1. Central machine room project

Romonet Ltd. were asked to assist Oxford University in ensuring the sound environmental (from an in-use energy and cost perspective) design and implementation of a new Central Machine Room (data centre) as well as the Mechanical and Electrical refurbishment of the existing OUCS Machine Room.

Oxford University wish the new CMR to be a design exemplar from an energy and environmental perspective that clearly support the University’s sustainability strategy

This report describes the findings that resulted from the workshops held at the Computing Services department on the 5th and 6th November 2008.

2. Overview

Romonet Ltd was engaged by Oxford University Computing Services (OUCS) to facilitate and explore the challenges faced by the University in successfully achieving the environmental sustainability and low carbon IT (energy efficiency) goals of a new Central Machine Room (CMR) project. The computing services department’s existing Machine Room (MR) was constructed in the 1970’s and has had a number of upgrades since, those being mostly in the mechanical and electrical infrastructure in order to support the increased and higher density demand over the years.

The CMR project will bring the University two primary benefits: a) Additional data centre capacity b) the opportunity to provide a higher level of resilience (thus lower risk) for critical IT services by creating the ability to split services between the current MR and the new CMR.

The University is very keen that the new CMR demonstrates a state-of-the-art design emphasising sustainability and low carbon ICT. Due to the limited resources, the focus of this study has been on the design and in-use energy efficiency rather than the embodied carbon used within the materials and equipment housed within the OMPI building and the CMR.

The CMR has been designed within the basement of a new building to house the Oxford Molecular Pathology Institute (OMPI) which itself has a significant requirement for controlled environmental capabilities for the laboratory areas within the building.

Many departments and areas of expertise are required during such a project and whilst each group may be considering energy efficiency within their area of knowledge and expertise, experience has taught us that these areas are rarely brought together in order to optimise and maximise the overall design efficiency and ability to meet such in terms of the achieved efficiency.

The project team were aware that it is possible to create a ‘sound’ mechanical and electrical design in isolation that could go some way to optimising the in-use energy efficiency of a data centre but in order to create an exemplar for the University, the use of the facility in terms of the IT and communications equipment was of vital importance.

3. Romonet background

Romonet Ltd was founded in 2006 to address the cost, energy and business issues within the European data centre market. Romonet has consulting, research, training and software development practices. Although the company is recently formed, the three principals, Zahl Limbuwala, Liam Newcombe and Sean Newcombe have between them over three decades of experience in the design, implementation and operation of data centres and the specification, design and delivery of ICT services in both the private and public sectors both within the EU and internationally. This depth of experience is now leveraged through the consulting, research and training practices of Romonet.

4. Data gathering

Romonet was given access to the internal business case for the CMR project along with a report created from an early feasibility study carried out by a data centre design and build consultancy. Romonet then organised a cross functional two-day workshop to explore the current status of the project, gain an understanding of how well the requirements had captured the sustainability, energy efficiency and low carbon goals and how well these goals had filtered through the various departments, stakeholders and sub-contractors.

Working with the IT Director for the University, a detailed list of required roles and functions for the two day workshop was drawn up and taken to the OMPI project sponsor and other stakeholders to ensure high level support and buy-in. The required roles and functions required were as follows:

  • Head of Estates (or representative)
  • Project Sponsor (or representative)
  • New OMPI building Project Manager
  • Director of IT (University)
  • Computing Services Director
  • Current MR Manager
  • Networks Manager
  • IT Systems Manager
  • CMR Mechanical and Electrical Consultant/s or Contractors
  • University Sustainability Officer (or representative)

Day One of the workshop was designed to give each functional area a chance to present their current thinking and plans for the CMR via a short (60 mins) presentation. This would enable the group to share a basic but common understanding of the issues, challenges and opportunities in each area in terms of achieving the project goals.

Day Two of the workshop was designed to lead the group through a structured approach to the design of the CMR in terms of achieving the most optimally efficient design (in terms of in-use energy). This would involve taking the group through a Business Impact Assessment exercise to gain a more granular understanding of business requirements and how they drove IT requirements that ultimately should drive the mechanical and electrical design of the CMR.

5. Findings

This section details the findings from the two-day workshop along with follow-up discussions with staff from the project team and OUCS.

