Formalizing Model Selection in LLMOps: A Systematic UML-Based Process Model

Abstract

: The efficient adoption of Large Language Models (LLMs) in enterprises requires formalizing and systematically implementing LLM Operations (LLMOps), as it could reduce costs and ensure the reproducibility of LLM solutions. One of the critical phases of LLMOps is selecting a suitable LLM, as it can significantly affect a system’s performance, feasibility, and maintainability during the operational phase. As a result, uninformed decisions about model selection that do not align with business, functional, and non-functional requirements may severely impact subsequent stages of the LLMOps life cycle. To investigate the model selection phase, we conducted an extensive Systematic Literature Review (SLR) and synthesized its findings to derive a set of activities fundamental to this phase. These activities are presented in an end-to-end UML activity diagram. The proposed model aims to support the formalization of model selection processes, improve decision-making, and enhance the traceability and transparency of LLMOps practices. This work forms part of a broader research effort toward the formalization of the entire LLMOps life cycle, with the goal of facilitating scalable and reliable integration of LLMs in enterprise environments.