Best Practices for Designing AI-Ready Data Center Networks

Modular design has truly emerged as a best practice for supporting both rapid expansion and efficient resource utilization in AI data centers, because modular approaches allow operators to scale up by upgrading existing resources, such as adding memory or deploying more powerful processors, and to scale out by adding additional servers, GPU clusters, or storage nodes as demand grows. Prefabricated and modular data center components, including network racks and cable assemblies, enable faster deployment and easier upgrades, minimizing downtime and installation labor. This flexibility is critical as AI racks now often require 50–100 kW of power and generate heat loads far beyond what traditional facilities were designed to handle.

Future-proofing the network requires anticipating the rapid evolution of AI hardware, such as the transition to 800 G and 1.6 T interconnects, and the increasing density of GPU nodes. Planning must account for both the scale and unpredictability of AI traffic, as well as the integration of new cooling systems, chiplet-based processors, and advanced packaging techniques that enhance performance and efficiency. Hybrid cloud and edge computing strategies are also becoming more prevalent, distributing AI processing closer to end users and reducing latency for real-time applications. This hybrid approach requires robust, high-speed interconnects between core and edge facilities and the ability to segment and manage distributed workloads.

Industry standards and interoperability are essential for ensuring that data centers can integrate new technologies as they emerge. Adhering to widely adopted protocols such as Ethernet, InfiniBand, and RoCE enables compatibility across a diverse ecosystem of hardware and software, reducing vendor lock- in and future upgrade costs. Standardized modular components, such as MPO-16 fiber connectors and high-density patch panels, make it easier to swap out or upgrade network elements as bandwidth requirements increase, while maintaining operational continuity. Interoperability also extends to management and automation platforms, allowing operators to orchestrate resources across on-premises, cloud, and edge environments.

By combining modular design principles, proactive planning for evolving AI demands, and a commitment to open standards, data centers can build resilient infrastructure that supports both current and future growth. This approach ensures agility, cost- effectiveness, and the ability to capitalize on emerging AI opportunities as the technology landscape continues to evolve.

Solutions and Innovations

CommScope has developed a comprehensive suite of solutions to address the unique challenges posed by AI-driven data center growth, focusing on high- density connectivity, rapid deployment, and future- proof scalability. Among its flagship offerings are the Propel, Propel Shuffle, FiberGuide, and Propel XFrame platforms, each designed to tackle the bandwidth, complexity, and operational demands of modern AI environments.

Propel is CommScope’s modular fiber platform engineered for extreme density and flexibility. It supports all major MPO connector variants, including MPO-8, MPO-12, MPO-16, and MPO-24, enabling seamless migration from 400 G to 800 G and even 1.6 T speeds as AI workloads intensify. The system’s preterminated, plug-and-play design accelerates installation and reduces the need for skilled labor, a critical advantage as hyperscale data centers race to deploy new capacity. Propel also embraces the latest Very Small Form Factor (VSFF) connectors, which are up to three times smaller than traditional connectors. This allows for even greater fiber density in patch panels and cabinets, maximizing valuable rack space and supporting the densification required by modern AI clusters. The flexibility of the Propel offering also enables rapid reconfiguration and cable management, supporting the dynamic needs of AI clusters where server and GPU interconnects may need to be changed or upgraded with minimal downtime.

FiberGuide provides a robust raceway and pathway management system capable of handling the massive increase in fiber volume that AI clusters demand. Its design accommodates rollable ribbon cables and slimmer, high-fiber-count trunks, which reduce cable bulk and weight by up to 50%, helping data centers consolidate compute resources and reduce overall footprint. Propel XFrame complements these solutions by offering high-density patch panels and connectivity hardware, maximizing cabinet space, and supporting the densification required for AI-scale deployments.

These solutions directly address the pain points identified by industry operators: They enable rapid, error-free installation, support both Ethernet and InfiniBand protocols for front-end and backend AI networks, and provide a clear migration path to future network speeds and architectures. For example, CommScope’s preterminated cable assemblies, capable of delivering up to 1,728 fibers per trunk, have enabled AI cloud providers to connect thousands of GPUs and switches in a fraction of the time required by traditional methods, as seen in recent hyperscale deployments.

This approach not only accelerates time-to-profitability but also ensures that infrastructure investments remain viable as AI technologies and standards evolve.

By integrating these advanced connectivity platforms, data centers can manage the explosive growth in fiber demand, streamline operations, and confidently scale to meet the ever-increasing performance and efficiency requirements of AI workloads.

Download the full report, Future-Proofing Data Center Networking in the Era of AI, featuring CommScope, to learn more. In our next article, we’ll discuss the future of data center networking in the AI era.