Uptime Intelligence regularly addresses IT infrastructure efficiency, particularly servers, in our reports on data center energy performance and sustainability. Without active contribution from IT operations, facility operations alone will not be able to meet future energy and sustainability demands on data center infrastructure. Purchases of renewable energy and renewable energy certificates will become increasingly — and, in many locations, prohibitively — expensive as demand outstrips supply, making the energy wasted by IT even more costly.
The power efficiency of a server fleet, that is, how much work servers perform for the energy they use, is influenced by multiple factors. Hardware features receive the most attention from IT buyers: the server’s technology generation, the configuration of the system and the selection of power supply or fan settings. The single most significant factor that affects server efficiency, however, is the level at which the servers are typically utilized; a seemingly obvious consideration — and enough for regulators to include it as a reporting requirement in the EU’s new Energy Efficiency Directive (see EED comes into force, creating an enormous task for the industry). Even so, the process of sourcing the correct utilization data for the purposes of power efficiency calculations (as opposed to capacity planning) remains arguably misunderstood (see Tools to watch and improve power use by IT are underused).
The primacy of server utilization in data center efficiency has increased in recent years. The latest server platforms are only able to deliver major gains in energy performance when put to heavy-duty work — either by carrying a larger software payload through workload consolidation, or by running scalable, large applications. If these conditions are not met, running lighter or bursty workloads on today’s servers (regardless of whether based on Intel or AMD chips) will deliver only a marginal, if any, improvement in the power efficiency compared with many of the supposedly outdated servers that are five to seven years old (see Server efficiency increases again — but so do the caveats).
Cycles of a processor’s sleep
This leads into the key discussion point of this report: the importance of taking advantage of dynamic energy saving features. Settings for power and performance management of servers are often an overlooked — and underused — lever in improving power efficiency. Server power management techniques affect power use and overall system efficiency significantly. This effect is even more pronounced for systems that are only lightly loaded or spend much of their time doing little work: for example, servers that run enterprise applications.
The reduction in server power demand resulting from power management can be substantial. In July 2023 Uptime Intelligence published a report discussing data (although sparse) that indicates 10% to 20% reductions in energy use from enabling certain power-saving modes in modern servers, with only a marginal performance penalty when running a Java-based business logic (see The strong case for power management). Energy efficiency gains will depend on the type of processor and hardware configuration, but we consider the results indicative for most servers. Despite this, our research indicates that many, if not most, IT operations do not use power management features.
So, what are these power management settings? Server power management settings are governed by the firmware statically (what modes are enabled upon system start up) and dynamically by the operating system or hypervisor once running through the Advanced Configuration and Power Interface.
There are many components in a server that may have power management features, enabling them to run slower or power off. Operating systems also have their own software mechanisms, such as suspending their operation and saving the machine state to central memory or the storage system.
But in servers, which tend to be always powered on, it is the processors’ power management modes that dictate most of the energy gains. Modern processors have sophisticated power management features for idling, that is, when the processor does not execute code. These are represented by various levels of C-states (the C stands for CPU) denoted by numbers, such as C1 and C2 (with C0 being the fully active state).
The number of these states has expanded over time as chip architects introduce new, more advanced power-saving features to help processors reduce their energy use when doing no work. The chief benefit of these techniques is to minimize leakage currents that would otherwise increasingly permeate modern processor silicon.
The higher the C-state number, the more of its circuitry the CPU sends to various states of sleep. In summary:
C0: processor active.
C1/C1E: processor core halts, not performing work, but is ready to immediately resume operation with negligible performance penalty, optionally reducing its voltage and frequency to save power.
C3: processor clock distribution is switched off and core caches are emptied.
C4: enhancement to C3 that extends the parts covered.
C6: essentially powers down entire cores after saving the state to resume from later.
C7 and higher: shared resources between cores may be powered downs, or even the entire processor package.
Skipped numbers, such as C2 and C5, are incremental, transitionary processor power states between main states. Not all these C-states are available on all processor architectures.
A good sleep in a millisecond
The levels of C-states and understanding them matters because they largely define the cost in performance and the benefit in power. The measured results of 10% to 20% reduction in energy use when enabling certain power management features, as discussed earlier, have allowed the server processor (an AMD model) to enter processor power states up to C6. These sleep states save power even when the server, on a human level of perception, is processing database transactions and responding to queries.
This is because processors operate on a timescale measured in nanoseconds, while software-level requests between commands can take milliseconds even on a busy machine. This is a factor of one million difference: milliseconds between work assignments represent millions of processor cycles waiting. For modern server processors, some of the many cores may often have no work to do for a second or more, which is an eternity on the processor’s time scale. On a human scale, a comparable time would be several years of inactivity.
However, there is a cost associated with the processor cores going to sleep. Entering ever deeper sleep states across processor cores or entire chips can take thousands of cycles, and as many as tens of thousands of cycles to wake up and reinstate operation. This added latency to respond to wake-up requests is what shows up as a loss of performance in measurements. In the reference measurement running the Java-based business logic, this is in the 5% to 6% range — arguably a small price to pay.
Workloads will vary greatly in the size of the performance penalty introduced by this added latency. Crucially, they will differ even more in how costly the lost application performance is for the business — high-frequency trading or processing of high volumes of mission-critical online transactions are areas where any loss of performance is unacceptable. Another area may include storage servers with heavy demand for handling random read-write operations at low latency. But a vast array of applications will not see material change to the quality of service.
Using server power management is not a binary decision either. IT buyers can also calibrate the depth of sleep they enable for the server processor (and other components) to enter. Limiting it to C3 or C1E may deliver better trade-offs. Many servers, however, are not running performance-critical applications and spend most of their time doing no work — even if it seems that they are often, by human standards, called upon. For servers that are often idle, the energy saved can be in the 20% to 40% range, which can amount to tens of watts for every lightly loaded or idle server.
Optimizing server energy performance does not stop with C-states. Performance-governing features (setting performance levels when the processor is actively working), known as P-states, offer another set of possibilities to find better trade-offs between power and performance. Rather than minimizing waste when the processor idles, P-states direct how much power should be expended on getting the work done. Future reports will introduce P-states for a more complete view of server power and performance management for IT infrastructure operators that are looking for further options in meeting their efficiency and sustainability objectives.
The Uptime Intelligence View
A server processor’s power management is a seemingly minute function buried under layers of technical details of an infrastructure. Still, its role in the overall energy performance of a data center infrastructure will be outsized for many organizations. In the near term, blanket policies (or simply IT administrator habits) of keeping server power management features switched off will inevitably be challenged by internal stakeholders in pursuit of cost efficiencies and better sustainability credentials; or, possibly in the longer term, by regulators catching on to technicalities and industry practices. Technical organizations at enterprises and IT service providers will want to map out server power management opportunities ahead of time.
https://journal.uptimeinstitute.com/wp-content/uploads/2024/07/Understanding-how-server-power-management-works-featured.jpg5401030Daniel Bizo, Research Director, Uptime Institute Intelligence, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngDaniel Bizo, Research Director, Uptime Institute Intelligence, [email protected]2024-07-10 15:00:002024-07-09 10:40:07Understanding how server power management works
The European Green Deal, a set of policy initiatives approved in 2020, aims for a sustainable and competitive economy with net-zero greenhouse gas emissions by 2050. Along with the legislation driving this transition, such as the Energy Efficiency Directive recast (see EED comes into force, creating an enormous task for the industry), the strategy will require much higher rates of electrification in transport and industries to displace the use of fossil fuels. This aim is combined with the policy objective of adding large amounts of renewable power generation capacity.
However, this direction is leading toward a new environmental challenge: increased sales of electric vehicles (EVs) will create future end-of-life battery problems, drawing attention to the unresolved issue of reusing and recycling large battery banks. Many industrial stationary applications are also seeing a strong take-up of EV-type (mostly lithium-ion) batteries for a variety of reasons. These include the displacement of valve-regulated lead-acid (VRLA) batteries, which are highly recycled, new energy storage installations for grid demand-response schemes and the elimination of standby engine generators.
Until now, this area has been governed by the 2006 Battery Directive (2006/66/EC). However, this directive is being replaced by Regulation 2023/1542 — the main objective of which is to create an updated set of rules to ensure high sustainability standards regardless of the battery chemistry. As an EU Regulation, it applies automatically to all member states without implementation in national laws.
The new regulations address aspects such as carbon footprint, recycled content, safety, labeling and end-of-life management. Industrial customers, including data center suppliers and their customers, will need to start reporting by mid-2025 — although this date may yet change. Although these rules only apply to members of the EU, its standards and laws are often replicated in other countries.
The 2006 Battery Directive was put in place to mitigate the environmental impact of battery production and disposal of waste batteries. It introduced recycling and treatment targets, restrictions on some hazardous substances, labeling requirements (for hazardous substances and instructions for proper disposal), reporting obligations and extended producer responsibility.
Lead-acid versus Li-ion recycling: the facts
The most common batteries used in uninterruptible power supply (UPS) systems are VRLA and Li-ion batteries (of which several sub-types exist). Lead-acid batteries have the highest collection and recycling rates. In the EU, the recycling rate for automotive starter batteries is 99% and more than 90% of the lead is recovered. The figure for stationary applications, which includes data centers, is likely to be similarly high due to the stringent regulations and economic incentives to recycle.
In 2021, all EU member states met the target recycling rate of 65% by weight for lead-acid batteries (both automotive and non-automotive).
The recycling process of lead-acid batteries consists of draining the electrolyte, opening the casing and separating the materials. The lead plates are then smelted to obtain molten lead, which is purified and refined before being cast into ingots for reuse. The plastic components are also recycled. Lead-acid batteries have few components and contain approximately 70% lead, which means that it is an efficient process. It is also profitable because recycled lead can be used in the manufacture of new batteries and is recyclable at relatively low temperatures, which require less energy.
For Li-ion batteries, the view is more complicated. Currently, it is cheaper to mine the metals to make new Li-ion cells (regardless of Li-ion chemistry) than it is to recycle used batteries. As a result, the much higher environmental footprint of the supply chain to produce Li-ion cells has so far been an externality and not priced into the cost of making Li-ion batteries. This factors heavily into its current market advantage in price-performance compared to other, environmentally less damaging cell chemistries.
The two most common processes for recycling spent Li-ion batteries are pyrometallurgy and hydrometallurgy. During both processes, the batteries are discharged and dismantled. They are then either smelted at high temperatures or leached to recover high-value cathode materials, such as cobalt, nickel and copper. During pyrometallurgical smelting, the lithium is lost in the furnace, making the process for lithium not sustainable. Future recycling processes for Li-ion cells are in development and will likely involve a combination of heat treatment and leaching in various concentrations of acid to maximize recovery of valuable metals.
These processes are energy-intensive and therefore expensive to operate, as well as producing gaseous pollutants and industrial waste. According to some battery vendors, the costs involved with the transport and recycling of Li-ion batteries, which is considered a hazardous waste, are substantial.
