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RDHx in Colocation: The Smart Way to Cool High-Density Racks

Posted on July 18, 2025July 18, 2025 by yotta

As artificial intelligence, cloud computing, and high-performance workloads become central to enterprise IT, data centers are adapting to meet significantly higher power and thermal demands. Traditional air-cooling systems continue to play a vital role in data center operations, but as rack densities climb beyond 30kW per rack, Rear Door Heat Exchangers (RDHx) are emerging as increasingly valuable for delivering precise, rack-level cooling in high-density environments. By delivering efficient, rack-level cooling, RDHx technology offers a smarter, more localised way to manage heat in colocation data center environments – without overhauling the entire cooling infrastructure.

RDHx systems are designed to be mounted directly at the rear of server racks, where they intercept hot exhaust air before it enters the data hall. By using chilled water coils to absorb heat, RDHx units cool the air immediately and recirculate it back into the environment at acceptable temperatures. This localised cooling mechanism enables the support of high-density computing loads-up to 50-60kW per rack-without the need to overhaul the entire room’s cooling infrastructure.

RDHx for High-Density Colocation

Colocation facilities are increasingly catering to clients with high-density workloads, especially those running AI model training, financial simulations, or other compute-heavy applications. RDHx presents several advantages for colocation data center providers:

1. Localised Cooling Precision: Rear Door Heat Exchangers (RDHx) offer rack-level thermal management by directly capturing and cooling hot air as it exits the server chassis. Unlike room-based cooling systems that cool the data hall uniformly, RDHx delivers precision cooling exactly at the source. This not only improves thermal efficiency but also contributes to a lower Power Usage Effectiveness (PUE), helping data centers operate more sustainably while maintaining optimal performance for high-density workloads.

2. Maximising Usable Space: By mounting directly onto the rear of server racks, RDHx systems eliminate the need for raised floors, overhead ducting, or additional aisle containment solutions. This design-driven efficiency frees up valuable floor space, allowing operators to accommodate more equipment per square foot. For colocation providers, this translates to increased customer capacity and better utilisation of revenue-generating real estate without compromising airflow management.

3. Built-in Scalability and Mixed-Density Support: RDHx enables seamless integration of mixed-density deployments within the same environment. Data center operators can host racks with varying thermal profiles – such as 10kW general-purpose servers alongside 50kW AI or HPC nodes – within the same row. Since each rack has its own independent cooling unit, this flexibility simplifies capacity planning and accelerates customer onboarding, all while maintaining thermal stability across the floor.

4. Future-Ready, Air-Cooled Compatibility: One of RDHx’s greatest advantages lies in its ability to support conventional air-cooled hardware while accommodating modern high-density demands. It serves as a bridge between traditional cooling systems and advanced liquid cooling, enabling organizations to scale up without the operational complexity or capital investment required for immersion or direct-to-chip solutions. This makes RDHx a highly effective transitional technology for data centers evolving toward next-generation workloads.

Engineering Considerations

RDHx systems require careful planning and execution to deliver optimal performance in colocation settings.

1. Chilled Water Connections: Since RDHx systems rely on chilled water, they require precision plumbing and reliable monitoring devices to ensure safe and effective operation. Water flow rate, inlet temperature, and return temperature must be tightly regulated.

2. Integration with Rack OEMs: RDHx deployment needs to be closely coordinated with server rack manufacturers and IT hardware vendors. Variations in server designs, airflow patterns, and cable management can affect RDHx efficiency and installation feasibility.

3. Power Redundancy: To maintain uptime, RDHx units are typically powered by UPS systems with battery backup. Many also include Automatic Transfer Switches (ATS) to accept dual power sources, thereby ensuring redundancy and resilience.

4. Centralised Humidification Control: Unlike room-based CRAC/CRAH systems, RDHx units do not include built-in humidifiers. Therefore, centralised humidification systems need to be integrated into the overall HVAC design to maintain environmental conditions within ASHRAE standards.

RDHx Implementation: How Yotta Supports High-Density Racks

To efficiently manage high-density racks with loads of up to 60kW, Yotta has integrated Rear Door Heat Exchanger (RDHx) units across its data center infrastructure. These cooling units are installed at the rear of each rack, directing hot exhaust air straight into the RDHx inlets for immediate cooling. This approach ensures that heat is contained and dissipated right at the source, maintaining stable environmental conditions across the data center. Each RDHx is connected to an extended chilled water network, supported by precision valves and monitoring devices that ensure optimal flow and temperature control.

Yotta’s RDHx deployment is carefully aligned with rack OEMs and hardware manufacturers to deliver high-performance, seamless integration. The system is designed with centralised humidifier control to support balanced humidity levels, complementing the localised cooling provided by the RDHx. Each unit is powered by a UPS system with sufficient battery backup, ensuring uninterrupted cooling during power transitions. To further enhance reliability, every RDHx unit is equipped with an Automatic Transfer Switch (ATS) that draws from dual power sources-delivering robust power redundancy for mission-critical workloads.

Conclusion: Future-Proofing Colocation with RDHx

As the demand for compute-intensive applications continues to surge, colocation providers must adopt smarter, more scalable cooling strategies to keep pace. Rear Door Heat Exchangers offer a practical and energy-efficient solution, enabling high-density deployments without compromising space or uptime. With precise, rack-level cooling and integration flexibility, RDHx is becoming the preferred choice for modern data centers. At Yotta, our adoption of RDHx is a strategic step toward next-generation infrastructure. It allows us to support cutting-edge AI and HPC workloads, while maintaining the high availability, energy efficiency, and operational excellence our clients expect.

What Financial Institutions Must Consider When Choosing a Data Center

Posted on July 9, 2025July 9, 2025 by yotta

In 2024 alone, Indian banks processed over 100 billion digital transactions, worth more than ₹600 lakh crore, through UPI, NEFT, RTGS, and IMPS. Meanwhile, the financial services sector’s cloud adoption surged by 45% year-over-year, according to IDC, as banks accelerate digital transformation, AI adoption, and mobile-first offerings.

But behind every seamless payment, real-time trade, or fraud alert is an unseen hero: the data center. For financial institutions, choosing the right data center is no longer just a technical decision it’s a strategic imperative that influences regulatory compliance, customer trust, and business continuity.

So, what should BFSI leaders look for while selecting their Data Center Services Provider?

Regulatory Compliance Is Non-Negotiable

Banks operate in one of the most tightly regulated environments, being closely monitored by regulators like the RBI, SEBI, and the Ministry of Electronics and Information Technology (MeitY). From data localization mandates to ISO/PCI DSS certifications, there is no room for compromise.

– RBI’s IT Framework mandates that data pertaining to Indian citizens must reside within India.
– Compliance with ISO 27001, PCI DSS, and SOC 2 signal that your infrastructure meets global security and privacy benchmarks.
– Audit-readiness is crucial—data centers should support banks during regulatory inspections or third-party audits.

