As organizations increasingly migrate their applications to the cloud, the optimization of microservices architectures becomes imperative for achieving sustainability goals. Nonetheless, sustainable deployments may increase costs and deteriorate performance, thus the identification of optimal tradeoffs among these conflicting requirements is a key objective not easy to achieve. This paper introduces a novel approach to support cloud deployment of microservices architectures by targeting optimal combinations of application performance, deployment costs, and power consumption. By leveraging genetic algorithms, specifically NSGA-II, we automate the generation of alternative architectural deployments. The results demonstrate the potential of our approach through a comprehensive assessment of the Train Ticket case study.

翻译：随着企业日益将应用迁移至云端，优化微服务架构以实现可持续发展目标变得至关重要。然而，可持续部署可能导致成本增加和性能下降，因此在相互冲突的需求间识别最优权衡方案成为一项关键且难以实现的目标。本文提出了一种新型方法，通过聚焦应用性能、部署成本与功耗的最优组合，支持微服务架构的云端部署。我们利用遗传算法（特别是NSGA-II）自动生成替代性架构部署方案。通过对Train Ticket案例的综合评估，研究结果证明了该方法的潜力。