Operations | Monitoring | ITSM | DevOps | Cloud

The cloud bill explained: A guide for finance and engineering

The cloud bill arrives at the end of every month, and somewhere in it sits a line item that nobody outside the infrastructure team really understands. It might be called "data transfer," "egress," or "outbound bandwidth," and it might be 5% of the total or even 25%. Whatever it is, it tends to be the line that finance asks engineering about, and engineering struggles to explain in a way that finance can act on. The problem is that egress is a fee that hides in plain sight. It's not on the marketing page.

Why developer teams are rethinking their cloud provider this year

The default cloud choice for technically literate teams has shifted. It hasn't shifted dramatically; the major hyperscalers aren't going anywhere, and their enterprise position is still strong, but the conversation that used to start with "which hyperscaler" now genuinely starts with "what do we actually need." That's new.

How to monitor and optimize GPU utilization in the cloud

GPU utilization is one of the most expensive metrics in cloud infrastructure to get wrong. A GPU running at 30% utilization costs the same as one running at 90%, but it's doing a third of the useful work. For workloads measured in tens of thousands of GPU-hours, the difference between average utilization in the 30s and average utilization in the 70s is hundreds of thousands of dollars across the life of the workload.

How to run self-hosted AI on your own infrastructure with Konstruct

Civo Platform Engineer M R Rishi demonstrates how to go from zero to self-hosted AI in minutes using Konstruct. While most teams are stuck managing thousands of configuration values across multiple models and tools, Rishi shows how Konstruct eliminates that complexity with GPU cluster provisioning, GitOps catalog deployments, and production-ready infrastructure on day zero.

Who really controls your data?

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.

Sovereign GPU cloud: Data residency across training, inference, and model weights

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.

GPU cloud for AI inference in production: How infrastructure requirements change after training

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.

5 questions you should be asking about cloud dependency

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.