Microservices are a dominant architecture in cloud computing, offering scalability and modularity, but also posing complex deployment challenges. As data centers contribute significantly to global carbon emissions, carbon-aware scheduling has emerged as a promising mitigation strategy. However, most existing solutions target batch, high-performance, or serverless workloads and assume access to global-scale infrastructure. Such an assumption does not hold for many national or regional small to medium-sized enterprises (SMEs) with microservice applications, which represent the real-world majority. In this paper, we present HuntMS, an Adaptive Carbon and Efficiency-aware placement for microservices that considers carbon, cost, and latency constraints. HuntMS dynamically places microservices across geographically constrained regions using a scalable optimization strategy that leverages insight-based search space pruning techniques. Evaluation on a real-world deployment shows that HuntMS quickly adapts to real-time changes in workload and carbon intensity and reduces carbon emissions by 37.4% and operational cost by 3.6%, on average, compared to a static deployment within a single country, while consistently meeting SLOs. In this way, HuntMS enables carbon- and cost-aware microservice deployment for latency-sensitive applications in regionally limited infrastructures for SMEs.

翻译：微服务是云计算中的主导架构，具有可扩展性和模块化优势，但也带来了复杂的部署挑战。由于数据中心对全球碳排放贡献显著，碳感知调度已成为一种有前景的缓解策略。然而，现有解决方案大多针对批处理、高性能或无服务器工作负载，并假设可接入全球范围的基础设施。这一假设对许多拥有微服务应用的中小型企业（SMEs）并不成立，而这类企业恰恰构成了现实世界的主流。本文提出HuntMS——一种面向微服务的自适应碳排放与效率感知部署方法，综合考虑碳排、成本和延迟约束。HuntMS利用基于洞察的搜索空间剪枝技术，通过可扩展的优化策略，在地理受限区域内动态部署微服务。在真实部署环境中的评估表明，相比单一国家内的静态部署，HuntMS能快速适应工作负载和碳排放强度的实时变化，平均减少37.4%的碳排放和3.6%的运营成本，同时始终满足服务水平协议（SLO）。通过这种方式，HuntMS为中小企业在区域受限基础设施中运行延迟敏感型应用，提供了碳排放与成本感知的微服务部署方案。