Operations | Monitoring | ITSM | DevOps | Cloud

Data center vacancy rates in North America have hit record lows, with reports from CBRE and JLL indicating figures between 1.6% and 2.3% as of mid-2025. This is driven by exceptionally high demand from hyperscale and AI users, which is outstripping supply and leading to significant competition for space and power. The tight market is expected to continue through at least 2027, with preleasing of new construction at high levels.

Kubernetes is now the backbone of modern software infrastructure, helping teams deploy, scale, and manage applications efficiently across clouds. But when it comes to understanding costs, Kubernetes remains opaque. Teams often can’t answer basic questions like: How do you solve the gap between engineering usage and financial visibility? CloudZero’s new Kubernetes capabilities are built to address this challenge.

The AI said I had to do a database first, not code. Who am I to argue? So, with all the prompts outlining the goals of the project, I’ve gone forward with the project, and step one is creating a PostgreSQL database on Azure. This is part three of a multi-part set of articles. I’ll move this list to the bottom of future articles: Part 1: Introducing the Concept of dbRosetta Part 2: Defining the Project & Prompt Templates.

It’s now easier than ever to start testing Kubernetes with Dynatrace and Gremlin. With a new strategic integration, Kubernetes services set up in Dynatrace are automatically discovered in Gremlin to make testing set up simple and fast. At a time when AI is driving massive expansions in infrastructure and dramatically increasing deployment speed, being able to set up and test new services quickly is more important than ever. ‍

The tech world loves buzzwords. We’ve lived through the Cloud Era, the Mobile Era, the AI Era (we’re still in that one, apparently). But 2025 marks something different. Something developers have been craving for years but couldn’t quite name. Welcome to The Builders Era. Not because of some shiny new framework or yet another platform promising to 10x your productivity. The Builders Era is happening because developers are done being spectators in their own craft.

When you run services on Quarkus, you need a steady stream of signals to understand how the application behaves—CPU trends, request timings, memory patterns, and how each endpoint responds under load. Metrics give you that visibility. They help answer questions like: OpenTelemetry fits well here because it gives Quarkus a common way to generate and export metrics without locking you into a specific monitoring tool.

OpsGenie is shutting down. And Atlassian recommends migrating to Jira Service Management (JSM). But if you’re not sure JSM is the right fit for your team’s on-call management needs, this review will help you decide. I signed up for JSM and put it through real-world testing. I created on-call schedules, rotations, and overrides. Then, I reviewed JSM’s on-call management across 4 key criteria. For each criterion, I shared what I liked and what I didn’t.