How to succeed with The Performance Indicator #datacenter #datacentre @TheGreenGrid @6SigmaDC

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*Press Release on Data Center Knowledge: Performance Indicator, Green Grid’s New Data Center Metric, Explained

To find out more about The Performance Indicator visit thegreengrid.org

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@TheGreenGrid New #DataCenter Metric – Performance Indicator – Explained

The Green Grid Association is a non-profit, open industry consortium that works to improve the resource efficiency of information technology and data centers throughout the world. (PRNewsFoto/The Green Grid Association)

The Green Grid Association is a non-profit, open industry consortium that works to improve the resource efficiency of information technology and data centers throughout the world. 

The Green Grid published PUE in 2007. Since then, the metric has become widely used in the data center industry. Not only is it a straightforward way to take a pulse of a data center’s electrical & mechanical infrastructure efficiency, but it is also a way to communicate how efficient or inefficient that infrastructure is to people who aren’t data center experts.

Building on PUE with Two More Dimensions

Performance Indicator builds on PUE, using a version of it, but also adds two other dimensions to infrastructure efficiency, measuring how well a data center’s cooling system does its job under normal circumstances and how well it is designed to withstand failure.

Unlike PUE, which focuses on both cooling and electrical infrastructure, PI is focused on cooling. The Green Grid’s aim in creating it was to address the fact that efficiency isn’t the only thing data center operators are concerned with. Efficiency is important to them, but so are performance of their cooling systems and their resiliency.

All three – efficiency, performance, and resiliency – are inextricably linked. You can improve one to the detriment of the other two.

By raising the temperature on the data center floor, for example, you can get better energy efficiency by reducing the amount of cold air your air conditioning system is supplying, but raise it too much, and some IT equipment may fail. Similarly, you can make a system more resilient by increasing redundancy, but increasing redundancy often has negative effect on efficiency, since you now have more equipment that needs to be powered and more opportunity for electrical losses. At the same time, more equipment means more potential points of failure, which is bad for resilience.

Different businesses value these three performance characteristics differently, Mark Seymour, CTO of Future Facilities and one of the PI metric’s lead creators, says. It may not be a big deal for Google or Facebook if one or two servers in a cluster go down, for example, and they may choose not to sacrifice an entire multi-megawatt facility’s energy efficiency to make sure that doesn’t happen. If you’re a high-frequency trader, however, a failed server may mean missing out on a lucrative trade, and you’d rather tolerate an extra degree of inefficiency than let something like that happen.

PI measures where your data center is on all three of these parameters and, crucially, how a change in one will affect the two others. This is another crucial difference from PUE: PI, used to its full potential, has a predictive quality PUE does not.

It is three numbers instead of one, making PI not quite as simple as PUE, but Seymour says not to worry: “It’s three numbers, but they’re all pretty simple.”

The Holy Trinity of Data Center Metrics

The three dimensions of PI are PUE ratio, or PUEr, IT Thermal Conformance, and IT Thermal Resilience. Their relationship is visualized as a triangle on a three-axis diagram:

TGG Triangle Vectorized-01 (3)

Example visualization of Performance Indicator for a data center (Courtesy of The Green Grid)

PUEr is a way to express how far your data center is from your target PUE. The Green Grid defines seven PUE ranges, from A to G, each representing a different level of efficiency. A, the most efficient range, is 1.15 to 1.00, while G, the least efficient one, ranges from 4.20 to 3.20.

Every data center falls into one of the seven categories, and your PUEr shows how far you currently are from the lower end of your target range (remember, lower PUE means higher efficiency).

So, if your facility’s current PUE is 1.5, which places you into category C (1.63 – 1.35), and your target is to be at the top of C, you would divide 1.35 by 1.5 and get a PUEr of 90% as a result. You do have to specify the category you’re in, however, so the correct way to express it would be PUEr(C)=90%.

IT Thermal Conformance is simply the proportion of IT equipment that is operating inside ASHRAE’s recommended inlet-air temperature ranges. In other words, it shows you how well your cooling system is doing what it’s designed to do. To find it, divide the amount of equipment that’s within the ranges by the total amount of equipment, Seymour explains.

The Green Grid chose to use ASHRAE’s recommendations, but data center operators may choose to determine themselves what temperature ranges are acceptable to them or use manufacturer-specified thermal limits without degrading the metric’s usefulness, he adds.

