Over the next few weeks Tracy Collins will be sharing a series of articles highlighting the specific challenges that data center operations teams face. Tracy is also speaking about AI and Machine learning in data centers at the Data Center World Show in Texas on March 29th, 2022.
At EkkoSense we often talk about how it’s time for data centre monitoring to start getting much more granular – but what do we mean by that? And how granular do you need to be?
EkkoSense identifies the five issues operations teams will need to resolve to successfully balance increased workloads while still securing carbon savings.
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.