Downtime is one of the costliest events for data center operators and their clients. IDC has reported that the average cost of an infrastructure failure is US$100,000 per hour. In the case of critical application failure that figure increases to US$500,000 up-to $1 million. For data center operators, an incident could severely damage the center’s place as a key partner with its clients – damaging their reputation and business in the long run.
100% uptime is critical for data center operators.
In order to maintain operations at their maximum performance, the traditional approach is to combine the expertise of a highly skilled engineers, a network of electronic sensors, and a support staff that monitor power and cooling infrastructure daily. Yet, despite this robust approach, the daily systems that monitor data centers are in fact compromised by the very people who physically walk the floors.
This challenge demonstrates the limits of maintenance monitoring currently in place in data centers – and this challenge only increases with scale and complexity. Testing each and every feature combination to achieve peak performance within the modern data center is simply not realistic. In an innovative move, in 2014, Google began utilizing artificial intelligence, to overcome this hurdle and track the appropriate variables and calculate maximum efficiency at its server farms. The algorithms developed from the data collected is now used across the globe by operations teams for optimal performance.
In recent years, the scope of AI has grown. Its enormous potential has led IT innovators to devise machine learning systems to address the biggest challenge for today’s data centers: uptime. One of these innovators is the San Jose-based start-up LitBit.
LitBit developed AI software that listens and learns to magnify the availability and reach of those teams physically walking the floors. These sensors, in turn, become a natural extension to the technicians walking the data center floor – adding a layer of automation with the potential to identify and solve a problem, and the ability to predict failures before they happen.
ROOT will use LitBit’s state-of-the-art technology in 2018 to augment its core maintenance program and LitBit sensors are being installed this month.
To learn more about artificial intelligence and ROOT’s groundbreaking use of the technology to achieve 100% reliability, download the white paper here.