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AI and IoT in the data center

New rules, changing paradigms

August 21, 2019

AI and IoT in the data center
It’s happening in virtually every industry right now. AI and IoT are redefining how business is done, and companies are reaping the benefits.

Data centers, in particular, are experiencing a transformation. They really have no choice. Gartner predicts that by 2020, more than 30% of data centers that fail to implement these new technologies will cease to be operationally and economically viable.

Here are just some of the changes now underway:

  • AI-based cybersecurity—Data centers are using artificial intelligence to screen and analyze incoming and outgoing data and detect potential threats that deviate from normal network behavior. This is far less costly and time-intensive than hiring cybersecurity professionals to analyze new cyberattacks and develop mitigation strategies.

  • Improved energy efficiency—AI uses the data from the IoT sensors to analyze a number of factors that can affect energy consumption, including temperature set points, flow rates and equipment performance. It not only identifies sources of energy inefficiency but also can make adjustments to reduce energy consumption. Today power consumes about 10% of a data center’s operating budget, and Gartner predicts this will rise to about 15% by 2021. By using data analytics, companies can reduce the amount of energy used for cooling by up to 40%.

  • Troubleshooting and downtime reduction—Smart sensors and AI tools like the HPE artificial intelligence predictive engine can detect and predict outages by tracking power levels and monitoring server performance, network congestion and disk usage. Artificial intelligence can even autonomously implement strategies to help the data center recover from a data outage.

  • Server optimization—AI-based predictive analysis can help data centers balance loads more efficiently, distributing workloads across multiple servers during periods when there’s heavy demand. Artificial intelligence also enables better tracking of server performance, disk usage and network congestion.

  • Staff reduction and redefinition of IT personnel’s roles—The automation of many routine data management functions with IoT- and AI-driven solutions will eliminate jobs, for sure. But it will also allow higher-level IT staff to redirect their efforts to more strategic and advisory functions within the organization—which many will find more rewarding.
IoT and edge computing
The proliferation of connected devices brought about by the IoT explosion is driving the demand for edge computing, the distributed computing model that brings compute and data storage closer to the location where it’s needed. The low latency and reliability edge computing delivers are essential for most IoT uses cases. “When automated vehicles communicate with each other about hazards on the road, for example, they need the low latency provided by the nearby edge network to spread information fast enough to avoid crashes. Analogously, a smart factory can’t afford to stop production because the larger network has gone down. If it takes advantage of edge computing, the interconnected system of machines can keep running.”
This new paradigm has led many IT experts to predict a total rethinking of the data center concept—they foresee facilities that look and operate very differently than what we know today. George Slessman, the CEO of IO, believes “the traditional data center will go the way of the 8-track tape player,” making way for a new breed of more closely distributed “mini” data centers “optimized for machine-to-machine (M2M) workloads and the analytics that mine their data for business insights.”
Of course, your customers will look to you to help them make sense of it all. So, if you’re looking for more expert advice, feel free to reach out to one of Ingram Micro’s data center experts, Samuel Alt.