Today's networks are highly virtualized large distributed systems. With network observability we monitor holistically by incorporating all 3 network planes and their dependencies. For AIOps we require network data done right. Data taxonomy, schema and semantics being preserved and ready in real-time at the Data Mesh.

In this session I describe the relevance and differences between IPFIX, BMP and YANG-Push and its integration into Message Brokers for next generation Network Analytics applications and the differences between Data Lake and Data Mesh.

I demonstrate with a real-life Network Incident Postmortem how Network Anomaly Detection is applied at Swisscom and show how symptom ontology is derived, where Knowledge Graphs will help us to obtain a statistical view, and why we intend to automate the incident and problem process by leveraging AI capabilities.

Further, I will venture into the importance of network vendor, operator and academia collaboration in innovation and standards, and outline current innovation activities at the IETF NMOP working group.