This is a major reason behind the current expectation that Li-ion battery packs will find secondary and even tertiary uses rather than being recycled for their raw materials. Compared with lead-acid batteries, this is possible due to Li-ion cells’ higher endurance and shelf life. The new battery regulation actively considers this scenario with the introduction of battery passports.
What are the new rules?
The phased implementation of the rules (Regulation 2023/1542) begins in July 2024 and regulates the carbon footprint, recycled content of new batteries, labeling and the introduction of an online battery information system. The new battery regulation controls all battery chemistries, with rules varying by battery category, for example, EV, industrial and portable. Recycling targets differ between chemistries, with specific targets for the recovery of cobalt, lead, lithium and nickel. Figure 1 sets out the major milestones of the regulatory rollout for EU member states, as prescribed in the regulation.
Figure 1. Timeline of the EU’s battery regulation
New batteries put to market will be subject to mandatory minimum levels of recycled content requirements. From 2030, batteries will need to contain a minimum recycled content of 12% for cobalt, 4% for lithium, 4% for nickel and 85% for lead. By 2035, these thresholds will increase to 20% cobalt, 10% lithium, 12% nickel and 85% lead.
Alongside these requirements, there are also recycling efficiency and material recovery targets for end-of-life batteries. By the end of 2030, used batteries will have a recycling target by weight of 80% for lead-acid and 70% for Li-ion. The material recovery target is 95% for cobalt, copper, lead and nickel and 70% for lithium.
What does this mean for data center operators?
The new rules will mostly affect battery producers; however, some responsibilities will fall on end users, such as data center operators. These include performing due diligence to verify vendor (product carbon footprint) and recycler claims (environmental credentials of the recycling process), as well as maintaining up-to-date battery passports during the use of the products.
From August 18, 2025, battery suppliers and data center operators (with some exceptions), will have a legal requirement to adopt a battery due diligence policy covering the social and environmental risks. This policy will need to include annual reports on the risks in the supply chain and the steps taken to manage them, transparency on sourcing raw and recycled materials, and structuring an internal management system to support it. The due diligence policy should be verified by a third party and communicated to suppliers and the public via annual reports.
There are exceptions for suppliers and buyers of batteries with an annual net turnover of less than €40 million ($43 million) and those using batteries that have undergone preparation for reuse, repurposing, or remanufacturing before being placed on the market.
The introduction of battery passports in 2026 will affect both suppliers and end users, including data center operators. Battery producers will be required to report on properties such as the chemistry, carbon footprint and recycled content, while it will be the end user’s responsibility to update the battery passport on the state of its health throughout its life. This will likely include maintenance entries but also any substantial events or accidents, such as deviations from standard operating environmental conditions, overcharging or deep discharging, and other impacts.
Battery passports will be key to enabling a second-hand market for batteries that are appropriate for reuse. Alongside the labeling of batteries, this may lead to improvements in Li-ion battery recycling by simplifying the separation process by sorting batteries by chemistry before the start of the recycling process. However, the technical implementation of the battery passport has not been stipulated in the new regulation and will be left to future cooperation between EU member states.
The regulation states that producers shall cover the necessary costs incurred by the collection and recycling of waste batteries. Lead-acid batteries have an inherent economic value at the end of their useful lives, which guarantees incentives for both buyers and sellers to promote recycling. Li-ion batteries, however, currently incur substantial costs to pay for recycling. According to battery makers, this can amount to as much as the price of new Li-ion batteries. Another potentially overlooked detail is the cost of transporting large amounts of Li-ion batteries that are classified as hazardous and pose a fire risk.
It is possible (or even likely) that end users may see a marked increase in the price of Li-ion batteries — the selling price will need to cover the recycling costs as a result of this extended producer responsibility. Data center operators, with hundreds of batteries in their UPS systems, may have to set up databases and processes to ensure they are reliably tracked.
The regulation stipulates that the ultimate responsibility for managing end-of-life batteries will fall on suppliers — in practical terms: taking batteries from end-users for no charge and ensuring the batteries are reused or recycled. However, end users should also exercise due diligence, even when they are not legally required to at present. Data center owners and operators should be aware that battery manufacturers may overstate their recycling capabilities. This is particularly relevant given the long lifespan of industrial Li-ion batteries, which can remain in use for 10 to 15 years or longer. Companies placing such batteries on the market may not have adequate recycling plans in place.
End users should also consider what technology is used in the recycling facilities, and even verify the existence of these facilities by checking their reported location using satellite imagery and public records. Inevitably, some battery vendors will go out of business, leaving end users with a potentially costly liability.
Additionally, when considering Scope 3 emissions reporting (in accordance with the Greenhouse Gas Protocol), the new recycling obligations add complexity. End users will need to consider carbon emissions from transportation and recycling processes. While some may argue that recycling offsets carbon emissions compared with manufacturing new batteries from raw materials, this claim may not withstand closer scrutiny.
Where could these rules go in the future?
The 2023 battery regulation provides a timeline of implementation, but the rules will need further clarification when they start to come into effect. Potential secondary legislation could involve standardizing calculations for carbon footprint, recycling efficiency and material recovery. More clarification may follow for the implementation and functioning of the electronic exchange system as well as specifications for the content and accessibility of battery passports.
Additionally, EU member states may choose to enact further requirements (as long as they are not in conflict with EU law) to stimulate investments in research and development related to carbon footprint reduction and sustainability in battery production and recycling.
The Uptime Intelligence View
The new EU Battery Regulation is primarily a response to the mass-market adoption of EVs, however, it also covers industrial stationary applications, such as mission-critical power systems.
The EU’s objective is to ensure that huge quantities of new batteries will not simply end up as hazardous waste at the end of their lives but will either find new uses or be recycled to make new battery cells. It will also level the playing field with lead-acid batteries and other, more readily recyclable chemistries.
Rosa Lawrence, Research Associate, Uptime Institute, [email protected]
https://journal.uptimeinstitute.com/wp-content/uploads/2024/06/EU-battery-regulations-what-do-the-new-rules-mean-featured.jpg5401030Rosa Lawrence, Research Associate, Uptime Institute, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngRosa Lawrence, Research Associate, Uptime Institute, [email protected]2024-06-20 15:00:002024-06-20 09:40:06EU battery regulations: what do the new rules mean?
The colocation and public cloud sectors of the digital infrastructure industry continue to make headlines, with many organizations planning large-scale capacity expansion to meet rising demand. However, there is also a less public expansion underway — enterprises operators, for the third successive year, say they are going to invest in more data center capacity in 2024.
Results from the Uptime Institute Capacity Trends Survey 2023 reveal that 64% of enterprise operators are growing their data center capacity — a six percentage-point uptick from two years earlier in 2021 (see Figure 1). Notably, one in five organizations in this group say they are expanding by more than 20% annually. This scale of expansion is difficult to implement without significant investment.
Figure 1. Enterprise data center capacity shows strong growth
Some suppliers — and some operators — may be surprised by this rate of growth since it follows a decade-long period in which enterprise data centers were often dismissed as expensive, inflexible and outdated by many executives. However, Uptime’s data, which has been consistent over the past three years and is backed by many conversations, suggests that enterprise investment is strong.
What is driving this growth in enterprise data center capacity? Partly, it is simply a demand for more digital services. However, companies also say that they are investing to enhance the resiliency of their data centers (45% of survey respondents) and to support a hybrid cloud strategy (37%). Moving to cloud architectures often requires an increase in data center capacity, especially if an organization is developing distributed resiliency architectures.
Cost may also be a factor that is driving enterprise investment. According to separate Uptime research, of those enterprise operators that compared the cost of provisioning workloads on-premises versus off-premises, most report that corporate data centers are less expensive than using colocation (56%, n=154) or public cloud (51%, n=151). This is particularly true for enterprises that have already made significant investments to expand capacity.
One looming problem for enterprises — and indeed for colocation companies — is the widely forecast increase in rack power density in the coming years. To accommodate this, new investments in cooling and power distribution will be required.
Four-fifths (82%) of enterprises say that they are expecting more demand for higher power densities in the next two to three years, but more than one-third (36%) say that they cannot accommodate this demand with their existing infrastructure (see Figure 2). As a result, many workloads with higher density demands will, as Uptime expects, be outsourced to third parties that have the requisite power and cooling infrastructure.
Figure 2. Many need new investment to meet expected power densities
In spite of the increased enterprise sector spending, the trend towards greater outsourcing to colocation and cloud companies is expected to remain strong (see The majority of enterprise IT is now off-premises). For example, colocation companies report more growth than their enterprise counterparts by 15 percentage points (79%, n=130), with twice as many reporting annual growth rates of more than 20% (40%, n=130).
Taken together, Uptime’s survey data shows that chief information officers are investing in cloud, hosting, colocation and enterprise data centers. While more workloads may be outsourced, the enterprise data center will most likely continue to grow and evolve. Large companies with complex mission-critical workloads, especially those that are heavily regulated, will most likely maintain on-premises sites.
However, as colocation and public cloud providers expand the depth of their services in response to the industry’s staffing, regulatory and supply chain challenges, enterprises will increasingly integrate these resources over the next decade.
The Uptime Intelligence View
Enterprise data centers have been characterized as being in decline over the past five years, especially in the context of the significant, double-digit annual growth of large colocation and public cloud organizations. But Uptime survey data has consistently shown investment in the sector. Although owning and operating data centers may not feature in the strategies employed by many large and especially newer organizations, enterprise facilities will likely remain essential to businesses beyond the medium term.
https://journal.uptimeinstitute.com/wp-content/uploads/2024/06/Colocation-and-public-cloud-growth-masks-enterprise-expansion-featured.jpg5401030Douglas Donnellan, Senior Research Associate, Uptime Institute, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngDouglas Donnellan, Senior Research Associate, Uptime Institute, [email protected]2024-06-05 15:00:002024-06-03 17:19:21Colocation and public cloud growth masks enterprise expansion
Human error has been — and remains to be — a major cause of outages in data centers. Uptime Intelligence’s research shows that about four in 10 operators have had a major outage in the past three years in which human error played a role (Annual outage analysis 2023). Half of these respondents said errors were made because staff failed to follow the correct procedures.
Thorough training, regular practice in equipment testing and work experience all help to reduce these errors — particularly in an emergency when a prompt reaction is crucial. An often underappreciated factor is the importance of mental performance and the effects of fatigue.
The relationship between shift length, fatigue and human error is well documented, but less clear is how the data center industry can define shifts that help minimize human error. The recommended best practices for other industries do not always translate into the data center world, where 24/7 service availability is the standard. Additionally, data center owners and operators wanting to optimize shift length to limit fatigue need to navigate employee preferences and region-specific constraints.
What the research says
Studies indicate there is a tipping point after which the performance of most staff deteriorates. Researchers at the Chinese University of Hong Kong Department of Systems Engineering and Engineering Management analyzed 241 papers on the relationship between shift length and occupational health and found that individuals working more than 10-hour shifts are significantly more likely to experience fatigue. A similar review from the Finnish Institute of Occupational Health shows the risk of workplace injury due to fatigue-related accidents across a range of industries is 15% higher in 10-hour shifts than 8-hour shifts, and jumps to 38% higher at 12 hours.
