E4.2 Intermediate prototype for zero-touch and proactive network management

Based on the architecture described in Deliverable E4.3.2 "Initial Design of Zero-Touch and Proactive Network Management", we will explore the implementation phase of the described architecture. This implementation aims to create proactive and autonomous network management for future 6G infrastructures. Using the advanced Neuro-Symbolic (NeSy) AI framework, especially Logic Tensor Networks (LTN), this implementation offers an efficient CPU resource prediction service. The main goal is to balance the trade-off between providing too many and too few resources, ensuring the network runs smoothly and efficiently.This is an accompanying document to the full prototype already uploaded on the corresponding GitLab repository and not in itself a deliverable. This document serves as a practical complement to the theoretical insights provided in the original deliverable, bridging the gap between conceptual understanding and actionable implementation. By the end of this guide, readers will be equipped with the knowledge to replicate and extend this implementation for further research and development in zero-touch network management.