Design and Practice of AI Intelligent Mentor System for DevOps Education

Abstract

The design and application of the AI intelligent mentor system are aimed at meeting the support requirements for immediate code writing, build testing, and deployment and operation processes in DevOps education. Among them, the mixed characteristics of multi-source data and the correlation characteristics of the operation process make it difficult for traditional teaching to meet the requirements of refined immediate response. Therefore, this article explores how to apply AI to support an intelligent mentor system that can meet the requirements. First, describe the characteristics of code base records, pipeline logs, and operation monitoring data, summarize the technical support for system construction and application, and propose specific plans for the overall system architecture, functional module construction, model and algorithm design, etc. At the same time, provide mathematical representations Then discuss how the system responds to issues such as the execution status of the task chain, feedback on the operation process, and learning management during the specific execution training process, thereby providing a useful reference for constructing an intelligent support system with the characteristics of DevOps education.