LATEST INTELLIGENCE perform a given task . When used together , billions or trillions of operations per second may be performed in a single server enclosure running countless virtual machines or containers .
Unplanned interruptions due to power problems can set back a massive amount of work and result in downtime and lost revenue for the data center . It is in this environment that we most often see the impacts of unexpected power quality degradation .
Historically , assessing power quality has been undertaken during the commissioning and bringup phase of the data center as a one-time event utilizing manually placed sensors , and would likely not occur again until a massive server refresh cycle is undertaken . The facilities and IT teams of the data center both must participate , with electricians on standby to troubleshoot and make corrections . With the ongoing focus on improving both efficiency and sustainability of the data center , more frequent or even continuous power quality monitoring becomes desirable .
Continuous monitoring facilitates having a dynamic operating environment rather than a steady state , letting machines be turned off , on , or throttled back to support grid-interactive and follow-the-sun operation models of the data center .
Access to near real-time granular power quality information helps the facility and IT managers quickly resolve identified problems , improving uptime and power utilization efficiency . p
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