This paper discusses some problems with inadequate semantic interpretation of configuration information in microservices orchestration environments, including complicated YAML specifications, increased costs from cross-service change coordination, lack of contextual restrictions on automatic corrections, etc. Builds an LLM-based semantic construction of understanding and automated modification generation in Kubernetes orchestration environments. According to the review of research articles in LLM software engineering, Kubernetes configuration security and microservice operation for three years ago, this paper puts forward a closed-loop mechanism of "intent parsing-context retrieval-constraint verification-change generation-canary release veri\- fication", empirically analysizes its popularities and security issues based on public-sourced survey results. In view of the present status and development direction in application at home and abroad, they have two main reasons to pursue them as follows. In combination with a large-scale language model, coupled with rule engines, policy knowledge bases and rollback mechanisms to enhance the consistency, interpretable ability and change security of configuration generation. Theoretical basis and practical support of Intelligent Operation & Management (IO&M) for platforms Construction and autonomous orchestration.

Yunshu Zhang, A Framework for LLM-Based Semantic Configuration Understanding and Automated Change Generation in Microservice Orchestration. International Journal of Neural Network (2026), Vol. 5, Issue 1: 98-107. https://doi.org/10.38007/NN.2026.050111.

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