Rich Rogers, a senior vice president of product and engineering at Hitachi Vantara, envisions a data center in which AI-driven management software (some or all of it cloud-based) will monitor and control IT and facilities infrastructure, as well as applications, seamlessly and completely across single or multiple sites. Compute, power, storage, networking and cooling operations will flex dynamically to achieve maximum efficiency, productivity and availability. Human operators, meanwhile, will be free to do what they do best: plan new capabilities and innovate improvements.
“IoT and AI will enable data center issues to be root-caused and resolved automatically by software,” Rogers said. Data center administrators will no longer be woken-up at night to troubleshoot outages. “Voice technologies will enable data center operators to monitor and manage their data centers from any location, be [they] at the grocery store, gym or living room couch,” he predicted. IT Infrastructure gear will be deployed and maintained autonomously. “You simply stock new compute nodes and disk drives and robotics [will] streamline the technology to the appropriate systems,” Rogers explained.
AI-driven automation’s long-term goal is to drive IT managed services toward zero downtime. “Over time we expect the traditional SLA model—99.xx availability, etc.—will have no meaning as the system is always on, compliant, secure, agile and flexible,” advised Satheesh Kumar, IBM’s vice president of hybrid services, AI platform.
Data center infrastructure management is currently highly reactive due to the unexpected arrival of disruptions and delays. AI aims to fix this. “As infrastructure becomes increasingly vital and complex, this resource-intensive approach won’t work,” observed Milan Shetti, general manager of Hewlett Packard Enterprise’s storage division. “It’s no longer acceptable to find out about a disruption after it has occurred or spend the resources to resolve them—that’s the opportunity for AI.”
A rapidly growing number of smart sensors are becoming available to receive data from various data center elements, relaying critical insights into mechanical, electrical and environmental conditions.
“This data can be then used by sophisticated algorithms to analyze any potential problems or anomalies in the whole system, and warn data center managers well in advance,” noted Param Vir Singh, associate professor of business technologies at Carnegie Mellon University’s Tepper School of Business.
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