A Cost Effective Cloud Datacenter Capacity Planning Method Based on Modality Cost Analysis

In resource provisioning for datacenters, an important
issue is how resources may be allocated to an application such that
the service level agreements (SLAs) are met. Resource provisioning
is usually guided by intuitive or heuristic expectation of performance
and existing user model. Provisioning based on such methodology,
however, usually leads to more resources than are actually
necessary. While such overprovisioning may guarantee performance,
this guarantee may come at a very high cost. A quantitative
performance estimate may guide the provider in making informed
decisions about the right level of resources, so that acceptable
service performance may be provided in a cost-effective manner. A
quantitative estimate of application performance must consider its
workload characteristics. Due to the complex workload
characteristics of commercial software, estimation of its performance
and provisioning to optimize for cost is not straightforward. In this
work we looked at breaking the application into isolated modalities
(modality is a scenario in which an application is used, for example,
instant messaging, and voice calls are two different modalities of a
media application) and measuring resource cost per modality as an
effective methodology to provision datacenters to optimize for
performance and minimize cost. When breaking the application into
modalities, resource cost is assessed in isolation. Results are then
aggregated to estimate the overall resource provisioning
requirements. A validation tool is used to simulate the load and
validate the assumptions. This was applied to a commercially
available solution and validated in a datacenter setting.