The Data Center is Evolving - Are You?
Times moves fast...don't they? As the line between public and private cloud continues to blur, we're seeing the very definition of "data center" evolve right alongside it. Colocation, edge, interconnection - these aren't just technologies anymore. They're becoming foundational building blocks in how hybrid cloud actually operates today. We used to think of hybrid as static: pair a hyperscaler with some on-prem gear and bada-bing, bada-boom, call it a day...right? Wrong. That model no longer cuts it. Now, we're watching new hybrid patterns emerge that are more agile, distributed, and value-driven. Let's face it, it's no longer about where the workloads are - it's about how infrastructure adapts to optimize performance, cost, and connectivity in real-time. What are you seeing in your markets? Are you rethinking their hybrid strategies through the lens of colocation and interconnection? Are edge facilities shifting the center of gravity? Would love to hear your take - what are your thoughts?AI is Cleared for Takeoff in Aviation – Are We Ready?
The aviation industry is seeing record demand, yet it faces a complex web of challenges — from operational costs and workforce gaps to infrastructure strain. Enter AI. A recent article by our Aviation & Transportation team (Stefan Raab & Violeta Croce) explores how AI is reshaping the skies — from predictive maintenance and passenger flow optimization to real-time threat detection and data-driven decision-making. With Equinix interconnection at the core, airlines and airports can build the digital foundation to scale these innovations securely and efficiently. >> Check out the full blog here Which AI use case in aviation do you think will scale fastest? How do you see interconnection enabling real-time analytics at the edge in your industry? What’s the biggest challenge to deploying AI-powered operations at scale? 🚀 Let’s discuss how we’re turning runway complexity into opportunity.AI Chaos or AI Clarity? The Case for Centers of Excellence
As AI adoption accelerates, many enterprises are facing the same pitfalls we saw in early cloud rollouts: disconnected teams, duplicate stacks, and unpredictable costs. This latest article from the Equinix team (Kaladhar Voruganti-Senior Business Technologist & Aaron Delp-Director, AI Technical Solutions) introduces a compelling case for AI Centers of Excellence (CoEs) — not as a buzzword, but as a strategic framework to ensure: Centralized governance over AI models, data access, and security Infrastructure optimization to avoid redundant clouds and egress fees Predictable costs and low-latency performance for AI inference Alignment across functional, technical, and business teams 📌 What stood out: Equinix uniquely supports this model by providing proximity to clouds, data hubs, and private AI clusters — all while respecting global data residency and privacy needs. >> Check out the full blog here Is your organization centralizing or decentralizing AI initiatives right now? What challenges have you seen with shadow AI stacks? Where does your AI run best — cloud?AI Meets Nature: Accelerating Drug Discovery with Data Gravity
Did you know - Singapore-based Nanyang Biologics is using AI to unlock the therapeutic potential of natural compounds — and they’re doing it 68% faster and at a fraction of the cost. Powered by Equinix AI-ready data centers and global digital infrastructure, they’ve built a Drug-Target Interaction Graph Neural Network (DTIGN) to screen over a billion natural compounds and accelerate early-stage drug development. 90% reduction in R&D infrastructure costs 68% acceleration in discovery timelines 27% improvement in bioactivity prediction accuracy Low-latency data access via Equinix Fabric and NVIDIA/HPE-powered environments Crazy how the line is blurring between biotech and infrastructure - we’re seeing data gravity and interconnection emerge as critical enablers of innovation — even in traditionally lab-heavy fields. How is your industry leveraging AI to speed up discovery or innovation? What role does data proximity play in your AI workloads? Is the next big biotech breakthrough going to come from infrastructure? Let’s talk AI, science, and speed — and what it takes to move from hypothesis to health impact.
Why Liquid Cooling Is Essential for Efficient AI-Ready Data Centers
Have you adopted liquid cooling yet? Our latest Tech Talk discusses the urgent need for cutting-edge liquid cooling technology. Hi, I'm Alex Timofeyev, senior product Marketing Manager for colocation and xScale. In this video, I'm joined by Lindsay Schulz, Global Principal Technologist at Equinix, to discuss cutting-edge liquid cooling technology.