The errors that stem from disruption to circadian rhythms (biological processes over a 24-hour period) and mental exhaustion, and can lead to injury (e.g., from improper machine operation), can be considered products of cognitive oversight. This oversight, which is an unintentional failure to interpret events correctly, is at the root of much human error in data centers and can potentially result in not just injury, but a disruption to services.
Currently, 8- to10-hour single-day shifts are most common in the data center industry across all major regions, according to the Uptime Institute Data Center Staffing Survey 2023 (Operators struggle to overcome ongoing staff and skills shortage). There are, however, some geographic variations in the results: while 17% of all respondents report single-day shifts of more than 10 hours, Asia-Pacific leads at 22%. In contrast, respondents from Europe have more than three times as many 5- to 7-hour shifts as respondents from Asia-Pacific, but just over half (13%) report shifts of more than 10 hours.
Policy variations across different regions are clearly a factor in how data center owners and operators choose specific shift lengths for their employees, particularly in relation to night shifts. In Europe, labor laws in several major countries do not allow night shifts to exceed 8 or 10 hours as standard. Exceptions can be made to meet 24/7 staffing requirements, with night shifts extended to 12 hours, as long as employees are compensated with sufficient paid time off work.
These policy restrictions in Europe — along with the survey results indicating that European respondents provide more 5- to 7-hour shifts than respondents from other regions — may indicate that these companies are hiring more part-time employees to make up their staffing shortfall.
Companies in other regions attempting to replicate a similar strategy to reduce shift length face obstacles. Unlike European employees, workers in the US and several Latin-American countries risk losing access to healthcare coverage if their shifts become shorter. In the US there is no statutory obligation for the employer to provide healthcare coverage if employees work less than a 40-hour week. Staff are therefore reluctant to reduce their weekly hours.
Employers can limit long shifts — particularly night shifts (which have higher workplace injury risk) — to 8 hours. While this may appear to be an intuitive solution to avoid performance deterioration, Uptime Institute’s technical consultants advise that any change will not be without friction, and shift length may not even be the primary contributory factor. Some key considerations are:
Complacency and ownership. Shift structure should promote sharing of knowledge, break monotony of routines and help develop a sense of inclusion through rotating shifts. Shift silos, such as staff having a fixed schedule, with some only working at weekends or nights, may create unhealthy attitudes resulting from complacency or a lack of team cohesion.
Meeting staff lifestyle preferences. Despite data suggesting that long shifts are detrimental to performance, it is difficult for some operators to cut back hours. Uptime Institute technical consultants often see a staff preference for 12-hour shifts over several days, for the benefits of both additional overtime pay and extended blocks of time off work.
Relief shifts. Consensus in the industry is that extending shifts to more than 12 hours is ultimately worse for the business than sending employees home. For many operators, however, extending shifts to beyond 12 hours is unavoidable as a means of meeting staffing requirements. In practice, identifying individuals that can handle these extended shift lengths is not easy. It is not just very long shifts that carry the risks associated with fatigue. Staff not being able to rest sufficiently due to covering the shifts of absentee staff is another source of potential exhaustion, even if these shifts are not particularly long.
Long-term impact
Sourcing the appropriate, qualified individual for a relief shift in an understaffed industry is challenging. Typically, companies request employees to clock in on their rest days. This may work well for an employee during a week they are already off work, but it could also force employees to clock back on before they have had sufficient rest between shifts. Adding more staff into the shift rotation may prevent other employees from having to extend shifts or clock in with insufficient rest, but this simply patches over the root of the problem: the absence of staff from their scheduled shifts.
Operators need to monitor absence levels and understand the reasons behind these absence levels. The cumulative long-term impact of working shifts of more than 10 hours increases the risk of developing a range of health conditions, as well as fatigue. Although many data center operators have developed shift schedules to minimize errors, this needs to be balanced with a long-term view of health, work life balance and burn-out.
Planning ahead
Retroactively adjusting shift lengths of established employees could result in low morale and counterintuitively result in higher levels of fatigue as staff adjust to their new schedule changes. Many data center owners and operators, however, are undergoing significant infrastructure expansion, which need to be staffed on a shift rotation that minimizes human error and limits the risks of disruption to service availability. Owners and operators should consider the following recommendations:
Avoid shift lengths of more than 12 hours. Staffing levels and schedules should be defined to minimize the occurrences of abnormally long shifts.
Identify shifts that are not appropriate as relief shifts. Establish a system for ensuring well-rested coverage. Monitor overtime and rest periods between shifts to avoid calling in exhausted staff.
Consider individual employee preferences but remain mindful that shift workers often ignore potential risks to their own job performance and health when requesting their preferred schedule.
The Uptime Intelligence View
While many data center managers take a flexible approach to staffing, relief shifts remain a common source of human error. Employees experiencing long-term effects of extended shift work, in terms of risks to health and performance, may be perpetuating difficulties in filling the required shifts due to increased levels of staff absence. These factors can result in an operational stress of lower-than-ideal staffing levels in many facilities, leaving data center managers with few options to optimize shifts.
https://journal.uptimeinstitute.com/wp-content/uploads/2024/05/Long-shifts-in-data-centers-time-to-reconsider-featured.jpg5391030Rose Weinschenk, Research Associate, Uptime Institute, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngRose Weinschenk, Research Associate, Uptime Institute, [email protected]2024-05-22 15:00:002024-05-21 14:17:51Long shifts in data centers — time to reconsider?
Due to regulatory mandates and expanded stakeholder expectations, a growing share of operators are quantifying and publicly reporting a complete carbon dioxide equivalent (CO2e) emissions inventory for their data center infrastructure. An organization’s direct on-site emissions (classified as Scope 1 according to the Greenhouse Gas Protocol) and emissions from purchased energy sources (classified as Scope 2) are relatively easy to calculate from measured operational facility data and available grid emissions factors.
In contrast, Scope 3 data (comprising indirect emissions from the activities of other organizations and individuals) is more challenging to gather and has a high degree of uncertainty. This is because Scope 3 represents the Scope 1 and 2 emissions of both upstream suppliers and downstream buyers, which can be up to five layers deep in the value chain. By definition, this includes potentially millions of product users scattered around the globe. Despite the challenges, data center operators need to establish processes to collect and quantify their Scope 3 emissions while recognizing both the inherent uncertainty in the data and the limited levels of control over said emissions.
Carbon emissions (shorthand for CO2e greenhouse gases) embedded in IT equipment are an important Scope 3 category for IT infrastructure operators. The most valuable data is collected from manufacturers because they have the best insight into and connections with their supply chains. Where manufacturers do not supply the data, publicly available databases and proprietary estimation tools are useful for looking up or calculating embedded carbon values for IT equipment.
IT original equipment manufacturers (OEMs) can provide product carbon footprint (PCF) reports of typical configurations for some or all their machine models. These reports combine embedded carbon estimates from the product’s manufacture and transportation to the customer along with estimates of use emissions (Scope 2) and emissions associated with the management of end-of-life equipment (a separate Scope 3 category). The “manufacturing” and “transport” emissions categories are the most relevant for reporting embedded emissions from IT equipment. Tables 1a and Table 1b give select examples of PCF reports by some of the major OEMs.
Table 1a. Example server configurations from different manufacturers
Table 1b. Server manufacturers’ PCF reports for the example configurations
The “use” and “end of life” carbon footprint categories are of little value to a data center operator when purchasing IT equipment. The OEM estimate of emissions from operational energy use is redundant to the operator’s emission reports because this will be accounted for under Scope 2 calculations based on functional energy use and the data center emissions factor after the equipment is installed. Emissions generated by the end-of-use recovery and disposal of IT equipment are several years away and will depend on the vendor hired to manage the disposal process.
While manufacturers’ PCF reports are a convenient source of Scope 3 data, calculating carbon content for each of the four categories requires assumptions and highly uncertain estimates that limit the data’s accuracy and usefulness. Quantifying embedded carbon emissions is an academic exercise that provides little, if any, actionable insight for data center operators.
Embedded emissions: manufacture of IT equipment
The manufacture of IT equipment has two primary sources of carbon emissions: the emissions associated with the energy consumed by the manufacturing and assembly processes (typically 30% to 50% of the total) and those associated with component production, particularly semiconductors such as flash memory, dynamic random access memory (DRAM) and processors (50% to 70% of the total).
The supply chains are also geographically concentrated. Equipment manufacturing and assembly operations are mostly based in the Asia-Pacific region, where electricity emission factors vary between 0.4 and 0.8 metric tonnes of CO2 per megawatt-hour due to the high fossil fuel content in the generation mix. IT equipment has hundreds of components that are sourced from multiple companies around the globe.
IT hardware vendors, let alone buyers, cannot know the exact electricity mix as different components are manufactured and assembled in other countries with varying sources of electricity. The raw materials used in each component further complicate the problem because they are typically processed in different geographic areas, each with its own electricity source and associated variations in CO2 emissions.
The greenhouse gas emissions from semiconductor manufacturing are the result of energy consumption (about 40%), the use of perfluorinated compounds (about 20%) — these are high global warming potential gases used for chamber cleaning — and the production of the many materials and process chemicals used to fabricate a semiconductor device (about 40%).
Most of these emissions are generated deep in the supply chain of the server manufacturing process. Neither the equipment manufacturer nor the purchaser has the visibility to observe these processes or has direct leverage over the suppliers responsible for the energy use and manufacturing emissions. Academic research has found up to 30% uncertainties in IT equipment manufacturing and assembly emissions estimates.
Actions to drive emissions reductions in these processes need to be promoted by the individual suppliers and their immediate customers — there is little that the IT buyer can do to drive reductions. Importantly, there will be little difference in embedded carbon between IT OEMs for a comparable product configuration. Equally, the embedded carbon of IT equipment can be a trade-off with emissions from use because larger, more richly configured systems can also be more energy efficient.
The manufacturing emissions data for the three configurations of the HPE Proliant DL360 illustrates why manufacturing emissions estimates have high uncertainty. Using data from the EU, the base configuration, with a minimal (i.e., low component) configuration, has an embedded emissions estimate of 55% of the performance configuration. Because each server configuration is unique to the purchaser, estimating the emissions for a specific configuration adds to the 30% uncertainty inherent in assessing the embedded emissions.
This uncertainty escalates significantly for the Dell server cited in Tables 1a and 1b because the embedded manufacturing emissions are calculated for a base server with only 32 GB of memory, an improbable configuration for a data center. Reporting a low-end configuration is primarily responsible for the higher uncertainty in the Dell estimate compared with the HPE estimate.
An operator can reduce the uncertainty introduced by configuration choices by weighting the published manufacturing emissions. To make this adjustment, the weight of the purchased server (available from shipping documents) can be multiplied by the ratio of the manufacturing emissions to the weight of the server configuration used to estimate the PCF (available from the manufacturer) to get an adjusted estimate of the purchased server manufacturing PCF. This approach is best applied to the mainstream or performance configurations, as the base configuration has minimal quantities of DRAM and storage devices that contribute a significant portion of the manufacturing emissions footprint.
