End-to-end Development of an App Identification Solution for an Edge Device

Case Study

End-to-end Development of an App Identification Solution for an Edge Device

The Challenge

The client, a US-based global leader in secure real-time communications providing software, cloud, and network infrastructure solutions, was looking to implement a complete network traffic classifier solution. This solution ideally would be a generic, cost-effective solution that should have the ability to identify software applications for traffic and be increasingly critical for the Network Traffic Management Center.

The Solution

Ness built an ML-based app classification product to help the customer prioritize the traffic dynamically and ensure optimal network usage. This influenced business policies sitting on edge devices like bandwidth provisioning, security, blocking, and unblocking apps. Pairing Edge integration with analytics in the cloud allowed a truly dynamic solution without shipping new software/device updates.

The Results

  • Provides security, simplified interoperability, advanced session management, and carrier-grade reliability in public or private cloud deployments for fixed, mobile, cable, and interconnect/wholesale service providers, as well as enterprises.
  • Delivers deployment flexibility that enables security and service quality for applications such as SIP trunking, contact centers, unified communications, VoLTE, VoWiFi, RCS, and OTT.