Optimizing Stateful Microservice Migration in Kubernetes with MS2M and Forensic Checkpointing

Fuente: arXiv
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Main Authors: Dinh-Tuan, Hai, Jiang, Jialun
Format: Preprint
Published: 2025
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author Dinh-Tuan, Hai
Jiang, Jialun
author_facet Dinh-Tuan, Hai
Jiang, Jialun
contents The widespread adoption of microservices architecture in modern software systems has emphasized the need for efficient management of distributed services. While stateless microservices enable straightforward migration, stateful microservices introduce added complexity due to the need to preserve in-memory state during migration. However, most container orchestrators, including Kubernetes, lack native support for live stateful service migration. This paper proposes an optimized migration scheme for stateful services in Kubernetes by integrating the Message-based Stateful Microservice Migration (MS2M) framework with Kubernetes' Forensic Container Checkpointing (FCC) feature. Key enhancements include support for migrating StatefulSet-managed Pods and the introduction of a Threshold-Based Cutoff Mechanism to handle high incoming message rates. Evaluation results demonstrate that MS2M for individual Pods reduces downtime by 96.986% compared to cold migration methods, while the StatefulSet approach provides greater flexibility in managing stateful services. These insights provide practical strategies for optimizing stateful microservice migration in cloud-native environments.
format Preprint
id arxiv_https___arxiv_org_abs_2509_05794
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimizing Stateful Microservice Migration in Kubernetes with MS2M and Forensic Checkpointing
Dinh-Tuan, Hai
Jiang, Jialun
Performance
Computational Engineering, Finance, and Science
The widespread adoption of microservices architecture in modern software systems has emphasized the need for efficient management of distributed services. While stateless microservices enable straightforward migration, stateful microservices introduce added complexity due to the need to preserve in-memory state during migration. However, most container orchestrators, including Kubernetes, lack native support for live stateful service migration. This paper proposes an optimized migration scheme for stateful services in Kubernetes by integrating the Message-based Stateful Microservice Migration (MS2M) framework with Kubernetes' Forensic Container Checkpointing (FCC) feature. Key enhancements include support for migrating StatefulSet-managed Pods and the introduction of a Threshold-Based Cutoff Mechanism to handle high incoming message rates. Evaluation results demonstrate that MS2M for individual Pods reduces downtime by 96.986% compared to cold migration methods, while the StatefulSet approach provides greater flexibility in managing stateful services. These insights provide practical strategies for optimizing stateful microservice migration in cloud-native environments.
title Optimizing Stateful Microservice Migration in Kubernetes with MS2M and Forensic Checkpointing
topic Performance
Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2509.05794