Edge computing technologies facilitate the deployment of services on nearby edge servers with a large number of end users and their mobile devices to fulfill personalized demands. Owing to frequent changes in user mobility and demands, service systems deployed in an edge–cloud environment must continuously adapt to ensure that the quality of service (QoS) perceived by the end users is maintained at a stable and satisfactory level. As it is difficult for system operation engineers to manually deal with such frequent and large-scale evolution due to problems of cost and efficiency, self-adaptation of the system is essential. In this paper, we present a programming framework for microservices (EPF4M) and an infrastructure for self-adaptive microservice systems (EI4MS) for the cloud–edge environment based on microservice architecture. Our study follows a “monitoring–analyzing–planning–execution” control loop that empowers the service systems to redeploy the services according to changes in the QoS. A two-phase strategy is adopted to minimize the side effects of the loop on the performance of the service system. A prototype of this framework and infrastructure has been open-sourced and verified through experiments conducted in a real cloud–edge environment. The results demonstrate the usefulness and advantages of our approach.

边缘计算技术有助于在具有大量最终用户及其移动设备的附近边缘服务器上部署服务，以满足个性化需求。由于用户移动性和需求的频繁变化，部署在边缘云环境中的服务系统必须不断进行调整，以确保最终用户感知的服务质量（QoS）保持稳定和令人满意的水平。由于成本和效率问题，系统操作工程师难以手动应对这种频繁且大规模的演变，因此系统的自适应至关重要。在本文中，我们提出了微服务的编程框架（EPF4M）和自适应微服务系统的基础架构（EI4MS））用于基于微服务架构的云边缘环境。我们的研究遵循“监视，分析，规划，执行”控制回路，该回路使服务系统能够根据QoS的变化重新部署服务。采用两阶段策略以最大程度地减少环路对服务系统性能的负面影响。该框架和基础架构的原型已开源，并通过在真实的云边缘环境中进行的实验进行了验证。结果证明了我们方法的有效性和优势。