Amazon Technologies, Inc.

Andrew C Becker

Alexandra Juliet Brasch

Abhinav Maurya

Kerem Bulbul

Casey Lucas Klein

April Nell Drees

Cicerone Cojocaru

Ruben Ruiz Garcia

Philip Charles Anderson

Techniques for host fleet management in a cloud provider network are described. Forecast data including a forecasted demand for virtual machines in each capacity pool of a set of capacity pools is obtained. A mathematical optimizer application is executed to generate a first optimal fleet plan, the mathematical optimizer application having an objective function to minimize a number of new host computer systems to add to the set of host computer systems to satisfy the forecasted demand for each capacity pool, the first optimal fleet plan includes an identification of a set of hardware types and, for each hardware type in the set, a quantity of new host computer systems of the hardware type. A plurality of new host computer systems is deployed, based on the first optimal fleet plan, for a hardware type in the set of hardware types into the set of host computer systems.

Host fleet management optimizations in a cloud provider network

Various embodiments are disclosed for predicting true demand of network services that impose usage constraints. A computing environment may be configured to provide a network service for a user account, where a usage constraint for the network service is imposed on the user account. A truncated usage distribution of the network service may be generated based on usage history data. A demand curve of the network service may be generated for the user account, where the demand curve comprises at least a portion of the truncated usage distribution and a predicted usage of the at least one network service beyond the usage constraint. One or more actions may be performed based on the demand curve, such as increasing the usage constraint.

Predicting true demand of network services with usage constraints

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Seattle, WA, United States of America

Andrew C Becker