This adjustment may reduce the error and create a more representative manufacturing emissions estimate. However, given the limited value of this emission quantity, the additional time and effort to collect the data and perform the adjustment may not be worthwhile.
Embedded emissions: transportation to the customer
Product transportation from the assembly site to the customer accounts for a small percentage of embedded carbon in Scope 3 emission estimates. These vary based on geographical region and type of transport vehicle.
Greater geographical distances to the reporting company inevitably result in more fuel use and, therefore, higher emissions. Most products are assembled and shipped from Asia. The transport data for the HPE servers with a mainstream configuration has three to five times the transport emissions when shipped to Europe (98 kilograms, kg, of CO2e) or the US (150 kg of CO2e ) compared with Japan (31 kg of CO2e).
The most significant impact on transport emissions (and cost) is whether the product is shipped by sea or air. When demand for products is high and delivery time is critical, companies may opt for a faster transport method at the expense of greater CO2e emissions. The air transportation of goods has a 20 to 30 times larger carbon footprint than transport via ocean freight.
Use emissions
To reduce use emissions, data center operators should focus on energy use of IT instead of embedded carbon. This entails buying the most efficient IT equipment for their workloads as measured in work delivered per watt, maximizing hardware utilization, and deploying power management where the workload can tolerate the higher response times.
These aspects of evaluating or improving server efficiency are covered in several Uptime Intelligence Updates and Briefing Reports (listed at the end of this Update). Focusing on efficiency, and particularly the better utilization of IT assets, will not only drive lower Scope 2 through better energy performance but can also help Scope 3 inventories by requiring fewer IT systems to perform the same amount of work.
Manufacturers’ estimates of use emissions have no value to the purchaser. A sustainable purchase decision needs to minimize energy consumption by procuring the most efficient equipment for the workload. The use emissions will then be a function of the electricity emissions factor at the data center location where the IT equipment is installed. These will be reported as Scope 2 emissions in an environmental / sustainability report and required regulatory disclosures.
End-of-life product management emissions
The end-of-life product emissions estimate also offers no value to the data center operator. These emissions are not accounted for until the product is removed from service during a specified refresh cycle. The emissions associated with the refurbishment, recycling and disposal of the product and its components will be a function of the chosen end-of-life product management process.
Conclusion
Apart from massive IT buyers who can force shifts in upstream supply chain emissions, most data center infrastructure operators cannot influence the emissions generated within the supply chain. A select few hyperscalers can leverage their buying power by prioritizing sustainability in their purchasing decisions. And while smaller data centers can be indirect beneficiaries of hyperscaler-driven innovations in the industry, they cannot rely on this possibility as an actionable strategy for carbon reduction. Instead, most data centers that wish to track and curb Scope 3 emissions can focus on the following:
Require access to PCF for all products. IT buyers should expect to be able to obtain and compare equipment PCF data for their reporting purposes and to consider estimates when selecting their configurations. Buyers can signal their preference for transparency to vendors and, over time, choose to work with those companies that are more transparent in their reporting and methodology for calculating estimates.
Focus on IT energy performance. Scope 3 emissions are becoming an important component of emissions inventory reports, but Scope 2 emissions will likely account for most life-cycle emissions. Even for those data centers that use low-carbon power sources, good stewardship of energy resources should prioritize the reduction of energy consumption. Driving workload consolidation, a key component to helping infrastructure energy performance, will not only help energy performance but will also benefit the Scope 3 balance by using fewer IT systems and / or less hardware. Consequently, product configuration decisions should not be based solely on PCF for a single piece of equipment because better-performing, and thus potentially more efficient, configurations will often have more silicon and components (i.e., bigger processors, more memory, more storage), accompanied by a higher Scope 3 bill.
Factor in Scope 3 emissions into decisions about IT systems refresh. A relatively recent development in server technology is that replacing an older system with a newer one may not automatically mean better energy performance. Modern servers come with the caveat that, unless given a substantial amount of work, their utilization will not be high enough to perform more work for each kilowatt-hour of consumed energy. Without a considerable efficiency advantage, the new server may not be able to recover its manufacturing emissions.
The Uptime Intelligence View
Data center managers are facing mandates to report Scope 3 C02e emissions. Estimating the embedded carbon in IT equipment fails to produce actionable data because the values have a high degree of uncertainty and provide little guidance on how to reduce manufacturing emissions. Innovative operators and owners will instead focus on reducing their own direct emissions and forming collaborative partnerships with suppliers and manufacturers to encourage transparency in emissions reporting.
https://journal.uptimeinstitute.com/wp-content/uploads/2024/05/What-does-embedded-carbon-really-represent-featured.jpg5391030Jay Dietrich, Research Director of Sustainability, Uptime Institute, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngJay Dietrich, Research Director of Sustainability, Uptime Institute, [email protected]2024-05-08 15:00:002024-05-07 10:02:05What does embedded carbon of IT really represent?
A growing number of data center operators and equipment vendors are anticipating the proliferation of direct liquid cooling systems (DLC) over the next few years. As far as projections go, Uptime Institute’s surveys agree: the industry consensus for the mainstream adoption of liquid-cooled IT converges on the latter half of the 2020s.
DLC systems, such as cold plate and immersion, have already proved themselves in technical computing applications as well as mainframe systems for decades. More recently, IT and facility equipment vendors, together with some of the larger data center operators, have started working on commercializing DLC systems for much broader adoption.
A common theme running through both operators’ expectations of DLC and vendors’ messaging is that a main benefit of DLC is improved energy efficiency. Specifically, the superior thermal performance of liquids compared with air will dramatically reduce the consumption of electricity and water in heat rejection systems, such as chillers, as well as increase opportunities for year-round free cooling in some climates. In turn, the data center’s operational sustainability credentials would improve significantly. Better still, the cooling infrastructure would become leaner, cost less and be easier to maintain.
These benefits will be out of reach for many facilities for several practical reasons. The reality of mainstream data centers combined with the varied requirements of generic IT workloads (as opposed to high-performance computing) means that cost and energy efficiency gains will be unevenly distributed across the sector. Many of the operators deploying DLC systems in the next few years will likely prioritize speed and ease of installation into existing environments, as well as focus on maintaining infrastructure resiliency — rather than aiming for maximum DLC efficiency.
Another major factor is time: the pace of adoption. The use of DLC in mission-critical facilities, let alone a large-scale change, represents a wholesale shift in cooling design and infrastructure operations, with industry best practices yet to catch up. Adding to the hurdles is that many data center operators will deem the current DLC systems limited or uneconomical for their applications, slowing rollout across the industry.
Cooling in mixed company
Data center operators retrofitting a DLC system into their existing data center footprint will often do so gradually in an iterative process, accumulating operational experience. Operators will need to manage a potentially long period when liquid-cooled and air-cooled IT systems and infrastructure coexist in the same data center. This is because air-cooled IT systems will continue to be in production for many years to come, with typical life cycles of between five and seven years. In many cases, this will also mean a cooling infrastructure (for heat transport and rejection) shared between air and liquid systems.
In these hybrid environments, DLC’s energy efficiency will be constrained by the supply temperature requirements of air-cooling equipment, which puts a lid on operating at higher temperatures —compromising the energy and capital efficiency benefits of DLC on the facility side. This includes DLC systems that are integrated with chilled water systems (running the return facility loop as supply for DLC may deliver some marginal gains) and DLC implementations where the coolant distribution unit (CDU) is cooled by the cold air supply.
Even though DLC eliminates many, if not all, server fans and reduces airflow requirements for major gains in total infrastructure energy efficiency, these gains will be difficult to quantify for real-world reporting purposes because IT fan power is not a commonly tracked metric — it is hidden in the IT load.
It will take years for DLC installations to reach the scale where a dedicated cooling infrastructure can be justified as a standard approach, and for energy efficiency gains to have a positive effect on the industry’s energy performance, such as in power usage effectiveness (PUE) numbers. Most likely, any impact on PUE or sustainability performance from DLC adoption will remain imperceptible for years.
Hidden trade-offs in temperature
There are other factors that will limit the cooling efficiency seen with DLC installations. At the core of DLC’s efficiency potential are the liquid coolants’ favorable thermal properties, which enable them to capture IT heat more effectively. The same thermal properties can also be used for a cooling performance advantage as opposed to maximizing cooling system efficiency. When planning for and configuring a DLC system, some operators will give performance, underpinned by lower operating temperatures, more weight in their balancing act between design trade-offs.
Facility water temperature is a crucial variable in this trade-off. Many DLC systems can cool IT effectively with facility water that is as high as 104°F (40°C) or even higher in specific cases. This minimizes capital and energy expenditure (and water consumption) for the heat rejection infrastructure, particularly for data centers in hotter climates.
Yet, even when presented with the choice, a significant number of facility and IT operators will choose lower supply temperatures for their DLC systems’ water supply. This is because there are substantial benefits to using lower water temperatures — often below 68°F (20°C) — despite the costs involved. Chiefly, a low facility water temperature reduces the flow rate needed for the same cooling capacity, which eases pressure on pipes and pumping.
Conversely, organizations that use warm water and DLC to enable data center designs with dry coolers face planning and design uncertainties. High facility water temperatures not only require higher flow rates and pumping power but also need to account for potential supply temperature reductions in the future as IT requirements become stricter due to evolving server silicon. For a given capacity, this could mean more or larger dry coolers, which potentially require upgrades with mechanical or evaporative assistance. Data center operators that want free cooling benefits and a light mechanical plant have a complex planning and design task ahead.
On the IT side, taking advantage of low temperatures makes sense when maximizing the performance and energy efficiency of processors because silicon exhibits lower static power losses at lower temperatures. This approach is already common today because the primary reason for most current DLC installations is to support high IT performance objectives. Data center operators currently use DLC primarily because they need to cool high-density IT rather than conserve energy.
The bulk of DLC system sales in the coming years will likely be to support high-performance IT systems, many of which will use processors with restricted temperature limits — these models are sold by chipmakers specifically to maximize compute speeds. Operators may select low water temperatures to accommodate these low-temperature processors and to maximize the cooling capacity of the CDU. In effect, a significant share of DLC adoption will likely represent an investment in performance rather than facility efficiency gains.
DLC changes more than the coolant
For all its potential benefits, a switch to DLC raises some challenges to resiliency design, maintenance and operation. These can be especially daunting in the absence of mature and application-specific guidance from standards organizations. Data center operators that support business-critical workloads are unlikely to accept compromises to resiliency standards and realized application availability for a new mode of cooling, regardless of the technical or economic benefits.
In the event of a failure in the DLC system, cold plates tend to offer much less than a minute of ride-through time because of their small coolant volume. The latest high-powered processors would have only a few seconds of ride-through at full load when using typical cold plate systems. Operating at high temperatures means that there are thin margins in a failure, something that operators of mainstream, mission-critical facilities will be mindful of when making these decisions.
In addition, implementing concurrent maintainability or fault tolerance with some DLC equipment may not be practical. As a result, a conversion to DLC can demand that organizations maintain their infrastructure resiliency standard in a different way from air cooling. Operators may consider protecting coolant pumps with an uninterruptible power supply (UPS) and using software resiliency strategies when possible.
