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If you work in infrastructure or cloud operations, you may have noticed a new term floating around: neoclouds. No, it’s not just another buzzword invented to make slide decks more exciting, and it has nothing to do with “The Matrix”.
Neoclouds are actually a meaningful—and fast-growing—shift in how organizations consume cloud services.
Let’s take a deeper dive into this emerging tech.
A neocloud is essentially a next-generation, highly specialized cloud provider that sits somewhere between traditional hyperscalers like AWS, Azure, and GCP, and traditional hosting or colocation.
Neoclouds focus on delivering Graphics Processing Unit-as-a-Service (GPUaaS) performance, without the bottlenecks and encumbrances of a traditional cloud environment. To that end, they typically offer:
Neoclouds are usually built on open-source technology—Kubernetes, OpenStack, Ceph, KVM, and so on—and provide a cleaner, simpler operational model for teams who don’t want or need the full hyperscaler kitchen sink.
Leading neocloud providers currently include CoreWeave, Nebius, Vultr, Lambda, and Gcore, although there are many others. Their customers are a “who’s who” of industry hitters, including: Microsoft, OpenAI, Nvidia, Google, Samsung, and Oracle. And this is just a small sampling.
Why are they adopting neoclouds en masse? There are numerous reasons; some of the most important include:
The “Big Dog” public cloud providers (you know their names) are powerful, but complicated. Navigating thousands of services, deciphering pricing models, and staying on top of constant changes is resource-intensive.
Neoclouds dispense with these issues, offering fewer services, simpler architectures, and “what you see is what you pay” pricing. That’s music to many organizations’ ears, after struggling with public cloud complexity.
Predictability of expenditures is another major driver. Enterprises can tire of yo-yo pricing, including variable egress fees, erratic scaling behaviors, and invoices that spike unexpectedly.
Neoclouds often charge flat-rate or transparent per-resource pricing, with little or no egress fees, predictable monthly billing, and the elimination of “gotchas” for support or APIs. Finance departments love this.
For HPC workloads like databases, real-time apps, or high-throughput services, the neocloud GPUaaS model outperforms hyperscalers by offering:
Hyperscalers, of necessity, optimize for multi-tenancy; neoclouds instead optimize for raw performance.
These and other advantages are why Gartner is fully on board the neocloud train. “Neoclouds are reshaping AI infrastructure,” the analyst firm states. “By natively offering GPUaaS, they solve the cost, agility, and supply challenges that hyperscalers face. Tech service leaders who fail to integrate neoclouds in their portfolio risk higher costs, slower innovation, and diminished competitive edge in the AI services race.”
Given its AI-focused nature, it should be no surprise that one of neocloud’s predominant uses is for AI and ML workloads, including training large models.
In addition, scientific research relies on HPC for processing massive datasets, especially in fields like genomics and other medical research, and climate modeling. This makes it a natural fit for neocloud.
Edge computing is another area in which neoclouds shine. Because they often run on bare metal or super-fast NVMe storage, they can deliver better throughput and lower latency than hyperscalers at a fraction of the cost.
This low-latency ability is essential for edge uses like autonomous cars; predictive maintenance in Internet-of-Things (IoT) and other manufacturing environments; remote patient monitoring; and automation of power grid operations.