IT Thermal Resilience shows how much IT equipment is receiving cool air within ASHRAE’s allowable or recommended temperature ranges when redundant cooling units are not operating, either because of a malfunction or because of scheduled maintenance. In other words, if instead of 2N or N+1, you’re left only with N, how likely are you to suffer an outage?

This is calculated the same way IT Thermal Conformance is calculated, only the calculation is done while the redundant cooling units are off-line. Of course, The Green Grid would never tell you to intentionally turn off redundant cooling units. Instead, they recommend that this measurement be taken either when the units are down for maintenance, or, better yet, that you use modeling software to simulate the conditions.

Modeling Makes PI Much More Useful

Modeling software with simulation capabilities used in combination with PI can be a powerful tool for making decisions about changes in your data center. You can see how adding more servers will affect efficiency, resiliency, and cooling capacity in your facility, for example.

This is where it’s important to note that Future Facilities is a vendor of modeling software for data centers. But Seymour says that about 50 members of The Green Grid from many different companies, including Teradata, IBM, Schneider Electric, and Siemens, participated in the metric’s development, implying that the process wasn’t influenced by a single vendor’s commercial interest.

Four Levels of Performance Indicator

The Green Grid describes four levels of PI assessment, ranging from least to most precise. Not every data center is instrumented with temperature sensors at every server, and Level 1 is an entry-level assessment, based on rack-level temperature measurements. ASHRAE recommends taking temperature readings at three points per rack, which would work well for a Level 1 PI assessment, Seymour explains.

Level 2 is also based on measurements, but it requires measurements at every server. To get this level of assessment, a data center has to be instrumented with server-level sensors and DCIM software or some other kind of monitoring system.

If you want to get into predictive modeling, welcome to PI Level 3. This is where you make a PI assessment based on rack-level temperature readings, but you use them to create a model, which enables you to simulate future states and get an idea of how the system may behave if you make various changes. “That gives the opportunity to start making better future plans,” Seymour says.

This is where you can also find out whether your data center can handle the load it’s designed for. Say you’re running at 50% of the data center’s design load, which happens to be 2MW. If you create a model, simulate a full-load scenario, and find that either your IT Thermal Conformance or your IT Thermal Resilience is only what you want it to be at 1.8MW, you’ve wasted your money.

Those are just a couple of possible use cases. There are many more, especially with PILevel 4, which is similar to Level 3 but with a much more precise model. This model is calibrated using temperature readings from as many points on the data center floor as possible: servers, perforated tiles, return-air intake on cooling units, etc. This is about making sure the model truly represents the state of the data center.

Different operators will choose to start at different levels of PI assessment, Seymour says. Which level they choose will depend on their current facility and their business needs. The point of having all four levels to avoid preventing anyone from using the new metric because their facility doesn’t have enough instrumentation or because they haven’t been using monitoring or modeling software.

To find out more about The Performance Indicator visit thegreengrid.org

Originally released on Data Center Knowledge: http://www.datacenterknowledge.com/archives/2016/07/18/performance-indicator-green-grids-new-data-center-metric-explained/

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#DataCenter Efficiency – Using #CFD Simulation to Optimize Cooling in Design & Operation

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Modern Simulation Software for Data Centers. Source: Future Facilities

 

Energy is one of the biggest (if not the biggest) cost factors associated with data center operations, and represents the highest year over year growth rate. Unfortunately the efficient use of cooling can be like a game of Tetris. In Tetris, efficient use of space is impacted by the unpredictable shape of the blocks.  In the data center efficient use of cooling is impacted by the unpredictable airflow requirements of the IT equipment.  In Tetris, you can see the blocks and how they use the space.  But how can you do the same for cooling in the data center?

Are you confident the cooling optimization efforts have no negative impact on your data center operation and do not cause problems? Do you know if your current airflow is sufficient for the latest generation of server you plan to install? Can the cooling design for your facility still cope with today’s requirements of high-density deployments?

As today’s facilities have to be efficient and resilient it is a considerable advice to avoid trial and error strategies. State-of-the-art simulation techniques, such as Computational Fluid Dynamics (CFD), make the invisible visible, and validate the impact of IT infrastructure changes before putting them into action. CFD has become an essential tool for many companies as it allows users to quantify the airflow and temperature which would occur if physical alterations were made to the data center space.

