Design and Practice of AI Intelligent Mentor System for DevOps Education
Zhengrui Lu
European Journal of Education Science, 2025, vol. 1, issue 3, 25-31
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.
Keywords: DevOps education; AI intelligent mentor system; system design; technical practice (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://pinnaclepubs.com/index.php/EJES/article/view/391/393 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:dba:ejesaa:v:1:y:2025:i:3:p:25-31
Access Statistics for this article
More articles in European Journal of Education Science from Pinnacle Academic Press
Bibliographic data for series maintained by Joseph Clark ().