Operations | Monitoring | ITSM | DevOps | Cloud

When CloudZero’s CTO Erik Peterson joined the FinOps Weekly podcast in October 2025, he didn’t hold back. Instead of going on about the usual best practices of AI cost optimization, he posed challenges to how we approach AI spending. From “zombie AI experiments” eating your budget to why you should stop apologizing for using AI, these 10 insights from the podcast are worth considering in how we approach AI FinOps. (Watch the full podcast below and keep reading for more!)

A key advantage of Kubernetes for container management is its high scalability. Kubernetes nodes are directly involved in this, and they can significantly impact your efficiency, cost-effectiveness, and service availability. This guide provides an in-depth look at Kubernetes nodes, including types of nodes and operational best practices.

I recently wrote about the impending SaaS crisis, driven by companies’ newfound ability to use AI to build software they used to have to buy. I predicted this phenomenon would make it even harder for SaaS vendors to drive growth, and that elite SaaS margins would fall from the mid-70s to the mid-60s as companies leaned more into their data and AI.

The benefits of observability are clear: deep visibility into system health, faster troubleshooting, and improved reliability (to name a few). But what’s equally clear is that, as organizations scale and evolve their observability strategies, they need a way to tap into these benefits without runaway costs. According to Grafana Labs’ 2025 Observability Survey, 74% of respondents say cost is a top priority for selecting tools.

Downtime is brutally expensive and damaging. Enterprises can lose about $9,000 every minute systems are down, while smaller businesses lose hundreds of dollars per minute. A single outage can often cost over $100,000, and nearly a third of companies lose customers due to downtime. That’s why many organizations turn to platforms like SolarWinds to maintain reliable systems and minimize the risk of costly disruptions.

In July 2024, CrowdStrike — one of the world’s top cybersecurity companies — shipped a minor configuration update to its Windows security product. Within minutes, airlines, banks, hospitals, and retailers worldwide began crashing. The update wasn’t new code. It was a routine content file that slipped through with a bug in its safety checks. When Windows machines loaded it, the agent hit an out-of-bounds memory error and crashed. Devices blue-screened and got stuck in reboot loops.

Cloud computing offers several undeniable benefits to businesses. Some of the biggest ones are agility, cost savings, data recovery, and developing new apps and services to meet changing customer needs. Despite these benefits, the cloud can be complex, demand specialized skills, and require companies to follow up-to-date cloud security best practices. Why?

Engineering teams need to deliver reliable, secure, and high-performing applications, all while keeping costs under control. But engineers often lack visibility into cloud cost data, relying on finance-driven reports that they receive only after the billing cycle closes. Without daily cost insights alongside observability data, they don’t know until it’s too late that an infrastructure change caused a significant cost increase.