Abstract: A processor from an introspection daemon running on a virtual machine can receive an introspection report comprising configuration state data of the virtual machine. The virtual machine can comprise a guest operating system hosting the introspection daemon. The configuration state data can comprise an execution state of an application running on the guest operating system of the virtual machine. The processor can generate a virtual machine image of the virtual machine in view of the introspection report. The processor can further initiate a migration of the virtual machine to at least one target cloud in view of the virtual machine image.

Abstract: Embodiments relate to systems and methods for a self-moving operating system installation in cloud-based network. A host cloud in which a guest operating system operates can be identified by a processor. A set of applications in a host cloud can be instantiated, where each of the set of applications is operated using the guest operating system. Information related to an operation of a first application of the set of applications can be received from the host cloud. The processor can update data related to the operation of the guest operating system using the received information.

Abstract: Embodiments relate to systems and methods for a self-moving operating system installation in cloud-based network. A guest operating system can be instantiated in a cloud-based host environment to support a set of virtual machines. The operating system can be configured with resources in the kernel to detect and manage the identity of the cloud in which the operating system is installed, as well as to interrogate potentially new target host clouds to determine the configuration settings required to move or copy the guest operating system to that target. The resulting mobility of the guest operating system affords the ability to be self-moving, and an administrator or other user can simply specify a desired target cloud to host the operating system without a need to manually configure APIs or other resources.

Abstract: A kernel of a guest operating system receives a cloud identifier that identifies a host cloud in which the guest operating system is installed. The kernel determines duration information indicative of a length of time the guest operating system operates in the host cloud. The kernel stores the cloud identifier and the duration information in a kernel hosting record of the kernel of the guest operating system.

Abstract: Embodiments relate to systems and methods for tracking cloud installation information using a cloud-aware kernel of operating system. A guest operating system can be hosted in a cloud-based network which to support a set of virtual machines operating in that set of host clouds. The guest operating system can be configured with resources in the kernel to detect and manage the identity of the cloud in which the operating system is installed, as well as the duration of operation of the operating system and potentially, usage and other details of the set of virtual machines and their associated guest operating systems. Because the cloud identification and other data capture occurs directly in a cloud-aware kernel of the guest operating system, security and responsiveness are enhanced. The resulting set of kernel hosting data can be securely exported to a metering system or other platform for billing or other purposes.

Abstract: A processor from an introspection daemon running on a virtual machine can receive an introspection report comprising configuration state data of the virtual machine. The virtual machine can comprise a guest operating system hosting the introspection daemon. The configuration state data can comprise an execution state of an application running on the guest operating system of the virtual machine. The processor can generate a virtual machine image of the virtual machine in view of the introspection report. The processor can further initiate a migration of the virtual machine to at least one target cloud in view of the virtual machine image.

Abstract: Embodiments relate to systems and methods for generating multi-cloud incremental billing capture and administration. A set of aggregate usage history data can store patterns for a user in a set of host clouds recording consumption of processor, memory, storage, operating system, or other resources subscribed to by the across the host clouds. The user can be a corporation or other collective user. An entitlement engine can access a set of subscription parameters and analyze the set of aggregate usage history data based on deviation from consumption limits or other subscription parameters. When resource limits (e.g. operating system instances) are exceeded in a host cloud, the entitlement engine can determine which resource was exceeded, and in which host cloud it was exceeded. Incremental billing for those events can be generated by the entitlement engine, and transmitted to the user via the host cloud and/or resource provider for presentation, collection, and reconciliation.

Abstract: Embodiments relate to systems and methods for introspective application reporting to facilitate virtual machine movement between cloud hosts. A set of aggregate usage history data can record consumption of processor, software, or other resources subscribed to by one or more users in a or clouds. A cloud management system can host a cloud-based operating system which can support a set of virtual machines via a set of guest operating systems that are virtualized in the operating system. One or more of the virtual machines can be configured with an introspection daemon which is configured to inspect the application set and configuration state of the associated virtual machine. The introspection daemon can generate an introspection report containing application inventories, execution states, and other information and transmit that report to the kernel of the cloud-based operating system.

Abstract: A policy management tool can access a set of usage history data for a set of resources consumed by the workload and generate a migration policy stack in view of a set of user-selected policy parameters, wherein the set of user-selected policy parameters comprises a set of multiple selectable inputs, and the migration policy stack comprises a set of one or more migration policies. The policy management tool can evaluate the set of one or more workload migration policies in view of the set of usage history data to configure a migration of the workload, and schedule the migration of the workload in view of the evaluating.

Abstract: Implementations relate to accessing a set of usage history data associated with a user account operating a workload on a set of virtual machines in a default deployment, generating, by a hardware processor, a predictive workload associated with the user account in view of the set of usage history data associated with the user account, responsive to generating the predictive workload, identifying a set of available resources in a set of host clouds of virtual machines provided by a cloud provider over the first period of time, accessing a set of deployment criteria received from the cloud provider, and generating a set of subscription parameters in view of the predictive workload, the set of available resources, and the set of deployment criteria to migrate the predictive workload to the set of host clouds of virtual machines.

Abstract: A processor accesses usage history data, which includes subscription events for a virtual machine, and generates translatable time periods to which the subscription events can be assigned. Each of the translatable time periods is temporally shifted and each of the subscription events is assigned to one or more translatable time periods. The processor generates translation outcomes for a user of the virtual machine for the translatable time periods in view of assigned subscription events. The translation outcomes include an identified change in subscription costs of the user over the translatable time periods. The processor identifies a translated base period from the translatable time periods for which the subscription parameters will be applied to the usage history data in view of applying selection criteria to the translation outcomes and tracks resource usage of the user in view of the identified translated base period to determine an alternate set of subscription costs.

