Abstract: Tasks of a group are respectively assigned to devices for execution. For each task, a completion time for a task is determined based on an associated cluster of the device to which the task has been assigned for execution is determined. If the completion time of a task exceeds an execution window of the device to which the task has been assigned, the task is removed from the group. The tasks remaining in the group are executed on the devices to which the tasks have been assigned for execution.

Abstract: Tasks of a group are respectively assigned to devices for execution. For each task, a completion time for a task is determined based on an associated cluster of the device to which the task has been assigned for execution is determined. If the completion time of a task exceeds an execution window of the device to which the task has been assigned, the task is removed from the group. The tasks remaining in the group are executed on the devices to which the tasks have been assigned for execution.

Abstract: Systems and methods are described for creating a personalized capacity planning scenario using a reusable capacity planning scenario template. In accordance with one method, a system topology model can be maintained. The system topology model includes tags describing components and constraints on components within the system topology. The tags can be compared with a plurality of reusable capacity planning scenario templates. The capacities of the components can be identified based on at least one of topology and services executing on the components. At least a portion of the system topology model can be replaced with a reusable capacity planning scenario template based on the identified capacities. An impact of the replacement of the at least a portion of the system topology model can be evaluated. A scenario recommendation can be made to an administrator based on the impact.

Abstract: Systems and methods are described for creating a capacity planning scenario. In one example, a method includes maintaining a topology model of computing resources in a configuration management database. A workload model of workload constraints for workloads put on the computing resources is also maintained. The constraints include limits on at least one of how, when, and where the workload may be used with regards to the computing resources. A service model of business services for workloads put on the computing resources can also be maintained. The service model can include relationships between workloads and demand traces. Constraint tags can be assigned to computing resources within the topology model, workload model, and service model. The constraint tags can include information about topology relationships, workload constraints, and service model services. A capacity planning scenario can be generated for the business services, workloads, and resources based on the assigned constraint tags.

Abstract: Systems and methods are described for creating a reusable capacity planning scenario template. In one example, a method includes maintaining a system topology model of resources in a configuration management database. The topology model can include at least one computing device and at least one facility in which the computing device is used. The method can include assigning minimum and maximum constraint values to resources within the system topology. The constraints can be maximal or minimal limits on at least one of how, when, and where workloads may be used with regards to the resources. The method can further include identifying resources within the system topology model to include in the reusable capacity planning scenario template. The identified resources can be projected into a data mart. The reusable capacity planning scenario template can be created using a scenario planner based on the topology model and constraints of the identified resources in the data mart.