Patent application number | Description | Published |
20110077997 | METHOD AND SYSTEM FOR CHARGEBACK ALLOCATION IN INFORMATION TECHNOLOGY SYSTEMS - The invention provides a system and method for chargeback cost allocation in an information technology (IT) system including multiple resources. The method includes categorizing cost attributes of different resources into multiple levels defining a cost attribute hierarchy, defining different chargeback groups for resources with similar cost attributes and chargeback policies at different levels of the hierarchy, and performing chargeback cost allocation by allocating the cost for resources at each hierarchy level independently using chargeback policies defined for the resources at that hierarchy level. | 03-31-2011 |
20110078695 | CHARGEBACK REDUCTION PLANNING FOR INFORMATION TECHNOLOGY MANAGEMENT - Reducing cost chargeback in an information technology (IT) computing environment including multiple resources, is provided. One implementation involves a process wherein resource usage and allocation statistics are stored for a multitude of resources and associated cost policies. Then, time-based usage patterns are determined for the resources from the statistics. A correlation of response time with resource usages and outstanding input/output instructions for the resources is determined. Based on usage patterns and the correlation, a multitude of potential cost reduction recommendations are determined. Further, a multitude of integrals are obtained based on the potential cost reduction recommendations, and a statistical integral is obtained based on the statistics. A difference between the statistical integral and each of the multiple integrals is obtained and compared with a threshold to determine potential final cost reduction recommendations. A final cost reduction recommendation is then selected from the potential cost reduction recommendations. | 03-31-2011 |
20110238672 | COST AND POWER EFFICIENT STORAGE AREA NETWORK PROVISIONING - Various embodiments for efficiently provisioning a storage area network (SAN) are provided. In one embodiment, SAN information is provided to an engine for optimization. The SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model. Based on the SAN information, those of an available plurality of storage resources not meeting at least one storage criterion are filtered. The filtered storage resources are ranked on a cost basis. A resource configuration graph is constructed based on the ranked storage resources. The resource configuration graph is traversed to obtain a plurality of possible SAN configuration plans. At least one power profile is applied to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption. | 09-29-2011 |
20120042055 | END-TO-END PROVISIONING OF STORAGE CLOUDS - Embodiments discussed in this disclosure provide an integrated provisioning framework that automates the process of provisioning storage resources, end-to-end, for an enterprise storage cloud environment. Such embodiments configure and orchestrate the deployment of a user's workload and, at the same time, provide optimization across a multitude of storage cloud resources. Along these lines, input is received in the form of workload requirements and configuration information for available system resources. Based on the input, a set (at least one) of storage cloud configuration plans is developed that satisfy the workload requirements. A set of scripts is then generated that orchestrate the deployment and configuration of different software and hardware components based on the plans. | 02-16-2012 |
20120047265 | PERFORMANCE ISOLATION FOR STORAGE CLOUDS - Embodiments of the present invention provide performance isolation for storage clouds. Under one embodiment, workloads across a storage cloud architecture are grouped into clusters based on administrator or system input. A performance isolation domain is then created for each of the clusters, with each of the performance isolation domains comprising a set of data stores associated with a set of storage subsystems and a set of data paths that connect the set of data stores to a set of clients. Thereafter, performance isolation is provided among a set of layers of the performance isolation domains. Such performance isolation is provided by (among other things): pooling data stores from separate performance isolation domains into separate pools; assigning the pools to device adapters, RAID controller, and the set of storage subsystems; preventing workloads on the device adapters from exceeding capacities of the device adapters; mapping the set of data stores to a set of Input/Output (I/O) servers based on an I/O capacity and I/O load of the set of I/O servers; and/or pairing ports of the set of I/O servers with ports of the set of storage subsystems, the pairing being based upon availability, connectivity, I/O load, and I/O capacity. | 02-23-2012 |
20120233310 | COMPREHENSIVE BOTTLENECK DETECTION IN A MULTI-TIER ENTERPRISE STORAGE SYSTEM - Embodiments of the present invention provide approaches (e.g., online methods) to analyze end-to-end performance issues in a multi-tier enterprise storage system (ESS), such as a storage cloud, where data may be distributed across multiple storage components. Specifically, performance and configuration data from different storage components (e.g., nodes) is collected and analyzed to identify nodes that are becoming (or may become) performance bottlenecks. In a typical embodiment, a set of components distributed among a set of tiers of an ESS is identified. For each component, a total capacity and a current load are determined. Based on these values, a utilization of each component is determined. Comparison of the utilization with a predetermined threshold and/or analysis of historical data allows one or more components causing a bottleneck to be identified. | 09-13-2012 |
20120254640 | ALLOCATION OF STORAGE RESOURCES IN A NETWORKED COMPUTING ENVIRONMENT BASED ON ENERGY UTILIZATION - Embodiments of the present invention provide an approach to provision storage resources (e.g., across an enterprise storage system (ESS) such as a general parallel file system (GPFS) or the like) for different workloads in an energy efficient manner. The system evaluates different energy profiles/workloads' energy consumption characteristics of storage devices to determine an allocation plan that reduces the energy cost (e.g., results in the lowest cost/energy consumption for handling a storage workload). In a typical embodiment, energy consumption characteristics for handling a particular storage workload will be determined. Thereafter, a type of storage device capable of handling the workload will be determined. Then, an allocation plan that results in the most efficient energy consumption for handling the workload will be developed. In general, the allocation plan is based upon the energy consumption characteristics and an energy efficiency algorithm. The energy efficiency algorithm serves to identify storage device(s) that can handle the workload in such a way as to reduce total energy consumption and, accordingly, costs. Along these lines, the energy efficiency algorithm may also consider other factors such as capacity and load of storage devices and service level agreement (SLA) terms in addition to energy costs (e.g., over times of day and/or days of week). In any event, at least one storage device can then be selected for handling the storage workload according to the allocation plan. | 10-04-2012 |
20120271678 | CHARGEBACK REDUCTION PLANNING FOR INFORMATION TECHNOLOGY MANAGEMENT - Minimizing cost chargeback in an information technology (IT) computing environment including multiple resources. One implementation involves determining time-based usage patterns and allocation statistics for a plurality of resources and associated resource workloads. Using a regression function for determining a correlation of response time with resource usages and outstanding input/output instructions for the plurality of resources. Based on the time-based usage patterns, allocation statistics and the correlation, deriving an interpolation using positive and negative integrals to minimize a difference between allocated resource values and average allocation values. Determining service level objectives (SLOs) and resource allocation for minimizing cost chargeback for the resource workloads based on the derived interpolation. | 10-25-2012 |
20140223012 | CLUSTER-AWARE RESOURCE PROVISIONING IN A NETWORKED COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for providing cluster-aware (storage) resource provisioning in a networked computing environment (e.g., a cloud computing environment) based upon policies, best practices, and/or storage cluster/environment configurations. In a typical embodiment, a set of characteristics (e.g., computing resources/components, etc.) of a storage environment will be determined. A set of requirements for a set of workloads to be processed by the components of the storage environment will then be identified. A set of policies and a set of best practices will then be determined to identify a configuration of the storage environment to optimize the processing of the set of workloads according to the set of requirements. Based on the configuration, a plan will be generated that indicates a data path through the set of computing resources that minimizes a potential for error in processing the set of workloads. | 08-07-2014 |