KOSMOS: Vertical and Horizontal Resource Autoscaling for Kubernetes

被引:15
作者
Baresi, Luciano [1 ]
Hu, Davide Yi Xian [1 ]
Quattrocchi, Giovanni [1 ]
Terracciano, Luca [1 ]
机构
[1] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Milan, Italy
来源
SERVICE-ORIENTED COMPUTING (ICSOC 2021) | 2021年 / 13121卷
关键词
Kubernetes; Containers; Resource provisioning; Control theory;
D O I
10.1007/978-3-030-91431-8_59
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cloud applications are increasingly executed onto lightweight containers that can be efficiently managed to cope with highly varying and unpredictable workloads. Kubernetes, the most popular container orchestrator, provides means to automatically scale containerized applications to keep their response time under control. Kubernetes provisions resources using two main components: i) Horizontal Pod Autoscaler (HPA), which controls the amount of containers running for an application, and ii) Vertical Pod Autoscaler (VPA), which oversees the resource allocation of existing containers. These two components have several limitations: they must control different metrics, they use simple threshold-based rules, and the reconfiguration of existing containers requires stopping and restarting them. To overcome these limitations this paper presents KOSMOS, a novel autoscaling solution for Kubernetes. Containers are individually controlled by control-theoretical planners that manage container resources onthe-fly (vertical scaling). A dedicated component is in charge of handling resource contention scenarios among containers deployed in the same node (a physical or virtual machine). Finally, at the cluster-level a heuristicbased controller is in charge of the horizontal scaling of each application.
引用
收藏
页码:821 / 829
页数:9
相关论文
共 13 条
[1]  
[Anonymous], IN PLACE UPDATE RESO
[2]  
[Anonymous], STATE ENTERPRISE OPE
[3]  
[Anonymous], KUBERNETES VPA
[4]  
[Anonymous], 2014, Advanced Science and Technology Letters, DOI DOI 10.14257/ASTL.2014.66.25
[5]  
[Anonymous], KUBERNETES 1 20 CHAN
[6]  
[Anonymous], KUBERNETES LOGGING A
[7]   Adaptive scaling of Kubernetes pods [J].
Balla, David ;
Simon, Csaba ;
Maliosz, Markosz .
NOMS 2020 - PROCEEDINGS OF THE 2020 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2020: MANAGEMENT IN THE AGE OF SOFTWARIZATION AND ARTIFICIAL INTELLIGENCE, 2020,
[8]   COCOS: a Scalable Architecture for Containerized Heterogeneous Systems [J].
Baresi, Luciano ;
Quattrocchi, Giovanni .
IEEE 17TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2020), 2020, :103-113
[9]  
Felter W, 2015, INT SYM PERFORM ANAL, P171, DOI 10.1109/ISPASS.2015.7095802
[10]  
Kubernetes HPA, US