Organizational procedures for procurement, commissioning, maintenance and operations need to be re-examined because DLC disrupts the current division of facilities and IT infrastructure functions. For air-cooling equipment, there is strong consensus regarding the division of equipment between facilities and IT teams, as well as their corresponding responsibilities in procurement, maintenance and resiliency. No such consensus exists for liquid cooling equipment. A resetting of staff responsibilities will require much closer cooperation between facilities and IT infrastructure teams.
These considerations will temper the enthusiasm for large-scale use of DLC and make for a more measured approach to its adoption. As operators increasingly understand the ways in which DLC deployment is not straightforward, they will bide their time and wait for industry best practices to mature and fill their knowledge gaps.
In the long term (i.e., 10 years or more), DLC is likely to handle a large share of IT workloads, including a broad set of systems running business applications. This will happen as standardization efforts, real-world experience with DLC systems in production environments and mature guidance take shape in new, more robust products and best practices for the industry. To grow the number and size of deployments of cold plate and immersion systems in mission-critical facility infrastructure, DLC system designs will have to meet additional technical and economic objectives. This will complicate the case for efficiency improvements.
The cooling efficiency figures of today’s DLC products are often derived from niche applications that differ from typical commercial data centers — and real-world efficiency gains from DLC in mainstream data centers will necessarily be subject to more trade-offs and constraints.
In the near term, the business case for DLC is likely to tilt in favor of prioritizing IT performance and ease of retrofitting with a shared cooling infrastructure. Importantly, choosing lower, more traditional water supply temperatures and utilizing chillers appears to be an attractive proposition for added resiliency and future-proofing. As many data center operators deem performance needs and mixed environments to be more pressing business concerns — free cooling aspirations, along with their benefits in sustainability, will have to wait for much of the industry.
https://journal.uptimeinstitute.com/wp-content/uploads/2024/04/DLC-will-not-come-to-the-rescue-of-data-center-sustainability-featured.jpg5391030Jacqueline Davis, Research Analyst, Uptime Institute, [email protected]https://journal.uptimeinstitute.com/wp-content/uploads/2022/12/uptime-institute-logo-r_240x88_v2023-with-space.pngJacqueline Davis, Research Analyst, Uptime Institute, [email protected]2024-04-25 15:00:002024-04-24 13:58:20DLC will not come to the rescue of data center sustainability
Understanding how server power management works
/in Design, Executive, Operations/by Daniel Bizo, Research Director, Uptime Institute Intelligence, [email protected]Uptime Intelligence regularly addresses IT infrastructure efficiency, particularly servers, in our reports on data center energy performance and sustainability. Without active contribution from IT operations, facility operations alone will not be able to meet future energy and sustainability demands on data center infrastructure. Purchases of renewable energy and renewable energy certificates will become increasingly — and, in many locations, prohibitively — expensive as demand outstrips supply, making the energy wasted by IT even more costly.
The power efficiency of a server fleet, that is, how much work servers perform for the energy they use, is influenced by multiple factors. Hardware features receive the most attention from IT buyers: the server’s technology generation, the configuration of the system and the selection of power supply or fan settings. The single most significant factor that affects server efficiency, however, is the level at which the servers are typically utilized; a seemingly obvious consideration — and enough for regulators to include it as a reporting requirement in the EU’s new Energy Efficiency Directive (see EED comes into force, creating an enormous task for the industry). Even so, the process of sourcing the correct utilization data for the purposes of power efficiency calculations (as opposed to capacity planning) remains arguably misunderstood (see Tools to watch and improve power use by IT are underused).
The primacy of server utilization in data center efficiency has increased in recent years. The latest server platforms are only able to deliver major gains in energy performance when put to heavy-duty work — either by carrying a larger software payload through workload consolidation, or by running scalable, large applications. If these conditions are not met, running lighter or bursty workloads on today’s servers (regardless of whether based on Intel or AMD chips) will deliver only a marginal, if any, improvement in the power efficiency compared with many of the supposedly outdated servers that are five to seven years old (see Server efficiency increases again — but so do the caveats).
Cycles of a processor’s sleep
This leads into the key discussion point of this report: the importance of taking advantage of dynamic energy saving features. Settings for power and performance management of servers are often an overlooked — and underused — lever in improving power efficiency. Server power management techniques affect power use and overall system efficiency significantly. This effect is even more pronounced for systems that are only lightly loaded or spend much of their time doing little work: for example, servers that run enterprise applications.
The reduction in server power demand resulting from power management can be substantial. In July 2023 Uptime Intelligence published a report discussing data (although sparse) that indicates 10% to 20% reductions in energy use from enabling certain power-saving modes in modern servers, with only a marginal performance penalty when running a Java-based business logic (see The strong case for power management). Energy efficiency gains will depend on the type of processor and hardware configuration, but we consider the results indicative for most servers. Despite this, our research indicates that many, if not most, IT operations do not use power management features.
So, what are these power management settings? Server power management settings are governed by the firmware statically (what modes are enabled upon system start up) and dynamically by the operating system or hypervisor once running through the Advanced Configuration and Power Interface.
There are many components in a server that may have power management features, enabling them to run slower or power off. Operating systems also have their own software mechanisms, such as suspending their operation and saving the machine state to central memory or the storage system.
But in servers, which tend to be always powered on, it is the processors’ power management modes that dictate most of the energy gains. Modern processors have sophisticated power management features for idling, that is, when the processor does not execute code. These are represented by various levels of C-states (the C stands for CPU) denoted by numbers, such as C1 and C2 (with C0 being the fully active state).
The number of these states has expanded over time as chip architects introduce new, more advanced power-saving features to help processors reduce their energy use when doing no work. The chief benefit of these techniques is to minimize leakage currents that would otherwise increasingly permeate modern processor silicon.
The higher the C-state number, the more of its circuitry the CPU sends to various states of sleep. In summary:
Skipped numbers, such as C2 and C5, are incremental, transitionary processor power states between main states. Not all these C-states are available on all processor architectures.
A good sleep in a millisecond
The levels of C-states and understanding them matters because they largely define the cost in performance and the benefit in power. The measured results of 10% to 20% reduction in energy use when enabling certain power management features, as discussed earlier, have allowed the server processor (an AMD model) to enter processor power states up to C6. These sleep states save power even when the server, on a human level of perception, is processing database transactions and responding to queries.
This is because processors operate on a timescale measured in nanoseconds, while software-level requests between commands can take milliseconds even on a busy machine. This is a factor of one million difference: milliseconds between work assignments represent millions of processor cycles waiting. For modern server processors, some of the many cores may often have no work to do for a second or more, which is an eternity on the processor’s time scale. On a human scale, a comparable time would be several years of inactivity.
However, there is a cost associated with the processor cores going to sleep. Entering ever deeper sleep states across processor cores or entire chips can take thousands of cycles, and as many as tens of thousands of cycles to wake up and reinstate operation. This added latency to respond to wake-up requests is what shows up as a loss of performance in measurements. In the reference measurement running the Java-based business logic, this is in the 5% to 6% range — arguably a small price to pay.
Workloads will vary greatly in the size of the performance penalty introduced by this added latency. Crucially, they will differ even more in how costly the lost application performance is for the business — high-frequency trading or processing of high volumes of mission-critical online transactions are areas where any loss of performance is unacceptable. Another area may include storage servers with heavy demand for handling random read-write operations at low latency. But a vast array of applications will not see material change to the quality of service.
Using server power management is not a binary decision either. IT buyers can also calibrate the depth of sleep they enable for the server processor (and other components) to enter. Limiting it to C3 or C1E may deliver better trade-offs. Many servers, however, are not running performance-critical applications and spend most of their time doing no work — even if it seems that they are often, by human standards, called upon. For servers that are often idle, the energy saved can be in the 20% to 40% range, which can amount to tens of watts for every lightly loaded or idle server.
Optimizing server energy performance does not stop with C-states. Performance-governing features (setting performance levels when the processor is actively working), known as P-states, offer another set of possibilities to find better trade-offs between power and performance. Rather than minimizing waste when the processor idles, P-states direct how much power should be expended on getting the work done. Future reports will introduce P-states for a more complete view of server power and performance management for IT infrastructure operators that are looking for further options in meeting their efficiency and sustainability objectives.
The Uptime Intelligence View
A server processor’s power management is a seemingly minute function buried under layers of technical details of an infrastructure. Still, its role in the overall energy performance of a data center infrastructure will be outsized for many organizations. In the near term, blanket policies (or simply IT administrator habits) of keeping server power management features switched off will inevitably be challenged by internal stakeholders in pursuit of cost efficiencies and better sustainability credentials; or, possibly in the longer term, by regulators catching on to technicalities and industry practices. Technical organizations at enterprises and IT service providers will want to map out server power management opportunities ahead of time.
EU battery regulations: what do the new rules mean?
/in Executive, Operations/by Rosa Lawrence, Research Associate, Uptime Institute, [email protected]The European Green Deal, a set of policy initiatives approved in 2020, aims for a sustainable and competitive economy with net-zero greenhouse gas emissions by 2050. Along with the legislation driving this transition, such as the Energy Efficiency Directive recast (see EED comes into force, creating an enormous task for the industry), the strategy will require much higher rates of electrification in transport and industries to displace the use of fossil fuels. This aim is combined with the policy objective of adding large amounts of renewable power generation capacity.
However, this direction is leading toward a new environmental challenge: increased sales of electric vehicles (EVs) will create future end-of-life battery problems, drawing attention to the unresolved issue of reusing and recycling large battery banks. Many industrial stationary applications are also seeing a strong take-up of EV-type (mostly lithium-ion) batteries for a variety of reasons. These include the displacement of valve-regulated lead-acid (VRLA) batteries, which are highly recycled, new energy storage installations for grid demand-response schemes and the elimination of standby engine generators.
Until now, this area has been governed by the 2006 Battery Directive (2006/66/EC). However, this directive is being replaced by Regulation 2023/1542 — the main objective of which is to create an updated set of rules to ensure high sustainability standards regardless of the battery chemistry. As an EU Regulation, it applies automatically to all member states without implementation in national laws.
The new regulations address aspects such as carbon footprint, recycled content, safety, labeling and end-of-life management. Industrial customers, including data center suppliers and their customers, will need to start reporting by mid-2025 — although this date may yet change. Although these rules only apply to members of the EU, its standards and laws are often replicated in other countries.
The 2006 Battery Directive was put in place to mitigate the environmental impact of battery production and disposal of waste batteries. It introduced recycling and treatment targets, restrictions on some hazardous substances, labeling requirements (for hazardous substances and instructions for proper disposal), reporting obligations and extended producer responsibility.
Lead-acid versus Li-ion recycling: the facts
The most common batteries used in uninterruptible power supply (UPS) systems are VRLA and Li-ion batteries (of which several sub-types exist). Lead-acid batteries have the highest collection and recycling rates. In the EU, the recycling rate for automotive starter batteries is 99% and more than 90% of the lead is recovered. The figure for stationary applications, which includes data centers, is likely to be similarly high due to the stringent regulations and economic incentives to recycle.
