Executive Outlook:
The ever-evolving world of data centers is set for a transformative journey in 2024. As the demand for data processing skyrockets, accompanied by stringent sustainability regulations and cost pressures, data center operators face a pivotal year of challenges and innovations. The Uptime Institute sheds light on five key trends that will shape the data center landscape, prompting a delicate balance between business expansion and infrastructure reliability.
1. Tougher Sustainability Regulations:
According to the institute, the top prediction for this year is that the data center sector will continue to use more power, and emit more carbon, as its footprint rapidly grows. As a result, publicly stated net-zero goals and other commitments will become harder and more expensive to maintain. Some companies may have to backtrack on their commitments or increase their investments in energy efficiency to meet tighter reporting and accountability regulations.
âItâs going to be a challenging period for the sector over the next five years,â said Andy Lawrence, the instituteâs executive director of research. He pointed to new regulations and stricter reporting requirements in Europe, UK, China, Europe and other geographies.
âA lot of different countries now are beginning to apply some quite strict laws,â Lawrence said. âIn the EU in particular, the Energy Efficiency Directive is going to require organizations to report energy and carbon use and a lot more else besides â things like water, workloads, and megawatt use and so on.â
Even when the targets are voluntary and set by the companies themselves, the fact that they are published alongside financial reports may make them legally binding, he added. âCompanies will have to close that gap,â he said. âI think a lot of companies are going to go rather quiet and possibly walk back on some of their commitments. But, hopefully, there will be some serious attention and investment paid to the issue of efficiency and a lot of new innovation will happen.â
2. AI's Impact on Supply Chains:
While artificial intelligence (AI) continues to capture industry excitement, its immediate impact on data center operators lies in supply chain dynamics. AI-driven innovations strain equipment supply chains, influence server chip power levels, and necessitate a reconsideration of resiliency postures. Hyperscalers hosting demanding AI models will mitigate excessive power and cooling requirements. The competitive landscape for facility equipment is set to intensify, even for operators with minimal AI deployments.
3. Rise of Intelligent Data Center Software:
New data center infrastructure management tools using machine learning have emerged that can optimize efficiency, maintenance, and capacity utilization. But traditional DCIM and BMS vendors have been slow to evolve, said research analyst Max Smolaks.
Instead, a group of startups have appeared that leverage sensor, monitoring, and other facilities data to improve cooling, predict problems, reduce waste, and discover stranded capacity. They include Phaidra, Coolgradient, QIO, TycheTools, Vigilent, and EkkoSense.
However, most data centers have been slow to adopt these technologies for a variety of reasons, including implementation risks, the need for more data collection and network connectivity, and cybersecurity concerns due to the bigger attack surface.
On a scale of one to five, with five being fully autonomous, most data centers are now at level three, Smolaks said. âBut weâre finally seeing the beginning of a shift towards level four â and then level five.â
At level three, data centers use software to track physical equipment characteristics, location, and operational status. At level four, machine learning starts to be used for prediction, service management, and making recommendations about optimizing the data center for power consumption or cooling. At level five, AI is used to automatically manage data center operations.
Moving up the maturity scale will require data center operators to learn how to collect, manage, and analyze data. âYou might also need to hire analysts and data scientists,â said Smolaks.
However, AI can also help alleviate some staffing issues.
There are many procedures that havenât been documented, and data centers rely on engineers to know what handle to turn, what toggle to tweak, he said. âBut there arenât enough engineers,â he says. âWeâre facing a staffing shortage â and also a silver tsunami. The most experienced people are going to leave.â AI can be used before they leave in order to codify their knowledge in software, he said.
4. Challenges in Direct Liquid Cooling Adoption:
Direct liquid cooling, despite its touted advantages, faces obstacles that hinder its broad implementation. This cooling method, while holding promise, introduces concerns about the resilience of data centers. If there’s an outage affecting a liquid cooling system, temperatures might increase faster compared to traditional air-cooled systems, posing potential risks.
Moreover, the slow adoption rate of direct liquid cooling limits the efficiency benefits that were initially anticipated. The integration of liquid and air cooling systems is expected to persist within data centers for a considerable period. This suggests that the impact of adopting direct liquid cooling will be more about enhancing performance than achieving efficiency gains. As data centers navigate these challenges, the coexistence of various cooling methods becomes a pragmatic approach to ensure reliability and gradual adaptation to new technologies.
5. Hyperscale campuses emerge
The emergence of massive hyperscale colocation campuses marks a significant trend in the data center landscape. These sprawling campuses, spanning millions of square meters with gigawatts of power capacity, are anticipated to address the escalating demand for computing resources. Hyperscale campuses serve diverse tenants, accommodating hyperscale cloud providers as well as individual enterprises seeking colocation space.
While North America is expected to host the most substantial hyperscale campuses, developments are also underway in the Asia-Pacific region and other parts of the world. Notably, the North Virginia region stands out with a staggering investment of $45 billion, surpassing other regions by a significant margin. Challenges faced by these burgeoning facilities include power considerations and the imperative to utilize renewable or carbon-free energy sources.
Several factors influence the selection of locations for these hyperscale campuses, such as connectivity, proximity to customers and other data centers, tax policies, regulatory environments, and the availability of a skilled labor pool. As these hubs materialize, they are poised to be globally interconnected and characterized by advanced levels of automation, operational efficiency, and power utilization, marking a transformative phase in the data center industry.
Wrap-Up
The data center industry faces a challenging landscape in 2024, characterized by rising workloads, stringent sustainability regulations, and cost pressures. These factors are driving innovation but also increasing infrastructure complexity, requiring a delicate balance between reliability, efficiency, and business expansion. The Uptime Institute identifies five key trends, including the intensification of sustainability regulations, the indirect impact of AI on supply chains, the evolution of smarter data center software, challenges in the widespread adoption of direct liquid cooling, and the emergence of massive hyperscale colocation campuses. Navigating these challenges necessitates embracing technological approaches like infrastructure automation, standardized designs, economies of scale, cross-domain skill-building, and leveraging data analytics. As the industry matures, there’s a critical need for adaptation and innovation to address the evolving demands and complexities within the data center landscape.