Wide Area Network Autoscaling for Cloud Applications

被引:1
|
作者
Serracanta, Berta [1 ]
Paillisse, Jordi [1 ]
Claiborne, Anna [2 ]
Rodriguez-Natal, Alberto [3 ]
Ward, Dave [2 ]
Maino, Fabio [3 ]
Cabellos, Albert [1 ]
机构
[1] UPC BarcelonaTech, Barcelona, Spain
[2] PacketFabr, Los Angeles, CA USA
[3] Cisco, San Jose, CA USA
关键词
Autoscaling; Wide Area Networks; Kubernetes; Cloud Computing; Network-Application Interface;
D O I
10.1145/3472727.3472797
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Modern cloud orchestrators like Kubernetes provide a versatile and robust way to host applications at scale. One of their key features is autoscaling, which automatically adjusts cloud resources (compute, memory, storage) in order to adapt to the demands of applications. However, the scope of cloud autoscaling is limited to the datacenter hosting the cloud and it doesn't apply uniformly to the allocation of network resources. In I/O-constrained or data-in-motion use cases this can lead to severe performance degradation for the application. For example, when the load on a cloud service increases and the Wide Area Network (WAN) connecting the datacenter to the Internet becomes saturated, the application flows experience an increase in delay and loss. In many cases this is dealt with overprovisioning network capacity, which introduces additional costs and inefficiencies. On the other hand, thanks to the concept of "Network as Code", the WAN exposes a set of APIs that can be used to dynamically allocate and de-allocate capacity on-demand. In this paper we propose extending the concept of cloud autoscaling into the network to address this limitation. This way, applications running in the cloud can communicate their networking requirements, like bandwidth or traffic profile, to a Software-Defined Networking (SDN) controller or Network as a Service (NaaS) platform. Moreover, we aim to define the concepts of vertical and horizontal autoscaling applied to networking. We present a prototype that automatically allocates bandwidth to the underlay network, according to the requirements of the applications hosted in Kubernetes. Finally, we discuss open research challenges.
引用
收藏
页码:1 / 6
页数:6
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