Abstract:
The described implementations relate to processing of electronic data. One implementation is manifest as one or more computer-readable storage devices comprising instructions which, when executed by one or more processing devices, cause the one or more processing devices to perform acts. The acts can include determining service levels provided by multiple network configurations, determining costs associated with the multiple network configurations, and evaluating the multiple network configurations based on both the costs and the service levels. The multiple network configurations can include redundantly-deployed devices. Furthermore, some implementations may determine cost/service level metrics that can be used to compare devices based on expected costs to provide a particular service level.
Abstract:
The described implementations relate to processing of electronic data. One implementation is manifest as a system that can include an event analysis component and one or more processing devices configured to execute the event analysis component. The event analysis component can be configured to obtain events from event logs, the events reflecting failures by one or more network devices in one or more data centers and characterize a service level of an application or a network device based on the events. For example, the event analysis component can be configured to characterize the availability of an application based on one or more network stamps of the application.
Abstract:
A system for managing allocation of resources based on service level agreements between application owners and cloud operators. Under some service level agreements, the cloud operator may have responsibility for managing allocation of resources to the software application and may manage the allocation such that the software application executes within an agreed performance level. Operating a cloud computing platform according to such a service level agreement may alleviate for the application owners the complexities of managing allocation of resources and may provide greater flexibility to cloud operators in managing their cloud computing platforms.
Abstract:
This patent application relates to an agile network architecture that can be employed in data centers, among others. One implementation provides a virtual layer-2 network connecting machines of a layer-3 infrastructure.
Abstract:
The described implementations relate to energy-aware server management. One implementation involves an adaptive control unit configured to manage energy usage in a server farm by transitioning individual servers between active and inactive states while maintaining response times for the server farm at a predefined level.
Abstract:
Described are performance-based pricing models for pricing execution of a client job in a cloud service. Client-provided performance-related parameters are used to determine a price. The price may be a minimum bid price that is evaluated against a bid received from client bidder to accept or reject the bid. Alternatively, the price may be returned as a quote. For batch application-type jobs, performance parameters include a work volume parameter and a deadline or the like. For an interactive-type application job, example performance-related parameters may include an average load parameter, a peak load parameter, an acceptance rate parameter, a minimum capacity parameter, a maximum capacity parameter, and/or a time window parameter over which load is specified.
Abstract:
One or more computers manage power consumption in a plurality of computers by repeatedly evaluating power consumption of pluralities of computers such that any given plurality of computers is evaluated by aggregating indicia of power consumption of the individual computers in the given plurality. The evaluation identifies or predicts pluralities of computers that are over-consuming power and identifies pluralities of computers that are under-consuming power. A first plurality of computers identified as over-consuming power are sent messages to instruct some of its comprising computers or virtual machines (VMs) to lower their computational workload. A second plurality of computers identified as under-consuming power are sent messages instructing the other computers to increase their computation workload.