Ripple: Large-Scale Service and Configuration Management in the Cloud

Microservice architectures backed by container technology have been widely used in many real-world cloud-native applications. By enabling customers to manage their services and configurations in the cloud in a centralized, externalized, and dynamic manner, efficient service and configuration management plays a fundamental role in building cloud-native service-centric applications. The number of containers in cloud data centers continues to increase. For example, in the Alibaba Cloud, the number of containers reached hundreds of thousands by 2023 and is expected to reach several million soon. At this scale, existing service and configuration management solutions have limited efficiency, scalability and robustness. Other related approaches, such as message bus systems and publish/subscribe (pub/sub for short) systems, also do not work well for large-scale service and configuration management in the cloud, as their designs are more general purpose directed. To overcome these limitations, we design a system, called Ripple, that uniquely combines several existing and some novel features such as consistent hashing-based workload distribution, dynamic destination list-based and client-assisted message delivery, incremental update, and adaptive load balancing. Approaches exhibiting these features have not been well investigated in the domain of service and configuration management. We compare our proposed solution with existing academic and industrial approaches. The experiments show that our solution greatly outperforms its counterparts. For example, for the same workload, when Ripple is used, the average message delivery latency and network bandwidth consumption can be reduced by up to 77% and 93%, respectively.