Data centers and the workloads they power are simply too critical to be left to automated systems. While machine learning and AI have enormous potential, we don’t believe you should just trust AI to get on with managing the sensitive security and controls needed for critical data center cooling duty performance.
For several years, AI and machine learning have been used as buzzwords to signal the vision of an automated data center that’s more resilient and costs less to run. But the reality as we have shown is that most data center operators are still living in a reactive world – often spending most of their time chasing down problems and putting out fires.
Michael Yong, Director of Sales for APAC at EkkoSense, shares the first in a series of four articles on AI and Machine Learning in data centers.
The first one is titled – “Traditional data center software toolsets simply can’t balance escalating IT workloads with the need to cut energy consumption" and Michael discusses how data centres have to balance being busier than ever with the pressure to be energy efficient.
While we recognize that Vertiv’s decision to discontinue its flagship DCIM platform is indicative of challenges across the DCIM space, at EkkoSense we also acknowledge that the data center management challenges customers were trying to solve haven’t just gone away. So, what can be done to support current Vertiv Trellis and Vertiv Aperture customers as they evaluate their options?
Expect data centres to come under renewed pressure as one of the highest energy users within organisations. And while data centre teams clearly want to deliver on their carbon obligations, that can be challenging when they don’t always have a clear understanding of how exactly their rooms are performing from a cooling, capacity and power perspective. Adrian Barker, Key Account Director at EkkoSense shares his views.
Organizations clearly want to deliver on their carbon obligations, but that can be challenging when data center operators don’t always have a clear understanding of how their rooms are performing from a cooling, capacity and power perspective.
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