Abstract: A method and associated systems for using complexity probability to plan a physical datacenter relocation. One or more processors receive descriptions of each entity to be relocated, each of which is identified by a classification and by a tier that is associated with a level of complexity. Normalized random numbers are generated for each classification/tier combination and are each associated with a relocation scenario in which random complexity has a distinct amount of effect on the duration of time needed to relocate entities of the corresponding classification and tier. These numbers are then used to identify probable relocation times, each associated with one scenario, one classification, and one amount of complexity effect. These probable relocation times are then organized by classification so as to identify complexity-compensated probabilities that relocating all entities of a particular classification will require a specific duration of time.

Abstract: The invention comprises a computer-implemented process for managing computing resources provided to customers in an on-demand data center. The process comprises: providing a shared computing environment; providing to each customer one or more logical partitions of computing resources within the shared computing environment; allocating at least one processing engine to each logical partition; modeling a selected customer's resource utilization as a beta distribution; iteratively selecting a random resource utilization value from the beta distribution and, for each logical partition, calculating a processing engine differential; for each iteration, calculating a collective processing engine differential until the collective processing engine differential converges on an optimal processing engine differential; and adjusting the number of processing engines by the optimal processing engine differential to achieve an optimal free pool size.

Abstract: The invention comprises a computer-implemented process for managing computing resources provided to customers in an on-demand data center. The process comprises: providing a shared computing environment; providing to each customer one or more logical partitions of computing resources within the shared computing environment; allocating at least one processing engine to each logical partition; modeling a selected customer's resource utilization as a beta distribution; iteratively selecting a random resource utilization value from the beta distribution and, for each logical partition, calculating a processing engine differential; for each iteration, calculating a collective processing engine differential until the collective processing engine differential converges on an optimal processing engine differential; and adjusting the number of processing engines by the optimal processing engine differential to achieve an optimal free pool size.

Abstract: The invention is a system for installing a new operating system on a logical partition that has no existing software or data. The system comprises a baseline code and a process for customizing and configuring the baseline code for use in an on-demand environment. The process for customizing and configuring the baseline code comprises establishing a plurality of datasets that allow users to access the operating system after installation. The critical datasets that produce an operable system include virtual telecommunications parameters, job entry system parameters, operating system parameters, and security parameters.

Abstract: A method is disclosed for managing the performance of shared computing resources in furtherance of delivering on-demand IT services to multiple customers. The inventive method comprises predicting the performance of resources allocated among the customers to minimize performance related problems; preventing performance related problems by evaluating the impact of changes in resource allocations; reacting to performance alerts to resolve performance related problems; and determining the appropriate level of resource performance needed in service level agreements, and that these requirements detailed in the service level agreements are achieved. This Performance Management method ensures that the demands of the customers are not affected by the allocation and utilization of the shared IT resources.

Abstract: An example of a solution provided here comprises: providing a shared platform that is prepared to accept an incoming customer; for the incoming customer (a) planning a configuration of hardware, software, and network components; (b) designing the configuration; and (c) utilizing at least one configuration management control point; accepting the incoming customer, among multiple customers, on the shared platform; sharing hardware and software, among the multiple customers; and maintaining information concerning the shared platform.

Abstract: A system and method is disclosed for managing information technology resources to provide processing capacity to multiple customers with varying requirements in a shared computing environment. The inventive process comprises producing and maintaining a capacity plan that allocates capacity resources, handling requests for additional capacity resources, and analyzing requests for additional capacity resources to identify issues that should be resolved in future allocations.