What to Ask:

1. Is the data center RBI-compliant and ISO/PCI certified?
2. Can it provide real-time logs and documentation during audits?

Uptime: Because Finance Never Sleeps

In an always-on economy, even 1 minute of downtime can cost a bank crores in transaction losses, customer churn, and reputational damage. Look for:

– Tier III+ or Tier IV certification from the Uptime Institute.
– Redundant power, cooling, and network systems.
– Service Level Agreements (SLAs) offering 99.99% or higher uptime.

A resilient data center should ensure operations remain unaffected during natural disasters, cyberattacks, or infrastructure failures.

What to Ask:

1. What’s your historical uptime record?
2. Do you offer dual power feeds, backup generators, and N+1 cooling?

Uncompromising Physical and Cyber Security

The financial sector is among the top 3 targets for cybercrime globally, making layered security essential. Institutions must demand:

– Physical security: 24/7 guards, CCTV, biometric access, multi-factor authentication.
– Cybersecurity: DDoS mitigation, managed firewalls, SIEM, IDS/IPS, and regular penetration testing.
– Zero Trust architecture for internal segmentation and access control.

What to Ask

1. Do you offer SOC-as-a-Service or Managed SIEM?
2. How do you handle DDoS attacks and ransomware threats?

Disaster Recovery (DR) & Business Continuity

A robust DR plan is essential for operational continuity. The ideal data center partner should offer:

– Geographically separated DR sites.
– Automated backup and recovery systems.
– Continuous replication for critical workloads.

With RBI requiring a working DR site for Core Banking Systems (CBS), failover readiness is no longer optional.

What to Ask:

1. How far is your DR site from the primary?
2. How quickly can you recover services during a disaster?

Scalability and Flexibility

With fintech partnerships, open banking APIs, and real-time KYC/AML systems, the pace of data growth is relentless. Choose a provider that offers:

– Modular infrastructure (rack, cage, suite, or floor options).
– High-density rack support (10–40 kW).
– Flexible contracts (pay-as-you-grow, OPEX-first).

What to Ask:

1. Can I scale from 1 rack to 50 without major capex?
2. What’s your average power density per rack?

Connectivity and Low Latency

High-frequency trading, UPI payments, or fraud detection all demand sub-second responses.

– Direct connectivity to financial hubs like BSE/NSE.
– Carrier-neutral facility with access to multiple ISPs.
– Cloud-on-ramps to AWS, Azure, Google Cloud for hybrid deployments.

What to Ask:

1. Do you have fiber diversity and dual paths?
2. Can I peer with exchanges or fintech partners from your facility?

Operational Expertise & Transparency

Choose a partner that acts like an extension of your IT team.

– 24×7 Network Operations Center (NOC) and on-site engineers.
– Remote hands, migration support, rack-and-stack services.
– Transparent pricing with no hidden charges.

How Yotta is empowering BFSI with Trust, Compliance & Scale

Built for Regulation and Resilience

Yotta’s hyperscale data centers are designed to meet the unique demands of India’s financial ecosystem.

Key Compliance Features:

– Tier IV-certified (e.g., Yotta NM1 in Navi Mumbai).
– Strategic presence in the IFSC zone with access to global and domestic markets.(eg: Yotta G1 in Gujarat)
– Aligned with RBI guidelines.
– Certified for ISO 27001, ISO 22301, PCI DSS, and more.
– MeitY-empaneled for hosting critical government and BFSI workloads.

Secured & Always-On

– Yotta NM1 provides 48+ hours of backup power, 15+ security layers, and 99.999% uptime SLAs.
– With SEZ-based billing that offers significant cost advantages, Yotta G1 is also uniquely positioned to function as a Data Embassy, ensuring data sovereignty and regulatory compliance for international institutions operating in India.
– Security includes SOC-as-a-Service, SIEM, DDoS protection, and advanced access controls.

Hyper-Scalable & AI-Ready

– Rack supports up to 40 kW, perfect for AI/ML training, HFT, or analytics.
– Modular deployments let you scale from 1 rack to thousands without major rework.

In Summary

For today’s banks, NBFCs, fintechs, and payment gateways, the data center is no longer just backend plumbing—it’s a pillar of innovation and trust. Choosing a provider like Yotta—with regulatory alignment, unmatched uptime, and hyperscale capability—offers a competitive edge in an increasingly digital financial world.

Ready to reimagine your digital infrastructure? Yotta is already there.

The Future of Colocation Hosting: Emerging Trends Transforming Data Centers in 2025

Posted on June 25, 2025July 9, 2025 by yotta

As digital transformation accelerates and enterprises expand their hybrid IT strategies, colocation hosting is undergoing a significant evolution. Colocation is no longer about just rack space, power & connectivity – it has evolved into a critical enabler of cloud-native agility, AI-driven workloads, ESG compliance, and edge-ready infrastructure. With global AI workloads projected to grow by 25–35% annually through 2027 (Bain & Company), colocation data centers must now support high-density GPU clusters, real-time data processing, and ultra-low-latency connectivity. The industry is evolving with next-gen facilities, intelligent automation, and sustainable operations tailored to the demands of modern enterprises.

AI-Ready Colocation: The Rise of High-Density Infrastructure

One of the most transformative shifts in colocation hosting is the rise of high-performance computing (HPC) infrastructure. The explosion of generative AI, large language models, and real-time analytics is pushing colocation providers to adopt high-density racks with liquid cooling, advanced thermal management, and low-latency connectivity. GPU clusters and bare metal AI training workloads are increasingly being deployed in colocation environments that are optimised for high-density operations and scalable interconnects.

Colocation facilities must now support up to 100kW+ per rack densities, driven by AI and HPC use cases. Data Centers are now transitioning from traditional air-cooled setups to hybrid and direct-to-chip liquid cooling systems. This shift not only improves performance and energy efficiency but also enables enterprises to cut model training times by half, accelerating time to market and delivering a critical competitive edge in AI-driven innovation.

The Sustainability Imperative

As power consumption in data centers rises, sustainability is no longer optional it is a business imperative.. Enterprises have to meet ESG goals, and colocation providers are expected to align their infrastructure and operations with sustainability priorities. The future belongs to data centers that can guarantee green power, achieve low PUE (Power Usage Effectiveness) scores, and offer transparency in carbon reporting.

From on-site solar and wind power integration to 100% green energy sourcing options and innovative battery backup systems, colocation hosts are transforming into energy-conscious digital ecosystems.

Rise of Edge-Ready, Interconnected Ecosystems

Colocation is also moving closer to end-users, driven by the growing need for low-latency, high-bandwidth edge computing. In sectors like fintech, retail, gaming, and autonomous systems, the ability to process data in near real-time is business-critical. This is fueling the rise of modular, containerised, and regionally distributed micro-data centers that bring compute power to the edge.

Carrier-neutral colocation providers are building dense, software-defined connectivity fabrics that enable direct, private interconnects between enterprises, cloud platforms, SaaS providers, and ISPs. One can expect widespread adoption of on-demand interconnection services, giving enterprises plug-and-play access to global cloud on-ramps, AI platforms, and low-latency cross-connects that power distributed applications and real-time data flows.

