Resilient and Efficient Microservices: Stochastic Modeling and Quantification of Energy Consumption and Recovery Times
Iure Fé, Luis Guilherme Silva, André Castelo Branco Soares, Francisco Airton Silva, Alessandro Mei, Paulo A. L. Rêgo, Eunmi Choi, Tuấn Anh Nguyễn, Jae-Woo Lee, Dugki Min · 2024
As the adoption of microservices architectures in cloud deployments grows, so does the challenge of ensuring rapid recovery and minimal energy consumption in the face of disasters. This paper introduces a Generalized Stochastic Petri Net (GSPN) model specifically designed to quantify recovery times and electrical consumption in such environments. The model supports the development of resilient and eco-conscious systems by allowing precise manipulation and planning based on various configuration scenarios. We identify critical architectural elements and define intervals that yield significant improvements. Our findings not only enhance the understanding of energy and recovery dynamics in microservices but also serve as a crucial tool for system designers aiming to optimize both performance and sustainability. The implications of this research facilitate a strategic approach to disaster recovery planning, contributing to the broader field of cloud computing resilience.