In 2021, all EU member states met the target recycling rate of 65% by weight for lead-acid batteries (both automotive and non-automotive).
The recycling process of lead-acid batteries consists of draining the electrolyte, opening the casing and separating the materials. The lead plates are then smelted to obtain molten lead, which is purified and refined before being cast into ingots for reuse. The plastic components are also recycled. Lead-acid batteries have few components and contain approximately 70% lead, which means that it is an efficient process. It is also profitable because recycled lead can be used in the manufacture of new batteries and is recyclable at relatively low temperatures, which require less energy.
For Li-ion batteries, the view is more complicated. Currently, it is cheaper to mine the metals to make new Li-ion cells (regardless of Li-ion chemistry) than it is to recycle used batteries. As a result, the much higher environmental footprint of the supply chain to produce Li-ion cells has so far been an externality and not priced into the cost of making Li-ion batteries. This factors heavily into its current market advantage in price-performance compared to other, environmentally less damaging cell chemistries.
The two most common processes for recycling spent Li-ion batteries are pyrometallurgy and hydrometallurgy. During both processes, the batteries are discharged and dismantled. They are then either smelted at high temperatures or leached to recover high-value cathode materials, such as cobalt, nickel and copper. During pyrometallurgical smelting, the lithium is lost in the furnace, making the process for lithium not sustainable. Future recycling processes for Li-ion cells are in development and will likely involve a combination of heat treatment and leaching in various concentrations of acid to maximize recovery of valuable metals.
These processes are energy-intensive and therefore expensive to operate, as well as producing gaseous pollutants and industrial waste. According to some battery vendors, the costs involved with the transport and recycling of Li-ion batteries, which is considered a hazardous waste, are substantial.
This is a major reason behind the current expectation that Li-ion battery packs will find secondary and even tertiary uses rather than being recycled for their raw materials. Compared with lead-acid batteries, this is possible due to Li-ion cells’ higher endurance and shelf life. The new battery regulation actively considers this scenario with the introduction of battery passports.
What are the new rules?
The phased implementation of the rules (Regulation 2023/1542) begins in July 2024 and regulates the carbon footprint, recycled content of new batteries, labeling and the introduction of an online battery information system. The new battery regulation controls all battery chemistries, with rules varying by battery category, for example, EV, industrial and portable. Recycling targets differ between chemistries, with specific targets for the recovery of cobalt, lead, lithium and nickel. Figure 1 sets out the major milestones of the regulatory rollout for EU member states, as prescribed in the regulation.
Figure 1. Timeline of the EU’s battery regulation
New batteries put to market will be subject to mandatory minimum levels of recycled content requirements. From 2030, batteries will need to contain a minimum recycled content of 12% for cobalt, 4% for lithium, 4% for nickel and 85% for lead. By 2035, these thresholds will increase to 20% cobalt, 10% lithium, 12% nickel and 85% lead.
Alongside these requirements, there are also recycling efficiency and material recovery targets for end-of-life batteries. By the end of 2030, used batteries will have a recycling target by weight of 80% for lead-acid and 70% for Li-ion. The material recovery target is 95% for cobalt, copper, lead and nickel and 70% for lithium.
What does this mean for data center operators?
The new rules will mostly affect battery producers; however, some responsibilities will fall on end users, such as data center operators. These include performing due diligence to verify vendor (product carbon footprint) and recycler claims (environmental credentials of the recycling process), as well as maintaining up-to-date battery passports during the use of the products.
From August 18, 2025, battery suppliers and data center operators (with some exceptions), will have a legal requirement to adopt a battery due diligence policy covering the social and environmental risks. This policy will need to include annual reports on the risks in the supply chain and the steps taken to manage them, transparency on sourcing raw and recycled materials, and structuring an internal management system to support it. The due diligence policy should be verified by a third party and communicated to suppliers and the public via annual reports.
There are exceptions for suppliers and buyers of batteries with an annual net turnover of less than €40 million ($43 million) and those using batteries that have undergone preparation for reuse, repurposing, or remanufacturing before being placed on the market.
The introduction of battery passports in 2026 will affect both suppliers and end users, including data center operators. Battery producers will be required to report on properties such as the chemistry, carbon footprint and recycled content, while it will be the end user’s responsibility to update the battery passport on the state of its health throughout its life. This will likely include maintenance entries but also any substantial events or accidents, such as deviations from standard operating environmental conditions, overcharging or deep discharging, and other impacts.
Battery passports will be key to enabling a second-hand market for batteries that are appropriate for reuse. Alongside the labeling of batteries, this may lead to improvements in Li-ion battery recycling by simplifying the separation process by sorting batteries by chemistry before the start of the recycling process. However, the technical implementation of the battery passport has not been stipulated in the new regulation and will be left to future cooperation between EU member states.
The regulation states that producers shall cover the necessary costs incurred by the collection and recycling of waste batteries. Lead-acid batteries have an inherent economic value at the end of their useful lives, which guarantees incentives for both buyers and sellers to promote recycling. Li-ion batteries, however, currently incur substantial costs to pay for recycling. According to battery makers, this can amount to as much as the price of new Li-ion batteries. Another potentially overlooked detail is the cost of transporting large amounts of Li-ion batteries that are classified as hazardous and pose a fire risk.
It is possible (or even likely) that end users may see a marked increase in the price of Li-ion batteries — the selling price will need to cover the recycling costs as a result of this extended producer responsibility. Data center operators, with hundreds of batteries in their UPS systems, may have to set up databases and processes to ensure they are reliably tracked.
The regulation stipulates that the ultimate responsibility for managing end-of-life batteries will fall on suppliers — in practical terms: taking batteries from end-users for no charge and ensuring the batteries are reused or recycled. However, end users should also exercise due diligence, even when they are not legally required to at present. Data center owners and operators should be aware that battery manufacturers may overstate their recycling capabilities. This is particularly relevant given the long lifespan of industrial Li-ion batteries, which can remain in use for 10 to 15 years or longer. Companies placing such batteries on the market may not have adequate recycling plans in place.
End users should also consider what technology is used in the recycling facilities, and even verify the existence of these facilities by checking their reported location using satellite imagery and public records. Inevitably, some battery vendors will go out of business, leaving end users with a potentially costly liability.
Additionally, when considering Scope 3 emissions reporting (in accordance with the Greenhouse Gas Protocol), the new recycling obligations add complexity. End users will need to consider carbon emissions from transportation and recycling processes. While some may argue that recycling offsets carbon emissions compared with manufacturing new batteries from raw materials, this claim may not withstand closer scrutiny.
Where could these rules go in the future?
The 2023 battery regulation provides a timeline of implementation, but the rules will need further clarification when they start to come into effect. Potential secondary legislation could involve standardizing calculations for carbon footprint, recycling efficiency and material recovery. More clarification may follow for the implementation and functioning of the electronic exchange system as well as specifications for the content and accessibility of battery passports.
Additionally, EU member states may choose to enact further requirements (as long as they are not in conflict with EU law) to stimulate investments in research and development related to carbon footprint reduction and sustainability in battery production and recycling.
The Uptime Intelligence View
The new EU Battery Regulation is primarily a response to the mass-market adoption of EVs, however, it also covers industrial stationary applications, such as mission-critical power systems.
The EU’s objective is to ensure that huge quantities of new batteries will not simply end up as hazardous waste at the end of their lives but will either find new uses or be recycled to make new battery cells. It will also level the playing field with lead-acid batteries and other, more readily recyclable chemistries.
Rosa Lawrence, Research Associate, Uptime Institute, [email protected]
Daniel Bizo, Research Director, Uptime Institute, [email protected]
Colocation and public cloud growth masks enterprise expansion
/in Executive, Operations/by Douglas Donnellan, Senior Research Associate, Uptime Institute, [email protected]The colocation and public cloud sectors of the digital infrastructure industry continue to make headlines, with many organizations planning large-scale capacity expansion to meet rising demand. However, there is also a less public expansion underway — enterprises operators, for the third successive year, say they are going to invest in more data center capacity in 2024.
Results from the Uptime Institute Capacity Trends Survey 2023 reveal that 64% of enterprise operators are growing their data center capacity — a six percentage-point uptick from two years earlier in 2021 (see Figure 1). Notably, one in five organizations in this group say they are expanding by more than 20% annually. This scale of expansion is difficult to implement without significant investment.
Figure 1. Enterprise data center capacity shows strong growth
Some suppliers — and some operators — may be surprised by this rate of growth since it follows a decade-long period in which enterprise data centers were often dismissed as expensive, inflexible and outdated by many executives. However, Uptime’s data, which has been consistent over the past three years and is backed by many conversations, suggests that enterprise investment is strong.
What is driving this growth in enterprise data center capacity? Partly, it is simply a demand for more digital services. However, companies also say that they are investing to enhance the resiliency of their data centers (45% of survey respondents) and to support a hybrid cloud strategy (37%). Moving to cloud architectures often requires an increase in data center capacity, especially if an organization is developing distributed resiliency architectures.
Cost may also be a factor that is driving enterprise investment. According to separate Uptime research, of those enterprise operators that compared the cost of provisioning workloads on-premises versus off-premises, most report that corporate data centers are less expensive than using colocation (56%, n=154) or public cloud (51%, n=151). This is particularly true for enterprises that have already made significant investments to expand capacity.
One looming problem for enterprises — and indeed for colocation companies — is the widely forecast increase in rack power density in the coming years. To accommodate this, new investments in cooling and power distribution will be required.
Four-fifths (82%) of enterprises say that they are expecting more demand for higher power densities in the next two to three years, but more than one-third (36%) say that they cannot accommodate this demand with their existing infrastructure (see Figure 2). As a result, many workloads with higher density demands will, as Uptime expects, be outsourced to third parties that have the requisite power and cooling infrastructure.
Figure 2. Many need new investment to meet expected power densities
In spite of the increased enterprise sector spending, the trend towards greater outsourcing to colocation and cloud companies is expected to remain strong (see The majority of enterprise IT is now off-premises). For example, colocation companies report more growth than their enterprise counterparts by 15 percentage points (79%, n=130), with twice as many reporting annual growth rates of more than 20% (40%, n=130).
Taken together, Uptime’s survey data shows that chief information officers are investing in cloud, hosting, colocation and enterprise data centers. While more workloads may be outsourced, the enterprise data center will most likely continue to grow and evolve. Large companies with complex mission-critical workloads, especially those that are heavily regulated, will most likely maintain on-premises sites.
However, as colocation and public cloud providers expand the depth of their services in response to the industry’s staffing, regulatory and supply chain challenges, enterprises will increasingly integrate these resources over the next decade.
The Uptime Intelligence View
Enterprise data centers have been characterized as being in decline over the past five years, especially in the context of the significant, double-digit annual growth of large colocation and public cloud organizations. But Uptime survey data has consistently shown investment in the sector. Although owning and operating data centers may not feature in the strategies employed by many large and especially newer organizations, enterprise facilities will likely remain essential to businesses beyond the medium term.
Long shifts in data centers — time to reconsider?