Automation, AI Ops, and Digital Twins

Colocation operations are becoming smarter and more efficient, thanks to the deep integration of AI, automation, and advanced DCIM (Data Center Infrastructure Management) tools. Predictive maintenance powered by machine learning helps preempt hardware failures, while AI-driven energy management systems dynamically adjust power and cooling to IT load minimizing energy waste and operational costs.

Digital twin technology is now widely used for real-time simulation, capacity planning, and lifecycle management. These AI-powered replicas of physical infrastructure enable data centers to model equipment placement, refine thermal design, and proactively identify scalability constraints before they impact performance.

Environmental factors like temperature, humidity, and airflow are continuously analysed to optimize rack-level efficiency and prevent overheating, while AR-assisted interfaces are beginning to support remote diagnostics and on-site coordination. Remote monitoring, robotic inspections, and real-time dashboards now provide granular visibility into power usage, environmental metrics, carbon footprint, and equipment health.

Security and Compliance by Design

According to Grand View Research, the global data center security market was valued at $18.42 billion in 2024 and is expected to grow at a CAGR of 16.8% between 2025 and 2030. With increasing cyber risks and stringent data localisation laws, security and compliance have become foundational to colocation services. Providers are investing heavily in physical security, biometric access controls, air-gapped zones, and continuous surveillance. Certifications like ISO 27001, PCI DSS, and Uptime Tier IV are business enablers.

Modern colocation facilities are also integrating zero-trust architectures, sovereign cloud zones, and encryption-as-a-service offerings. As data regulations become stricter, especially in financial and healthcare sectors, enterprises are turning to colocation partners that can offer built-in compliance.

Yotta Data Services: Pioneering India’s Colocation Future

Yotta Data Services is at the forefront of building and operating the country’s largest and most advanced data center parks. Strategically located across Navi Mumbai, Greater Noida, and Gujarat, Yotta’s facilities are engineered for scale, efficiency and digital sovereignty – making them ideal for enterprises embracing AI, cloud, and high-performance computing.

With a design PUE as low as 1.4, Yotta integrates green energy and intelligent infrastructure to deliver high-density colocation that supports demanding AI workloads. Its sovereign data centers also host Shakti Cloud, India’s powerful AI cloud platform, ensuring performance, compliance, and data locality.

Yotta’s multi-tenant colocation services offer highly customisable options from single rack units (1U, 2U, and more) to full server cages, suites, and dedicated floors. These are housed in state-of-the-art environments with robust power redundancy, advanced cooling, fire protection, and environmental controls – delivering enterprise-grade reliability, energy efficiency, and cost-effectiveness to support the digital ambitions of tomorrow.

Understanding Data Center Pricing: The Four Pillars Explained

Posted on May 29, 2025May 29, 2025 by yotta

As enterprises undergo rapid digital transformation, data centers have emerged as critical enablers of always-on, high-performance IT infrastructure. From hosting mission-critical applications to powering AI workloads, data centers offer organisations the scale, reliability, and security needed to compete in a digital-first economy. However, as more businesses migrate to colocation and hybrid cloud environments, understanding the intricacies of data center pricing becomes vital.

At the core of every data center pricing model are four key pillars: Power, Space, Network, and Support. Together, these elements determine the total cost of ownership (TCO) and influence operational efficiency, scalability, and return on investment.

1. Power: Power is the single largest cost component in a data center pricing model, accounting for up to 50-60% of the overall operational expense. Power is typically billed based on either actual consumption (measured in kilowatts or kilowatt-hours) or committed capacity – whichever pricing model is chosen, understanding usage patterns is essential.

High-density workloads such as AI model training, financial simulations, and media rendering demand substantial compute power, and by extension, more electricity. This makes the power efficiency of a data center critical measured by metrics like Power Usage Effectiveness (PUE). A lower PUE indicates that a greater proportion of power is used by IT equipment rather than cooling or facility overheads, translating to better cost efficiency.

When evaluating power pricing, businesses should ask:

– Is pricing based on metered usage or a flat rate per kW?

– What is the data center’s PUE?

– Can the data center support high-density rack configurations?

– Is green energy available or part of the offering?

2. Space: Data centers are increasingly supporting high-density configurations, allowing enterprises to pack more compute per square foot – a shift driven by AI workloads, big data analytics, and edge computing. Instead of traditional low-density deployments that require expansive floor space, high-density racks (often exceeding 10–15 kW per rack) are becoming the norm, delivering greater value and performance from a smaller footprint.

Advanced cooling options such as hot/cold aisle containment, in-rack or rear-door cooling, and even liquid cooling are often available to support these dense configurations, minimising thermal hotspots and improving energy efficiency.

Key considerations when evaluating space pricing include:

– What is the maximum power per rack the facility can support?

– Are advanced cooling solutions like in-rack or liquid cooling supported for AI or HPC workloads?

– Are there flexible options for shared vs. dedicated space (cage, suite, or row)?

– Is modular expansion possible as compute demand grows?

– Does the provider offer infrastructure design consulting to optimize space-to-performance ratios?

3. Network: While power and space house the infrastructure, the network enables it to function connecting systems, users, and clouds seamlessly. Power and space host your infrastructure, but it’s the network that activates it – enabling data to flow seamlessly across clouds, users, and geographies. Network performance can make or break mission-critical services, especially for latency-sensitive applications like AI inferencing, financial trading, and real-time collaboration.

Leading hyperscale data centers operate as network hubs, offering carrier-neutral access to a wide range of Tier-1 ISPs, cloud service providers (CSPs), and internet exchanges (IXs). This diversity ensures better uptime, lower latency, and competitive pricing.

Modern facilities also offer direct cloud interconnects that bypass the public internet to ensure lower jitter and enhanced security. Meanwhile, software-defined interconnection (SDI) services and on-demand bandwidth provisioning have introduced flexibility never before possible.

The network pricing model varies by provider, but key factors to evaluate include:

– Are multiple ISPs or telecom carriers available on-site for redundancy and price competition?

– What is the pricing model for IP transit flat-rate, burstable, or 95th percentile billing?

– Are cross-connects priced per cable or port, and are virtual cross-connects supported?

– Is there access to internet exchanges or cloud on-ramp ecosystems?

– Does the data center support scalable bandwidth and network segmentation (VLANs, VXLANs)?

4. Support: The fourth pillar Support encompasses the human and operational services that keep infrastructure running smoothly. From basic tasks like reboots and cable management to advanced services such as patching, compliance assistance, and disaster recovery, support offerings can vary significantly between providers.

Beyond tangible infrastructure, support services form the fourth critical pillar of data center pricing. These include remote hands, monitoring, troubleshooting, infrastructure management, and compliance support – all of which have a direct impact on uptime and business continuity.