Why Unified Observability Is the Future of Infrastructure Management
Today’s organizations juggle a mix of physical equipment and digital services, spanning on-premises, cloud, SaaS, and remote locations. But as IT and OT environments grow more intertwined, so do the challenges of managing them. Siloed teams, fragmented data, and reactive monitoring are holding businesses back from true operational efficiency. What if you could gain a single, unified view of all your technology assets—no matter where they reside? Imagine proactively preventing outages, streamlining operations, and boosting cost efficiency with insights from across your IT and OT environments. In one of our latest blogs, we explore: • Why the convergence of IT and OT is reshaping infrastructure management • The business benefits of a unified observability approach across OT and IT • How leading organizations are breaking down silos for better decision making 👉 Read the full blog now!Fabric Cloud Connect for June 2025
Amazon Web Services (AWS) Customers can now order virtual connections with bandwidths up to 25 Gbps in the following metros: Istanbul, Turkey (IL) Lisbon, Portugal (LS) Equinix and AWS have enabled 25 Gbps (the highest hosted connection tier available) in 27 of the 41 Equinix Fabric metros with local AWS Direct Connect on-ramps. Get Started with Equinix Fabric If you'd like more information on connecting your business to the cloud, visit our service provider search tool or product documentation site for service availability, feature descriptions, and deployment considerations.Optimal by Design: Architecting for Hybrid from Day One in AI and Application Development
For every new AI or application project you embark on, your initial architectural choices will determine the probability of long-term success of that effort, especially as it scales or needs to adapt to changing regulatory or business environments. This article discusses why architecting for hybrid up front puts you in the optimal position for anything that comes your way. https://blog.equinix.com/blog/2025/05/21/why-you-need-a-hybrid-first-strategy/ Do you agree? Is 'hybrid-first' truly the silver bullet for future-proofing, or are there scenarios where a pure cloud or colo/on-prem approach still makes sense? Share your perspective!Equinix + Nvidia: Building the AI Factories of the Future
Look, AI isn’t coming. It’s already here — and it’s growing fast. Not linear growth. We’re talking exponential. The kind that breaks things. AI workloads are now so intense they’re overwhelming the networks, data centers, and power grids we built for a different era. The old infrastructure? It’s like trying to power a space launch with a car battery. Just doesn’t work. That’s why Equinix and NVIDIA are working together to rethink how we build and scale the physical backbone of AI. We’re not talking about incremental upgrades. This is about building AI factories — purpose-built, energy-efficient, high-performance, globally distributed systems that can actually keep up. Here's 3 principles to get us there: First: Everything starts with data. No data, no intelligence. And moving massive volumes of data — fast — requires serious interconnection. Equinix just happens to sit at the core of that. Clouds, enterprises, AI services — they all plug in here. That kind of neutral ground is critical when the entire AI ecosystem is converging. Second: Latency matters. A lot. AI inference is becoming incredibly time-sensitive. Location is crucial. With presence in 73 metros worldwide, Equinix lets you put compute where the data is and where the users are — edge, core, whatever. This isn’t a nice-to-have; it’s fundamental to real-time AI. Third: Trust. Enterprises don’t want black boxes. They want control over their AI environments — the data, the models, the infrastructure. That’s where private AI with NVIDIA DGX comes in. Combine that with Blackwell and you get 30x more energy efficiency and 35x better AI performance. Which is, frankly, insane. Now layer on Equinix’s work in liquid cooling — which is cool, literally — and the push to 100% renewable energy across their entire footprint? We’re not just scaling AI. We’re making it sustainable. Bottom line: AI is the next industrial revolution. But revolutions don’t run on yesterday’s infrastructure. They need something new. And fast. That’s what we’re building. Together. Want to see how it all comes together? Watch how Equinix and Nvidia together are building what's actually needed for the AI era. Check out this full video >>Unlocking AI Potential: The Power of a Robust Ecosystem 🌐
Yes, we know AI is growing fast, but let’s be real—navigating this fast-paced landscape can be tricky. To truly harness the power of AI, organizations need to build a diverse ecosystem of partnerships. According to Deloitte, a staggering 83% of top-performing companies are doing just that, leveraging collaborations with data providers, AI model creators, and infrastructure experts to drive their AI strategies forward. In this latest blog co-authored by Aaron Delp (Dir. AI Tech. Solutions) and Justin Beck (Dir. Global Principal) dive into the essential elements of a successful AI ecosystem. From ensuring data readiness to selecting the right AI models and infrastructure, they cover it all. Plus, they highlight how Equinix can be your go-to platform, connecting you with a rich network of AI partners to help you stay agile in this ever-evolving landscape. By leveraging our vendor-neutral environment, you can easily adapt to changing market demands, access cutting-edge technologies, and foster the collaborations necessary for driving innovation. Whether you're just starting your AI journey, looking to enhance your existing capabilities, or just curious to learn more about future-proofing your AI strategy. Check out the full blog here: AI Ecosystems 101: Choosing Data, AI Model & AI Infrastructure Providers
