QoS for best‐effort batch jobs in container‐based cloud

Abstract

The resource orchestrators in the cloud provide different QoS classes. Existing studies have mainly focused on resource guarantee for high-priority class jobs, but yet to consider delicate QoS control of low-priority jobs in the cloud. In this paper, we propose the differentiated shares that provide weighted CPU scheduling for low-priority batch jobs in container-based cloud. To implement the differentiated shares, we extend resource reservation interfaces provided by Kubernetes and suggest an algorithm that maps the resource management attributes of Kubernetes into those of Linux. The proposed differentiated shares can avoid worsening interference with high-priority containers by exploiting the hierarchical resource sharing of task groups in Linux. In addition, we suggest a node scoring policy to provide efficient inter-node job scheduling with the consideration of the differentiated shares. The performance measurement results show that the differentiated shares can provide weighted CPU scheduling for best-effort batch containers without interference with high-priority containers (less than 3% with respect to application-level performance).

Niyama: Node scheduling for cloud workloads with resource isolation

“…Other work on resource isolation in Kubernetes 44 also show that performance degradation of containers due to interference can be attributed mainly to CPU contention. Recent work 45 has also focused on improving performance of Kubernetes containers under the Best Effort QoS class by means of differentiated shares which grant the containers weighted CPU allocation. The authors also describe the policy changes required at the inter‐node level to make the single node technique more efficient.…”