Adapting new validation methods

CFD provides the capability to analyze every square inch of the data center, and determine the effectiveness of cooling within the racks and aisles. It also helps consider all the relevant aspects of cooling optimization with monitoring measures to validate simulation and planning results during operation.

The engineering simulation allows you to model any type of data center configuration whether it’s raised floor, slab, overhead cooling, in-row cooling, etc. Modern free-cooling technology can be incorporated such as direct and indirect evaporative cooling. You can even model complete control systems, hot-aisle or cold-aisle containment easily and compare each design variation. The simulation also allows you to analyze the impact of losing power to the entire facility (transient). Using CFD in the design phase is the best practice; today most sites are designed with the help of CFD tools in planning process by contractors. When the site is handed over to the user, CFD is usually no longer used on a regular basis – and that’s exactly where problems start to occur.

That’s why CFD is ideal to maintain to prevent changes for the worse. CFD can be employed when operators wish or need to check for a cooling perspective to make sure every piece of IT equipment is getting sufficient air flow at the right temperature in event of a failure. It has the capability to predict consequences of cooling failure.

Predict before you commit

CFD solves and even prevents many problems in data center design and operations. There are many benefits to CFD as there is no risk as changes are modeled and validated before action is taken. CFD integrates seamlessly into planning workflows and including it in operational procedures is nowadays a must for mature state-of-the-art data center management. Cooling optimization reduces energy costs, allows reclaiming of lost capacity, reduces downtime by preventing hotspots and optimizes space usage.

Modeling CFD allows effective communication between equipment suppliers, data center designers and operators. It is a risk-free way of experimenting within the data center to improve performance and capacity.

Though CFD modeling requires information about the size, content and layout of the data center to create a 3D model. If you are using a DCIM tool, the relevant data is already available at your fingertips and you just need to share it with the CFD tool.

An off-the-shelf adapter is available to connect FNT Command with Future Facilities 6SigmaDCX and share all changes between these tools. Integrating Engineering Simulation 6SigmaDCX with FNT Command IMAC Processes is a simple, 3-step planning process:

  • Run a simulation on your current planning scenario to visualize airflow and temperature
  • Look at the effects of the change that has been proposed
  • Cooling limits per cabinet can be committed back to FNT Command to facilitate further planning using internal threshold checks on the updated values.
 

Oliver Lindner, Head of Business Line DCIM at FNT, recently wrote an Expert Paper on this topic and explains in detail how to achieve performance improvements both in design and operation phase.

Download the expert paper titled here: Data Center Efficiency: Using CFD to Optimize Cooling in Design and Operation

This post originally appeared on the FNT blog: http://blog.fntsoftware.com/data-center-efficiency-using-cfd-optimize-cooling-design-operation/#more-489

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Airflow Management Can Help #DataCenter Operators Realize Robust Energy Savings

Upsite Technologies’ “4 R’s” Approach to Airflow Management Shown to Lower PUE and Increase Equipment Reliability

Holistic Methodology to Improve Computer Room Airflow Management Can Help Data Center Operators Realize Robust Energy Savings and Improve the Environment, as shown by new CFD Video by Future Facilities

Upsite Technologies, Inc., (Upsite) a leader in data center airflow management solutions, announced today that Computational Fluid Dynamics (CFD) modeling has demonstrated the energy savings outlined by its Video (below) 4 R’s of Airflow Management™ methodology. The company tapped Future Facilities North America (Future Facilities NA), the premier provider of engineering simulation software for data center design and operational planning, to demonstrate the findings through the utilization of its 6SigmaDCX CFD simulation tool.