5.1. General

In order to create the optimal CMR design from an energy and carbon standpoint it is essential that the energy efficiency goals are communicated to the entire project team. However this alone will not result in an optimal design. The way the customer (OUCS – as the ‘end user’ of the CMR) plans to use the facility plays a very large part in turning an efficient design on paper into an efficient one in practice. This is the first barrier that M and E designers often come across and is the hardest part of turning a ‘template’ design into a facility that actually achieves high efficiency from day one.

There are many factors that affect efficiency within a data centre which, by its very nature, is a complex system. The data centre influences the efficiency of the ICT equipment housed within it and vice-versa. The resulting system can be difficult to predict and understand and inherent loops within the system can also make efficiency analysis or prediction difficult. Moreover the measurement of and the metrics to report energy efficiency within the data centre is a relatively new area that is not yet adequately developed.

5.2. Demand forecasting

The importance of business demand forecasting is often overlooked beyond the initial ‘wet-finger’ demand figures that are needed to support the business case for any new data centre facility. It is however a demonstrable fact that getting the most accurate and granular view of business demand and how that translates to IT demand in advance of committing the data centre design, is the largest factor in achieving a target design efficiency.

As mechanical and electrical engineers understand, knowing what load will be placed on their systems within the data centre as well as when and how this load will change and grow is critical information to enable them to design a suitably modular facility which can operate efficiently under both initial and fully filled out loads. An explanation of design capacity and its impact on energy efficiency can be found in section 6.1.

Business demand forecasting is not a simple task within a University environment. Furthermore the follow-on task of Business Impact Analysis can also be very challenging within an environment that operates on a very loose supplier-customer relationship basis.

However, difficulty aside, the effort expended in carrying out these activities in order to produce a clear IT requirements forecast is well invested time in terms of how efficient the new data centre will be on day one and also how flexible the resultant data centre design is in it’s ability to deal with variability in forecast, technology steps, unexpected requirements or demand yet still be able to operate in a highly efficient manner.

While an initial study had been carried out by a third party which helped produce the figures that went into the business case, a much more concerted effort was required by the computing services department in order to get the level of data required by the people designing the data centre M and E infrastructure.

Business Impact Analysis was found to be another challenging task within the University environment as defining ‘Business Impact’ could vary from one department to another. The normal approach would be to identify the business services provided by the computing services department and carry out an impact assessment to understand what level of design resilience was required from the IT platform(s) that underpinned that service. In this case there was much debate around what actually represented services as the computing department offered low level services such as networking, DNS, authentication to some departments and high-level services such as email, collaboration and intranet services to others.

However it was well understood within the computing services department after years of support experience what level of resilience or redundancy was required for most of the major services both low and high level. This enabled the department to add another dimension to the demand forecast; ‘do I require redundancy?’ to achieve the required resilience.

5.3. IT requirements

One of the features of the initial OUCS CMR design was limited UPS capacity due to constrained physical space and budget. Having established the business demand forecast along with an understanding of the level of resilience required on a service-by-service basis, the computing services department were encouraged to make efficient use of the UPS resource by creating different infrastructure resilience levels to maximise the use of the UPS where it was needed most. For example, for dual power supplied IT equipment the following simple policy could be adopted:

Resilience level requiredA-feedB-feed
Medium UPS Non-UPS
Low Non-UPS Non-UPS

The additional advantage available in this instance was the fact that the new CMR was planned as incremental rather than replacement capacity to the existing MR. This would allow the computing service department to gain a much higher level of achieved reliability by splitting critical services across both facilities and only require the medium level of local UPS resilience.

Finally it was discussed and accepted that in general IT equipment lifespan was around 10%-20% of the expected lifespan of the CMR itself and that a CMR designed today wouldlikely run into technology generation mismatch issues within 3-5 years. The best example of this that can be observed in almost every data centre today is the issue of power density. In other words the general trend for equipment to get smaller while heat output continues to rise. This leads us to look at a much more modular and flexible CMR design which is in harmony with the energy efficiency goals of modular provisioning of M and E infrastructure to maximise the point in time load and thus the energy efficiency.

5.3.1. Data centre (CMR) requirements

Having already made a solid case for a more modular design, it was decided that addressing the power density issue to help future proof the facility whilst maximising the efficiency was the critical step in the CMR design requirements.

