A comparative study towards designing a hybrid architecture of microservices and LLM-based multi-agent systems

LLM-based Multi-Agent Systems (LLM-MAS) present an emerging paradigm for constructing intelligent and adaptive applications that enable autonomous reasoning and collaborative problem-solving. Empirical studies show that current LLM-MAS still suffers from overlapping agent roles, unclear capabilities, and goal misalignment. In contrast, Microservice Systems (MS) are designed with modularity, and each service encapsulates a well-defined context and interface with structured and deterministic execution. From the system architecture principles, these paradigms demonstrate parallel attributes and complementary strengths that lead to a synthesized hybrid architecture. In this paper, we analyze the design factors of hybrid MS and LLM-MAS, as well as the main challenges, through a comparative study across eight architectural dimensions, including function encapsulation, orchestration, API design, auto-correction, data communication, operations, quality attributes, and environment awareness. The analysis reveals critical mismatches, design synergies, and transferable best practices. To motivate future work, we define four research questions to categorize the challenges. The goal is to create a converging design space for exploring architecture design towards intelligent, autonomous, modular, and adaptive systems.