An Architecture For Automated It Event Management In Municipal Government: Integrating Itil 4, Zabbix, A Fuzzy Inference Engine, and Glpi

Digital transformation in Brazilian municipalities has expanded the offering of digital public services in distributed and often poorly integrated environments, where monitoring limitations compromise end-to-end visibility, continuity, and service reliability. In this context, the absence of automated IT Event Monitoring and Management (EMM) mechanisms hinders the consistent classification of criticality and increases dependence on manual triage. This article presents a configurable fuzzy inference mechanism, implemented in Python and integrated with Zabbix and GLPI, to support the contextual classification of event criticality based on impact and urgency. The artifact is based on ITIL 4 event management, fuzzy set theory, and the Design Science Research (DSR) methodological framework, following the six-step methodology described in [1]. The study includes problem identification, objective definition, flow modeling, prototype implementation, and demonstration in a municipal environment, supported by historical MTTD and MTTR metrics from the pre-implementation period as an exploratory reference. The results of the qualitative pilot evaluation indicate the mechanism's technical feasibility, capacity for automated criticality classification, and functional integration with the ticket processing cycle, strengthening traceability and reducing manual interventions in the initial stages of the process. This work contributes a configurable and modular artifact for the automated classification and processing of IT events in complex institutional contexts of public administration.