Abstract: The present invention provides an approach for automatic storage planning and provisioning within a clustered computing environment (e.g., a cloud computing environment). The present invention will receive planning input for a set of storage area network volume controllers (SVCs), the planning input indicating a potential load on the SVCs and its associated components. Configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load.

Abstract: Embodiments of the invention relate to creating and maintaining consistent data sets in a shared pool of configurable computer resources to support disaster recovery support. Data from an application is stored in local data storage and replicated to another data storage. A consistency point of the data is created in both of the data storage, with the consistency point representing an identical data set at a point-in-time. Based upon the created consistency points, a consistent set of application data may be requested to support a read operation for a migrated application.

Abstract: Embodiments of the invention relate to creating and maintaining consistent data sets in a shared pool of configurable computer resources to support disaster recovery support. Data from an application is stored in local data storage and replicated to another data storage. A consistency point of the data is created in both of the data storage, with the consistency point representing an identical data set at a point-in-time. Based upon the created consistency points, a consistent set of application data may be requested to support a read operation for a migrated application.

Abstract: A method, computer readable storage medium and computer system for controlling the allocation of data to one of a plurality of storage units of a storage system, the method comprising: accessing a source storage unit comprising the data; gathering file system level (FS-level) metadata from the source storage unit; analyzing the gathered FS-level metadata for determining if the data should be moved to one of the other storage units, said other storage unit acting as a destination storage unit; and in case the data should be moved, displaying an indication of the destination storage unit and/or automatically moving the data to the determined destination storage unit.

Abstract: Embodiments of the present invention provide lifecycle storage management for data within a Cloud computing environment. Specifically, a set of policies can be defined that allow for automatic valuation of the data and migration of the data between a set of storage tiers. Before a policy set is deployed, it can be assessed to determine effects it will have on cost, performance, and data location. Based on data characteristics and access patterns, a set of policy recommendations can be provided that predict the value of the data over time, and offer an improved migration strategy for moving the data between the set of storage tiers as the value of the data changes.

Abstract: Embodiments of the present invention provide an approach for intelligent storage planning and planning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will first determine/identify a set of storage area network volume controllers (SVCs) that is accessible from a host that has submitted a request for access to storage. Thereafter, a set of managed disk (mdisk) groups (i.e., corresponding to the set of SVCs) that are candidates for satisfying the request will be determined. This set of mdisk groups will then be filtered based on available space therein, a set of user/requester preferences, and optionally, a set of performance characteristics. Then, a particular mdisk group will be selected from the set of mdisk groups based on the filtering.

Abstract: The present invention provides an approach for automatic storage planning and provisioning within a clustered computing environment (e.g., a cloud computing environment). The present invention will receive planning input for a set of storage area network volume controllers (SVCs), the planning input indicating a potential load on the SVCs and its associated components. Configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load.

Abstract: Management of a planner through use of a middleware layer. A computer system is configured with the middleware layer in communication with both a planner and a data repository. One or more modules are provided in the middleware layer to support the functionality of the planner. Application program interface calls are employed to call the modules, thereby mitigating duplication of the functionality in separate planners.

Abstract: An incompatible software level of an information technology infrastructure component is determined by comparing collected inventory information to a minimum recommended software level. If a knowledge base search finds that the incompatible software level is associated with a prior infrastructure outage event, an outage count score is determined for the incompatible software level by applying an outage rule to a historic count of outages caused by a similar incompatible software level, and combined with an average outage severity score assigned to the incompatible software level based on a level of severity of an actual historic failure of the component within a context of the infrastructure to generate a normalized historical affinity risk score. The normalized historical affinity risk score is provided for prioritizing the correction of the incompatible software level in the context of other normalized historical risk level scores of other determined incompatible software levels.

Abstract: A method and system for intelligent tiering is provided. The method includes receiving a request for enabling a tiering process with respect to data. The computer processor retrieves a migration list indicating migration engines associated with the data. Additionally, an entity list of migration entities is retrieved and each migration entity is compared to associated policy conditions. In response, it is determined if matches exist between the migration entities and the associated policy conditions and a consolidated entity list is generated.

Abstract: Computing resource allocation for map-reduce job execution comprises determining the volume of input data to the map-phase and the reduce-phase of a map-reduce job prior to execution. Based on said determination, data blocks and virtual machines (VMs) are selectively placed for locality aware map-reduce job execution on a cluster of computing nodes in a network. Selectively placing data blocks and VMs comprises integrally placing the data and the VMs at selected nodes to lower data transfer network hops for a map-phase and a shuffle-phase of the map-reduce job upon execution by the VMs.

