Abstract
Advanced network assurance tools provide for the ability to manage network assurance across a variety of service domains. Such tools may facilitate synthetic network monitoring through active monitoring of live flow data. While this opens new opportunities for network assurance, architecturally it also presents challenges related to the orchestration of how and where flow reporting is established and managed. Techniques are proposed herein that include providing an AI/ML mechanism to predict network problems such that flow collection can be automated to be performed only where necessary, when necessary, and for the protocols and/or hosts that are experiencing issues. The techniques further propose a closed-loop mechanism that provides for dynamically moderating the volume of flows being collected and adjusting (sampled) flow collection frequency so that distributed flow collectors do not become overloaded and/or send too much data to a central repository/network analysis engine.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Barton, Robert; Henry, Jerome; Kumar, Abhishek; and Corleto, Gino, "PREDICTIVE FLOW CAPTURE CONTROLS FOR MULTI-DOMAIN NETWORK ASSURANCE TOOLS", Technical Disclosure Commons, (December 18, 2024)
https://www.tdcommons.org/dpubs_series/7661