While some providers bundle basic support into the overall pricing, others follow a pay-as-you-go or tiered model. The range of services can vary from basic reboots and cable replacements to advanced offerings like patch management, backup, and disaster recovery services.

Important support considerations include:

– What SLA’s are in place for incident resolution and response times?

– Is 24/7 support available on-site and remotely?

– What level of expertise do support engineers possess (e.g., certifications)?

– Are managed services or white-glove services available?

For enterprises without a local IT presence near the data center, high-quality support services can serve as a valuable extension of their internal teams.

Bringing It All Together

Evaluating data center pricing through the lens of Power, Space, Network, and Support helps businesses align their infrastructure investments with operational needs and long-term goals. While each of these pillars have individual cost implications, they are deeply interdependent. For instance, a facility offering lower space cost but limited power capacity might not support high-performance computing. Similarly, a power-efficient site without robust network options could bottleneck AI or cloud workloads.

As enterprise IT evolves driven by trends like AI, edge computing, hybrid cloud, and data sovereignty so too will pricing models. Providers that offer transparent, flexible, and scalable pricing across these four pillars will be best positioned to meet the demands of tomorrow’s digital enterprises.

As enterprise IT & data center needs evolve – driven by trends like AI, hybrid cloud, edge computing, and data sovereignty – so will pricing models. Providers that offer transparent, scalable, and flexible offerings across these four pillars will be best positioned to meet the demands of future digital enterprises.

Conclusion: For CIOs, CTOs, and IT leaders, decoding data center pricing goes beyond cost it’s about creating long-term value and strategic alignment. The ideal partner delivers a well-balanced approach across Power, Space, Network, and Support, combining performance, scalability, security, sustainability, and efficiency. Focusing solely on price, can result in infrastructure bottlenecks, hidden risks, and lost opportunities for innovation. A holistic, future-ready evaluation framework empowers organizations to build infrastructure that supports innovation, resilience, and growth.

Colocation Infrastructure – Reimagined for AI and High-Performance Computing

Posted on May 29, 2025May 29, 2025 by yotta

The architecture of colocation is undergoing a paradigm shift, driven not by traditional enterprise IT, but by the exponential rise in GPU-intensive workloads powering generative AI, large language models (LLMs), and distributed training pipelines. Colocation today must do more than house servers it must thermodynamically stabilize multi-rack GPU clusters, deliver deterministic latency for distributed compute fabrics, and maintain power integrity under extreme electrical densities.

Why GPUs Break Legacy Colocation Infrastructure

Today’s AI systems aren’t just compute-heavy, they’re infrastructure-volatile. The training of a multi-billion parameter LLM on an NVIDIA H100 GPU cluster involves sustained tensor core workloads pushing 700+ watts per GPU, with entire racks drawing upwards of 40–60 kW under load. Even inference at scale, particularly with memory-bound models like RAG pipelines or multi-tenant vector search, introduces high duty-cycle thermal patterns that legacy colocation facilities cannot absorb.

Traditional colocation was designed for horizontal CPU scale, think 2U servers at 4–8 kW per rack, cooled via raised floor air handling. These facilities buckle under the demands of modern AI stacks:

i. Power densities exceeding 2.5–3x their design envelope.

ii. Localized thermal hotspots exceeding 40–50°C air exit temperatures.

iii. Inability to sustain coherent RDMA/InfiniBand fabrics across zones.

As a result, deploying modern AI stacks in a legacy colocation isn’t just inefficient it’s structurally unstable.

Architecting for AI: The Principles of Purpose-Built Colocation

Yotta’s AI-grade colocation data center is engineered ground-up with first-principle design addressing the compute, thermal, electrical, and network challenges introduced by accelerated computing. Here’s how:

1. Power Density Scaling: 100+ kW Per Rack: Each pod is provisioned for densities up to 100 kW per rack, supported by redundant 11–33kV medium voltage feeds, modular power distribution units (PDUs), and multi-path UPS topologies. AI clusters experience both sustained draw and burst-mode load spikes, particularly during checkpointing, optimizer backprop, or concurrent GPU sweeps. Our electrical systems buffer these patterns through smart PDUs with per-outlet telemetry and zero switchover failover.

We implement high-conductance busways and isolated feed redundancy (N+N or 2N) to deliver deterministic power with zero derating, allowing for dense deployments without underpopulating racks, a common hack in legacy setups.

2. Liquid-Ready Thermal Zones: To host modern GPU servers like NVIDIA’s HGX H100 8-GPU platform, direct liquid cooling isn’t optional it’s mandatory. We support:

– Direct liquid cooling

– Rear Door Heat Exchangers (RDHx) for hybrid deployments

– Liquid Immersion cooling bays for specialized ASIC/FPGA farms

Our data halls are divided into thermal density zones, with cooling capacity engineered in watts-per-rack-unit (W/RU), ensuring high-efficiency heat extraction across dense racks running at 90–100% GPU utilization.

3. AI Fabric Networking at Rack-Scale and Pod-Scale: High-throughput AI workloads demand topologically aware networking. Yotta’s AI colocation zones support:

– InfiniBand HDR/NDR up to 400 Gbps for RDMA clustering which allows data transfer directly between the memory of different nodes

– NVLink/NVSwitch intra-node interconnects

– RoCEv2/Ethernet 100/200/400 Gbps fabrics with low oversubscription ratios (<3:1)

Each pod is a non-blocking leaf-spine zone, designed for horizontal expansion with ultra-low latency (<5 µs) across ToRs. We also support flat L2 network overlays, container-native IPAM integrations (K8s/CNI plugins), and distributed storage backplanes like Ceph, Lustre, or BeeGFS critical for high IOPS at GPU memory bandwidth parity.

Inference-Optimized, Cluster-Ready, Sovereign by Design

The AI compute edge isn’t just where you train it’s where you infer. As enterprises scale out retrieval-augmented generation, multi-agent LLM inference, and high-frequency AI workloads, the infrastructure must support:

i. Fractionalized GPU tenancy (MIG/MPS)

ii. Node affinity and GPU pinning across colocation pods

iii. Model-parallel inference with latency thresholds under 100ms

Yotta’s high-density colocation is built to support inference-as-a-service (IaaS) deployments that span GPU clusters across edge, core, and near-cloud regions all with full tenancy isolation, QoS enforcement, and AI service-mesh integration.

Yotta also provides compliance-grade isolation (ISO 27001, PCI-DSS, MeitY-ready) with zero data egress outside sovereign boundaries enabling inference workloads for BFSI, health, and government sectors where AI cannot cross borders.

Hybrid-Native Infrastructure with Cloud-Adjacent Expandability

AI teams don’t want just bare metal they demand orchestration. Yotta’s colocation integrates natively with Shakti Cloud, providing:

i. GPU leasing for burst loads

ii. Bare-metal K8s clusters for CI/CD training pipelines

iii. Storage attach on demand (RDMA/NVMe-oF)

This hybrid model supports training on-prem, bursting to cloud, inferring at edge all with consistent latency, cost visibility, and GPU performance telemetry. Whether it’s LLM checkpoint resumption or rolling out AI agents across CX platforms, our hybrid infra lets you build, train, and deploy without rebuilding your stack.

