Monitoring metabolic flux in 3D tissue models is essential for validating physiological maturity and maintaining homeostatic balance. However, conventional optical based analytical techniques often fail to capture dynamic and transient metabolic shifts due to phototoxicity, signal attenuation in thick 3D constructs, and the requirement for invasive labeling, all of which hinder long-term, continuous monitoring. Standard assays such as high-performance liquid chromatography (HPLC) and enzyme-linked immunosorbent assay (ELISA) are also inherently time consuming and labor-intensive. Although electrochemical sensors offer a promising alternative, their integration into microfluidic platforms is frequently constrained by limited mass transport and the poor scalability of traditional lithography-based fabrication methods. Herein, we report an integrated, roughness-engineered microfluidic platform that addresses these limitations by strategically exploiting the “stair-stepping” artifacts inherent to fused deposition modeling (FDM) 3D printing as functional passive micromixers. By repurposing these manufacturing defects into deterministic micro-topographies, the platform induces chaotic advection,disrupting the boundary layer and enhancing solute exchange at physiologically relevant low flow rates. Numerical simulations elucidate the correlation between surface roughness and fluidic vorticity, providing a robust framework for performance optimization. Experimental validation demonstrates superior sensitivity, with a glucose response of 6.983 nA/mM and a lactate response of 5.669 nA/mM. Finally, real-time monitoring of biomimetic hydrogel phantoms over 500 min underscores the platform’s potential as a scalable and cost-effective quality control tool for 3D in vitro tissue engineering and regenerative medicine.