A framework for cost, profit, and pricing evaluation of cloud native CPU
resources
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%.