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Messy data in, treasure out: boosting Autonomous Networks

URN C25.0.830

Topics AI (Artificial Intelligence), Autonomous networks, Data management

In this Catalyst, we will process and collect a wide variety of data formats using AI, and attempt to visualize and manage network configurations

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A key element in realizing an autonomous network is to accurately manage the network status. Among these, network configuration information is an important element. However, in many CSPs, network configurations are collected using multiple methods, are siloed, and are not standardized. (Especially in legacy networks) This situation is an obstacle to realizing an autonomous network from end to end. To solve this problem, data processing and formatting is required to visualize and manage accurate network configurations from end to end using multiple methods from a wide variety of data formats. In this Catalyst, we will process and collect a wide variety of data formats using AI, and attempt to visualize and manage network configurations. In the future, we would like to realize auto-healing and intent-based network configuration changes in the network configuration management realized by this Catalyst.