Feature Management for Machine Learning Operation Pipelines in AI Native Networks

Artificial intelligence (AI) has emerged as a key technology in various domains, including telecommunications. The use of AI in cellular networks has the potential to revolutionize the way we communicate by enabling new capabilities, improving network efficiency, and providing better user experiences. However, domain specific data transformations, pre-processing and management in modern data driven pipelines is yet to be addressed. In this paper we perform a discuss Machine Learning Operations automation for with focus on feature management and feature store selection. The design of features and their subsequent management by specialized feature stores are one of the key components of successful infrastructure automation. We also study existing feature stores qualitatively and quantitatively.