Simplifying Network Orchestration using Conversational AI

ONAP is a comprehensive platform for orchestration, management and automation of network and edge computing services for 5G, 6G and Next Generation Networks. Unlike traditional OSSs, it is an open-source project where companies all over the world are collaborating to build different functionalities of an end-to-end Network operating system. For this reason, the ONAP platform has several different sub projects and APIs each performing a specific function to achieve Network Management. There is some complexity associated with using these APIs and knowing and understanding the many parameters associated with them, which impedes adoption. This not only prevents an end- to-end cloud service orchestration like experience for network services, but also increases the time and money spent on network orchestration. This paper proposes and discusses the design of a conversational AI solution that can interface with some significant APIs in ONAP to solve these problems. The conversational AI solution has the potential to significantly simplify network orchestration tasks. This work is being further extended to using Large Language Models (LLMs) to achieve simplified Intent-Based management and orchestration paradigms within ONAP.