Operations | Monitoring | ITSM | DevOps | Cloud

As organizations move beyond traditional hypervisors, Harvester continues to lead the way as an open source, Kubernetes-native virtualization solution. With the release of Harvester 1.5, users now have greater flexibility and ecosystem alignment than ever before—with General Availability (GA) for ARM64 and support for CSI-compatible storage backends. Harvester is part of a growing shift toward cloud-native infrastructure that unifies VMs and containers under the Kubernetes API.

For organizations providing vital mental health assistance, safety crisis services and delivering critical humanitarian support when disaster strikes, reliable digital infrastructure is essential. Whether connecting individuals to crisis counselors via text or coordinating face-to-face healthcare support, these digital services must operate seamlessly.

IT operations aren’t broken; they’re overloaded. Every alert, every outage, every ticket is a symptom of scale. Cloud sprawl, hybrid infrastructure, and tool overload have turned ops into a constant scramble. AIOps has been in the conversation for years, mostly as potential.

You’re looking at an error in Sentry—a failed payment in your Flask backend or an unexpected null in your Node API. You’ve got the stack trace. The request details. Even the full trace. What you don’t have: the logs your app emitted right before everything went sideways. With Sentry Logs (now in open beta), you can send application logs straight to Sentry and see them automatically connected to the errors and traces you already use.

ServiceNow’s Knowledge 25 unveiled transformative innovations designed to embed AI deeply within every enterprise workflow. These advancements—like AI Agents, the AI Agent Fabric, and the AI Control Tower—mark a leap forward in digital operations. But what if you could amplify these capabilities even further, achieving truly proactive, automated, and seamless responses across your entire organization?

Is SCOM dead? Not even close - It has just evolved System Center Operations Manager (SCOM) is far from dead. While a growing number of monitoring alternatives have emerged in recent years, SCOM in 2025 remains a critical tool, especially for organizations running hybrid environments. Thanks to its stateful, object-oriented monitoring model and a rapidly evolving ecosystem of modern Management Packs (MPs).

Machine learning models must do more than make accurate predictions; they also need to adapt as the world around them changes. In real-world systems, data distributions shift due to seasonality, equipment wear, user behavior changes, or other external forces. If your models can’t keep up, the result is poor predictions. This can lead to outages, inefficiencies, or missed opportunities. That’s why forecasting systems need to be monitored and resilient, not just accurate.

Show a customized, crash-specific message when your game crashes. Locked in an intense battle, hanging on for dear life, on the verge of nigh-impossible victory and then… boom! Positively, absolutely, unquestionably, no one wants a crash to interrupt their favorite game. Crashes are a frustrating yet inevitable part of gaming, and the only thing worse than being on the receiving end of a crash is being on the receiving end of the same crash repeatedly.

We’re excited to share that Rollbar is now part of the ilert integration catalog! This new technical partnership allows software teams to detect application errors in real time with Rollbar and instantly respond using ilert’s powerful alerting and incident management features. What is Rollbar? Rollbar is a comprehensive, real-time error monitoring and debugging platform designed to help development teams detect, diagnose, and resolve issues faster—before they impact users.

We work in a digital landscape where IT teams are expected to move faster, scale smarter, and deliver flawless digital experiences, automation is no longer optional; it’s foundational. But while most organizations have started down the automation path, far fewer can answer the critical question: How do we measure success? The problem isn’t just a lack of metrics. It’s that the wrong metrics are still steering the ship.