Upsite’s 4 R’s of Airflow Management provides a guide for implementing changes to optimize cooling and achieve the greatest benefits of airflow management, including a lower Power Usage Effectiveness (PUE) score, reduced energy costs, and increased IT equipment reliability. The 4 R’s methodology details the improvements and best practices made to a data center’s racks, raised floor, rows, and room that will provide these benefits and optimize the cooling infrastructure. 6SigmaDCX was used to model a 4,000 sq. ft. data center and provide engineering simulation to assess the impact of the changes made to these four areas: rack, raised floor, row, and room. The simulation provided valuable information about how problem areas (e.g. hot spots) could be rectified and how capacity and operating cost benefits could be realized after making AFM improvements to each of the 4R’s. The execution of the steps resulted in:

  • Reduction in the maximum IT inlet temperature of 8.4° F
  • Cooling supply temperature increase of 10° F
  • Cooling unit fan speeds reduced by 35% and one cooling unit turned off
  • Partial PUE (pPUE) reduced from 1.54 to 1.34
  • Over $60,000 in annual savings for a 4,000 Sq. Ft. Data Center
  • 15 month ROI

“Given the many solutions available to improve data center airflow, the process of creating an effective airflow management plan can seem overwhelming,” said Lars Strong, Senior Engineer and Company Science Officer of Upsite Technologies. “Our 4 R’s of Airflow Management approach provides a clear strategy to optimize cooling and lower PUE. With the impressive results now demonstrated by CFD modeling, I anticipate that more owners and operators will be utilizing our 4 R’s methodology to accomplish this quickly, efficiently, and with a faster ROI.”

 

Original posted by BusinessWire

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Data Centers aren’t doing enough to be green

Most data centers are running well below capacity and hiding inefficiencies with green heat transfer initiatives

Posted by Ben Rossi on 4 May 2016 – InformationAge

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The technology boom of the last ten years has seen people’s reliance on data centers increase exponentially. All of the online platforms that have made lives more convenient and connected, from streaming sites to instant messaging platforms, rely upon information stored in data facilities.

In the advent of trends such as the Internet of Things, this demand for data storage is set to skyrocket even further. However, we are already facing a critical problem: the environmental impact of data centers.

According to research from the Global Sustainability Initiative, data centers are now responsible for 2% of the world’s total greenhouse gas emissions. If the demand for data storage escalates at predicted rates, the volume of emissions that facilities produce will simply become unsustainable.

However, there is some good news – many of the problems with the current data center situation stem not from the sheer number of facilities in existence, but the ways in which they are operated.

Excess heat

Most data centers are currently running well below capacity. This inefficiency is often due to a fear of operational failure, and the belief that over-engineering is the only way to minimize this risk.

As a result, many data center operators are attempting to mask these inefficiencies through green heat transfer initiatives – using the excess heat to power public buildings such as swimming pools.

But this shortsighted strategy of ‘donating’ excess heat does nothing to address the underlying issues. Wouldn’t it be easier to solve the problem at the source?

Whilst the scale of new demand for data storage facilities is bound to require a certain amount of extra power, an ‘engineering gap’ currently exists, which prevents existing data centers from adapting to demands placed on them by businesses in the most efficient way.

As a result, the majority of data center energy expenditure via excess heat generation is avoidable. But there are techniques and tools that can be used on even the oldest data centers to reduce excess energy use and create truly ‘green’ facilities.

Green data centers

IT and facilities managers often over-provision and under-utilize the resources at their disposal, in order to avoid risk. In addition to being harmful to the environment, these inefficiencies also result in significant avoidable costs to the business.

Therefore, the challenge involved with making data centers greener lies in reducing operational inefficiencies without increasing the risk of downtime.

In part, this can be achieved through data center infrastructure management (DCIM) techniques. But if an operator is reliant on DCIM alone, the issue of the engineering gap remains.

The engineering gap in this instance refers to the disconnect between an IT manager’s prioritization of capacity, compared to a facility manager’s focus on efficiency.

The risk of making a change within the data center to improve efficiency is often, from an IT perspective, not worth the potential consequences should the system fail.

This means that the ability to predict the engineering impact of changes to the data center is potentially invaluable.

Predicting the impact of change on a data center requires a safe, offline environment to test proposals for change without the fear of disastrous consequences.

>See also: A change in tide: P.U.E vs. W.U.E and the future of the green data centre

One of the best ways to do this is to use engineering simulation. Through the use of 3D modelling to represent the data center, power system simulation (PSS) and computational fluid dynamics (CFD), it is possible to identify whether a data center is operating with wasted capacity, and therefore excess heat production as a result.

Implementation of these methodologies means businesses can drive up utilization, thereby minimizing excess heat production.

An added bonus is that engineering simulation can be used to assist with installing high power density IT into a legacy facility, resulting in a technology boost for business processes, without the need for additional data center construction and unnecessary heat generation.

