Machine Learning in DCIM Software
Before the emergence of ecommerce, most data centers could still be small and uncomplicated, with a few servers, storage and network devices sitting in a couple of small scale racks. Today, data centers have grown to mega-server farms located in remote areas. These mega-centers consist of tens of thousands of servers and devices contained in thousands of racks.
As data center operations continue to grow, many of the larger outfits are adopting automation. This includes the use of predictive analytics in data center infrastructure management (DCIM) software.
DCIM software is a type of machine-learning software that can automate processes involved with maintaining data centers. This is especially useful with those large mega-server farms. Depending on the DCIM software, processes such as monitoring temperature, power use and risk of failure can prompt an automated response such as turning cooling units on and off or predicting what will happen if a human operator were to perform certain actions, including turning off a cooling unit or increasing set temperatures.
This machine learning software continually learns and makes adjustments as needed. It saves money by reducing energy costs, easing pressures on human staff, and averting downtime.
It will be interesting to see how the data center technology used by giants like Microsoft and Amazon scales to smaller operations. Network architecture, system monitoring, and environmental control remain as important as ever. Whether your server room needs cleanup or you're building a data center from the ground up, Elontec handles procurement, design and build, maintenance, recovery, and more.