By: Michael Bradley, Commercial Regional Sales Manager
Why Scale-Out (and Scale-Up) Matter More Than Ever
Companies today are being asked to do more with data than ever before. Bigger AI models, faster insights, and workloads that don’t stay in one place, it’s a lot to keep up with. Traditional infrastructure just isn’t built for this kind of speed and flexibility.
The answer isn’t about throwing more hardware at the problem. It’s about building smarter, more agile infrastructure that adapts as demands change. And that’s where scale-out and increasingly, a blend of scale-out and scale-up come into play.
Scale-Out vs. Scale-Up — And Where OSS Fits
When people talk about scale-out, they usually mean adding more nodes or servers and running them in parallel. It’s the model the cloud made mainstream modular, cost-effective, and great for distributed workloads.
Scale-up, on the other hand, is about making a single system stronger by adding GPUs, storage, or memory. That’s often the right answer at the edge, where you don’t have the luxury of endless racks but still need serious compute power.
Here’s the thing: most customers don’t live fully in one world or the other. They need both. And that’s exactly where Agile Infrastructure comes in. Agile infrastructure lets you pool resources: GPUs, storage, accelerators and assign them where they’re needed most. That means you can scale up inside a single box, or scale out across multiple systems, sometimes even both at once.
Think about it this way:
This hybrid flexibility is where OSS shines.
Why This Approach Matters Now
AI Isn’t Slowing Down
AI workloads are getting bigger and more complex by the day. Training giant models or running real-time inference at the edge takes GPU-dense systems with serious bandwidth and low latency. No single system can shoulder it all anymore. Scale-out paired with agile infrastructure and dynamic orchestration gives you a way to grow capacity without ripping and replacing your infrastructure.
Data Growth Is Relentless
Sensors, platforms, and applications are generating mountains of data. Centralized systems can’t keep up. Agile Infrastructure lets you expand as you go, scaling up individual systems when needed or scaling out clusters when workloads demand it.
Flexibility Beats Overbuilding
The old way of buying oversized systems upfront in the name of “future-proofing” leaves you with idle resources and wasted budget. Agile, modular infrastructure changes that. You add exactly what you need when you need it, whether that’s GPUs for training or NVMe storage for streaming workloads.
Smarter Economics
Scaling in line with demand lowers capex and improves ROI. Even better, Agile infrastructure makes sure GPUs, and other accelerators don’t sit idle, they’re always allocated where they’ll do the most good.
Not Just for Hyperscalers
Cloud giants might have pioneered scale-out, but the need is everywhere now. Defense, healthcare, autonomous systems, industrial automation all of them need dense compute they can control, customize, and sometimes deploy in rugged, mobile environments.
That’s why OSS builds systems that deliver datacenter-grade performance wherever you need it from racks in enterprise datacenters to mobile command centers at the tactical edge.
Speaking the Language of Modern Infrastructure
The way the industry talks about infrastructure is changing too. It’s not just “scale-up” and “scale-out” anymore.
Final Take
If you’re relying on just vertical scaling, you’re already behind. If you’re only focused on horizontal scaling, you’re still leaving flexibility on the table.
The future is hybrid scaling, the ability to scale up and scale out as needed, powered by agile infrastructure and guided by dynamic orchestration.
And that’s exactly where OSS sits. Whether it’s training next-gen AI in a datacenter or running rugged systems at the edge, we help our customers scale smarter, faster, and without limits.
The rugged edge computing landscape is becoming increasingly complex with new generations of technologies, such as the latest AI focused GPUs, releasing annually rather than every 2-3 years. Whether the end application is commercial or defense, rugged edge servers must not only deliver cutting-edge compute performance but also withstand extreme environmental conditions.
When the PCI-SIG formally added support for 675W add-in card devices in the PCI Express Card Electromechanical (CEM) specification in August 2023, NVIDIA’s most powerful CEM GPU, the NVIDIA H100 80GB had a maximum power consumption of 350W. While some devices were starting to push the limits of datacenter thermodynamics – high density systems of many 675W devices seemed like a distant reality. However, with power constraints uncapped and the need for higher performing GPUs skyrocketing, the industry quickly came out with devices taking full advantage of the new specification capability. NVIDIA quickly replaced the H100 80GB with the H100 NVL, increasing power density to 400W. While this small jump was manageable for existing installations, NVIDIA then dove all-in with the H200 NVL released in late 2024 at 600W. The rapid transition from 350W to 600W has put power and cooling technologies in the spotlight in a race to solve this next generation challenge.