail;
        • trended over time;
        • easily interpreted;
        • at incremental CapEx cost;
  • Questions / Comments / Discussion
  • Thank You! Henry Hsu • Raritan, Inc. Solutions Consulting, Datacenter Efficiency Henry.Hsu@raritan.com • (732) 764-8886 x1273