Many variables need to be considered to achieve an optimum design. The initial design for Oxford was a standard raised floor with underfloor cooling in conjunction with a hot-aisle / cold-aisle design and opposing CRAC units.

The physical requirements being driven out of the IT requirements were steering the CMR design to a zoned approach with different zones being capable of supporting differing power densities.

The simplest approach to achieving this was to use either partial or full hot or cold aisle containment with a pair of CRAC units matched to each aisle end. This design would enable the CMR to start on day one with a single pair of CRAC units cooling a single ‘zone’. The partial or full containment would ensure minimum air remix and thus maximum efficiency. It was also agreed that containing the hot or cold air and avoiding remix would allow a much better tracking of fan power within the CRAC to IT load within the zone, again ensuring maximum efficiency through matching the delivered M and E cooling capacity to the local IT load.

6. Understanding energy efficiency within the data centre

6.1. Design capacity, IT load and efficiency

In order to design for high energy efficiency, there is a need to match the IT load requirements to the design capacity of the M and E infrastructure. This is due to fact that most electrical and mechanical systems operate at maximum efficiency when at full load. Dependent on the type of device, the load to power function can vary significantly, but most M and E devices are designed to achieve their maximum energy efficiency near maximum load.

The same is true at a system level, meaning the overall energy efficiency of the data centre M and E infrastructure will occur when the system is close to its maximum rated capacity, or in other words when the IT electrical load is at 100%.

Much like today’s IT devices, the system wide capability for the data centre M and E infrastructure to ‘turn down’ from 100% load and remain efficient is very limited. Many of the devices within the more modern designs simply do not work properly without a suitable base load. This is particularly true of components such as absorptive chillers in CCHP plant.

Figure 1.
Figure 1.

Figure 1 illustrates a typical energy efficiency surface plot for a data centre, the vertical axis depicts the DCiE (Data Centre infrastructure Efficiency) where a DCiE of 1 represents 100% of the energy supplied from the utility being delivered to the IT equipment within the data centre. The illustration shows the influence of IT load on the overall efficiency of the data centre and thus the importance of ensuring a close match between data centre provisioned capacity and the average utilisation of this capacity at any point in time. This has a direct bearing on the optimal CMR design from an energy and carbon efficiency perspective.

Figure 2.
Figure 2.

If we look at an IT device, a server for example illustrated in Figure 2, we see a typical commodity x86 server’s load to power transfer function. It can be seen that the server’s electrical load varies between 200 watts with no load applied and 300 watts when it is working flat out. The yellow diagonal line shows how a load-to-power linear server would behave. That is, when it is doing no work, it is drawing little or no power.

6.2. Metrics

There has been much effort within the data centre industry to develop metrics that span the entire data centre and map energy consumption to the useful work of the facility. The development of metrics that described the basic energy transfer of the physical data centre are now relatively stable and well understood. There is not yet any useful metric for the IT work or application work of the data centre. As such this section will address the metrics for the physical facility.

6.2.1. Measuring energy efficiency (DCiE and PUE)

Data Centre Infrastructure (DCiE) or Power Usage Effectiveness (PUE) are two metrics in common use within the data centre industry for reporting the energy efficiency of a data centre. They are calculated as follows:

The Data Center infrastructure Efficiency metric is defined as the fraction of the IT equipment power divided by the total facility power;

DciE = IT Equipment Power / Total Facility Power

The total facility power is defined as the power measured at the incoming utility meter. The IT equipment power is defined as the power consumed by the IT equipment supported by the data centre as opposed to the power delivery and cooling components and other miscellaneous loads. For a full description of DCiE see the Green Grid paper on DCiE and PUE.

The PUE metric is simply the reciprocal of the DCiE metric;

PUE = 1 / DCE = Total Facility Power / IT Equipment Power

While both DCiE and PUE are simple metrics to understand and measure, their usefulness in predicting and managing energy efficiency are limited as both are influenced by how full the data centre is from an IT equipment power draw perspective (due to the fact that they are simple ratios). Therefore in terms of measuring and understanding the achieved vs. design efficiency of a data centre, they are of little use.

Figure 3.
Figure 3.