Rather than worrying about ways to recycle excess heat produced by facilities, businesses can instead conduct an evaluation of the ways in which they can be optimized.

Sourced from Jon Leppard, director, Future Facilities

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Uncovering the Value of Calibrating #DataCenter #CFD Models

Why should you care about engineering simulation and calibration in your data center?

 

Future Facilities has teamed up with the Center for Energy-Smart Electronics Systems (ES2) to uncover the true value of calibrating a virtual facility model from thermal and airflow perspectives.

Video Gallery        Calibration Paper        ES2 Website        Technical Papers

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Your #datacenter can’t change fast enough

Originally posted in DatacenterDynamicsoptimized

How do you create data centers that can respond to business needs with speed, control and visibility?

Jon Leppard Jon Leppard

The speed and resilience of a data center is something we obsess over – making efficiencies and improving performance is what makes working in IT so satisfying. We live for the next tech breakthrough that can process more, store more, or just work harder on less power. Luckily, with Moore’s law (well, roughly), we’ve enjoyed a steady supply of these breakthroughs over the past decade.

But, when the pressure is on to make a change, most data centers are slow. There’s a lot to consider, especially when we are talking about larger facilities with mission critical workloads, multiple systems, failsafes, cooling setups etc. to take into account.

Do we want fast change?

Pit stop

The speed of business is only increasing – the successful launch of in-memory analytics such as SAP HANA proves that businesses are taking competitive advantage not just from big data, but fast data. Time is, more than ever before, money. The trend over the near term appears to be hardware struggling to keep up with the demands placed upon it by new software workloads.

When the pressure therefore inevitably comes down to begin migration to faster, more efficient data centers, the DC team’s ability to control the risk of the process is far too limited. When varied workloads are pushed into the data center by the business, or something needs to change within the facility itself, it poses questions about capacity and resilience which need very precise answers in order to avoid lengthy and costly mistakes.

Can we change fast?

The reality for most data center managers is that answering questions like do we have the capacity? or are we exposing ourselves to too much risk? is often a combination of historic trends, experience and a bit of educated guesswork. Therefore, quite rightly, the IT team will appeal for time from the business to assess and get things as close to “right” as possible – who can blame them? The data center is dealing with mission critical applications, SLA’s and customer data, failure is unacceptable.

Right now, the facilities and IT teams in this situation simply can’t change fast. But businesses don’t have the time to wait on the data center. The collective data center industry is doing what it’s done for the past decade – it’s waiting for a technological breakthrough to save the day.

Is there a solution on the horizon?

Yes, there certainly is! New designs for software-defined, homogenized facilities look like they will be going a long way towards responding to this need. The only problem here is that for most organizations (those without ludicrously large IT budgets) the software-defined data centers are between five and 10 years away.

That’s a bit beyond the scope of the timeline most businesses are setting their data center teams to implement change, sadly.

We therefore need to create data centers that can respond to these business needs with absolute control and visibility, to remove risk for the equation. We call this concept the ‘Fluid Data Center’.

What’s a Fluid Data Center?

Rather than an amazing new cooling system, the Fluid Data Center is a concept where capacity and risk can be accurately and quickly snap-shotted. A Fluid Data Center can “pour” my resource towards either end of this spectrum with safe knowledge of the impact this will have on either the capacity or the resilience of the entire facility.

It can do this on a case by case basis, and can do this quickly.

It’s achieved by knowing exactly what is happening currently within a data center and then using advanced engineering simulation tools to map out what the impact of any given change would be. Not just in terms of power draw, but on what the impact would be on the air flow of a room, the additional strain on a given AC unit etc. down to the fine detail.

What this tends to result in, aside from happier business teams, is incredibly efficient data centers. At the moment the only solution to not knowing precisely the limit of a DC is to factor in a healthy safety margin – this could be an extra AC unit or two, in simple cases. A fluid data center has these turned off – bringing down PUE – and is able to smartly communicate with the business that these will be turned back on if X occurs.

A Fluid Data Center knows exactly how much juice it has, and the size of the container – and it uses this information to act faster and safer than human predictions could ever achieve.

But the best bit about it is that it’s a solution to a growing problem that is available right now, instead of on the horizon.

Jon Leppard is a director at Future Facilities, a company that specializes in engineering simulation tools.

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