Conclusion

In an era where GPUs are the engines of progress and data is the new oil, colocation must evolve from passive hosting to active enablement of innovation. At Yotta, we don’t just provide the legacy colocation, we deliver AI-optimized colocation infrastructure engineered to scale, perform, and adapt to the most demanding compute workloads of our time. Whether you’re building the next generative AI model, deploying inference engines across the edge, or running complex simulations in engineering and genomics, Yotta provides a foundation designed for what’s next. The era of GPU-native infrastructure has arrived and it lives at Yotta.

Partnering for the AI Ascent: Critical role of Colocation Providers in the AI Infrastructure Boom

Posted on May 20, 2025May 20, 2025 by yotta

As the global race to adopt and scale artificial intelligence (AI) accelerates from generative AI applications to machine learning-powered analytics, organisations are pushing the boundaries of innovation. But while algorithms and data often take center stage, there’s another crucial component that enables this technological leap: infrastructure. More specifically, the role of colocation providers is emerging as pivotal in AI driven transformation.

According to Dell’Oro Group, global spending on AI infrastructure including servers, networking, and data center hardware is expected to reach $150 billion annually by 2027, growing at a compound annual growth rate (CAGR) of over 40%. Meanwhile, Synergy Research Group reports that over 60% of enterprises deploying AI workloads are actively leveraging colocation facilities due to the need for high-density, scalable environments and proximity to data ecosystems. AI’s potential cannot be unlocked without the right physical and digital infrastructure and colocation providers are stepping in as strategic enablers of this transformation.

The Infrastructure Strain of AI

Unlike traditional IT workloads, AI applications require massive computational resources, dense GPU clusters, ultra-fast data throughput, and uninterrupted uptime. Traditional enterprise data centers, originally designed for more moderate workloads, are increasingly unable to meet the demands of modern AI deployments. Limitations in power delivery, cooling capabilities, space, and network latency become significant bottlenecks. Enterprises that attempt to scale AI on-premises often face long lead times for infrastructure expansion, high capital expenditures, and operational inefficiencies. This is where colocation data centers offer a compelling, scalable and efficient alternative.

Why Colocation is the Backbone of AI Deployment

1. Rapid Scalability: AI projects often require rapid scaling of compute power due to the high computational demands of training models or running inference tasks. Traditional data center builds, or infrastructure procurement, can take months, but with colocation, companies can quickly expand their capacity. Colocation providers offer pre-built, ready-to-use data center space with the required power and connectivity. Organisations can scale up or down as their AI needs evolve without waiting for the lengthy construction or procurement cycles that are often associated with in-house data centers.

2. High-Density Capabilities: AI workloads, particularly those involving machine learning (ML) and deep learning (DL), require specialised hardware such as Graphics Processing Units (GPUs). These GPUs can consume significant power, with some racks filled with GPUs requiring 30kW or more of power. Colocation facilities are designed to handle such high-density infrastructure. Many leading colocation providers have invested in advanced cooling systems, such as liquid cooling, to manage the extreme heat generated by these high-performance computing setups. Additionally, custom rack designs allow for optimal airflow and power distribution, ensuring that these systems run efficiently without overheating or consuming excessive power.

3. Proximity to AI Ecosystems: AI systems rely on diverse data sources like large datasets, edge devices, cloud services, and data lakes. Colocation centers are strategically located to provide low-latency interconnects, meaning that data can flow seamlessly between devices and services without delays. Many colocation facilities also offer cloud on ramps, which are direct connections to cloud providers, making it easier for organisations to integrate AI applications with public or hybrid cloud services. Additionally, peering exchanges allow for fast, high-volume data transfers between different networks, creating a rich digital ecosystem that supports the complex and dynamic workflows of AI.

4. Cost Optimisation: Building and maintaining a private data center can be prohibitively expensive for many organisations, especially startups and smaller enterprises. Colocation allows these companies to share infrastructure costs with other tenants, benefiting from the economies of scale. Instead of investing in land, physical infrastructure, cooling, power, and network management, businesses can rent space, power, and connectivity from colocation providers. This makes it much more affordable for companies to deploy AI solutions without the large capital expenditures associated with traditional data center ownership.

5. Security & Compliance: AI applications often involve handling sensitive data, such as personal information, proprietary algorithms, or research data. Colocation providers offer enterprise-grade physical security (such as biometric access controls, surveillance, and on-site security personnel) to ensure that only authorised personnel have access to the hardware. They also provide cybersecurity measures such as firewalls, DDoS protection, and intrusion detection systems to protect against external threats. Moreover, many colocation facilities are compliant with various regulatory standards (e.g., DPDP, GDPR, HIPAA, SOC 2), which is crucial for organisations that need to meet legal and industry-specific requirements regarding data privacy and security.

Yotta: Leading the Charge in AI-Ready Infrastructure

While many colocation providers are only beginning to adapt to AI-centric demands, Yotta is already several steps ahead.

1. Purpose-Built for the AI Era: Yotta’s data centers are designed with AI workloads in mind. From ultra-high rack densities to advanced cooling solutions like direct-to-chip liquid cooling, Yotta is ready to host the most demanding AI infrastructure. Their facilities can support multi-megawatt deployments of GPUs, enabling customers to scale seamlessly.

2. Hyperconnectivity at Core: Yotta’s hyperscale data center parks are strategically designed with hyperconnectivity at the heart of their architecture. As Asia’s largest hyperscale data center infrastructure, Yotta offers seamless and direct connectivity to all major cloud service providers, internet exchanges, telcos, and content delivery networks (CDNs). This rich interconnection fabric is crucial, especially for data-intensive workloads like Artificial Intelligence (AI), Machine Learning (ML), real-time analytics, and IoT. We also actively implement efficient networking protocols and software-defined networking (SDN) to optimise bandwidth allocation, reduce congestion, and support the enormous east-west traffic typical in AI training clusters. The result is greater throughput, lower latency, and improved AI training times.

3. Integrated AI Infrastructure & Services: Yotta is more than just a space provider — it delivers a vertically integrated AI infrastructure ecosystem. At the heart of this is Shakti Cloud, India’s fastest and largest AI-HPC supercomputer, which offers access to high-performance GPU clusters, AI endpoints, and serverless GPUs on demand. This model allows developers and enterprises to build, test, and deploy AI models without upfront infrastructure commitments. With Shakti Cloud:

– Serverless GPUs eliminate provisioning delays enabling instant, usage-based access to compute resources.

– AI endpoints offer pre-configured environments for training, fine-tuning, and inferencing AI models.

– GPU clusters enable parallel processing and distributed training for large-scale AI and LLM projects.