Figure 3 illustrates that on day one, if very little IT equipment is installed into the CMR the achieved efficiency shown by the DCiE metric would be close to zero. While such a figure may well be accurate it gives little indication as to how cost or carbon efficient the CMR will be under load in absolute terms. It is the absolute utility load (irrespective of howmuch IT equipment is installed) that will influence a data centre’s carbon footprint and any claims to be ‘low carbon’.

6.2.2. Fixed and Proportional

A data centre has a fixed base load, which would be drawn even if all of the IT equipment were to be unplugged, as such we can represent the facility power draw in two components, the fixed and variable power draw. This is represented by the fixed and proportional overheads. Whilst there is some non-linearity from the square law losses these are dominated by the fixed and proportional losses, allowing this representation to be an effective approximation as shown in Figure 4.

  • Facility Power(zero): The power drawn at the Utility feed at zero IT electrical load
  • Facility Power(full): The power drawn at the Utility feed at full IT electrical load
  • Rated IT Load: The rated IT electrical load of the facility
  • Fixed overhead = Facility Power(zero) / Rates IT Load

Fixed overhead has no units as the component units are Watts / Watts.

  • Proportional Load = Facility Power(full) - Facility Power(zero) / Rated IT Load

Again, proportional overhead has no units as the component units are Watts / Watts.

Once these two values are determined for the facility the two loss components can be plotted together, in the case of the data centre example below these are;

  • Fixed Overhead = 0.65
  • Proportional Overhead = 1.41
Figure 4.
Figure 4.

The ability to lower the fixed overhead of a data centre through modular provisioning will have a material impact on the facilities ability to be more energy responsive to IT load and thus have a greater measurable impact on energy consumed from the utility feed.

7. Recommendations

The new CMR program is intended to deliver a direct increase in both the physical and power capacity available to OUCS. There is a substantial opportunity within the new design to enhance this through data centre and IT efficiency improvements to deliver more effective utilisation of the available physical and energy capacity and therefore further improvement in the available computing services. This section summarises three sets of direct recommendations for the facility in the areas of energy metering, implementation and operational practices and the management of services within the facilities.

7.1. Measuring operational energy efficiency

One of the benefits of designing and building a green field data centre is the ability to include effective and useful instrumentation within the design at little additional cost.

Before spending additional money on metering equipment it is important to understand what benefits are expected from this instrumentation and the uses to which the data can be put. Many operators have installed expensive products that meter at the IT power strip or socket level in the data centre. Whilst per socket metering can provide very granular information this data is not directly useful to OUCS who do not charge occupants collocation fees including a multiple of metered power. As indicated in section 6.2.2 it is not reasonable or useful to allocate energy use or cost to a device based only on the metered power at the PSU, further, as technology advances and more devices are virtualised the notional relationship between a power socket and a logical server or service component is removed. Many IT devices also now report their energy use through management APIs (this is required in the new Energy Star for Compute Servers standard) which avoids the additional problems involved in associating a physical IT device with a numbered socket.

Whilst many operators have installed instrumentation to measure power within the data centre this is normally the energy used by the IT equipment and not the energy we are concerned with, the energy wasted by non-IT equipment. If this is measured at all it is frequently in Building Management Software and not visible to the IT department.

Figure 5.
Figure 5.

If the goal is to understand and manage IT energy use, energy efficiency and cost then a combination of IT and Mechanical and Electrical device consumption metering is required. PDU or rack level metering of the IT load is all that is necessary for OUCS when coupled with effective reporting of the data centre infrastructure loads.

Figure 5 illustrates three levels of data centre energy instrumentation. It is recommended for the OUCS CMR that at least the detailed measurement points (light blue) be instrumented. The meters should be network connected and able to log their data to a central station. Many BMS systems available today are able to accept logging data from remote energy meters. This data should be available from the BMS to other software. The historic reporting data should be stored in as granular a form as possible, at least hourly if not at the 300 second IT polling rate.

Data captured from the detailed measurement points will allow the simulation of future energy impacting changes and thus give a much greater understanding and control of energy management within the CMR.

7.2. Applying the EU Code of Conduct for Data Centres

It is recommended that Oxford University implement the EU Code of Conduct for Data Centre operators. The Code details best practices that apply to M and E infrastructure, IT systems and software. The best practices have been developed and reviewed by industry experts and represent a practical and effective approach to energy efficient design and on-going energy management within the data centre.

