Towards Minimum Latency in Cloud-Native Applications via Service-Characteristic- Aware Microservice Deployment
Ru Xie, Liming Wang, Song Chen · 2024
Microservice applications are gaining popularity as cloud-native embraced by the IT industry. However, they suffer from a latency problem because they intrinsically involve mass inter-microservice data exchange that introduces additional latency. The remarkable gap of data transmission speed between co-location and cross-server communication necessitates the need of utilizing microservice deployment strategies to accelerate data transmission and reduce end-to-end latency. Previous works characterize communication dependencies among microservices and put strongly inter-dependent ones on the same server to reduce communication overhead. Unfortunately, they overlook characteristics of microservice applications, and the resulting modeling is neither fine-grained enough nor comprehensive, which misleads microservice deployment and ultimately results in prolonged communication delay. To address the above problems, we propose a novel microser-vice deployment strategy based on fine-grained and comprehensive modeling of microservice dependencies, on the basis of an in-depth analysis of service characteristics. In this paper, dependencies are measured on the request level and combined with data sharing relationships to jointly decide microservice division, aiming to facilitate inter-microservice communication. After that, a selective scale-up strategy is designed to further reduce cross-server communication and shorten response latency. Extensive experiments on a real-world microservice application demonstrate that our method is effective in mitigating commu-nication overhead and can reduce end-to-end latency by 15.64% ~ 29.18 % compared with the state-of-the-art methods.