Edge and Gen AI: Infrastructure for the Needs of Tomorrow
The telecommunications industry is on the cusp of a seismic shift, driven by the rise of edge computing and generative AI (Gen AI) technologies. This transformation – according to research by STL Partners – could be as transformative as the advent of cloud computing, or an ‘AWS moment’: presenting both opportunities and challenges for network service providers (NSPs) and telco operators.
As Andres Vasquez, Global Segment Director at Schneider Electric, explains, today’s telcos are redefining themselves as distributed compute businesses: embracing edge computing, AI and next-generation connectivity like 5G and beyond. Traditionally, telcos have relied on proprietary hardware and software systems. However, with the adoption of 5G, their data centres are transitioning to standard IT servers running software-defined networking (SDN) and Network Functions Virtualization (NFV) in multi-cloud environments.
“When telco architectures resemble cloud service providers, it introduces the opportunity of hosting cloud services and telco controls in the same network edge data centre,” Andres says.
This convergence of telco and cloud infrastructures paves the way for telcos to offer innovative edge computing services, bringing computational power and intelligence closer to end-users and devices. Here, the best practice for NSPs and telcos is not to go it alone, but rather to partner at the edge with those who can provide real value, with a learn-and-scale approach.
“At Schneider Electric, we see ourselves as the strategic partner that can offer a whole ecosystem approach for telcos to build out innovative infrastructure for tomorrow’s needs.
“We are fully aware of the challenges in implementing edge computing and have both the experience and the portfolio to ensure it can be done securely, efficiently and in a timely manner.”
The rise of edge and AI
As AI workloads become increasingly critical to enterprise strategies, they are changing data architectures and infrastructure requirements.
Generative AI applications, such as large language models and image synthesis, are particularly compute-intensive and latency-sensitive. By processing these workloads at the edge, enterprises can achieve real-time responsiveness, reduced network congestion and enhanced data privacy and security.
However, these opportunities do not come without challenges. Andres outlines three major challenges that traditional telcos, cloud service providers and data centre colocation providers face when building an edge data centre ecosystem.
The first challenge, he says, is creating a multi-access edge framework, which requires retrofitting legacy infrastructure to systems based on standard IT server hardware and software based on open standards. It also demands solid relationships and partnerships among telcos, colocation providers and hyperscalers to distribute data processing according to latency needs and clarify roles in building, owning and managing these converged edge data centres.
The second challenge lies in meeting the unique requirements of edge data centres, which often exist outside of traditional data centre environments. These edge data centres require remote monitoring, higher rack densities, liquid cooling, and enhanced security measures, as they typically lack on-site IT staff.
The third challenge is minimising the environmental impact of distributed edge data centres. As Andres notes: “It might be easy to overlook the environmental impact of distributed edge data centres due to their reduced size. But with increasing emphasis on sustainability from regulators, shareholders, and customers, distributed local edge data centre owners and operators need to report the environmental impacts of edge locations.”
To address these challenges, Schneider Electric positions itself as a strategic partner offering a comprehensive ecosystem approach. “We uniquely offer more than just a full infrastructure portfolio from power to racks and cooling; we have the necessary expertise in Operational Technology (OT) and IT convergence, underpinned by expert sustainability consultancy,” Andres explains.
“This capability is important not just in helping telco operators transition towards fully distributed compute businesses, but in providing the visibility and availability of data that will support sustainability goals, but also facilitating automation and optimisation.”
Strategic partnerships for success
Schneider Electric has a long history of understanding telco needs and partnering to drive value, as evidenced by its collaborations with companies like NTT on Internet of Things (IoT) networks and Orange on industrial 5G trials.
One notable collaboration is the co-innovation with NTT DATA, which allows enterprises to harness the power of edge computing through a solution that seamlessly integrates Edge, Private 5G, IoT and Modular Data Centres. This powerful combination enables companies to maximise energy efficiency and meet the demands of compute-intensive tasks such as machine vision, predictive maintenance, and other AI inferencing applications at the edge.
The joint offering combines NTT DATA’s Edge as a Service, which includes fully managed Edge to Cloud, Private 5G, and IoT capabilities, with Schneider Electric’s EcoStruxure, a modular data centre combining OT solutions with the latest in IT technologies. “This powerful combination enables companies to maximise energy efficiency and meet the demands of compute-intensive tasks such as machine vision, predictive maintenance and other AI inferencing applications at the edge,” Andres says.
“Our global experience in advanced IT infrastructure has been honed for the telco industry, across implementations in North America, Europe, MENA and APAC, to ensure a holistic approach that elevates our value proposition beyond vendor status to true strategic partnership.”
Data and infrastructure: Changing requirements
As AI integrations and workloads become more prevalent and critical to enterprise strategies, they are changing data architectures and infrastructure requirements. To address this, Schneider Electric has conducted extensive research and produced a white paper to help enterprises cope with the new demands, even at the network edge. The white paper, ‘The AI Disruption: Challenges and Guidance for Data Center Design,’ explains the relevant attributes and trends of AI workloads and addresses the challenges in each physical infrastructure category, including power, cooling, racks and software management.
“We have produced resources to address the role of edge computing infrastructure in AI-powered industrial automation, encompassing the development of robust physical infrastructures, covering connected sensors, edge data centres, and multicloud software, operating within a hybrid edge compute environment, that play a pivotal role in the delivery of AI applications
“With Schneider Electric as a strategic partner, Cloud and Network Service Providers can sustainably build new services and business models on infrastructure that is already the foundation of the digital economy.”
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