Metering Energy Consumption in Data Centres - Michael Rudgyard

Commercial in Confidence

Energy Usage Optimisation in the

Data Centre

Michael Rudgyard (CTO)

Concurrent Thinking Ltd


• 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 product


• 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 DC


• 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 %


• 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 !


• 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 DC


• 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 strategy


• The potential for savings comes from multiple sources

Start with a PUE of 2

IT Equipment

Cooling and power overhead


• 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

Saving



– Identification of unused, under-used, inefficient or over-spec’ed IT equipment

Perhaps 5 % of servers ?

IT Equipment


Saving




– Using active power management during low utilisation periods

– Identification of poor equipment usage (ITUE) by end-users

Say 10% improvement ?

IT Equipment


Saving






– Size and virtualise

Say 20% improvement ? IT Equipment


Saving







– Replace old servers

Say 10% saving ?

IT Equipment


Saving







– Replace old servers

– Dynamic orchestration of virtual machines based on environmental, power and IT usage constraints

??????


Concurrent Thinking’s

Products


Environmental Monitoring

Power Management

Integration with Data

Centre Systems

Server Health Monitoring

OS & VM Monitoring and Management



Power Management


Centre Systems



o Low cost 5V temperature,

humidity… sensors

o 3rd party SNMP sensors



Power Management


Centre Systems



o 3rd Party PDU control

o Server PSUs (PMBus)

o Device association

o Power charge-back

o Scheduled actions



Power Management


Centre Systems



o 3rd party SNMP devices

o Modbus (and others..)

via SNMP bridge



Power Management


Centre Systems



o IPMI / DCMI support

o Power capping via

Intel Node Manager

o Scheduled actions



Power Management


Centre Systems


OS & VM Management

o OS monitoring

o Script repository

o OS Deployment

o VM migration (TBA)


Comprehensive Data Centre Management

and Orchestration


Power Management


Centre Systems



Optiimise real-time DC

Facilities Efficiency

(PUE)

Optimise combined

Facilities & IT Efficiency

(ITUE)

Power & efficiency

metrics by rack /

users / customer/

application etc,

Identify unused,

under-used,

inefficient or cost

in-effective IT

equipment

Active power

management

during low

utilisation periods

Active

Environmental

Management & VM

Migration


Pretty Pictures…









Education

Metering Energy Consumption in Data Centres - Michael Rudgyard