How Fibre Infrastructure is Driving the Next Wave of AI-Ready Data Centres Across India – CRN

By Matias Peluffo, Asia Pacific, Vice President, Data Centers, CommScope

As artificial intelligence (AI) accelerates across industries, it is prompting businesses in India to fundamentally rethink how to build and operate data centres. With Digital India’s focused infrastructure and AI-driven transformation on the rise, the Indian data centre market is expected to grow from USD 4.5 billion in 2023 to USD 11.6 billion by 2032, according to the Indian Economic Survey 2024-2025.

In this next phase of growth, data centres in India must evolve into AI-optimized environments capable of powering massive parallel workloads, accelerating deployment cycles, and supporting high-density compute clusters.

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Meeting the demands of AI Data Centres

India is already in the process of building its first AI based Data Centre Park in Chhattisgarh, aligning with the increasing demand for the mass adoption of AI-based applications in the enterprise space, as well as industry 4.0. According to Industry Resports, apart from key hubs such as Mumbai and Chennai, tier 2 and tier 3 cities including Jaipur, Ahmedabad, Kochi, Vizag, Lucknow, Patna, and Bhubaneswar, are anticipated to emerge as locations for decentralised data centre facilities. These edge data centres will play a vital role in the processing of latency-sensitive and generative AI services and applications.

Leveraging the expansive reach and impact of AI-based services, companies like Meta and Reliance Industries have announced significant investments for data centre developments centred on the India market. However, the Indian data centre industry faces some key challenges related to the supply chain, availability of skilled professionals, and statutory clarity.  To re-engineer the entire data centre ecosystem to support the demands of high-performance computing, ultra-low latency, and seamless scalability will be one of the first few most important actions that will need the government and private sector working closely together. Indian data centres need to play catch-up as data centre design is evolving rapidly. High performance Graphics Processing Units (GPUs), essential to AI workloads, require more connections between servers than ever before. At the same time, in traditional Central Processing Unit (CPU) based data centre designs, power and cooling limitations often mean fewer servers or GPU nodes can be accommodated in a cabinet, resulting in an increased amount of cabling required to connect everything. Each server needs high-speed links to switches, storage systems, and management tools, which puts enormous pressure on the network.

To put this into perspective, NVIDIA’s DGX SuperPOD, a leading example of AI infrastructure, contains 32 GPU servers connected to 18 switches in a single row. That setup alone requires 384x400GE fibre links to handle data movement across the cluster, not including additional connections for storage and management. It’s a remarkable increase in the volume of fibre cabling required inside the data hall, and a clear example of why traditional network designs are no longer sufficient.

This increased density demands new approaches to energy management and cooling to handle higher power consumption and heat output, while supporting continuous, heavy internal data traffic across highly interconnected systems. This shift toward higher density also demands advanced cooling and power solutions.According to ICRA, India’s data centre operational capacity is expected to increase to 2,000-2,100 MW by March 2027, from approximately 1,150 MW as of December 2024. In Tier 1 cities, the management of heat and energy efficiency in India’s current data centre hubs is becoming a challenge due to space constraints, rising power costs, and regulatory pressures.

Together, these pressures mean data centres can no longer rely on traditional design or incremental upgrades. Scaling AI effectively requires a complete rethink of how data moves, how power is delivered, and how heat is managed—while ensuring speed, reliability, and scalability.

Transform your data centre for AI with advanced fibre networks

For data centre operators, AI is reshaping the entire foundation of their facility. The traditional focus on compute power is no longer enough. Success depends on the network that connects across high-density AI clusters.

This is why fibre must form the backbone of AI-ready data centre operations. AI workloads depend on high-speed, low latency connections between GPUs working together, as well as to scale out the network, encompassing multiple thousands of GPUs in the rapidly emerging AI factories. To deliver on these requirements, avoid bottlenecks of slow performance, high costs and scalability stalls, fibre networks must evolve. Moreover, with a limited pool of trained fibre technicians and growing pressure to speed up project rollouts, Indian operators are increasingly turning to pre-terminated fibre cabling. These ready-to-use, plug-and-play systems accelerate installation and reduce the risk of errors and costly downtime, enabling faster, more reliable AI deployment across the country.

To grow along the AI curve, data centres are shifting from point-to-point cabling to more scalable structured cabling systems. The choice between single mode and multimode fibre depends on the size and design of the facility. At the same time InfiniBand and Ethernet continue to play critical roles in managing different types of AI traffic.

The industry is pushing towards even greater speeds and capacity, to support next-generation performance—moving from 400 Gb/s to 800 Gb/s, 1.6 Tb/s, and beyond using 8 and 12 fibre connectivity, and with industry developments for higher speeds pointing towards 16-fibre connectivity in the future.

As AI reshapes services and operations in key areas like manufacturing, scientific and governmental applications, a high-performance optical fibre network architecture in Data Centers is the need of the hour. This will ensure data moves at higher speeds, help businesses scale seamlessly and networks are built not just for today’s demands, but for the future of all AI-powered innovation.

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