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Wide Area Network Autoscaling for Cloud Applications

Published: 23 August 2021 Publication History

Abstract

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.

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cover image ACM Conferences
NAI'21: Proceedings of the ACM SIGCOMM 2021 Workshop on Network-Application Integration
August 2021
77 pages
ISBN:9781450386333
DOI:10.1145/3472727
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 August 2021

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Author Tags

  1. Autoscaling
  2. Cloud Computing
  3. Kubernetes
  4. Network-Application Interface
  5. Wide Area Networks

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  • Article
  • Research
  • Refereed limited

Funding Sources

  • MINECO
  • Catalan Institution for Research and Advanced Studies (ICREA)

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SIGCOMM '21
Sponsor:
SIGCOMM '21: ACM SIGCOMM 2021 Conference
August 23, 2021
Virtual Event, USA

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NAI'21 Paper Acceptance Rate 12 of 24 submissions, 50%;
Overall Acceptance Rate 12 of 24 submissions, 50%

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