Control cooling with cool computer algorithm
Vigilent has released a prescriptive analytics suite which uses AI to enhance thermal management of mission critical facilities.
The dynamic cooling management system provider offers Vigilent Prescriptive Analytics in three modules - Reliability, Capacity and Energy. The product proactively responds to situations.
AI-based thermal control
“Our customers are telling us that they need to know more than what happened, or what will happen,” Vigilent CEO Dave Hudson said. “They want to know the specific actions they can take to lower risk, reduce cost and accelerate revenue. Vigilent Prescriptive Analytics does exactly that, and puts managers in the driver’s seat.”
The analytics software uses the company’s “billions of data points across hundreds of mission critical facilities” to predict future thermal issues, producing worksheets that advise customers on how to fix any potential problems such as faulty equipment or inadequate cooling redundancy. The company claims it can also point out opportunities such as hidden capacity and overcooled spaces.
“Data center environments are becoming increasingly dynamic due to virtualized computing, server power variability, and the migration to cloud architectures,” said Rhonda Ascierto, research director, data center technologies, 451 Research.
“To help avoid service disruption, there needs to be visibility into and control of available cooling in each rack, row, room, and datacenter. Vigilent Prescriptive Analytics provides such insights and gives specific recommendations based on actual operating conditions, allowing managers to more safely and cost-effectively manage their facilities.”
The three modules, which can be bought seperately or as a bundle, are available now, with the individual charactistics of each module viewable in the factbox below.
’Reliability Assurance’ module
- Identifies actual (versus designed) cooling redundancy
- Pinpoints where there is heightened risk of extreme temperature events
- Discovers subpar cooling units and predicts which ones are most likely to fail
- Prioritizes limited capex to maximize operating performance
- Recommends specific actions that increase reliability
’Capacity Optimization’ module
- Identifies actual (versus designed) cooling capacity
- Predicts where extreme weather will cause capacity shortfalls
- Discovers which sites, rooms, rows, and racks can handle additional IT load based on actual capacity and forecasted weather
- Avoids investing capex in unnecessary cooling
- Prescribes how to free up revenue-generating cooling capacity
’Energy Efficiency’ module
- Quantifies the expense of business-as-usual, also known as the “cost of inaction”
- Predicts the impact of cooling equipment maintenance and upgrades
- Ensures savings persistence by spotting areas of deterioration
- Identifies which sites or rooms have the greatest efficiency opportunity
- Recommends actions that result in specific levels of energy savings