15 MW Noida Data Center for AI, Cloud, and Enterprise Applications

Cyfuture Cloud’s 15 MW Noida Data Center delivers a highly secure, scalable, and performance-optimized environment tailored for AI, cloud-native workloads, and enterprise applications. It combines high-density power and cooling, low-latency connectivity to major Indian metros, enterprise-grade security and compliance, and managed services to accelerate AI training, inference, cloud migration, and critical business workloads with predictable SLAs.

What this facility offers 

Capacity & density: 15 MW total IT power capacity, supporting racks with high-power densities required for multi-GPU AI servers and HPC nodes.

Purpose-built cooling: Adaptive cooling systems (chilled water, in-row or liquid-assisted cooling options) to support sustained high thermal loads from GPUs.

Network connectivity: Carrier-neutral connectivity with multiple Tier-1 fiber providers and low-latency routes to Delhi NCR, Mumbai, and Bangalore.

Resiliency & uptime: Redundant power feeds (A/B), N+1 or 2N configurations for critical systems, and modular UPS systems to meet enterprise SLAs.

Security & compliance: Physical security layers (24/7 guards, biometric access, CCTV), SOC controls, and support for regulatory requirements (ISO 27001, and capabilities to assist with local compliance needs).

Managed services & support: Onsite NOC, remote hands, managed backup, colocation, private cloud and hybrid cloud orchestration, and bespoke AI infrastructure provisioning.

Sustainability: Energy-efficient infrastructure and opportunities for renewable power procurement or carbon reporting integration.

Why a 15 MW Noida facility matters for AI and enterprises

Supports GPU-scale AI training: The power and cooling headroom is essential for clusters of H100/H200-class GPUs (or equivalent accelerators), enabling large model training, distributed data parallel jobs, and inference at scale.

Predictable performance: Dedicated infrastructure reduces noisy-neighbor risks common in shared public cloud environments when running latency-sensitive AI inference or real-time enterprise apps.

Cost control and flexibility: Colocation or managed private cloud options can lower long-term TCO compared to public cloud for sustained, heavy GPU usage while offering flexible consumption models.

Data locality and compliance: On-premise or near-premise placement in Noida helps meet data residency and latency requirements for Indian enterprises and regulated industries.

Typical use cases

AI/ML model training and fine-tuning (large LLMs, CV, recommender systems) requiring sustained GPU throughput and large memory capacity.

AI inference clusters for real-time personalization, voice assistants, and vision pipelines.

High-performance computing (HPC) workloads in research, engineering, and simulations.

Hybrid cloud deployments where core data or latency-sensitive services run in colocated infrastructure while burst workloads leverage public cloud.

Enterprise applications requiring high availability—databases, ERP, CRM, and transactional systems with strict RTO/RPO targets.

Technical considerations when choosing this data center

Power per rack: Confirm available kW per rack (e.g., 15–30 kW+ options) to support GPU nodes.

Cooling architecture: Verify support for high-density racks, liquid cooling options, and hot-aisle containment for thermal efficiency.

Network fabric: Check for direct cloud interconnects (AWS Direct Connect, Azure ExpressRoute, Google Cloud Interconnect) and multi-carrier access for redundancy.

Physical and cyber security: Review access controls, audit logs, SIEM integrations, and vulnerability management processes.

Expansion & modularity: Ensure space and power can scale with GPU growth and future accelerators.

Compliance support: Determine documentation and controls available to meet industry regulations (financial services, healthcare, defense-related restrictions where applicable).

Operational and cost benefits

Reduced latency for local users and faster data transfer between on-prem systems and cloud endpoints.

Potentially lower costs for steady, predictable GPU workloads versus on-demand public cloud pricing.

Customizable SLAs and managed services that match enterprise operational models and staffing levels.

Simplified multi-cloud/hybrid orchestration with physical proximity to cloud onramps and national backbone.

Follow-up questions and answers

Q: What GPU server densities can the facility support?
A: The 15 MW capacity is designed to support high-density deployments, typically accommodating racks delivering 15–30+ kW per rack for multi-GPU servers (SXM or PCIe-based nodes). Exact densities depend on cabinet configuration and cooling options—discuss with Cyfuture Cloud for tailored rack specifications.

Q: Can I deploy liquid-cooled GPU clusters?
A: Yes—Cyfuture Cloud’s Noida data center supports advanced cooling options, including in-row cooling and liquid-assisted approaches, where available. Liquid cooling is recommended for tightly packed GPU clusters to maintain thermal performance and energy efficiency.

Q: Is there direct connectivity to major cloud providers?
A: The facility is carrier-neutral and supports direct cloud onramps (Direct Connect/ExpressRoute/Interconnect) through partner networks and interconnect partners for hybrid-cloud scenarios.

Q: How does Cyfuture Cloud ensure data security and compliance?
A: Cyfuture Cloud implements multi-layer physical security, role-based access, logging, and supports ISO-standard controls. For specific regulatory requirements, Cyfuture Cloud can provide documentation, audit support, and architecture recommendations to help meet compliance needs.

Q: What managed services are available for AI workloads?
A: Available services typically include rack- or pod-level provisioning, GPU orchestration (cluster management), remote hands, monitoring, backups, networking setup, private cloud setup (OpenStack/Kubernetes), and managed AI Ops support. Custom managed offerings can be created based on workload profile.

Conclusion

A 15 MW Noida data center by Cyfuture Cloud is well-suited to meet the demands of AI, cloud, and enterprise applications that require sustained power, advanced cooling, and robust connectivity. By combining high-density infrastructure, managed services, and compliance-ready operations, it offers an attractive option for organizations seeking performance, control, and cost predictability for large-scale AI workloads and critical enterprise systems.