Additionally, Yotta provides hybrid and multi-cloud management services, allowing enterprises to nify deployments across private, public, and colocation infrastructure. This is critical as many AI pipelines span multiple environments and demand consistent performance and governance. From infrastructure provisioning to managed services, Yotta empowers businesses to focus on building and deploying AI models not managing underlying infrastructure.

4. Strategic Geographic Advantage: Yotta’s data center parks are strategically located across key economic and digital hubs in India including Navi Mumbai, Greater Noida, and Gujarat ensuring proximity to major business centers, cloud zones, and network exchanges. This geographic distribution minimises latency and enhances data sovereignty for businesses operating in regulated environments. Additionally, this pan-India presence supports edge AI deployments and ensures business continuity with multi-region failover and disaster recovery capabilities.

The Future of AI is Built Together

As organisations race to capitalise on AI, the importance of choosing the right infrastructure partner cannot be overstated. Colocation providers offer the agility, scale, and reliability needed to fuel this transformation. And among them, Yotta stands out as a future-ready pioneer, empowering businesses to embrace AI without compromise. Whether you’re a startup building your first model or a global enterprise training LLMs, Yotta ensures your infrastructure grows with your ambitions.

Importance of Data Center Certifications

Posted on April 29, 2025April 29, 2025 by yotta

As businesses become increasingly data-driven, the demand for highly secure, efficient, and reliable data infrastructure has never been higher. Data center certifications play a crucial role in assuring that facilities meet the highest standards for reliability, security, and regulatory compliance. These certifications guide businesses in selecting the right cloud or colocation partner especially in regulated industries like banking, healthcare, retail, media, and government.

Understanding Data Center Certifications and What They Mean for Your Business

Finance & BFSI: Where Security and Compliance Are Non-Negotiable

1. Uptime Institute Tier III & IV: These certifications ensure that data centers are built for continuous operations, even during maintenance or unexpected failures. For BFSI organisations that handle real-time transactions, any downtime could result in significant financial loss and customer dissatisfaction. Tier III and IV infrastructure guarantees availability and resilience, which are foundational for maintaining trust and operational stability.

2. RBI Cybersecurity Certification: Issued by the Reserve Bank of India, this certification confirms that a data center meets stringent cybersecurity protocols tailored for financial institutions. It includes standards for data protection, incident response, and access controls crucial for protecting digital assets and customer data in India’s rapidly digitising banking sector.

3. RBI Data Localisation Certification: With RBI mandating that all financial and customer data be stored within Indian borders, this certification is critical. It ensures that data sovereignty is upheld and that BFSI entities remain compliant with evolving regulatory mandates avoiding legal complications and maintaining seamless operations.

4. ISO Certifications: ISO 27001 is the global gold standard for information security. It provides assurance that the data center has robust security controls in place, from risk assessments to threat mitigation. For financial firms handling confidential data, it ensures protection against breaches and cyber threats, bolstering regulatory compliance and customer trust.

Additionally, ISO 9001 certifies our commitment to quality management, ensuring consistent service excellence. ISO 14001 demonstrates our dedication to environmental sustainability, and ISO 45001 ensures that our health and safety practices meet international best practices. For financial firms handling confidential data, these certifications collectively strengthen protection against breaches, bolster regulatory compliance, enhance customer trust, and support a sustainable, safe, and high-quality operational environment.

5. PCI DSS Compliance: Payment Card Industry Data Security Standard (PCI DSS) compliance is essential for any organisation dealing with card transactions. It ensures secure data handling, encryption, and access management. Without it, businesses risk hefty fines, fraud exposure, and reputational damage.

Healthcare, Government & Regulated Sectors: Trust Built on Compliance

1. ISO 22301 & ISO 20000-1: ISO 22301 ensures that our data center can maintain seamless business continuity during disruptions, safeguarding critical operations when they are needed most. Complementing this, ISO 20000-1 certifies the reliability and quality of our IT service management, ensuring consistent, high-performance service delivery. Together, these standards enhance operational stability, support compliance with strict regulatory requirements, and build lasting trust with the communities we serve.

2. MeitY Empanelment (VPC & GCC): Authorised by the Ministry of Electronics and Information Technology (MeitY), this certification enables data centers to host sensitive government workloads on virtual private or community cloud platforms. It ensures full regulatory compliance, making it indispensable for public sector projects requiring sovereign and secure cloud hosting.

Sustainability-Focused Businesses: Certifications that Support ESG Goals

1. LEED Gold Certification: LEED (Leadership in Energy and Environmental Design) Gold certification signifies that the data center is built with energy-efficient architecture and sustainable materials. Businesses today are under increasing pressure to meet ESG goals, and a LEED-certified facility helps them reduce environmental impact while enhancing their brand’s sustainability credentials.

2. IGBC Certification: The Indian Green Building Council (IGBC) certification highlights the data center’s commitment to eco-friendly operations, from power usage to water efficiency. It’s a strategic asset for companies looking to strengthen their sustainability programs and attract ESG-conscious stakeholders or investors.

Media, SaaS & Content-Driven Businesses: Protecting What’s Valuable

1. AICPA SOC 2 Certification: SOC 2 certification focuses on operational controls around data security, confidentiality, privacy, and availability —vital for SaaS providers and companies that handle user-sensitive data. It assures clients that their data is managed responsibly and is protected from unauthorized access or leaks, reinforcing trust in cloud environments.

2. Trusted Partner Network (TPN): Endorsed by the Motion Picture Association, TPN certification ensures that the data center adheres to the highest standards of digital content protection. It’s indispensable for media, entertainment, and broadcasting companies that need to protect intellectual property from piracy or leaks, especially during production and post-production workflows.

Enterprise IT & Interconnection: Powering Scalable, Neutral Infrastructure

1. Open-IX OIX-2 Certification: This certification validates network neutrality, redundancy, and operational best practices. It’s particularly valuable for enterprises and hyperscalers requiring robust, carrier-neutral interconnection points. Without OIX-2, organizations may face issues with vendor lock-in, poor scalability, and lower network reliability.

2. SAP Certification: For enterprises running SAP ERP systems, this certification guarantees that the data center is optimized to host SAP applications securely and efficiently. It ensures performance benchmarks are met, providing confidence in the stability and scalability of mission-critical SAP workloads.

Why Yotta is Ahead of the Curve

Yotta stands apart by offering the most comprehensive portfolio of certifications across compliance, performance, sustainability, and industry-specific standards. This commitment means that when you choose Yotta, you’re partnering with a provider that’s already aligned with your regulatory, operational, and strategic goals. Whether you’re in BFSI, healthcare, media, or government, Yotta helps you mitigate risk, achieve compliance, and scale with confidence.

This comprehensive certification portfolio positions Yotta as a strategic partner that empowers your business to:

i. Stay compliant with evolving regulations
ii. Ensure high availability and uptime
iii. Reduce environmental impact
iv. Protect sensitive data and digital assets
v. Be future-ready for scale, performance, and audits

Yotta’s investment in achieving and maintaining these certifications reflects operational excellence, innovation, and customer trust, making it the smart choice for businesses that demand the best from their IT infrastructure.