Romonet recommends that Oxford University implements the following best practices defined in the EU Code of Conduct for data centres at a minimum. Ideally Oxford University would become a full Participant of the code and report its energy data back to the EU under the requirements of Participant status. The mandatory requirement for reporting of high-level power data will ensure regular (six monthly) senior visibility of the energy data from the CMR and an increased understanding and appreciation of how the efficiency of the facility is being managed. Regular reviews of the reporting will also give a much better appreciation of the rate of growth in IT service related energy.

7.2.1. Design stage best practices

Listed below are the minimum best practices expected to be implemented during a new-build or major data centre re-fit.

TypeDescriptionImplementation stage
Group involvement Establish an approval board containing representatives from all disciplines (software, IT, M and E). Require approval for any significant decision to ensure that the impacts of the decision have been properly understood and an optimal solution reached. For example, this would include the definition of standard IT hardware lists. Design and Operational
Build resilience to business requirements Only the level of resilience actually justified by business requirements and impact analysis should be built. 2N infrastructures are frequently unnecessary and inappropriate. Resilience for a small portion of critical services can be obtained using DR / BC sites. Design
Consider multiple levels of resilience It is possible to build a single data centre to provide multiple levels of power and cooling resilience to different floor areas. Many co-location providers already deliver this, for example, optional ‘grey’ power feeds without UPS or generator back up. Design
Design – Contained hot or cold air There are a number of design concepts whose basic intent is to contain and separate the cold air from the heated return air on the data floor:
  • Hot aisle containment
  • Cold aisle containment
  • Contained rack supply, room return
  • Room supply, Contained rack return
  • Contained rack supply, Contained rack return
This action is expected for air-cooled facilities over 1kW per square meter power density.
Design and Operational
Efficient part load operation Optimise the facility for the partial load it will experience for most of operational time rather than max load. e.g. sequence chillers, operate cooling towers with shared load for increased heat exchange area Design
Variable Speed Fans Many old CRAC units operate fixed speed fans which consume substantial power and obstruct attempts to manage the data floor temperature. This is particularly effective where there is a high level of redundancy in the cooling system, low utilisation of the facility or highly variable IT electrical load. Design
Modular UPS Deployment It is now possible to purchase modular UPS systems across a broad range of power delivery. Physical installation, transformers and cabling are prepared to meet the design electrical load of the facility but the sources of inefficiency, switching units and batteries are installed, as required in modular units. This substantially reduces both the capital cost and the fixed overhead losses of these systems. In low power environments these may be frames with plug in modules, in larger environments these are likely to be entire UPS units. Design
Lean provisioning of power and cooling for a maximum of 18 months of data floor capacity The provisioning of excess power and cooling capacity in the data centre drives substantial fixed losses and is unnecessary. Planning a data centre for modular expansion and then building out this capacity in a rolling program of deployments is more efficient. This also allows the technology ‘generation’ of the IT equipment and supporting M and E infrastructure to be matched, improving both efficiency and the ability to respond to business requirements. Design

7.2.2. Operational stage best practices

Listed below are the minimum expected best practices that should be implemented once the new CMR goes live.

