Machines are better than humans at many things, and data center management may be on its way to becoming one of them.
Romonet, a London-based maker of data center management software, is preparing to file a number of patents that describe machine learning capabilities it has devised over the past year or so for its software platform, the company announced Wednesday.
The cloud-based platform helps companies analyze cost of their data center assets and trace the impact of infrastructure decisions, such as particular aspects of data center design, on their bottom line.
After several years in operation, the company has amassed a deep trove of operational and financial data on hundreds of data centers. The goal is to apply machine learning algorithms to that data in combination with Romonet’s modeling and predictive-analytics capabilities and generate more accurate predictions and recommended actions for data center operators.
Data center management is a perfect application for machine learning. Analyzing the huge amount of variables and constant changes happening in the environment to make optimization decisions is an overwhelming task for a human operator, regardless of the amount of expertise they may have.
There are already examples of machine learning being applied successfully to data center management. The most well-known one is Google’s application of machine learning algorithms to fine-tune its data centers for maximum efficiency.
There are also several software startups that are using machine learning in applications designed for data center management.
One of them is Coolan, which applies machine learning to things like helping data center managers make informed decisions about selecting server components or predicting when a particular hard drive might fail.
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Another example is LitBit, which uses machine learning as part of its platform for managing and analyzing data from countless types of connected devices that make up the Internet of Things. Data center management is one of LitBit’s biggest initial target markets.