IBM Watson to Crunch Nlyte DCIM Data to Optimize Data Center Operations

DCIM software vendor Nlyte Software has partnered with IBM’s Watson IoT group to bring to market a machine learning-powered DCIM solution, aiming to tap into the power of AI to make data centers more resilient and efficient.

Expecting to bring the product to market this July, Nlyte said it will “unlock hidden patterns” in millions of data points collected from sources such as temperature and humidity sensors, electrical infrastructure, and other systems that comprise a typical data center.

The promise of using Nlyte with IBM Watson’s machine learning capabilities is to “head off potential power and performance issues while also optimizing workload infrastructure operations and ultimately workloads placement,” Enzo Greco, Nlyte’s chief strategy officer, said in a statement.

The potential value of applying machine learning to data center management is enormous. Alphabet’s Google blazed the trail several years ago, when it announced it had been using machine learning algorithms to fine-tune power and cooling systems in its server farms, which led to meaningful energy savings.

Since then, numerous companies have introduced machine learning-powered data center management solutions focused primarily on physical infrastructure, including Vigilent, LitBit, AdeptDC, and Virtual Power Systems.

Related:AI in Data Center Management: What It Means for Staffing and Processes

Big cloud platforms that offer machine learning capabilities as a service – the likes of IBM, Amazon Web Services, Microsoft Azure, and Google Cloud Platform – make it easier for any software developer to integrate machine learning into their application. Computing infrastructure for training and using machine learning algorithms is extremely complex and costly, and the tech giants are leveraging their scale and resources to build and maintain it, creating a potentially lucrative new growth avenue for their cloud services businesses.