loading page

A framework for cost, profit, and pricing evaluation of cloud native CPU resources
  • +3
  • Federico Tonini ,
  • Carlos Natalino ,
  • Dagnachew Temesgene ,
  • Zere Ghebretensaé ,
  • Lena Wosinska ,
  • Paolo Monti
Federico Tonini
Chalmers University of Technology

Corresponding Author:[email protected]

Author Profile
Carlos Natalino
Author Profile
Dagnachew Temesgene
Author Profile
Zere Ghebretensaé
Author Profile
Lena Wosinska
Author Profile
Paolo Monti
Author Profile

Abstract

Online service provisioning involves two main entities, i.e., cloud providers renting cloud resources to service providers. In this process, the service provider would like to minimize its costs, while the cloud providers seek ways to increase their profit. Novel container orchestration platforms like Kubernetes allow deploying services on the same physical or virtual (e.g., virtual machines) infrastructure while delivering both hard and soft resource isolation. When the soft resource isolation is allowed, guaranteed (or request) resources of one service can be used (if idle) by another one as limit resources, for short time intervals in a best-effort manner. The use of limit resources represents an extra font of revenue for the cloud provider to charge different service providers for the same resources. At the same time, soft isolation allows service providers to decrease the number of request resources and rely on more limit resources, paid only when accessed, reducing the overall resources needed. Therefore, soft resource isolation has potential benefits for both cloud and service providers. To enable these benefits, the price of limit resources should be carefully set by the cloud provider to generate, on one hand, extra profits and, on the other, be appealing to service providers. This paper proposes a framework for evaluating the pricing window for the limit resources under which it is possible to reduce the cost for service providers and increase the profits of cloud providers. Results in a sample simulated scenario show that by pricing limit resources within six to twelve times the request resources, cloud and service providers can achieve financial gains in the order of 10%-20%.