Runtime Observability in Micro-Frontend Architectures: Distributed Tracing, Error Boundary Instrumentation, and Performance Budget Monitoring at Scale

Abstract

Micro-frontend architectures distribute UI ownership across independently deployed modules, each maintained by a separate team. While this model improves deployment autonomy and team scalability, it creates monitoring gaps that conventional application performance tools do not address. When a remotely loaded module fails silently, when an LCP regression originates in one of several independently deployed remote modules, or when an error caught by a React error boundary lacks context about which module produced it, standard monitoring instrumentation yields incomplete signal. This paper presents a three-layer runtime observability framework for Module Federation-based micro-frontend systems. The first layer propagates distributed trace context across module load boundaries using the W3C Trace Context standard and the Open Telemetry JavaScript SDK. The second layer instruments React error boundaries in both host and remote modules to capture error reports that include the module identifier and the active trace ID, routing all errors to a shared collection endpoint regardless of which team deployed the faulting module. The third layer attaches per-module attribution tags to Core Web Vitals measurements collected through the Performance Observer API, making it possible to identify which remote module contributed to a page-level metric regression. We describe the architecture of each layer, discuss their interaction, and evaluate the framework against a set of six observable failure scenarios common in production micro-frontend deployments. Results show that the combined three-layer approach achieves root cause isolation for five of the six failure scenarios, compared to zero for single-application APM tools applied to the same scenarios.