Meaning and Architecture
Cloud computing infrastructure is the underlying physical and virtual infrastructure through which computing power, storage, networking and software resources are delivered remotely and on demand.
According to NIST, cloud computing enables ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released.
Its physical backbone consists of:
- hyperscale and edge data centres;
- servers, CPUs, GPUs and AI accelerators;
- storage and networking systems;
- terrestrial fibre and submarine cables;
- Internet Exchange Points;
- power, cooling and backup systems.
Virtualisation and containerisation allow this physical hardware to be pooled and dynamically allocated among users. Thus, the “cloud” is ultimately a highly capital-intensive physical infrastructure system.
Cloud services are commonly delivered as IaaS, PaaS and SaaS, while deployment may be public, private, hybrid or multi-cloud.
Why Cloud Infrastructure Has Become Strategic
Cloud infrastructure has evolved from an enterprise IT service into foundational infrastructure for the digital economy.
It supports:
- Digital Public Infrastructure and e-governance;
- banking, fintech and digital payments;
- e-commerce and platform businesses;
- cybersecurity and disaster recovery;
- scientific computing;
- AI training and inference.
Its performance depends heavily on latency, bandwidth, computing capacity and redundancy.
This makes submarine cables strategically important. International cables connect domestic data centres with global cloud regions, while domestic fibre networks and Internet Exchange Points carry traffic closer to users.
More geographically distributed cable landings and data centres also improve network resilience, since traffic can be rerouted when individual routes fail.
AI Is Reshaping the Cloud
Generative AI has fundamentally changed cloud-infrastructure requirements.
Traditional cloud workloads primarily required CPUs, storage and general-purpose servers. Training and operating frontier AI models requires large clusters of:
- GPUs and specialised accelerators;
- high-bandwidth memory;
- high-speed interconnects;
- advanced cooling;
- continuous high-quality electricity supply.
Cloud infrastructure is therefore increasingly converging with AI compute infrastructure.
India’s IndiaAI Mission, approved with an outlay of more than ₹10,300 crore, includes the IndiaAI Compute Capacity pillar to create shared access to high-end computing infrastructure. By May 2026, the government reported that more than 38,000 GPUs had been onboarded under the mission.
This is strategically important because access to compute is becoming as important for AI development as access to datasets and algorithms.
India’s Data-Centre and Cloud Ecosystem
India’s cloud opportunity rests on the convergence of a large digital market, expanding submarine-cable connectivity, data localisation requirements and rapidly growing AI demand.
Major data-centre clusters have developed around:
- Mumbai;
- Chennai;
- Hyderabad;
- Bengaluru;
- Delhi-NCR.
Mumbai and Chennai are particularly important because of their proximity to major submarine-cable landing infrastructure.
Government cloud adoption is supported through GI Cloud (MeghRaj), conceived to provide cloud services for government departments and accelerate delivery of e-governance applications.
The emerging infrastructure stack is therefore broader than data centres alone:
Submarine connectivity + Domestic fibre + Data centres + Cloud platforms + AI compute + Digital applications
This infrastructure increasingly influences India’s ability to retain, process and derive economic value from its rapidly expanding domestic data.
Strategic Vulnerabilities and Policy Issues
The expansion of cloud infrastructure creates several new dependencies.
- Compute dependence: India remains dependent on imported high-end GPUs, processors, servers and semiconductor supply chains.
- Cloud concentration: A large share of global hyperscale cloud capacity is controlled by a small number of technology companies, creating concerns around vendor dependence and systemic concentration.
- Cybersecurity: Centralisation of enormous volumes of data and computing workloads makes cloud infrastructure a high-value target for cyberattacks.
- Data governance: Cloud services can involve data storage and processing across jurisdictions. This raises questions of privacy, cross-border data transfers, lawful access and regulatory control. India’s Digital Personal Data Protection Act, 2023 and DPDP Rules, 2025 form an important part of this evolving governance architecture.
- Resilience: Cable cuts, power disruptions, cyber incidents or failure of a major cloud region can affect multiple digital services simultaneously. Redundant cable routes, distributed data centres and disaster-recovery systems are therefore increasingly matters of economic security.
Energy and Resource Challenge
Cloud and especially AI infrastructure is highly energy intensive.
The International Energy Agency estimates that global data-centre electricity consumption could more than double to around 945 TWh by 2030, with AI being the most important driver of this increase.
Large facilities also create demand for:
- reliable round-the-clock electricity;
- cooling infrastructure;
- water in some cooling systems;
- land and grid connectivity.
For India, rapid expansion therefore has to be aligned with renewable electricity, energy-efficient computing, advanced cooling and stronger power grids.
Cloud infrastructure should consequently be understood not merely as an IT service, but as part of India’s emerging digital strategic infrastructure, connecting telecommunications, data centres, AI compute, energy security, cybersecurity and data sovereignty.
