AI is transforming the way data centers consume power—fast. With higher-density racks, unpredictable load swings, and more harmonics than ever, electrical infrastructure is under increasing strain. But here’s the part that keeps data center operators up at night: most monitoring tools weren’t built to detect the faults that AI workloads trigger.
The Problem:
Traditional fault detection systems rely on slow, coarse data. They generate generic alerts without context. And they don’t go deep enough to catch the subtle early signs of the problems that cost millions in downtime.
The Opportunity:
That’s why we built a free self-assessment: “Can Your FDD Handle AI Workloads? 10 Questions for Data Center Ops Leaders”
It’s a quick, diagnostic-style checklist to help you determine whether your current FDD tools are really keeping up—or silently missing faults as your power profile evolves.
What You’ll Learn:
This checklist helps you answer questions like:
- Can your system catch faults that last just a few seconds?
- Are you monitoring down to the circuit level?
- Can you spot voltage imbalances, harmonics, or nuisance trips before they cause issues?
If you’re answering "No" to more than 3, your team may be exposed to risks you can’t see.✅ Take the checklist, tally your score, and get a clear picture of how AI-ready your fault detection really is.
