Abstract: A system and method for configuring a cloud service center is described. The system accesses usage data of resources of the cloud service center. The usage data is standardized by applying a pre-processing operation to the usage data. The system generates a plurality of forecast models based on the standardized usage data. The forecast models predict a demand of the resources of the cloud service center. The system selects a demand forecast model from the forecast models based on a ranking of the forecast models. The system applies a postprocessing operation to the demand forecast that is generated based on the selected demand forecast model. The system configures the cloud service center based on the post-processed demand forecast.

Abstract: Techniques for capacity management in computing systems are disclosed herein. In one embodiment, a method includes analyzing data representing a number of enabled users or a number of provisioned users to determine whether the analyzed data represents an anomaly based on historical data. The method can also include upon determining that the data represents an anomaly, determining a conversion rate between a change in the number of enabled users or the number of provisioned users and a change in a number of active users of the computing service and deriving a future value of the number of active users of the computing service based on both the detected anomaly and the determined conversion rate. The method can further include allocating and provisioning an amount of the computing resource in the distributed computing system in accordance with the determined future value of the active users of the computing resource.