/in Executive, Operations/by Rose Weinschenk, Research Associate, Uptime Institute, [email protected]Human error has been — and remains to be — a major cause of outages in data centers. Uptime Intelligence’s research shows that about four in 10 operators have had a major outage in the past three years in which human error played a role (Annual outage analysis 2023). Half of these respondents said errors were made because staff failed to follow the correct procedures.
Thorough training, regular practice in equipment testing and work experience all help to reduce these errors — particularly in an emergency when a prompt reaction is crucial. An often underappreciated factor is the importance of mental performance and the effects of fatigue.
The relationship between shift length, fatigue and human error is well documented, but less clear is how the data center industry can define shifts that help minimize human error. The recommended best practices for other industries do not always translate into the data center world, where 24/7 service availability is the standard. Additionally, data center owners and operators wanting to optimize shift length to limit fatigue need to navigate employee preferences and region-specific constraints.
What the research says
Studies indicate there is a tipping point after which the performance of most staff deteriorates. Researchers at the Chinese University of Hong Kong Department of Systems Engineering and Engineering Management analyzed 241 papers on the relationship between shift length and occupational health and found that individuals working more than 10-hour shifts are significantly more likely to experience fatigue. A similar review from the Finnish Institute of Occupational Health shows the risk of workplace injury due to fatigue-related accidents across a range of industries is 15% higher in 10-hour shifts than 8-hour shifts, and jumps to 38% higher at 12 hours.
The errors that stem from disruption to circadian rhythms (biological processes over a 24-hour period) and mental exhaustion, and can lead to injury (e.g., from improper machine operation), can be considered products of cognitive oversight. This oversight, which is an unintentional failure to interpret events correctly, is at the root of much human error in data centers and can potentially result in not just injury, but a disruption to services.
Currently, 8- to10-hour single-day shifts are most common in the data center industry across all major regions, according to the Uptime Institute Data Center Staffing Survey 2023 (Operators struggle to overcome ongoing staff and skills shortage). There are, however, some geographic variations in the results: while 17% of all respondents report single-day shifts of more than 10 hours, Asia-Pacific leads at 22%. In contrast, respondents from Europe have more than three times as many 5- to 7-hour shifts as respondents from Asia-Pacific, but just over half (13%) report shifts of more than 10 hours.
Policy variations across different regions are clearly a factor in how data center owners and operators choose specific shift lengths for their employees, particularly in relation to night shifts. In Europe, labor laws in several major countries do not allow night shifts to exceed 8 or 10 hours as standard. Exceptions can be made to meet 24/7 staffing requirements, with night shifts extended to 12 hours, as long as employees are compensated with sufficient paid time off work.
These policy restrictions in Europe — along with the survey results indicating that European respondents provide more 5- to 7-hour shifts than respondents from other regions — may indicate that these companies are hiring more part-time employees to make up their staffing shortfall.
Companies in other regions attempting to replicate a similar strategy to reduce shift length face obstacles. Unlike European employees, workers in the US and several Latin-American countries risk losing access to healthcare coverage if their shifts become shorter. In the US there is no statutory obligation for the employer to provide healthcare coverage if employees work less than a 40-hour week. Staff are therefore reluctant to reduce their weekly hours.
Employers can limit long shifts — particularly night shifts (which have higher workplace injury risk) — to 8 hours. While this may appear to be an intuitive solution to avoid performance deterioration, Uptime Institute’s technical consultants advise that any change will not be without friction, and shift length may not even be the primary contributory factor. Some key considerations are:
Long-term impact
Sourcing the appropriate, qualified individual for a relief shift in an understaffed industry is challenging. Typically, companies request employees to clock in on their rest days. This may work well for an employee during a week they are already off work, but it could also force employees to clock back on before they have had sufficient rest between shifts. Adding more staff into the shift rotation may prevent other employees from having to extend shifts or clock in with insufficient rest, but this simply patches over the root of the problem: the absence of staff from their scheduled shifts.
Operators need to monitor absence levels and understand the reasons behind these absence levels. The cumulative long-term impact of working shifts of more than 10 hours increases the risk of developing a range of health conditions, as well as fatigue. Although many data center operators have developed shift schedules to minimize errors, this needs to be balanced with a long-term view of health, work life balance and burn-out.
Planning ahead
Retroactively adjusting shift lengths of established employees could result in low morale and counterintuitively result in higher levels of fatigue as staff adjust to their new schedule changes. Many data center owners and operators, however, are undergoing significant infrastructure expansion, which need to be staffed on a shift rotation that minimizes human error and limits the risks of disruption to service availability. Owners and operators should consider the following recommendations:
The Uptime Intelligence View
While many data center managers take a flexible approach to staffing, relief shifts remain a common source of human error. Employees experiencing long-term effects of extended shift work, in terms of risks to health and performance, may be perpetuating difficulties in filling the required shifts due to increased levels of staff absence. These factors can result in an operational stress of lower-than-ideal staffing levels in many facilities, leaving data center managers with few options to optimize shifts.
What does embedded carbon of IT really represent?
/in Design, Executive, Operations/by Jay Dietrich, Research Director of Sustainability, Uptime Institute, [email protected]Due to regulatory mandates and expanded stakeholder expectations, a growing share of operators are quantifying and publicly reporting a complete carbon dioxide equivalent (CO2e) emissions inventory for their data center infrastructure. An organization’s direct on-site emissions (classified as Scope 1 according to the Greenhouse Gas Protocol) and emissions from purchased energy sources (classified as Scope 2) are relatively easy to calculate from measured operational facility data and available grid emissions factors.
In contrast, Scope 3 data (comprising indirect emissions from the activities of other organizations and individuals) is more challenging to gather and has a high degree of uncertainty. This is because Scope 3 represents the Scope 1 and 2 emissions of both upstream suppliers and downstream buyers, which can be up to five layers deep in the value chain. By definition, this includes potentially millions of product users scattered around the globe. Despite the challenges, data center operators need to establish processes to collect and quantify their Scope 3 emissions while recognizing both the inherent uncertainty in the data and the limited levels of control over said emissions.
Carbon emissions (shorthand for CO2e greenhouse gases) embedded in IT equipment are an important Scope 3 category for IT infrastructure operators. The most valuable data is collected from manufacturers because they have the best insight into and connections with their supply chains. Where manufacturers do not supply the data, publicly available databases and proprietary estimation tools are useful for looking up or calculating embedded carbon values for IT equipment.
IT original equipment manufacturers (OEMs) can provide product carbon footprint (PCF) reports of typical configurations for some or all their machine models. These reports combine embedded carbon estimates from the product’s manufacture and transportation to the customer along with estimates of use emissions (Scope 2) and emissions associated with the management of end-of-life equipment (a separate Scope 3 category). The “manufacturing” and “transport” emissions categories are the most relevant for reporting embedded emissions from IT equipment. Tables 1a and Table 1b give select examples of PCF reports by some of the major OEMs.
Table 1a. Example server configurations from different manufacturers
Table 1b. Server manufacturers’ PCF reports for the example configurations
The “use” and “end of life” carbon footprint categories are of little value to a data center operator when purchasing IT equipment. The OEM estimate of emissions from operational energy use is redundant to the operator’s emission reports because this will be accounted for under Scope 2 calculations based on functional energy use and the data center emissions factor after the equipment is installed. Emissions generated by the end-of-use recovery and disposal of IT equipment are several years away and will depend on the vendor hired to manage the disposal process.
While manufacturers’ PCF reports are a convenient source of Scope 3 data, calculating carbon content for each of the four categories requires assumptions and highly uncertain estimates that limit the data’s accuracy and usefulness. Quantifying embedded carbon emissions is an academic exercise that provides little, if any, actionable insight for data center operators.
Embedded emissions: manufacture of IT equipment
The manufacture of IT equipment has two primary sources of carbon emissions: the emissions associated with the energy consumed by the manufacturing and assembly processes (typically 30% to 50% of the total) and those associated with component production, particularly semiconductors such as flash memory, dynamic random access memory (DRAM) and processors (50% to 70% of the total).
The supply chains are also geographically concentrated. Equipment manufacturing and assembly operations are mostly based in the Asia-Pacific region, where electricity emission factors vary between 0.4 and 0.8 metric tonnes of CO2 per megawatt-hour due to the high fossil fuel content in the generation mix. IT equipment has hundreds of components that are sourced from multiple companies around the globe.
IT hardware vendors, let alone buyers, cannot know the exact electricity mix as different components are manufactured and assembled in other countries with varying sources of electricity. The raw materials used in each component further complicate the problem because they are typically processed in different geographic areas, each with its own electricity source and associated variations in CO2 emissions.
The greenhouse gas emissions from semiconductor manufacturing are the result of energy consumption (about 40%), the use of perfluorinated compounds (about 20%) — these are high global warming potential gases used for chamber cleaning — and the production of the many materials and process chemicals used to fabricate a semiconductor device (about 40%).
Most of these emissions are generated deep in the supply chain of the server manufacturing process. Neither the equipment manufacturer nor the purchaser has the visibility to observe these processes or has direct leverage over the suppliers responsible for the energy use and manufacturing emissions. Academic research has found up to 30% uncertainties in IT equipment manufacturing and assembly emissions estimates.
Actions to drive emissions reductions in these processes need to be promoted by the individual suppliers and their immediate customers — there is little that the IT buyer can do to drive reductions. Importantly, there will be little difference in embedded carbon between IT OEMs for a comparable product configuration. Equally, the embedded carbon of IT equipment can be a trade-off with emissions from use because larger, more richly configured systems can also be more energy efficient.
The manufacturing emissions data for the three configurations of the HPE Proliant DL360 illustrates why manufacturing emissions estimates have high uncertainty. Using data from the EU, the base configuration, with a minimal (i.e., low component) configuration, has an embedded emissions estimate of 55% of the performance configuration. Because each server configuration is unique to the purchaser, estimating the emissions for a specific configuration adds to the 30% uncertainty inherent in assessing the embedded emissions.
This uncertainty escalates significantly for the Dell server cited in Tables 1a and 1b because the embedded manufacturing emissions are calculated for a base server with only 32 GB of memory, an improbable configuration for a data center. Reporting a low-end configuration is primarily responsible for the higher uncertainty in the Dell estimate compared with the HPE estimate.
An operator can reduce the uncertainty introduced by configuration choices by weighting the published manufacturing emissions. To make this adjustment, the weight of the purchased server (available from shipping documents) can be multiplied by the ratio of the manufacturing emissions to the weight of the server configuration used to estimate the PCF (available from the manufacturer) to get an adjusted estimate of the purchased server manufacturing PCF. This approach is best applied to the mainstream or performance configurations, as the base configuration has minimal quantities of DRAM and storage devices that contribute a significant portion of the manufacturing emissions footprint.
This adjustment may reduce the error and create a more representative manufacturing emissions estimate. However, given the limited value of this emission quantity, the additional time and effort to collect the data and perform the adjustment may not be worthwhile.
Embedded emissions: transportation to the customer
Product transportation from the assembly site to the customer accounts for a small percentage of embedded carbon in Scope 3 emission estimates. These vary based on geographical region and type of transport vehicle.
