Operations | Monitoring | ITSM | DevOps | Cloud

Last year, we launched a powerful new way for partners to transform how they resell and manage connectivity globally. With Console Connect Private Label, partners can deliver on-demand NaaS capabilities to their customers under their own brand, without the cost, risk or complexity of building and maintaining a SaaS platform.

Sovereignty is a concept that can have shown nuances in the way it is currently used by states and industry to describe some services. The term “strategic autonomy” has also been used, as to describe the need for governments to ensure that they have a hand on the full value chain (or at least know the gaps and accept the risks) and can apply their rules while it seats in its jurisdiction (autonomy derives from the greek autos (self) nomos (rule).

Over the past few months, we’ve shipped a significant amount of functionality in Konstruct. To make sense of it all, I’m kicking off a new monthly series where we’ll share what’s new, why we built it, and where it’s going next.

This month, two FinOps research reports landed in close proximity. One from the FinOps Foundation — their 6th annual State of FinOps, drawing on a broad global practitioner community. One from CloudZero: FinOps in the AI Era: A Critical Recalibration, built on responses from 475 senior leaders at cloud-mature, AI-active organizations, with a focused lens on how AI is reshaping cloud cost management. Read each alone, and you get a useful snapshot for your business.

Stop fighting cluster sprawl. Learn why traditional scripting and GitOps fail at scale, and discover how to achieve fleet-wide consistency without the complexity of Kubernetes Federation.

Stop fighting CrashLoopBackOff on your AI deployments. Learn why traditional Kubernetes primitives fail large models and GPU workloads, and how to orchestrate AI infrastructure without shadow IT.

Years in the FinOps trenches taught me one thing: The data has never been the problem. The data exists. It’s out there, scattered across provider invoices, buried in tagging gaps, locked behind dashboards that maybe three people in your org actually know how to navigate. The real problem? Nobody can get to it when they need it. Engineers ship features without understanding what they cost the business, let alone whether they improved margin.

Somewhere between a model’s first demo and its first production workload, the cost conversation changes completely. Training is a big number, but it’s a finite one. Inference isn’t. Every user interaction, every query, every API call triggers compute behind the scenes — and unlike training, inference never stops billing. That shift from one-time expense to ongoing operational cost is where inference economics begins.

Seven developer-requested features. Tighter control over branches, history, and large repos. No CLI detours required. If you have been using GitKraken Desktop in a complex repo, you already know what it feels like when the commit graph turns into a wall of branches. When rebasing requires more ceremony than it should. When you just need one file back from three commits ago but have to orchestrate a whole checkout to get it. GitKraken Desktop 11.10 is built for those moments.