ARTIFICIAL INTELLIGENCE IN DATA CENTRE
Hewlett Packard Enterprise – HPE is creating a self-managing data centre. HPE will offer an AI recommendation engine add-on that’s designed to predict and stop storage- and general-infrastructure trouble before it starts.
AI and machine learning are better at preventing downtime than humans. Through a form of machine learning, iffy-performing components can be identified automatically by AI . That can be done without any traditional human guess work. It can happen early on, too, before users perceive any kind of problem. Essentially, it’s accomplished by tallying massive amounts of collected data throughout the IT infrastructure stack and then analysing it.
HOW HPE’S SELF-MANAGING SOLUTION WORKS
The idea is to “detect and rapidly identify the root cause” and then to “resolve the problem through data collection.” Signatures are then built to identify other users, elements or customers that might be affected. Rules are then developed to instigate a solution, which can be automated.
Further, in the event that a user does indeed fail, the AI-machine learning solution, with its new signatures and rules, can quickly interject through the entire system and stop others from inheriting the same issue. Future software updates are optimized based on what’s learned through that AI.
AI REDUCES DOWNTIME
To accomplish downtime reduction, one needs full analysis of the entire IT stack .Through that, downtime can be predicted. Slowing infrastructure causes will be identified and then prevented with AI, as opposed to merely being human-monitored and flagged as potential trouble. And “prescriptive resolution” should be employed if the engine can’t prevent a failure.
That means that the engine should be able to fix the problem if it occurs. It should do that by knowing the root cause predictively and analytically, rather than through traditional, manual troubleshooting, and utilizing tools such as web-based forum lookups and so on.
SELF-MANAGING SYSTEMS REDUCE STAFFING LEVELS
Using this technology, staffing levels conceivably drop. Eliminating front-line tech support who are often simply collecting information and documenting issues brings the autonomous data centre closer to becoming a reality. (The AI engine knows there’s a problem, so you don’t need anyone fielding calls.)
“For the small percentage of problems that require the need to talk to an engineer, a customer can immediately reach a level three engineer,”. Levels one and two are eliminated.