Multiple tender for IT hardware – Power Include the Performance per Watt of the IT device as a high priority decision factor in the tender process. This may be through the use of Energy Star or SPEC Power type standard metrics or through application or deployment specific user metrics more closely aligned to the target environment. The power consumption of the device at the expected utilisation or applied workload should be considered in addition to peak performance per Watt figures. Operational
Multiple tender for IT hardware – Basic operating temperature and humidity range Include the operating temperature and humidity ranges of new equipment as high priority decision factors in the tender process. The minimum is the ASHRAE Recommended range for Class 1 Data Centers, 18-27C and 5.5C dew point up to 15C dew point and 60% RH Operational
Enable power management features Formally change the deployment process to include the checking and enabling of power management features on hardware. Operational
Provision to the as configured power Provision power and cooling only to the as-configured power draw capability of the equipment, not the PSU or nameplate rating. Operational
Deploy using Grid and Virtualisation Processes should be put in place to require senior business approval for any new service that requires dedicated hardware and will not run on a resource sharing grid or virtualised platform. Operational
Reduce IT hardware resilience level Determine the business impact of service incidents for each deployed service and deploy only the level of hardware resilience actually justified. Operational
Reduce Hot / Cold standby equipment Determine the business impact of service incidents for each deployed service and deploy only the level of site BC / DR actually required. Operational
Select efficient software Make the performance of the software, in terms of the power draw of the hardware required to meet performance and availability targets a primary selection factor. Operational
Develop efficient software Make the performance of the software, in terms of the power draw of the hardware required to meet performance and availability targets a critical success factor. Operational
Decommission unused services Completely decommission and switch off, preferably remove, the supporting hardware for unused services Operational
Data Management Policy Develop a data management policy to define which data should be kept, for how long and at what level of protection. Communicate the policy to users and enforce. Particular care should be taken to understand the impact of any data retention requirements. Operational
Rack air flow management – Blanking Plates Installation of blanking plates where there is no equipment to reduce cold air passing through gaps in the rack. This also reduces air heated by one device being ingested by another device, increasing intake temperature and reducing efficiency. Operational
Rack air flow management – Other Openings Installation of aperture brushes (draught excluders) or cover plates to cover all air leakage opportunities in each rack. This includes:
  • Floor openings at the base of the rack
  • Gaps at the sides, top and bottom of the rack between equipment or mounting rails and the perimeter of the rack
Raised floor air flow management Close all unwanted apertures in the raised floor. Review placement and opening factors of vented tiles. Maintain unbroken rows of cabinets to prevent bypass air – where necessary fill with empty fully blanked racks. Managing unbroken rows is especially important in hot and cold aisle environments. Any opening between the aisles will degrade the separation of hot and cold air. Operational
Provide adequate free area on rack doors Solid doors can be replaced (where doors are necessary) with partially perforated doors to ensure adequate cooling airflow which often impede the cooling airflow and may promote recirculation within the enclosed cabinet further increasing the equipment intake temperature. Operational
Review of cooling before IT equipment changes The availability of cooling including the placement and flow of vented tiles should be reviewed before each IT equipment change to optimise the use of cooling resources. Operational
Review of cooling strategy Periodically review the IT equipment and cooling deployment against strategy. Operational

7.3. Service categorisation and grouping

The services delivered by OUCS should be reviewed to determine the required resilience and availability levels for each service. For user facing services (such as email) this is dependent upon the level of direct user impact from service failures whilst for infrastructure services (such as dns) this is determined from the impact upon user facing services (such as Internet access).

As OUCS will have multiple machine rooms and the ability to deliver multiple levels of resilience at the facility, hardware, network and software level it is sensible to define a series of standard offerings to meet the range of common availability criteria. The following table suggests a range of recovery and continuity levels and mechanisms as an example.

LevelDescriptionImplementationContinuity or Recovery Mechanism
Low-medium Low protection. Single physical or logical server, UPS protected Repair or restore from backup.
Medium Manual recovery. Single logical server, UPS protected, VM image on shared disk Manually invoke virtual machine on alternate hardware in same or alternate machine room
Low No protection. Single physical or logical server, single feed, no UPS Repair or restore from backup.
High Auto Recovery Logical server with cold standby hardware in separate machine room, replicated shared data Automatically invoke virtual machine on designated hardware in alternate machine room.
Very high Continuity Active / Active logical or physical servers in separate machine rooms Automatic redirection of user traffic.

It should be noted that hardware level disk replication is only necessary for legacy applications that offer no higher level replication of data and should not be viewed as a strategic solution.

7.4. Service catalogue and CMDB

Many of the best practices identified above will be easier to achieve if a comprehensive Service Catalogue is implemented and maintained. Alongside the Service Catalogue, a Configuration Management Database should be established and rigorously maintained for the new CMR to ensure that existing IT equipment is both documented and controlled. All changes in location, connections, memory, storage etc. – i.e. “configuration” – should be recorded in detail in the CMDB.

8. Glossary

CMR Central Machine Room (the proposed new data centre)
OUCS Oxford University Computing Services
MR Machine Room (Existing OUCS data centre)
OMPI Oxford Molecular Pathology Institute
M and E Mechanical and Electrical equipment supporting the CMR (and OMPI)
IT/ICT Information Technology / Information Communications Technology (often used to mean generic compute, storage and telecommunications equipment)
BMS Building Management System
CRAC Computer Room Air Conditioner
UPS Uninterruptible Power Supply