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By Civo Team
Sovereign cloud conversations usually center on where customer data sits at rest. The provider points at a UK data center, the contract gets signed, and procurement marks the box. For most workloads, that's a defensible position. For GPU workloads, it isn't.
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By Civo Team
Training a model is a project with an end date. Inference is what happens for the rest of the model's working life. The two workloads share GPUs, frameworks, and a lot of vocabulary, but the infrastructure decisions that make sense during training are usually the wrong ones in production. Teams that treat inference as "training, but smaller" tend to discover the gap somewhere around their first traffic spike.
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By Civo Team
Cloud infrastructure has become the backbone of modern business operations. But as organizations deepen their reliance on cloud providers, a critical question often goes unasked: just how dependent are we, and at what cost? For years, the cloud adoption narrative focused on agility, scalability, and cost efficiency. Those benefits remain real. But the landscape is shifting.
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By Jubril Oyetunji
AI inference and training are terms you'd run into if you have been around software engineering or even just scrolled through the news. Both are integral to delivering the AI-powered experiences we have come to expect from many of the applications we use daily. According to McKinsey, by 2030 inference will overtake training as the dominant workload in AI data centers, making up more than half of all AI compute and roughly 30-40% of total data center demand.
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By Jubril Oyetunji
If you’re prepping for your first AI or MLOps interview, the hardest part usually isn’t always the hands-on element. For me, it’s the vocabulary. Interviewers sometimes lob single-word concepts at you (“what’s quantization?”) and watch how far you can carry the thread. The questions sound clear-cut, but each one is really a doorway into a bigger topic, and the interviewer is judging how cleanly you walk through it.
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By Dinesh Majrekar
"Blackwell sales are off the charts, and cloud GPUs are sold out. Compute demand keeps accelerating and compounding across training and inference, each growing exponentially. We've entered the virtuous cycle of AI." Jensen Huang, CEO, NVIDIA When NVIDIA's CEO makes that statement in a quarterly earnings release, it is not marketing language.
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By Civo Team
A GPU spec sheet is a confidence trick. It looks like an objective document - numbers, units, comparable rows - but most of the numbers on it don't map cleanly to the performance a real workload will see. Teams that pick GPUs by reading the headline figures usually find out the gap between spec and reality somewhere around the first production run. This is a working guide to reading GPU cloud instance specifications against actual ML workloads. The goal isn't to recommend a card.
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By John Dietz
May has been one of our busiest months yet for Konstruct. Across three releases, 0.5, 0.5.1, and 0.5.2, we've shipped some of the most requested platform-level changes since we launched: a unified model for sharing resources across organizations, native support for AI-driven workflows via MCP, a completely redesigned API keys experience, and a cleanup to how permissions actually work in multi-org environments. Let's walk through what shipped and why it matters.
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By Dinesh Majrekar
NVIDIA's infrastructure roadmap moves fast, and the next major milestone is already here. The NVIDIA Vera Rubin platform is the company's next-generation AI compute architecture, the successor to Blackwell, and it's shaping up to be one of the most significant leaps forward in AI infrastructure NVIDIA has ever shipped. Whether you're planning your next training cluster, scaling inference pipelines, or building the infrastructure to power autonomous agents, Vera Rubin is worth understanding now.
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By Civo Team
Every so often, NVIDIA releases something that quietly changes the direction of the industry. CUDA did it. DGX did it. NVLink did it. Vera Rubin feels like one of those moments again. At first glance, Rubin looks like the natural successor to Blackwell. Faster GPUs, larger memory pools, and eye watering performance numbers. But the more you dig into the architecture, the clearer it becomes that NVIDIA is not simply shipping another accelerator generation.
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By Civo
Digital sovereignty has moved from buzzword to boardroom priority. But most organisations are still asking the wrong question. Civo CEO Mark Boost cuts through the noise. Digital sovereignty isn't about marketing; it's about jurisdiction, accountability, and operational certainty. And it starts with where your data is hosted and how it's processed. Civo's UK Sovereign Cloud delivers public cloud, private cloud, and AI services, hosted and operated exclusively within the United Kingdom, under UK legal authority, with no exposure to foreign control.
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By Civo
The cloud shouldn't be two separate worlds. Civo delivers total cloud parity, the same features, APIs, and experience across public and private cloud. Powered by CivoStack, you can seamlessly move workloads anywhere, and with Konstruct, deploy alongside AWS, Azure, and Google. True multicloud freedom. No compromises. More control.
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By Civo
The hard part of deploying AI agents isn't the agent. It's the environment around it. As organisations move from AI experimentation into production, the question isn't just what agents can do; it's whether you can trust the environment they run in. Sandboxed execution gives you both the autonomy and the guardrails, keeping agents isolated, auditable, and under your control.
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By Civo
Digital sovereignty isn't a marketing buzzword. It's about jurisdiction, accountability, and operational certainty and it starts with where your data is hosted and how it's processed. Civo's UK sovereign cloud delivers public cloud, private cloud, and AI services, all hosted and operated exclusively within the United Kingdom under UK legal authority with no exposure to foreign control.
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By Civo
Most cloud providers think AI is just a hardware problem. They focus on the GPUs, the racks, and the raw compute, but they leave the strategy up to you. At Civo, we do AI differently. We don't just provide the hardware; we guide you through the full life cycle of AI adoption, from initial planning to scaling production workloads. By leveraging best-in-class NVIDIA models and GPUs, we give you the performance to unlock AI at scale without the fear of being bogged down by complexity. It's more than infrastructure, it’s cloud freedom with AI built-in.
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By Civo
Spin up a GPU workload cluster using Konstruct's new GPU cluster templates, deploy a self-hosted LLM, and use it in your organization — all live on stream. This hands-on session shows how shipping AI workloads to GPU clusters is just as easy as deploying to Konstruct physical or virtual clusters, and how open source apps in the GitOps Catalog make it even faster. Walk away knowing how to cut your token spend by running models privately on your own infrastructure.
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By Civo
Leave the lock-in of VMware behind. Migrate legacy workloads to Kubernetes-native infrastructure with air-gapped security, GPU passthrough, and consistent Terraform APIs.
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By Civo
When you can’t move your data to the cloud, we bring Civo to you. Using CivoStack Enterprise and FlexCore, you can deploy AI in secure, on-premise, or hybrid environments that you fully control. Your data, your rules, no compromises.
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By Civo
With hyperscalers, growth comes with a hidden cost. The more your data moves, the more you pay, by design. Egress fees are that cost. A model built to discourage migration, limit flexibility, and keep you trapped in their ecosystem. At Civo, we've eliminated that barrier completely. No egress fees, no hidden charges. Every cost is transparent and predictable, so you always know exactly what you're paying for. You stay because you choose to. That's cloud freedom.
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By Civo
What if you could own your platform and deploy it anywhere, without months of GitOps setup or vendor lock-in? Konstruct is an Internal Developer Platform that gives you a production-grade platform-as-a-service, deployed in minutes. It delivers a GitOps-powered experience that is fully owned and operated by you, distributing consistent, self-service control planes to development teams so they can ship without friction.
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