Abstract: The various embodiments may enable enterprise cloud based computing infrastructure to automatically scale cloud based applications in response to changing service demands. In at least one of the various embodiments, the monitoring application may collect operational and performance statistics about a cloud application from both internal and external monitors. In at least one of the various embodiments, a cloud application owner (user) may provide information to the system identifying one or more critical paths for one or more cloud applications. In at least one of the various embodiments, based on the monitoring data and the critical path information the cloud application scaling framework may determine the resource scaling and/or caching that may be appropriate for a monitored application.

Abstract: Embodiments may enable enterprise cloud based computing infrastructures to instantiate child virtual machines that may be linked to parent virtual machines where the child virtual machines and the parent virtual machines share storage that resides on a high-speed storage area network. Performance metrics of the child virtual machines may be monitored and collected for a period of time generating performance characteristics of the child virtual machines. In at least one of the various embodiments, if the monitoring period may have expired that child virtual machine may be moved to a storage pool that may be selected based on the performance characteristics of the child virtual machine. In at least one of the various embodiments, if the child virtual may be moved from the high-speed SAN to a storage pool the linked between the child virtual machine and the parent virtual machine may be broken.

Abstract: Embodiments may enable cloud based computing infrastructure to automatically scale in response to changing service demands. Auto-scaling may be enabled by automatically provisioning computing resources as they may be needed by hosted computing services. Historical utilization patterns may be tracked enabling the generation of models that may be employed to predict future computing resource requirements. The automatic scaling system may comprise one or more models that may be trainable using business rules that may be applied to determine to if and how computing resources are scaled. Further, business rules may be arranged to determine provisioning and scaling of computing resources based in part on the historical usage patterns of the computing services.

Abstract: The various embodiments may enable enterprise cloud based computing infrastructure to automatically scale cloud based applications in response to changing service demands. In at least one of the various embodiments, the monitoring application may collect operational and performance statistics about a cloud application from both internal and external monitors. In at least one of the various embodiments, a cloud application owner (user) may provide information to the system identifying one or more critical paths for one or more cloud applications. In at least one of the various embodiments, based on the monitoring data and the critical path information the cloud application scaling framework may determine the resource scaling and/or caching that may be appropriate for a monitored application.

Abstract: Embodiments may enable enterprise cloud based computing infrastructures to instantiate child virtual machines that may be linked to parent virtual machines where the child virtual machines and the parent virtual machines share storage that resides on a high-speed storage area network. Performance metrics of the child virtual machines may be monitored and collected for a period of time generating performance characteristics of the child virtual machines. In at least one of the various embodiments, if the monitoring period may have expired that child virtual machine may be moved to a storage pool that may be selected based on the performance characteristics of the child virtual machine. In at least one of the various embodiments, if the child virtual may be moved from the high-speed SAN to a storage pool the linked between the child virtual machine and the parent virtual machine may be broken.

Abstract: Embodiments may enable cloud based computing infrastructure to automatically scale in response to changing service demands. Auto-scaling may be enabled by automatically provisioning computing resources as they may be needed by hosted computing services. Historical utilization patterns may be tracked enabling the generation of models that may be employed to predict future computing resource requirements. The automatic scaling system may comprise one or more models that may be trainable using business rules that may be applied to determine to if and how computing resources are scaled. Further, business rules may be arranged to determine provisioning and scaling of computing resources based in part on the historical usage patterns of the computing services.