Metering Energy Consumption in Data Centres - Michael Rudgyard
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Metering Energy Consumption in Data Centres - Michael Rudgyard

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    Metering Energy Consumption in Data Centres - Michael Rudgyard Metering Energy Consumption in Data Centres - Michael Rudgyard Presentation Transcript

    • Energy Usage Optimisation in the Data Centre Michael Rudgyard (CTO) Concurrent Thinking LtdCommercial in Confidence
    • • A spin-out company of a well-established UK SI • Technology was developed for High Performance Computing – Management of HPC resources needs to be ‘system-wide’ – Scalability (of both the architecture and the GUI) is paramount • New company formed in March 2010 – Took on the product IP and existing HPC customer base – Notable investment from the UK Carbon Trust • Currently in ‘semi-stealth’ mode; product launch: Nov 2011 – Have developed new features for the Data Centre market – … that leverage the infrastructure of an existing productCommercial in Confidence
    • • The average data centre has a PUE of 1.9 (Kooney, 2010) • The majority of DCs operate at temperatures at >3-4oC below (old) ASHRAE recommendations (Paterson et al, 2009) • A 1oC increase in DC temperature equates to 2-4% reduction in energy costs (UK financial institution) • In a typical DC, 10% of running servers are not in use at all (Green Grid Survey, 2010) • Average IT utilisation is between 5 & 10% for an un-virtualised DC, rising to 10 & 20% for a fully virtualised DCCommercial in Confidence
    • • Traditionally, the focus has been to optimise PUE – For a 2MWatt DC with a PUE of 2, this would imply a maximum energy saving of 50% (1MWatt) • But what if (average) IT utilisation was only 10% ? – We could theoretically save 900Kwatt of power for IT – We could theoretically optimise the cooling overhead to zero • In this fully optimised DC, we would use only 100KWatts • An energy saving of 95 %Commercial in Confidence
    • • Assume a modern (dual socket,12 core) server is 6x faster than a 3 year- old dual socket, dual core server • Assume it draws the same energy • We would require 16% of the number of servers to deliver the same IT load: ie. 16kWatts • We have saved >99% of our energy bill – (and have potentially re-claimed 84% of the DC floor space !) • ‘Sweating’ the assets may not be so smart after all !Commercial in Confidence
    • • A: It is part of the answer • Typically human behaviour is: – A customer replaces a 3 year old (then state-of-the-art) server with a new state-of-the-art server – He puts 12 VMs on his new (6x faster) 12-core server rather than the single OS instance on his old 4-core server – His IT efficiency goes from 10% to 20% • This demonstrates the need to accurately spec new equipment based on real application and user requirements • This is also driving a new market for more, less power-hungry, less powerful servers in the DCCommercial in Confidence
    • • With few exceptions, the most successful methodology for improving energy conservation across all sectors is: – Step 1: Identify who/what is responsible for significant energy waste – Step 2: Drive behaviour to ‘encourage’ change • What is the implication for the Data Centre ? • We need to monitor and report IT Usage Effectiveness metrics by customer, department or end-user – Who or what applications/service are the worst offenders ? – Management can use data to drive better practice (charge-back ?) – Help guide virtualisation strategyCommercial in Confidence
    • • The potential for savings comes from multiple sources Start with a PUE of 2 IT Equipment Cooling and power overheadCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) Perhaps reduce PUE from 2.0 to 1.8 ? IT Equipment Cooling and Power Overhead SavingCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) – Identification of unused, under-used, inefficient or over-spec’ed IT equipment Perhaps 5 % of servers ? IT Equipment Cooling and Power Overhead SavingCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) – Identification of unused, under-used, inefficient or over-spec’ed IT equipment – Using active power management during low utilisation periods – Identification of poor equipment usage (ITUE) by end-users Say 10% improvement ? IT Equipment Cooling and Power Overhead SavingCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) – Identification of unused, under-used, inefficient or over-spec’ed IT equipment – Using active power management during low utilisation periods – Identification of poor equipment usage (ITUE) by end-users – Size and virtualise Say 20% improvement ? IT Equipment Cooling and Power Overhead SavingCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) – Identification of unused, under-used, inefficient or over-spec’ed IT equipment – Using active power management during low utilisation periods – Identification of poor equipment usage (ITUE) by end-users – Size and virtualise – Replace old servers IT Equipment Say 10% saving ? Cooling and Power Overhead SavingCommercial in Confidence
    • • The potential for savings comes from multiple sources: – Optimised environmental management to improve PUE (& ITUE) – Identification of unused, under-used, inefficient or over-spec’ed IT equipment – Using active power management during low utilisation periods – Identification of poor equipment usage (ITUE) by end-users – Size and virtualise – Replace old servers – Dynamic orchestration of virtual machines based on environmental, power and IT usage constraints ??????Commercial in Confidence
    • Concurrent Thinking’s ProductsCommercial in Confidence
    • Environmental Monitoring OS & VM Power Monitoring and Management Management Integration Server Health with Data Monitoring Centre SystemsCommercial in Confidence
    • o Low cost 5V temperature, humidity… sensors Environmental Monitoring o 3rd party SNMP sensors OS & VM Power Monitoring and Management Management Integration Server Health with Data Monitoring Centre SystemsCommercial in Confidence
    • Environmental Monitoring OS & VM Power Monitoring and Management Management o 3rd Party PDU control o Server PSUs (PMBus) o Device association o Power charge-back o Scheduled actions Integration Server Health with Data Monitoring Centre SystemsCommercial in Confidence
    • Environmental Monitoring OS & VM Power Monitoring and Management Management Integration Server Health with Data Monitoring Centre Systems o 3rd party SNMP devices o Modbus (and others..) via SNMP bridgeCommercial in Confidence
    • Environmental Monitoring OS & VM Power Monitoring and Management Managemento IPMI / DCMI supporto Power capping via Intel Node Manager Integrationo Scheduled actions Server Health with Data Monitoring Centre Systems Commercial in Confidence
    • o OS monitoringo Script repository Environmentalo OS Deployment Monitoringo VM migration (TBA) OS & VM Power Management Management Integration Server Health with Data Monitoring Centre Systems Commercial in Confidence
    • Optiimise real-time DC Optimise combined Facilities Efficiency Environmental Facilities & IT Efficiency (PUE) Monitoring (ITUE)Power & efficiency OS & VM Identify unused, Power metrics by rack / Monitoring and Management under-used,users / customer/ Management Comprehensive inefficient or cost Data Centre application etc, in-effective IT Management and equipment Orchestration Active power Active management Environmental during low Management & VM utilisation periods Integration Migration Server Health with Data Monitoring Centre Systems Commercial in Confidence
    • Pretty Pictures…Commercial in Confidence
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