Organizations are making slow but steady progress toward realizing the value of self-healing networks. One reason is that unlike other network automations, the self-healing network requires a wide range of intelligence to support diagnostic and predictive decisioning. In fact, the self-healing network represents the most concentrated area of intelligence for telcos and other network dependent businesses like financial services.

This paper starts with the current definition of the self-healing network and then unpacks the data and intelligence requirements to unlock the full potential of this advancement.

What is a self-healing network?

Self-healing networks are increasingly prevalent in modern network architectures. They leverage automation and artificial intelligence (AI) to constantly monitor network performance, identify potential issues and even take corrective action. Self-healing networks gather data on aspects of the network like traffic flow, device health and use AI and machine learning algorithms to analyze the collected data looking for patterns that predict potential problems. Finally, if an issue is detected the system is designed to automatically take corrective action.

Know all about the self-healing network including the Three stages of maturity for the self-healing network