Operations | Monitoring | ITSM | DevOps | Cloud

<span data-mce-type="bookmark" style="display: inline-block; width: 0px; overflow: hidden; line-height: 0;" class="mce_SELRES_start"></span> Andrew Hillier sits down with Dan Ciruli, who leads the cloud native product management team at Nutanix.

Cloud costs are no longer just an engineering problem or a finance problem. It’s now an everyone problem. That was the central message from the FinOps Training At Scale webinar that took place on Sept. 25, 2025, where CloudZero’s Larry Advey (a.k.a. “Fred FinOps”) and Director of Tech Enablement Umesh Rao walked through the realities of building FinOps practices that work in the real world.

The world of cloud costs is always evolving, and AI spend is quickly becoming one of the most unpredictable and confusing cost drivers. As more organizations integrate generative AI into their products, FinOps teams are struggling to account for — and control — these new, often mind-boggling cost streams. In fact, 44% of engineering professionals say improving AI explainability is a top priority in AI budgeting, according to CloudZero’s State Of AI Costs In 2025 report.

In this guide, you will build and deploy a serverless data processing workflow using AWS Step Functions and AWS Lambda. This approach enables you to orchestrate discrete processing tasks in a scalable and cost-efficient way, leveraging the event-driven architecture that AWS offers. You will begin by creating individual Lambda functions that handle specific tasks in your data pipeline.

Cloud costs don’t wait for your finance team to catch up. They spike on product launches, dip when usage slows, and sometimes blow past forecasts overnight. Every container spun up, every gigabyte stored, and every terabyte transferred adds to the tab. The main culprit is often variable costs. In this guide, we’ll break down how variable costs affect budgeting and the strategies you can use to turn cost variability into a competitive advantage.

AI adoption is reshaping how organizations innovate. It’s also driving cloud costs higher. CloudZero’s State Of AI Costs In 2025 report finds that for mature FinOps and engineering leaders, visibility into AI costs is a critical first step, but it’s not enough. To enable fast, responsible AI and machine learning innovation at scale, teams need pragmatic, flexible guardrails. They don’t need rigid budgets or knee-jerk shutdowns that slow progress or push teams into shadow ML.

In today’s small and medium-sized UK businesses, most of the cybersecurity budget goes into protecting data and strengthening authentication. Those are important measures – the cost of a data breach is still enough to close your firm, after all. But they aren’t enough. Because in 2025, thanks to increased capabilities of DDoS attacks, you don’t have to lose your data to lose your business– you just have to lose access to it.