Fine-Grained Management for Microservice Applications with Lazy Configuration Distribution

Abstract

Service mesh is gaining popularity as a microservice architecture paradigm due to its lightness, transparency, and scalability. However, fully releasing configurations to the data plane during the business development phase can result in noticeable performance degradation. Therefore, fine-grained traffic management of microservice applications is crucial to service performance. This paper proposes a novel configuration distribution algorithm, DATM, which utilizes inter-service dependencies from the service call chain to manage data-plane traffic and dynamically maintain cluster services. The proposed algorithms enable on-demand distribution based on the obtained service dependency relationships by combining monitoring, information processing, and policy distribution. We validate the proposed mechanism and algorithms via extensive experiments. We show that the approach reduces the memory usage of data-plane agents and improves system resource utilization. Additionally, this reduces the time to issue configuration while effectively saving storage space and significantly reducing the number of cluster updates. Consequently, this approach ensures application performance and guarantees the quality of microservice applications in clusters.