Increase service reliability and performance with autonomous network operations
AI Summary
This video features Naresh Raalo, a product manager at Google Cloud, and Yogesh Tiwari, a cloud data engineer, discussing the transformation of communication service providers through autonomous network operations (ANO). They outline a five-stage journey evolving from manual to fully autonomous network operations focused on increasing speed, reliability, and reducing operational costs.
The core concept is an intent-driven loop where business outcomes guide intelligent automation that continuously monitors and optimizes the network to meet these goals. The framework is built on Google Cloud technologies: a network digital twin constructed on Cloud Spanner for a unified source of truth, AI and machine learning fabrics, and API-driven orchestration enabling closed-loop action.
Challenges faced by telecom operators include complexity from legacy systems, slow manual troubleshooting, non-real-time insights, alert fatigue, siloed and inconsistent data, and lack of scalable AI-driven operations. Google Cloud Professional Services addresses these by building a temporal network digital twin that consolidates real-time network topology, faults, and performance in Cloud Spanner and BigQuery, enabling real-time analytics and operational intelligence.
The roadmap advances to applying graph neural networks (GNNs) for predictive insights, retrieval-augmented generation for contextual natural language queries, and agentic frameworks for autonomous diagnostic and healing functions. This shift towards autonomous AI-driven networks promises to transform telco operations from reactive to proactive and intelligent, ultimately improving efficiency and service quality.