Operations | Monitoring | ITSM | DevOps | Cloud

A global outage at Amazon Web Services (AWS) did more than knock popular apps offline. It laid bare the cost risks embedded in many cloud architectures. As services fail, the hidden costs of high availability, from redundancy planning to recovery operations, often multiply. For cloud cost leaders, this isn’t an issue of uptime; it’s a visibility and budget-shock issue. It’s a key reminder that architecting for resilience involves difficult trade-offs.

In 2018, attackers gained access to Tesla’s AWS cloud environment through an unprotected Kubernetes console (admin console). Because it lacked proper authentication, the hackers could see and control cluster resources. Once inside, they deployed new pods running cryptocurrency mining software, using Tesla’s compute power for profit. During the breach, the attackers also uncovered credentials stored in the cluster.

So you’ve run into cloud cost challenges — incomplete visibility, overspending, thinning margins — and you’re wondering whether you have what it takes to build a cloud cost optimization platform in-house. It’s a responsible question (one that the FinOps Foundation even advises you to ask). Be warned: Building your own cloud cost optimization platform seems cheaper than adding another SaaS subscription. It’s not.

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.