Greater geographical distances to the reporting company inevitably result in more fuel use and, therefore, higher emissions. Most products are assembled and shipped from Asia. The transport data for the HPE servers with a mainstream configuration has three to five times the transport emissions when shipped to Europe (98 kilograms, kg, of CO2e) or the US (150 kg of CO2e ) compared with Japan (31 kg of CO2e).
The most significant impact on transport emissions (and cost) is whether the product is shipped by sea or air. When demand for products is high and delivery time is critical, companies may opt for a faster transport method at the expense of greater CO2e emissions. The air transportation of goods has a 20 to 30 times larger carbon footprint than transport via ocean freight.
Use emissions
To reduce use emissions, data center operators should focus on energy use of IT instead of embedded carbon. This entails buying the most efficient IT equipment for their workloads as measured in work delivered per watt, maximizing hardware utilization, and deploying power management where the workload can tolerate the higher response times.
These aspects of evaluating or improving server efficiency are covered in several Uptime Intelligence Updates and Briefing Reports (listed at the end of this Update). Focusing on efficiency, and particularly the better utilization of IT assets, will not only drive lower Scope 2 through better energy performance but can also help Scope 3 inventories by requiring fewer IT systems to perform the same amount of work.
Manufacturers’ estimates of use emissions have no value to the purchaser. A sustainable purchase decision needs to minimize energy consumption by procuring the most efficient equipment for the workload. The use emissions will then be a function of the electricity emissions factor at the data center location where the IT equipment is installed. These will be reported as Scope 2 emissions in an environmental / sustainability report and required regulatory disclosures.
End-of-life product management emissions
The end-of-life product emissions estimate also offers no value to the data center operator. These emissions are not accounted for until the product is removed from service during a specified refresh cycle. The emissions associated with the refurbishment, recycling and disposal of the product and its components will be a function of the chosen end-of-life product management process.
Conclusion
Apart from massive IT buyers who can force shifts in upstream supply chain emissions, most data center infrastructure operators cannot influence the emissions generated within the supply chain. A select few hyperscalers can leverage their buying power by prioritizing sustainability in their purchasing decisions. And while smaller data centers can be indirect beneficiaries of hyperscaler-driven innovations in the industry, they cannot rely on this possibility as an actionable strategy for carbon reduction. Instead, most data centers that wish to track and curb Scope 3 emissions can focus on the following:
The Uptime Intelligence View
Data center managers are facing mandates to report Scope 3 C02e emissions. Estimating the embedded carbon in IT equipment fails to produce actionable data because the values have a high degree of uncertainty and provide little guidance on how to reduce manufacturing emissions. Innovative operators and owners will instead focus on reducing their own direct emissions and forming collaborative partnerships with suppliers and manufacturers to encourage transparency in emissions reporting.
Jay Dietrich, Research Director, [email protected]
Rose Weinschenk, Research Associate, [email protected]
DLC will not come to the rescue of data center sustainability
/in Design, Executive, Operations/by Jacqueline Davis, Research Analyst, Uptime Institute, [email protected]A growing number of data center operators and equipment vendors are anticipating the proliferation of direct liquid cooling systems (DLC) over the next few years. As far as projections go, Uptime Institute’s surveys agree: the industry consensus for the mainstream adoption of liquid-cooled IT converges on the latter half of the 2020s.
DLC systems, such as cold plate and immersion, have already proved themselves in technical computing applications as well as mainframe systems for decades. More recently, IT and facility equipment vendors, together with some of the larger data center operators, have started working on commercializing DLC systems for much broader adoption.
A common theme running through both operators’ expectations of DLC and vendors’ messaging is that a main benefit of DLC is improved energy efficiency. Specifically, the superior thermal performance of liquids compared with air will dramatically reduce the consumption of electricity and water in heat rejection systems, such as chillers, as well as increase opportunities for year-round free cooling in some climates. In turn, the data center’s operational sustainability credentials would improve significantly. Better still, the cooling infrastructure would become leaner, cost less and be easier to maintain.
These benefits will be out of reach for many facilities for several practical reasons. The reality of mainstream data centers combined with the varied requirements of generic IT workloads (as opposed to high-performance computing) means that cost and energy efficiency gains will be unevenly distributed across the sector. Many of the operators deploying DLC systems in the next few years will likely prioritize speed and ease of installation into existing environments, as well as focus on maintaining infrastructure resiliency — rather than aiming for maximum DLC efficiency.
Another major factor is time: the pace of adoption. The use of DLC in mission-critical facilities, let alone a large-scale change, represents a wholesale shift in cooling design and infrastructure operations, with industry best practices yet to catch up. Adding to the hurdles is that many data center operators will deem the current DLC systems limited or uneconomical for their applications, slowing rollout across the industry.
Cooling in mixed company
Data center operators retrofitting a DLC system into their existing data center footprint will often do so gradually in an iterative process, accumulating operational experience. Operators will need to manage a potentially long period when liquid-cooled and air-cooled IT systems and infrastructure coexist in the same data center. This is because air-cooled IT systems will continue to be in production for many years to come, with typical life cycles of between five and seven years. In many cases, this will also mean a cooling infrastructure (for heat transport and rejection) shared between air and liquid systems.
In these hybrid environments, DLC’s energy efficiency will be constrained by the supply temperature requirements of air-cooling equipment, which puts a lid on operating at higher temperatures —compromising the energy and capital efficiency benefits of DLC on the facility side. This includes DLC systems that are integrated with chilled water systems (running the return facility loop as supply for DLC may deliver some marginal gains) and DLC implementations where the coolant distribution unit (CDU) is cooled by the cold air supply.
Even though DLC eliminates many, if not all, server fans and reduces airflow requirements for major gains in total infrastructure energy efficiency, these gains will be difficult to quantify for real-world reporting purposes because IT fan power is not a commonly tracked metric — it is hidden in the IT load.
It will take years for DLC installations to reach the scale where a dedicated cooling infrastructure can be justified as a standard approach, and for energy efficiency gains to have a positive effect on the industry’s energy performance, such as in power usage effectiveness (PUE) numbers. Most likely, any impact on PUE or sustainability performance from DLC adoption will remain imperceptible for years.
Hidden trade-offs in temperature
There are other factors that will limit the cooling efficiency seen with DLC installations. At the core of DLC’s efficiency potential are the liquid coolants’ favorable thermal properties, which enable them to capture IT heat more effectively. The same thermal properties can also be used for a cooling performance advantage as opposed to maximizing cooling system efficiency. When planning for and configuring a DLC system, some operators will give performance, underpinned by lower operating temperatures, more weight in their balancing act between design trade-offs.
Facility water temperature is a crucial variable in this trade-off. Many DLC systems can cool IT effectively with facility water that is as high as 104°F (40°C) or even higher in specific cases. This minimizes capital and energy expenditure (and water consumption) for the heat rejection infrastructure, particularly for data centers in hotter climates.
Yet, even when presented with the choice, a significant number of facility and IT operators will choose lower supply temperatures for their DLC systems’ water supply. This is because there are substantial benefits to using lower water temperatures — often below 68°F (20°C) — despite the costs involved. Chiefly, a low facility water temperature reduces the flow rate needed for the same cooling capacity, which eases pressure on pipes and pumping.
Conversely, organizations that use warm water and DLC to enable data center designs with dry coolers face planning and design uncertainties. High facility water temperatures not only require higher flow rates and pumping power but also need to account for potential supply temperature reductions in the future as IT requirements become stricter due to evolving server silicon. For a given capacity, this could mean more or larger dry coolers, which potentially require upgrades with mechanical or evaporative assistance. Data center operators that want free cooling benefits and a light mechanical plant have a complex planning and design task ahead.
On the IT side, taking advantage of low temperatures makes sense when maximizing the performance and energy efficiency of processors because silicon exhibits lower static power losses at lower temperatures. This approach is already common today because the primary reason for most current DLC installations is to support high IT performance objectives. Data center operators currently use DLC primarily because they need to cool high-density IT rather than conserve energy.
The bulk of DLC system sales in the coming years will likely be to support high-performance IT systems, many of which will use processors with restricted temperature limits — these models are sold by chipmakers specifically to maximize compute speeds. Operators may select low water temperatures to accommodate these low-temperature processors and to maximize the cooling capacity of the CDU. In effect, a significant share of DLC adoption will likely represent an investment in performance rather than facility efficiency gains.
DLC changes more than the coolant
For all its potential benefits, a switch to DLC raises some challenges to resiliency design, maintenance and operation. These can be especially daunting in the absence of mature and application-specific guidance from standards organizations. Data center operators that support business-critical workloads are unlikely to accept compromises to resiliency standards and realized application availability for a new mode of cooling, regardless of the technical or economic benefits.
In the event of a failure in the DLC system, cold plates tend to offer much less than a minute of ride-through time because of their small coolant volume. The latest high-powered processors would have only a few seconds of ride-through at full load when using typical cold plate systems. Operating at high temperatures means that there are thin margins in a failure, something that operators of mainstream, mission-critical facilities will be mindful of when making these decisions.
In addition, implementing concurrent maintainability or fault tolerance with some DLC equipment may not be practical. As a result, a conversion to DLC can demand that organizations maintain their infrastructure resiliency standard in a different way from air cooling. Operators may consider protecting coolant pumps with an uninterruptible power supply (UPS) and using software resiliency strategies when possible.
Organizational procedures for procurement, commissioning, maintenance and operations need to be re-examined because DLC disrupts the current division of facilities and IT infrastructure functions. For air-cooling equipment, there is strong consensus regarding the division of equipment between facilities and IT teams, as well as their corresponding responsibilities in procurement, maintenance and resiliency. No such consensus exists for liquid cooling equipment. A resetting of staff responsibilities will require much closer cooperation between facilities and IT infrastructure teams.
These considerations will temper the enthusiasm for large-scale use of DLC and make for a more measured approach to its adoption. As operators increasingly understand the ways in which DLC deployment is not straightforward, they will bide their time and wait for industry best practices to mature and fill their knowledge gaps.
In the long term (i.e., 10 years or more), DLC is likely to handle a large share of IT workloads, including a broad set of systems running business applications. This will happen as standardization efforts, real-world experience with DLC systems in production environments and mature guidance take shape in new, more robust products and best practices for the industry. To grow the number and size of deployments of cold plate and immersion systems in mission-critical facility infrastructure, DLC system designs will have to meet additional technical and economic objectives. This will complicate the case for efficiency improvements.
The cooling efficiency figures of today’s DLC products are often derived from niche applications that differ from typical commercial data centers — and real-world efficiency gains from DLC in mainstream data centers will necessarily be subject to more trade-offs and constraints.
In the near term, the business case for DLC is likely to tilt in favor of prioritizing IT performance and ease of retrofitting with a shared cooling infrastructure. Importantly, choosing lower, more traditional water supply temperatures and utilizing chillers appears to be an attractive proposition for added resiliency and future-proofing. As many data center operators deem performance needs and mixed environments to be more pressing business concerns — free cooling aspirations, along with their benefits in sustainability, will have to wait for much of the industry.