HuntMS: A Framework for Microservice Geo-Distribution for Carbon and Cost Reduction
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866913163625103360 |
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| author | Christofidi, Georgia Álvarez-Terribas, Francisco Roumpos, Ioannis Kourtellis, Nicolas Iglesias, Jesus Omaña Doudali, Thaleia Dimitra |
| author_facet | Christofidi, Georgia Álvarez-Terribas, Francisco Roumpos, Ioannis Kourtellis, Nicolas Iglesias, Jesus Omaña Doudali, Thaleia Dimitra |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_10768 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | HuntMS: A Framework for Microservice Geo-Distribution for Carbon and Cost Reduction Christofidi, Georgia Álvarez-Terribas, Francisco Roumpos, Ioannis Kourtellis, Nicolas Iglesias, Jesus Omaña Doudali, Thaleia Dimitra Distributed, Parallel, and Cluster Computing 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. |
| title | HuntMS: A Framework for Microservice Geo-Distribution for Carbon and Cost Reduction |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2603.10768 |