This document provides an overview of the vast landscape of AI/ML frameworks. It identifies the most relevant open-source developments in the area of ML model training and inference and, in particular, those that cover the lifecycle of AI model management. The focus is set on MLOps frameworks, which provides an extension of the DevOps methodology to develop, train, and deploy ML models via automated procedures that encompass both software, data, security and infrastructure. The document also introduces the platform requirements specification, together with the methodology designed for requirements gathering, inspired by the Dynamic System Development Method (DSDM) Agile Project Framework, which is based on use cases definition and the identification of Personas, Epics, User Stories and Requirements.