Abstract: Embodiments relate to systems and methods for detecting resource consumption events over sliding intervals in cloud-based network. 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.

Abstract: Embodiments relate to systems and methods for a cloud deployment engine for selective workload migration or federation based on workload conditions. 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 deployment engine can analyze the short-term consumption trends, and generate a decision to either deploy any over-subscribed resources to a set of federated backup clouds, or to one or more new host clouds. In aspects, the decision to augment the capacity of the host cloud with either a cloud federation or a complete host cloud replacement can be based on a set of selection criteria, including the margin by which the resources are over-subscribed and/or whether the over-subscription is static, increasing or accelerating, among others.

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 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: Embodiments relate to systems and methods for detecting resource consumption events over sliding intervals in cloud-based network. 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, an associated scheduling engine can.

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 cloud deployment engine for selective workload migration or federation based on workload conditions. 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 deployment engine can analyze the short-term consumption trends, and generate a decision to either deploy any over-subscribed resources to a set of federated backup clouds, or to one or more new host clouds. In aspects, the decision to augment the capacity of the host cloud with either a cloud federation or a complete host cloud replacement can be based on a set of selection criteria, including the margin by which the resources are over-subscribed and/or whether the over-subscription is static, increasing or accelerating, among others.

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: Embodiments relate to systems and methods for generating optimized resource consumption periods for multiple users on a combined basis. 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/over-consumption of cloud resources by the users against subscription limits. The entitlement engine can track the short-term subscription margin for one or multiple resources over hours of a day, or over other intervals. The entitlement engine can thereby generate a set of variable or dynamic consumption periods over which to track the resource consumption, based on trends or conditions demonstrated in that consumption pattern by the set of users on a combined basis.

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 generating a marketplace brokerage exchange of excess subscribed resources using dynamic 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 set of estimated resource contributions of different users can be aggregated over one or more dynamic resource contribution intervals to generated a bundled brokerage resource tender, in which the processor, operating system, and/or other resources of multiple users are combined to be offered to a cloud marketplace for one or more contribution interval.

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 generating dynamically configurable subscription parameters for the temporary migration of predictive user workloads in a cloud network. Aspects relate to platforms and techniques for analyzing overnight or other off-peak or temporary deployments of user workloads to underutilized host clouds. A cloud management system can capture usage history data for a user operating in a default deployment, such as a premise/cloud mix. A deployment engine can determine the resources required for the user's workload pattern, and examine corresponding resources available in a set of other geographically-dispersed host clouds. The host clouds can comprise clouds based in different time zones, so that cloud capacity during U.S. West Coast evening time or European overnight hours can be packaged and offered to U.S. East Coast users at reduced rates.

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.

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.