GPU Colocation for AI: High-Density, Secure Infrastructure with Lightedge
May 29, 2025
Lightedge
Author
As the demand for GPU-intensive workloads continues to rise in artificial intelligence (AI) and machine learning (ML), IT teams are increasingly looking for ways to optimize infrastructure—without the headaches of managing unpredictable compute demands or runaway cloud costs. One proven strategy is to offload the infrastructure burden by leveraging colocation (colo) services.
In this post, we’ll explore how Lightedge provides the necessary foundation for high-density, AI-driven workloads—and how one of our clients successfully built a scalable, self-service AI infrastructure using Lightedge’s colocation facilities.
Self-Service AI Deployment: A Case Study
Picture this: a company focused on large-scale AI and ML solutions was facing significant challenges with public cloud providers. Frequent compute delays, high costs, and limited infrastructure control made it nearly impossible to meet training timelines and stay on budget. They needed a flexible, high-performance solution that could scale rapidly during training surges yet remain cost-effective during quieter periods. And with sensitive datasets involved, airtight security and compliance were non-negotiable.
By moving their AI infrastructure to Lightedge’s colocation facilities, this organization unlocked a more strategic, controlled approach to infrastructure:
- Full Control Over GPU-Intensive Workloads: Unlike managed AI services where compute resources are shared or scheduled, Lightedge’s colocation allows deployment of custom hardware optimized for AI—specifically, GPU clusters designed to handle intensive AI/ML workloads. This gave the client the flexibility to allocate resources as needed, without concerns over throttling or delays.
- Scalable High-Density Environments: Lightedge’s colo services are designed to handle high-density compute environments, ensuring the power and cooling infrastructure can support intensive workloads. The client was able to scale their GPU resources dynamically without worrying about thermal constraints or power limitations often encountered in smaller on-premise setups.
- Cost Efficiency and Resource Utilization: Rather than paying by the second for GPU usage, the client benefited from a fixed-cost model based on power, space, and cooling. This provided predictable budgeting without sacrificing performance.
- Enhanced Security and Compliance: Given the sensitive nature of their data, including personal and financial information, our client required compliance with regulatory frameworks like HIPAA and GDPR. Lightedge’s data centers offer SOC 1, 2, and 3 certifications, as well as advanced physical and network security features. This allowed the client to deploy their infrastructure with confidence, knowing that both their data and hardware were fully secure.
Lightedge Colocation: Built for AI
Lightedge is engineered to support high-performance, GPU-based AI workloads. Here are some of the key technical features that enable our clients to build a resilient AI infrastructure:
1. High-Density Compute Support
AI workloads, especially those that leverage GPUs, place significant strain on data center power and cooling systems. Lightedge’s facilities are designed with high-density racks that can handle the power consumption and heat dissipation required for GPU-heavy infrastructure. This allows companies to scale up their infrastructure without worrying about infrastructure bottlenecks.
2. Dedicated Network Resources
AI workloads require low-latency, high-bandwidth networks, especially during data-intensive phases like model training. Lightedge provides dedicated network resources, including high-speed fiber connectivity, ensuring minimal latency between compute nodes and storage. This is critical for AI workloads where delays in data transfer can significantly impact performance.
3. Hybrid and Private Cloud Integration
While the focus of this article is colocation, Lightedge also offers hybrid solutions that combine private cloud with colocation. This allows organizations to manage their most sensitive workloads in a secure, dedicated environment while leveraging the flexibility of public cloud when needed. For AI workloads, this hybrid approach can optimize both cost and performance, allowing workloads to burst to the cloud when necessary, without compromising on control or security.
4. On-Demand Scalability
AI workloads are often unpredictable. Training a model might require substantial GPU resources for several days, followed by a period of inactivity or lighter inference tasks. Lightedge’s colocation services are flexible, allowing organizations to scale their infrastructure up or down as needed. Clients are able to deploy additional GPUs during peak periods and dial back resources during downtime, optimizing their overall costs.
5. Compliance and Security by Design
Data security and regulatory compliance are critical for organizations working with sensitive data. Lightedge’s facilities meet stringent compliance requirements, offering physical security, disaster recovery, and encrypted network options. These features were essential for our clients, ensuring that their AI infrastructure not only met performance requirements but also adhered to industry standards for data protection.
A Successful AI Strategy Starts with Infrastructure Flexibility
The public cloud can be a powerful tool—but it’s not the right fit for every AI workload. Our clients often find that once their models hit a certain scale or complexity, costs balloon, performance becomes inconsistent, and support for specialized hardware is limited.
That’s why Lightedge’s colocation services are becoming a go-to solution for AI teams that need:
- Full hardware control
- Support for custom AI architectures
- Budget predictability at scale
- High-performance GPU environments
- Seamless hybrid cloud options
Whether you’re a fast-growing startup building new AI products, or an enterprise with complex, compliance-driven datasets, Lightedge offers a flexible foundation that aligns with your AI roadmap.
Key Considerations for Hosting AI Workloads in a Colo Environment
Not all colo environments are created equal. When considering a colocation provider like Lightedge for AI workloads, it’s key to understand the operational and infrastructure requirements that will enable your success and ensure performance. Here are five critical areas to evaluate when selecting a provider:
- Power and Cooling Capacity: AI workloads, especially those that use GPUs, can consume significant power and generate heat. Ensure the colocation provider offers high-density racks and advanced cooling systems to prevent throttling or downtime due to overheating.
- Network Latency and Bandwidth: AI workloads depend on fast data transfers, especially during training. Evaluate whether the provider offers low-latency, high-bandwidth network options to ensure smooth operation between compute and storage nodes.
- Scalability: AI workloads can spike unpredictably. Choose a colocation provider that allows for easy scaling of resources, whether it’s adding more GPUs or expanding storage capacity, without requiring long-term commitments.
- Security and Compliance: For organizations working with sensitive or regulated data, compliance is a top priority. Ensure the colocation provider meets all relevant security standards and can handle the physical and network security requirements necessary for AI workloads.
- Resource Management Flexibility: The ability to control your own infrastructure is critical when working with GPU-based AI models. Make sure the colocation provider allows you to deploy, manage, and scale hardware without needing to rely on third-party management services, which can introduce latency and complexity.
Colocation isn’t just about relocating your hardware, it’s about rethinking how you scale, secure, and manage your AI infrastructure with greater precision. Choosing the right partner means unlocking the ability to run mission-critical AI workloads on your terms, with predictable costs and reliable performance.
Unlock Your AI Potential
Organizations that need performance, flexibility, and control are turning to Lightedge for the foundation for their AI infrastructure. With our high-density-ready data centers, direct connections to hyperscale clouds, and decades of expertise in secure, compliant infrastructure operations, we help you remove the operational roadblocks between your AI strategy and real-world execution.
Whether you’re building large language models, accelerating computer vision training, or driving real-time insights across your supply chain, Lightedge provides the infrastructure, support, and scalability to move faster—with confidence and control at every layer.
