Abstract: Partitioning execution of a program between a client device and a cloud of network resources, exploits the asymmetry between the computational and storage resources of the cloud and the resources and proximity of the client access device to a user. Programs may be decomposed into work units. Those work units may be profiled to determine execution characteristics, modeled based on current state information and the profile, and a model performance metric (MPM) generated. Based on the MPM, work units may be partitioned between the client and the cloud.

Abstract: Deployment and execution of a service in a multiple datacenter environment may be facilitated using datacenter execution templates. Developers, business managers, and other interested parties may select and/or modify a declarative execution template embodying multiple factors. The execution template may then be used to generate an execution plan, which is then executed by datacenters which run the service. The execution template may be optimized after deployment of the service, allowing for ongoing adjustment in response to changing business, regulatory, and operational factors.

Abstract: An exemplary matching module includes instructions for receipt of information about sellable resources for running web-based services; for a solver for minimizing or maximizing a function subject to constraints; and for output of cost information for purchasing or buying sellable resources for running web-based services where the cost information is based at least in part on minimizing or maximizing the function. An exemplary matching module may be configured to receive information in a domain-specific language. Other methods, devices and systems are also disclosed.

Abstract: Partitioning execution of a program between a client device and a cloud of network resources, exploits the asymmetry between the computational and storage resources of the cloud and the resources and proximity of the client access device to a user. Programs may be decomposed into work units. Those work units may be profiled to determine execution characteristics, modeled based on current state information and the profile, and a model performance metric (MPM) generated. Based on the MPM, work units may be partitioned between the client and the cloud.

Abstract: Deployment and execution of a service in a multiple datacenter environment may be facilitated using datacenter execution templates. Developers, business managers, and other interested parties may select and/or modify a declarative execution template embodying multiple factors. The execution template may then be used to generate an execution plan, which is then executed by datacenters which run the service. The execution template may be optimized after deployment of the service, allowing for ongoing adjustment in response to changing business, regulatory, and operational factors.