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We are thrilled to announce a significant update across our DAC (Data Access Components) product line. This release focuses on expanding compatibility with the latest development environments, extending support for modern databases, strengthening security, and adding powerful new functionality for AI-driven applications.

Even a simple upgrade can cause unexpected issues. Here’s what happened when a PVS upgrade broke XenServer licensing, and how we fixed it.

Network Resilience in Healthcare: More Than Uptime, It’s About Lives When a retailer’s point-of-sale system crashes, the fallout is lost revenue. When a hospital’s network fails, the consequences can be catastrophic: ICU monitors freeze, diagnostic imaging is delayed, telehealth appointments drop mid-session, and clinicians can’t access electronic health records (EHRs).

One kind of data in most relational databases is what we call static data. This is also referred to as lookup data, code data, domain data or even list data. Whatever you like to call it, it’s usually smaller data sets consisting of data that never changes, or changes very slowly. One example might be Canadian postal codes. Another example, and one I’m going to use, is the amateur radio band definitions within a given country.

Level 1 engineers face incoming tickets without real-time visibility into endpoints. The result? Endless tool-switching, guesswork diagnostics, missed SLAs, and unnecessary escalations. Critical issues remain hidden until they impact productivity.⁠ Then came Nexthink.⁠ Now engineers see issues in real time, fix faster, and even prevent problems users don’t notice.

AI has made it faster and easier to change a codebase than ever before. But in a system as complex and interdependent as modern software delivery, writing code has never been the biggest challenge. For most teams, the real constraint is getting that code safely into production. So while AI assistants and autonomous coding agents have dramatically accelerated the pace of change, for many organizations those changes are piling up against bottlenecks that were already slowing them down.

If you have worked in IT for more than five minutes, you know Murphy’s Law: anything that can go wrong will go wrong sooner or later (sometimes at the worst possible time). Systems do not wait for you to finish your coffee, much less for you to get back to your desk. So, yes, we know your pain. That is why more IT pros are leaning on mobile tools–like Pulseway RMM Mobile App–to stay ahead of problems instead of scrambling back to the office or dragging around a laptop everywhere.

We love to talk about IT revolutions. We celebrate the leaps in innovation that change how we work and live. We look at the 1980s and see the personal computer, which turned computing from a command-line chore into an intuitive experience for everyone. We point to the 1990s as the decade the internet connected the world, the 2000s as the era when virtualization and the cloud broke the chains of physical hardware, and this decade as the dawn of mainstream AI. Each of these moments was transformative.

It's 3 AM. Your phone starts buzzing with alerts, and you stumble to your laptop only to be greeted by a dashboard that looks like the control panel of a nuclear reactor in meltdown: Red lights everywhere. Numbers that should be green are decidedly not green. And your brain, still foggy from sleep, is asking the most fundamental question in all of IT operations: "Okay, yes, there's clearly a problem... but, now what?".

In a recent survey, Udacity’s team explored the evolving landscape of AI adoption by asking 2000 professionals (including those in the legal sector) if they used AI. Unsurprisingly, over 90% of respondents said they did. More concerning, 72% of managers reported personally paying out of pocket for AI tools to use at work, introducing uncontrolled risk into corporate environments.