Interactions between the mechanical and electrical equipment, along with their associated setpoints, control schemes, and feedback loops, make it extremely difficult to determine a data center’s ‘optimal state.’ Traditional engineering formulas often won’t work because they fail to capture such complex interdependencies, as previously acknowledged by The Uptime Institute. However, by applying advanced Machine Learning algorithms to all this sensor data (we currently process over 200 billion sensor readings), the platform detects patterns in a data center that were previously unknown due to this complexity.

Unraveling these patterns, our products offer clear and easy-to-use answers to many roles within the data center organization, like senior leadership, operational managers, site engineers, and data analysts. Depending on their needs, they can move through all these patterns themselves with advanced root-cause-analysis, receive timely and automated reports whenever the most critical patterns change, or are directly handed recommendations on the most optimal settings, reducing cooling energy and increasing operational reliability at the same time.