Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

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.

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.

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).

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.

Engineering teams are writing more code than ever. AI coding tools have made individual developers dramatically more productive, yet most organizations report moving only about 20% faster than before. The real constraint has always been the operational fabric surrounding the act of writing code. The processes, standards, visibility, and coordination that determine whether hundreds of engineers and thousands of services ship reliable software at speed have always been where the real work happens.

There’s a common saying: “A backup isn’t a backup until you’ve tested it.” The same is true whether it’s a simple database failover or an entire data center/cloud provider failover. You simply won’t know if it works if you don’t test it. When it comes to disaster recovery testing, that can be an expensive, painful, and arduous process. But it’s required by companies for a reason. And not just for disasters like hurricanes, flooding, or earthquakes.

Kubernetes troubleshooting traditionally requires deep platform expertise. Understanding pod lifecycle, decoding error messages, correlating events across resources, and identifying root cause all demand experience that takes years to build. This expertise gap creates a bottleneck where only senior engineers can handle production issues, limiting how quickly teams can resolve incidents.