Operations | Monitoring | ITSM | DevOps | Cloud

(Almost) everyone is using generative AI, and just as many aren’t seeing any benefits. Research firm Gartner calls it the “gen AI paradox” — nearly 80% of companies say they’ve invested in generative solutions, and the same number report no benefits to their bottom line. What’s more, 90% of projects are stuck in pilot mode; ready to take off, but just can’t get up to speed.

Information architecture used to be about structure. We organized menus and pages into trees, built hierarchies, and created pathways for people to follow. For years, that worked. Navigation was the interface. But that world is changing. People aren’t clicking their way through information anymore. They’re asking for it. They’re refining questions, expecting context, and assuming that systems will not only understand what they mean, but act on it.

Read a few articles on artificial intelligence and financial operations, and you’re bound to run across a sentence like this: AI enables FinOps teams to reduce TCO and boost ROI. Or one like this: The future of FinOps uses agentic AI-powered systems to detect and remediate cost issues automatically. Keep reading and you’ll find piece after piece that say a lot about AI and FinOps … without really saying anything.

I admit I was a little skeptical going into KubeCon 2025. The last time I went, in 2022, it felt tactical. I heard lots of conversations around small solutions to small problems. Practical knowledge-sharing is of course beneficial, but I’m most inspired by the big picture — ideally, a picture bigger than you can see anywhere outside of your mind. I’m heartened to say that KubeCon 2025 was exactly that.

Discover the basics of cloud efficiency as well as six advanced data-driven strategies you can use to make your cloud environment more efficient. With incredibly complex cloud architecture — that may even include Kubernetes and multi-tenant infrastructure — organizations are finding it hard to measure and monitor the performance and cost of their cloud environments.

Kubernetes has reshaped how teams build and scale infrastructure, but it’s also made cost visibility a lot harder. For platform engineers, SREs, and FinOps leads, breaking down shared cluster costs, understanding per-team usage, and driving efficient resource allocation is still a major challenge. That’s why one CloudZero webinar with Umesh Rao, Director, Tech Enablement and John Hashem, Senior Sales Engineer, stood out.

If you’ve ever tried to make sense of your AWS bill, you know how fast things get messy. Different accounts, hundreds of services, random tags, and suddenly, no one can say for sure who’s spending what or why the total looks so high. It’s not that teams don’t care about costs — it’s that AWS billing data isn’t always easy to interpret. Finance wants accountability. Engineering wants visibility. And somewhere between the two, ownership disappears.

If there’s one thing we’ve learned at CloudZero, it’s that success in FinOps isn’t just about having the right tools. It’s about knowing how to use them, and understanding the “why” behind every number, dimension, and dashboard.

The cloud has long promised limitless scalability and near-perfect uptime. But if you tried to access your Microsoft 365 dashboard or recline your smart bed last week, and got nothing but a spinning icon, you weren’t alone. In the span of 10 days, both Amazon Web Services (AWS) and Microsoft’s Azure Cloud suffered widespread outages that rippled across industries.

After three days of demos, sessions, and hallway conversations at KubeCon Atlanta, one thing became clear to CloudZero CTO Erik Peterson: the cloud-native world is shifting from cost control to value engineering. Teams aren’t just fighting bills anymore. They’re fighting complexity, GPU scarcity, Kubernetes sprawl, and pressure from the business to justify every dollar of technical investment. And this year’s KubeCon attendees? They were ready for those conversations.