Abstract: A policy management tool can access a set of usage history data for a set of resources consumed by the workload and generate a migration policy stack in view of a set of user-selected policy parameters, wherein the set of user-selected policy parameters comprises a set of multiple selectable inputs, and the migration policy stack comprises a set of one or more migration policies. The policy management tool can evaluate the set of one or more workload migration policies in view of the set of usage history data to configure a migration of the workload, and schedule the migration of the workload in view of the evaluating.

Abstract: Embodiments relate to systems and methods for a self-moving operating system installation in cloud-based network. A guest operating system can be instantiated in a cloud-based host environment to support a set of virtual machines. The operating system can be configured with resources in the kernel to detect and manage the identity of the cloud in which the operating system is installed, as well as to interrogate potentially new target host clouds to determine the configuration settings required to move or copy the guest operating system to that target. The resulting mobility of the guest operating system affords the ability to be self-moving, and an administrator or other user can simply specify a desired target cloud to host the operating system without a need to manually configure APIs or other resources.

Abstract: Embodiments relate to systems and methods for triggering workload movement based on a policy stack having multiple selectable inputs. A set of aggregate usage history data can record consumption of processor, software, or other resources subscribed to by one or more users in a or clouds. An entitlement engine can analyze the usage history data to identify a subscription margin and other trends or data reflecting short-term consumption trends. An associated policy management tool can receive, build, and update a migration policy stack containing a set of configurable policies that can be applied to the conditions of the workload to determine whether, when, and where to migrate the workload or portions thereof to a new cloud host or hosts. In aspects, the policy stack can include user-selectable policy parameters, such as resource consumption thresholds and/or subscription time periods, which can dynamically vary and/or which can be expressed as functions of other policies or resource-consumption variables.

Abstract: Embodiments relate to systems and methods for a self-moving operating system installation in cloud-based network. A guest operating system can be instantiated in a cloud-based host environment to support a set of virtual machines. The operating system can be configured with resources in the kernel to detect and manage the identity of the cloud in which the operating system is installed, as well as to interrogate potentially new target host clouds to determine the configuration settings required to move or copy the guest operating system to that target. The resulting mobility of the guest operating system affords the ability to be self-moving, and an administrator or other user can simply specify a desired target cloud to host the operating system without a need to manually configure APIs or other resources.

Abstract: Embodiments relate to systems and methods for metering cloud resource consumption using multiple hierarchical subscription periods. A set of aggregate usage history data can record consumption of processor, software, or other resources subscribed to by a set of users, in one cloud or across multiple clouds. An entitlement engine can analyze the usage history data to identify a subscription margin for the subscribed resources, reflecting collective under-consumption of resources by the set of users on a collective basis, over different and/or dynamically updated subscription periods. In aspects, the entitlement engine or other logic can generate multiple hierarchical time periods or layers over which resource consumption can be tracked. For instance, processor usage can be tracked over blocks of two hours or other intervals, but can also be tracked over 24 hour intervals for which additional subscription costs, terms, or factors may apply.

Abstract: Embodiments relate to systems and methods for aggregating marginal subscription offsets in a set of multiple host clouds. A set of aggregate usage history data can record consumption of processor, memory, operating system, or other resources subscribed to by a user across multiple host clouds. An entitlement engine can analyze the aggregate usage history data to identify a short-term subscription margin for one or more subscribed resources, such as processor throughput, operating system instances, or other resources reflecting the under or over-consumption of a cloud resource against subscription limits on an hourly or other basis across multiple clouds. The entitlement engine can track the short-term subscription margin for one or multiple resources each hour of a day, and/or over other intervals, and determine the positive or negative subscription offset cost for each interval. The offsets can be combined to generate a net or aggregate subscription offset cost, or to provide other subscription adjustments.

Abstract: A processor accesses usage history data, which includes subscription events for a virtual machine, and generates translatable time periods to which the subscription events can be assigned. Each of the translatable time periods is temporally shifted and each of the subscription events is assigned to one or more translatable time periods. The processor generates translation outcomes for a user of the virtual machine for the translatable time periods in view of assigned subscription events. The translation outcomes include an identified change in subscription costs of the user over the translatable time periods. The processor identifies a translated base period from the translatable time periods for which the subscription parameters will be applied to the usage history data in view of applying selection criteria to the translation outcomes and tracks resource usage of the user in view of the identified translated base period to determine an alternate set of subscription costs.

Abstract: A method and system for managing cloud consumption including accessing a set of aggregate usage history data for a set of users each operating a set of machines consuming a set of resources in a host cloud, generating a set of variable consumption periods over which the consumption of the set of resources will be tracked for the set of users on a combined basis, identifying a set of subscription margins for a resource in the set of resources based on a comparison of the consumption of the resource to a resource subscription limit for the set of users on a combined basis over the set of variable consumption periods, generating a set of marginal consumption values for the set of users for a resource for the set of variable consumption periods in the host cloud, and generating a management action based on the marginal consumption value.

Abstract: Embodiments relate to systems and methods for managing subscribed resource limits in a cloud network using variable or instantaneous consumption tracking periods. A set of aggregate usage history data can record consumption of processor, memory, software, or other resources subscribed to by a user across multiple host clouds. An entitlement engine can analyze the usage history data to identify a subscription margin for the subscribed resources, reflecting under or over-consumption of cloud resources against subscription limits across multiple clouds. The entitlement engine can by default track the short-term subscription margin for one or multiple resources each hour of a day, and/or over other intervals. The entitlement engine can also generate a set of variable consumption periods over which to track the user's resource consumption, based on trends or conditions demonstrated in that consumption pattern.