Aricent, a global design and engineering company, has launched NetAnticipate, a self-learning capability for private/public clouds, central offices rearchitected as data centers (CORD), 5G, and satellite networks.
The carrier-grade solution combines a library of network Artificial Intelligence (AI) models, semantic telemetry and intent-based orchestration capabilities. With NetAnticipate, a network operations center can improve efficiency and enhance the customer experience from quick troubleshooting, reduced mean time to resolve problems, auto-ticketing and autonomous resolution.
A recent study by Cisco predicts that mobile data traffic will increase seven-fold by 2021, reaching 49 exabytes per month and exceeding half a zettabyte annually.
To keep up with the ever-increasing volumes of traffic and to manage subscribers Quality of Experience, the network must not only be predictive, but also capable of optimizing outcomes in real-time.
Most networks today are still managed by static rules that cannot scale to all possible issues and can only detect faults that have known signatures. Instead, Machine Learning (ML) algorithms can surface unexpected patterns in traffic flows and make recommendations to avert problems. Allowing network engineers to express “what” needs to be done in a natural language then letting the infrastructure determine “how”, further simplifies and streamlines operations.
Walid Negm, Chief Technology Officer at Aricent said, “The story of an event or alarm that impacts a service is extremely hard to stitch together. A network engineer is swamped with trouble tickets that are irrelevant, not prioritized or lack context. If the “devil is in the details” then why not auto-enrich tickets? More importantly, why not predict the onset of a fault or delay — to keep customers happy.” Negm added, “We believe that companies must augment their problem solvers so that they can be freed to innovate. That means intelligent “augmentors” such as design simulation tools, test automation and auto-resolution to drive-up productivity gains”.