Operations | Monitoring | ITSM | DevOps | Cloud

For a decade, one idea has guided everything we’ve built at Tigera: How do you secure a dynamic system with a lot of moving parts that is changing rapidly, with a programmatic approach? Calico has applied that idea for Global 2000 companies running the largest Kubernetes platforms in the world, securing tens of millions of mission-critical transactions every day. Today I’m excited to announce the next chapter of that work: Lynx, a unified control plane for Kubernetes-native AI agents.

For years, vendor lock-in has been discussed as a theoretical risk. A concern to acknowledge in architecture reviews. A box to tick in compliance frameworks. A future problem that might need addressing. Our latest research reveals something more urgent. For UK organizations, lock-in isn't theoretical anymore. It's structural. It's measurable. And it's preventing organizations from acting on their own strategic priorities.

Datadog Kubernetes monitoring tells an SRE team what failed, which pod failed, and when. It does so within seconds of the alert firing. The investigation then stalls at the same point every time: nothing in the dashboard layer can prove why a specific request behaved the way it did inside a running JVM at the moment of failure. Variable values, feature flag evaluations, and code branches are never captured.

In recent years, the conversation about digital sovereignty has focused on data. Where it is stored, who can access it, and which laws apply when something goes wrong. Those questions still matter, but AI is forcing us to think about sovereignty in a different way.

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.

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.

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.

We rebuilt large parts of the Qovery Console: new navigation, overviews at every level, dark mode, and a modernized frontend architecture with TanStack Router and React Suspense. Rémi is a staff frontend engineer at Qovery. He writes about frontend architecture, developer experience, and building scalable UI systems for platform engineering tools. Théo is a senior product designer at Qovery.