MicroForge: An Integrated Platform for Accelerating Experiments in Microservice Research With the Universal Evolution Model
Xiang He, Teng Wang, Zihang Su, Zhenxiang Zhao, Yin Chen, Jihong Yan, Zhongjie Wang · IEEE Transactions on Services Computing · 2025
The rapid adoption of microservice architectures has spurred research into addressing various challenges in microservice system evolution, such as service deployment and task offloading. While numerous solutions have been proposed by researchers, validating these approaches requires extensive experimentation, including both algorithmic testing and simulations across different Microservice-Based Applications (MBAs). However, current research lacks sufficient physical experimentation, which is essential for evaluating how these solutions perform when deployed on actual computing infrastructure with running microservice instances. This gap exists mainly because conducting physical experiments is complex and costly, primarily due to two barriers: the lack of standardized problem modeling approaches and the absence of suitable experimental platforms. To address these challenges, the Universal Evolution Model (UEM) was proposed that unifies different microservice research problems within a common evolution framework. This model frames research problems as approaches to evolve microservice systems under specific constraints to achieve desired objectives. Based on UEM and the widely-adopted Monitor-Analyze-Plan-Execute over a shared Knowledge (MAPE-K) model, a general Microservice System Evolution Architecture was designed that standardizes experimental processes across diverse research scenarios. Building on these foundations, MicroForge was presented, an open-source experimental platform equipped with tools for accelerating experiments. The platform incorporates RescueService, a carefully curated MBA. Through comprehensive evaluation across various MBAs, the functional effectiveness of MicroForge was validated. Additionally, a practical user guide was provided to facilitate the platform's adoption and utilization.