Gujarat’s Data Center Infrastructure: Driving Digital Transformation for Enterprises

Posted on April 3, 2025April 3, 2025 by yotta

Gujarat has rapidly emerged as a powerhouse for enterprise growth, driven by its robust business ecosystem, progressive policies, and strong digital infrastructure. As a key economic hub, the state offers enterprises a strategic advantage with seamless connectivity, investor-friendly policies, and a thriving technology-driven environment. Yotta G1, Gujarat’s premier data center, is a testament to this evolution, providing enterprises with a world-class facility to power their digital transformation.

As the digital backbone for enterprises across industries, Yotta G1 is designed to meet the most demanding requirements. It is strategically located within Gujarat, providing businesses with a highly secure and reliable data hosting environment. And while its presence in GIFT City, India’s first International Financial Services Centre (IFSC), offers significant regulatory and financial advantage.

While its presence in GIFT City brings added benefits for financial institutions and global enterprises, the data center’s significance extends far beyond regulatory compliance. Gujarat’s pro-business policies, combined with a rapidly expanding digital economy, make it an ideal destination for organizations seeking a secure, scalable, and high-performance IT infrastructure.

One of the most defining aspects of Yotta G1 is its unwavering commitment to high performance and energy efficiency. With a design PUE of less than 1.6, the facility optimizes power usage without compromising reliability. The data center is built with a total power capacity of 2MW, including 1MW dedicated to IT workloads, ensuring enterprises have the infrastructure to scale seamlessly. To support uninterrupted operations, Yotta G1 features redundant 33KV power feeders from two independent substations, eliminating the risk of power failures. The facility is further reinforced with N+1 2250 KVA diesel generators, ensuring continuous availability with 24 hours of backup fuel on full load. Additionally, our dry-type transformers and N+N UPS system with lithium-ion battery backup provide enterprises with the peace of mind that their critical operations will never be disrupted.

Ensuring optimal performance of IT infrastructure requires state-of-the-art cooling mechanisms, and Yotta G1 is equipped with a combination of district cooling and DX-type precision air conditioning. This enables businesses to run high-density workloads efficiently while maintaining the longevity of their hardware. Security and resilience are at the core of our operations. The facility is protected by Novec 1230 and CO2 gas-based fire suppression systems, offering advanced safety measures for mission-critical IT assets.

What truly differentiates Yotta G1 is its ability to provide enterprises with a secure, compliant, and growth-ready environment. The data center aligns with IFSC and Indian data privacy regulations, making it the ideal choice for businesses in BFSI, IT, healthcare, and other sectors that require stringent compliance. Coupled with round-the-clock monitoring by expert tech engineers, physical security, and customer service teams, Yotta G1 ensures that enterprises can focus on their core operations while we manage their infrastructure needs.

Beyond its world-class infrastructure, Yotta G1 data center in Gujarat is designed to support enterprises with flexible and scalable solutions. From colocation and private cloud to managed services, businesses can tailor their IT strategy with the confidence that their infrastructure will evolve alongside them. Spanning 21,000 sq. ft. with a capacity for 350 racks, the data center is built for future expansion, enabling organizations to scale without limitations.

Connectivity is another critical aspect of enterprise success, and Yotta G1 is engineered to facilitate seamless, high-speed data exchange. With redundant fiber and copper cross-connects, businesses benefit from uninterrupted access to global markets and high-speed processing capabilities. Additionally, enterprises operating out of Yotta G1 can leverage the cost efficiencies of Gujarat’s progressive business policies, including tax incentives, zero GST, and stamp duty exemptions, reducing overall operational expenses.

At Yotta, we believe that a colocation data center should not only provide infrastructure but also empower enterprises with the tools to innovate. Yotta G1 brings cutting-edge AI and cloud computing capabilities, allowing businesses to harness next-generation technologies without the need for massive capital investments. By combining high-performance computing with a secure, scalable, and cost-efficient infrastructure, we are enabling enterprises to redefine the way they operate in an increasingly digital world.

Conclusion

Yotta G1 is more than just Gujarat’s first hyperscale-grade data center it is a catalyst for enterprise transformation. Whether you are a growing startup, a multinational corporation, or a financial powerhouse, Yotta G1 delivers the reliability, compliance, and scalability your business needs to thrive in a digital-first economy. As enterprises navigate the complexities of this evolving landscape, Yotta G1 is here to provide the foundation for their success, ensuring that Gujarat remains at the forefront of India’s digital revolution.

How AI and ML are Shaping Data Center Infrastructure and Operations

Posted on February 25, 2025February 25, 2025 by yotta

The rapid evolution of cloud computing, edge computing, and the rising demands of AI-driven workloads have made efficient data center management increasingly complex. As data volumes surge and the need for faster processing grows, traditional data center infrastructure and operations are being stretched beyond their limits. In response, Artificial Intelligence (AI) and Machine Learning (ML) are driving a fundamental transformation in how data centers operate, from optimising resource allocation to improving energy efficiency and security.

AI and ML are addressing key industry challenges such as scaling infrastructure to meet growing demands, reducing operational costs, minimising downtime, and enhancing system reliability. These technologies not only streamline the day-to-day operations of data centers but also lay the groundwork for the future of digital infrastructure—enabling more autonomous, adaptable, and sustainable systems.

AI and ML: Transforming Data Center Operations

1. AI-Driven Automation and Predictive Maintenance: Traditionally, data center management required extensive manual oversight, leading to inefficiencies and delays. However, AI-driven automation is reshaping this landscape by enabling real-time monitoring, self-healing systems, and predictive maintenance.

AI-Driven Automation optimises workflows, reducing human intervention and ensuring more consistent performance. By automating repetitive tasks, staff can focus on higher-valueoperations. Self-healing systems autonomously detect, diagnose, and rectify faults without service disruption. Predictive Maintenance uses ML algorithms to analyse sensor data from servers, power supplies, and cooling systems to detect anomalies before failures occur. AI-powered digital twins analyse data silos, track facility components, and make real-time adjustments, enabling predictive maintenance and minimising operational disruption.

Sustainable operations are not just about cost savings; they are integral to meeting corporate and regulatory sustainability targets. AI enables data centers to achieve these goals while maintaining high operational efficiency

2. Energy Efficiency and Sustainable Operations: With increasing concerns about carbon footprints and rising operational costs, AI is playing a crucial role in enhancing energy efficiency in data centers. ML algorithms analyse historical power consumption patterns, enabling intelligent decision-making that optimises cooling, workload distribution, and power management to minimise energy waste. Dynamic cooling mechanisms, powered by AI, adjust cooling systems based on real-time data, such as server workload, external climate conditions, and humidity levels.

Energy-efficient operations are not just about cost savings—they are also about meeting sustainability targets. Many data centers are now integrating renewable energy sources, with AI playing a critical role in balancing and optimising these resources. AI can predict power needs, helping data centers leverage renewables more effectively, thus reducing dependency on non-renewable sources.

