International Business Machines Corporation

Daniel Charles Birkestrand

Peter Joseph Heyrman

Terry Lyle Schardt

Edward Curtis Prosser

Paul F Olsen

Randall Lane Grimm

David Otto Lewis

Wade Byron Ouren

Stephanie L Jensen

Techniques are provided for providing computing resources from a pool a plurality of networked computing systems to a consumer. The method includes determining that the consumer's resource usage exceeds a predetermined threshold. After a predetermined period of time, and upon determining that the consumer's resource usage continues to exceed the predetermined threshold, the method identifies one or more computing systems from the pool having capacity to host at least part of the amount of excess resource usage. The method further includes allocating resources on one or more computing systems selected from the identified computing systems to satisfy the amount of excess resource usage, and transferring at least the amount of excess resource usage to the selected one or more computing systems.

Management of unreturned system pool resources

Workload, preferably as one or more partitions, is migrated from a source server to one or more target servers by computing a respective projected performance optimization for each candidate partition and target, the optimization being dependent on a projected processor-memory affinity resulting from migrating candidate workload to the candidate target, and selecting a target to receive a workload accordingly. A target may be pre-configured to receive a workload being migrated to it by altering the configuration parameters of at least one workload currently executing on the target according to the projected performance optimization.

Optimization of computer system logical partition migrations in a multiple computer system environment

Optimized placement of virtual machines in a cloud environment is based on factors that include processor-memory affinity. A smart migration mechanism (SMM) predicts an optimization score for multiple permutations of placing virtual machines on a target system to create an optimal move list. The optimization score is a theoretical score calculated using dynamic platform optimization (DPO). The SMM may allow the user to set initial parameters and change the parameters to create potential changes lists. The move lists are ranked to allow the user to select the optimal change list to provide the best affinity, quickest fulfillment of requirements and least disruption for a given set of parameters.

Virtual machine placement in a cloud computing environment based on factors including optimized processor-memory affinity

In a computer system that includes multiple nodes and multiple logical partitions, a dynamic partition manager computes current memory affinity and potential memory affinity to help determine whether a reallocation of resources between nodes may improve memory affinity for a logical partition or for the computer system. If so, the reallocation of resources is performed so memory affinity for the logical partition or computer system is improved. Memory affinity is computed relative to the physical layout of the resources according to a hardware domain hierarchy that includes a plurality of primary domains and a plurality of secondary domains.

Dynamically improving memory affinity of logical partitions

Method, apparatus and article of manufacture for on-demand access to computerized resources. A resource-time value includes a resource-identifying component and a usage limit component. The resource-identifying component specifies a given type of a resource and the usage limit component defines a maximum allowable usage value of the resource on the basis of time and quantity. Upon verifying the resource-time value, a quantity of the resource is enabled. The enabled resources may then be placed into service for specified time periods, wherein the quantity of resources placed into service and the time periods are delimited by the usage limit component.

Method to provide on-demand resource access

A capacity manager provides temporary resources on demand in a manner that assures the temporary resources may be recovered when the specified resource-time expires. Access to minimum resource specifications corresponding to the logical partitions is controlled to prevent the sum of all minimum resource specifications from exceeding the base resources on the system. By assuring the sum of minimum resource specifications for all logical partitions is satisfied by the base resources on the system, the temporary resources may always be recovered when required.

Assuring recovery of temporary resources in a logically partitioned computer system

A method, apparatus, system, and signal-bearing medium that, in an embodiment, determine whether an amount of usage of a resource, which is used under a temporary usage plan, exceeds a threshold. If that determination is true, a quantity of the resource is calculated and that quantity is converted from the temporary usage plan to a permanent usage plan, without further charge to the customer. In another embodiment, a different resource may be converted to the permanent usage plan than the resource that was temporarily used. In various embodiments, the calculation of the quantity is made based on an attribute of the computer that uses the resource or based on an activation code received from the provider of the resource. In various embodiments, the amount of the usage is either a time amount of use or a monetary amount charged for the resource under the temporary usage plan. In various embodiments, the quantity of the resource converted is based on a ratio of a number of permanent resources in use to a total number of resources, based on an attribute of the computer, based on the cost of the computer, based on the age of the computer, based on a speed of the resource, or based on the amount of resources in the computer.

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Rochester, MN, United States of America

Daniel Charles Birkestrand