System-level framework and uptime diagnostic tool.
Hottinger Brüel & Kjær (HBK) has launched Data Center Availability Intelligence - a system to protect users uptime - to help owners, developers and operators secure uptime in the high-density AI era,
As traditional component-level analysis is no longer enough to support complex modern facilities, HBK’s new offer moves the focus to system-level outcomes, helping teams engineer availability during early design phases and actively protect it, post-launch, across the three critical stages of planning, validation and operation.
During planning, users can model power, cooling and network architectures before major capital choices are locked in. Next they can virtually test redundancy, dependencies and maintenance strategies before the go-live date. And in the final stage, they can leverage real-world equipment and monitor data to identify emerging risks, before these cause downtime.
HBK has also introduced Uptime Diagnostic - a targeted, low-barrier evaluation of a single critical system, such as power, cooling or design architecture. This focused engagement provides several advantages including quantified baseline of availability and downtime risk. It provides direct proof on the outcome of planned redundancy strategies – and removes trade-offs between availability, capital expenditures (CapEx) and operating efficiency.
"Understanding individual component reliability is no longer enough; we must look at how the entire system performs together," said Adi Dhora, Principal Consultant at HBK. "Our system-level approach moves teams away from reactive troubleshooting, enabling them to optimise capital costs and target maintenance precisely where it prevents downtime."
HBK’s model, established by the initial diagnostic, easily scales into a live RAM (Reliability, Availability, Maintainability) Digital Twin. Powered by the ReliaSoft Asset Performance Framework, the solution connects real-time operational data with engineering models to guide ongoing investment, spares, and maintenance decisions.
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