3. Intelligent Workload and Resource Optimisation: AI and ML facilitate dynamic workload distribution, ensuring optimal allocation of resources such as compute, storage, and networking are allocated efficiently. These intelligent systems analyse workload patterns, redistribute resources dynamically, prevent bottlenecks, and improve overall system performance. This flexibility is critical as workloads become more diverse, particularly with the rise of AI workloads that require heavy computational power.

AI-driven orchestration tools empower data centers to scale workloads automatically based on demand. These tools optimise server utilisation, reducing unnecessary energy consumption, and preventing system overloads. As workloads become increasingly diverse, with the rise of AI-driven workloads such as real-time analytics, machine learning model inference, and AI training, it’s essential for data centers to utilise intelligent resource management to meet computational demands.

4. Enhanced Security and Threat Detection: As cybersecurity risks evolve, data centers are at the forefront of defense against increasingly sophisticated attacks. AI technologies are enhancing the security infrastructure by enabling real-time threat detection and faster response times.

AI-driven behavioural analytics can detect abnormal activity patterns indicative of cyberattacks or unauthorised access. These systems learn from historical data and continuously adapt to new attack vectors, ensuring more robust defenses against zero-day exploits and complex security breaches. By integrating ML-based security solutions, data centers can now protect against a wider range of threats, including DDoS attacks, insider threats, and ransomware. These systems can autonomously mitigate threats by triggering automatic responses such as isolating compromised systems or adjusting firewall settings.

Future of AI and ML in Data Centers

The future of AI and ML in data centers is poised to bring more advanced capabilities, including autonomous operations and edge computing. As AI continues to mature, we can expect smarter data centers that not only manage existing resources efficiently but also predict future needs. AI-powered edge computing will bring processing closer to data sources, reducing latency and improving response times. With the growth of IoT devices and edge deployments, AI will be integral in managing distributed infrastructure.

AI-driven data governance solutions will help hyperscale data centers meet compliance requirements and ensure data privacy. AI and ML are redefining data center infrastructure and operations by enhancing efficiency, optimising resource utilisation, improving security, and driving sustainability. Colocation data center companies like Yotta are leading the way in implementing these technologies to deliver state-of-the-art solutions, ensuring high performance, reliability, and cost-effectiveness.

Role of Advanced Cooling Technologies In Modern Data Centers

Posted on January 27, 2025January 28, 2025 by yotta

As data centers continue to scale to meet the demand for storage, processing power, and connectivity, one of the most pressing challenges they face is effectively managing heat. The increased density of servers, along with the rise of AI, ML, and big data analytics, has made efficient cooling technologies more critical than ever. Without proper cooling, the performance of IT equipment can degrade, resulting in costly failures, reduced lifespan of hardware, and downtime.

To address these challenges, data centers are adopting advanced cooling technologies designed to enhance energy efficiency and maintain operational reliability. The India Data Center Cooling Market, according to Mordor Intelligence, is expected to experience significant growth, with the market size projected to reach $8.32 billion by 2031, from $2.38 billion in 2025, growing at 23.21% CAGR.

Why Effective Cooling is Non-Negotiable for Data Centers

Modern data centers house thousands of servers and networking equipment, each running high workloads that generate significant heat. As data processing tasks grow more complex—especially with AI and machine learning applications that consume vast amounts of power—the heat generated becomes overwhelming.

The consequences of inadequate cooling can be catastrophic. For example, in October 2023, a major overheating incident in data centers led to several hours of service outages for prominent financial institutions in Singapore. The disruptions impacted online banking, credit card transactions, digital payments, and some ATMs.

Heat negatively impacts data centers in multiple ways. Servers operating at higher temperatures often throttle their performance to prevent overheating, resulting in slower processing times. In severe cases, system failures can lead to extended downtime, disrupting business continuity, compromising critical data, and incurring costly recovery efforts. Efficient cooling is particularly essential for colocation data centers, where multiple organisations share infrastructure, ensuring consistent performance across diverse workloads.

Innovative Cooling Solutions Shaping Data Centers

As the need for more powerful and efficient data centers continues to rise, so does the demand for innovative cooling technologies that can deliver better performance with less energy. Several advanced cooling methods have emerged in response to these challenges, transforming how data centers are designed and operated.

Liquid Cooling

Liquid cooling is gaining prominence for its superior heat transfer capabilities, especially in high-density server environments. Unlike traditional air cooling, which relies on air circulation, liquid cooling uses water or specialised coolants to transfer heat more efficiently.

1. Direct Liquid-to-Chip (DLC) Cooling: Coolant is pumped directly to processors and other critical components, removing heat at its source. DLC is ideal for AI and ML workloads, where traditional cooling methods struggle to meet thermal demands.

2. Immersion Cooling: Servers are submerged in non-conductive coolant, enabling exceptional thermal efficiency. Immersion cooling is particularly beneficial for AI model training, where processing power and heat generation are substantial.

Evaporative Cooling

Evaporative cooling relies on the natural process of water evaporation to lower air temperatures in data centers. Warm air is passed through water-saturated pads, and the evaporation of water cools the air, which is then circulated throughout the facility. This method offers an energy-efficient and sustainable solution for maintaining optimal temperatures in data centers.

Free Cooling

Free cooling capitalises on external environmental factors to minimise reliance on mechanical refrigeration. For instance, cold outside air or natural water sources like lakes can cool data centers effectively. This approach is cost-efficient and sustainable, making it a popular choice for green data centers.

Yotta Data Centers: Cooling Solutions for Modern IT Demands

Yotta, which operates hyperscale data centers, is adopting cutting-edge cooling technologies to meet the demands of modern IT environments. The facilities are designed to accommodate a wide range of cooling solutions, ensuring optimal performance, energy efficiency, and sustainability:

1. Air-Cooled Chillers with Adiabatic Systems: These systems achieve superior energy efficiency while maintaining consistent performance.

2. CRAH and Fan Wall Units: Located at the perimeter of data halls, these units provide N+1 or N+2 redundancy, ensuring continuous cooling even during maintenance or failure.

3. Inrow Units: Positioned near IT cabinets, these units offer precise cooling tailored to the needs of specific equipment.

4. Rear Door Heat Exchangers (RDHx): Ideal for high-density racks, these systems manage cooling for racks up to 50-60 kW, ensuring hot air is contained and effectively cooled.

5. Direct Liquid-to-Chip (DLC) Cooling: Designed in collaboration with hardware manufacturers, DLC systems can handle racks requiring up to 80 kW of cooling. Options include centralised or rack-specific Cooling Distribution Units (CDUs).

6. Liquid Immersion Cooling (LIC): Capable of providing up to 100% cooling for high-density racks, LIC systems are designed with hardware modifications for maximum efficiency.

With these advanced cooling technologies, Yotta ensures that its data centers in India remain robust, efficient, and future-ready, catering to the demands of AI, machine learning, and high-performance computing.