Abstract: Embodiments of the present invention provide an approach for intelligent storage planning and planning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will first determine/identify a set of storage area network volume controllers (SVCs) that is accessible from a host that has submitted a request for access to storage. Thereafter, a set of managed disk (mdisk) groups (i.e., corresponding to the set of SVCs) that are candidates for satisfying the request will be determined. This set of mdisk groups will then be filtered based on available space therein, a set of user/requester preferences, and optionally, a set of performance characteristics. Then, a particular mdisk group will be selected from the set of mdisk groups based on the filtering.

Abstract: Embodiments of the invention are directed to streaming virtual machine boot services over a network. An aspect of the invention includes booting a first virtual machine and recording data and metadata from a virtual machine boot image into a virtual machine boot file. The data and metadata are accessed in the process of booting the first virtual machine. The virtual machine boot image has setup information of the virtual machine type of the first virtual machine. The virtual machine boot file is configured for the virtual machine type of the first virtual machine. A descriptor is added to metadata of the virtual machine boot image, which references a location of the virtual machine boot file for the virtual machine type of the first virtual machine.

Abstract: Managing a data transfer from one or more source storage devices to one or more target storage devices. The data transfer comprises concurrent transfer of a multiplicity of data units pursuant to respective data transfer commands. The concurrent transfer of the multiplicity of data units is currently in-progress. A computer determines a currently-overloaded storage component involved in the data transfer. The computer determines a plurality of the data transfer commands that involve the overloaded storage component. The computer determines an approximately-minimum number of the data transfer commands to cancel to stop overload of the overloaded storage component. In response, the computer cancels the minimum number of the data transfer commands.

Abstract: Embodiments of the present invention provide an approach for intelligent storage planning and planning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will first determine/identify a set of storage area network volume controllers (SVCs) that is accessible from a host that has submitted a request for access to storage. Thereafter, a set of managed disk (mdisk) groups (i.e., corresponding to the set of SVCs) that are candidates for satisfying the request will be determined. This set of mdisk groups will then be filtered based on available space therein, a set of user/requester preferences, and optionally, a set of performance characteristics. Then, a particular mdisk group will be selected from the set of mdisk groups based on the filtering.

Abstract: An approach for automatic storage planning and provisioning within a clustered computing environment is provided. Planning input for a set of storage area network volume controllers (SVCs) will be received within the clustered computing environment, the planning input indicating a potential load on the SVCs and its associated components. Analytical models (e.g., from vendors) can be also used that allow for a load to be accurately estimated on the storage components. Configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load.

Abstract: A method, computer readable storage medium and computer system for controlling the allocation of data to one of a plurality of storage units of a storage system, the method comprising: accessing a source storage unit comprising the data; gathering file system level (FS-level) metadata from the source storage unit; analyzing the gathered FS-level metadata for determining if the data should be moved to one of the other storage units, said other storage unit acting as a destination storage unit; and in case the data should be moved, displaying an indication of the destination storage unit and/or automatically moving the data to the determined destination storage unit.

Abstract: The invention provides an enterprise administration system and method. The system includes a user interface module configured to enter administration terms or select a predetermined script of administration terms, a knowledge base configured to store system information, a meta information module configured to use the system information to store entity-objective indexes, and a workflow mapping module configured to map the administration terms to system information extraction tasks to extract relevant entities and objectives and apply a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order.

Abstract: Managing a data transfer from one or more source storage devices to one or more target storage devices. The data transfer comprises concurrent transfer of a multiplicity of data units pursuant to respective data transfer commands. The concurrent transfer of the multiplicity of data units is currently in-progress. A computer determines a currently-overloaded storage component involved in the data transfer. The computer determines a plurality of the data transfer commands that involve the overloaded storage component. The computer determines an approximately-minimum number of the data transfer commands to cancel to stop overload of the overloaded storage component. In response, the computer cancels the minimum number of the data transfer commands.

Abstract: Managing a data transfer from one or more source storage devices to one or more target storage devices. The data transfer comprises concurrent transfer of a multiplicity of data units pursuant to respective data transfer commands. The concurrent transfer of the multiplicity of data units is currently in-progress. A computer determines a currently-overloaded storage component involved in the data transfer. The computer determines a plurality of the data transfer commands that involve the overloaded storage component. The computer determines an approximately-minimum number of the data transfer commands to cancel to stop overload of the overloaded storage component. In response, the computer cancels the minimum number of the data transfer commands.