Now is a very exciting time for networking technologies, thanks to the recent news by Hughes Network Systems. The leading provider of managed network services has recently announced the commercial availability of its AI for IT operations (AIOps) solution for enterprise wider area networks (WANs).
The AIOps feature is integrated into the company's HughesON™ offering, which is a suite of end-to-end fully managed SD-WAN and cloud-based digital signage solutions. Today, the AIOps capability is already in use across more than 32,000 managed sites.
This new feature is a significant advancement in the self-healing AI arena, which not long ago, was only a pipedream. In fact, Hughes is the first managed service provider to deliver a self-healing WAN edge capability to enterprise customers.
The AIOps feature works by automatically predicting and preempting (or 'self-healing') undesirable network behaviour, preventing service-disrupting symptoms in 70% of cases. Speaking about the success rate, Dan Rasmussen, Senior Vice President at Hughes, said "We estimate that the 70% success rate for autonomous correction across the sites under our management has saved approximately 1,750 hours of network downtime in the first seven months of use. In the other 30% of cases, the system provided early diagnoses of potential hardware failure or chronic site issues so they could be addressed preemptively.”
The AIOps capability is driven by machine learning models that absorb and contextualise petabytes of proprietary network data. What's more, it detects deviations in key metrics against an evolving network baseline. The AIOps will then assess the risk-reward of potential corrective actions, before autonomously taking appropriate measures, and tracking performance to ensure a return to steady-state parameters.
With cutting-edge AI and ML techniques in its arsenal, Hughes has been able to deliver the best possible network transformation to businesses. Better still, Hughes is also able to offer customers shortened triage time for help-desk incidents, proactive detection of site, vendor, and geographic network anomalies, and prescriptive corrective recommendations.
