QoS-awareness of Microservices with Excessive Loads via Inter-Datacenter Scheduling
Jiuchen Shi, Jiawen Wang, Kaihua Fu, Quan Chen, Deze Zeng, Minyi Guo · 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS) · 2022
User-facing applications often experience excessive loads and are shifting towards microservice software architecture. While the local datacenter may not have enough resources to host the excessive loads, a reasonable solution is moving some microservices of the applications to remote datacenters. However, it is nontrivial to identify the appropriate migration decision, as the microservices show different characteristics, and the local datacenter also shows different resource contention situations. We therefore propose ELIS, an inter-datacenter scheduling system that ensures the required Quality-of-Service (QoS) of the microservice application with excessive loads, while minimizing the resource usage of the remote datacenter. ELIS comprises a resource manager and a reward-based microservice migrator. The resource manager finds the near-optimal resource configurations for different microservices to minimize resource usage while ensuring QoS. The microservice migrator migrates some microservices to remote datacenters when local resources cannot afford the excessive loads. Our experimental results show that ELIS ensures the required QoS of user-facing applications at excessive loads. Meanwhile, it reduces overall/remote resource usage by 13.1% and 58.1% on average, respectively.