ABC: Automatic Bottom-Up Construction of Configuration Knowledge Base for Multi-Vendor Networks

Wenlong Ding, Libin Liu, Li Chen, Hong Xu

Abstract: The Configuration Knowledge Base (CKB) facilitates network configuration management in multi-vendor environments by storing configuration snippet templates and pa-rameter settings for various vendors and intents, simplifying the deployment of the same configuration intent across different vendor devices. Current CKB construction methods follow a top-down manner, which requires handcrafted parameter labeling and snippet template creation for every new vendor or intent, resulting in significant expert effort. We seek to reduce this heavy human effort by leveraging our insights that different vendors share similar underlying intents and corresponding parameter types despite their different configuration languages, motivating bottom-up CKB construction manners which automatically create and align snippet templates of the same intent across all vendors by analyzing already existing device manuals and network configuration files. More specifically, we introduce ABC an active-learning-based tool that utilizes NLP models to produce snippet templates with manuals, extract labeled parameters in existing configuration files, and align those templates with common configuration models by encoding and comparing manuals of different vendors. We believe that creating such a tool would be a significant step towards achieving highly automated network configuration, which would also serve as a solid foundation for future endeavors such as intent-based network configuration, network configuration synthesis, and network device assimilation.

External IDs:dblp:conf/cogmi/DingLCX23