Event Correlation and Request Tracing in Asynchronous Microservice Architectures

Abstract

This article presents an analytical synthesis of scientific approaches to examining event correlation and request tracing in asynchronous microservice architectures. The study is conducted as a systematic analysis of peer-reviewed publications and focuses on interpreting the architectural and operational factors that determine the reconstruction of causal relationships under event-driven and hybrid inter-service communication. Particular attention is given to the impact of asynchrony, message delivery semantics, fault-tolerance mechanisms, and architectural antipatterns on the interpretability of distributed traces and the robustness of event correlation. It is demonstrated that traditional linear request tracing proves insufficient for explaining the behavior of asynchronous systems, whereas event correlation assumes the role of a foundational architectural mechanism rather than a supplementary observability tool. The findings indicate that correlation degradation exhibits a systemic nature and is largely driven by the structure of interactions among services, execution parameters, and the quality of context propagation, rather than by the selection of specific monitoring instruments. The transition toward managed analysis and response loops is shown to amplify the requirements for architectural consistency in correlation, as event-binding errors lead to distorted analytical conclusions and incorrect control interventions. The obtained results refine the architectural conditions for robust event correlation and can be applied in the design and operation of asynchronous microservice platforms with stringent demands for explainability and manageability.