Abstract: A computer-implemented method of information lifecycle management is disclosed. The computer-implemented method includes reading, by a data processing system of a storage environment, business rules and policies for managing data in storage volumes of the storage environment, the policies being based on the predetermined business rules, and analyzing, by the data processing system, available storage and capacity in the storage environment. The computer-implemented method further includes dynamically prioritizing, by the data processing system, the policies based, at least in part, on results of the analyzing, resulting in prioritized policies, cognitively translating, by the data processing system, one or more of the predetermined business rules into action(s) against one or more of the storage volumes based, at least in part, on the prioritized policies, and executing, by the data processing system, the action(s).

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: A method, computer system, and computer program product for determining whether data compression should be performed at a storage virtualization layer or a backend layer, within a storage area network, including assessing a volume of data to decide whether the volume of data should be compressed or is already compressed, and in response to deciding that the volume of data should be compressed: checking whether a restriction exists on the volume of data, and in response to deciding that the volume of data is already compressed: determining that the volume of data already compressed should be uncompressed based on at least one metric.

Abstract: A computer-implemented method of information lifecycle management is disclosed. The computer-implemented method includes reading, by a data processing system of a storage environment, business rules and policies for managing data in storage volumes of the storage environment, the policies being based on the predetermined business rules, and analyzing, by the data processing system, available storage and capacity in the storage environment. The computer-implemented method further includes dynamically prioritizing, by the data processing system, the policies based, at least in part, on results of the analyzing, resulting in prioritized policies, cognitively translating, by the data processing system, one or more of the predetermined business rules into action(s) against one or more of the storage volumes based, at least in part, on the prioritized policies, and executing, by the data processing system, the action(s).

Abstract: An indication of a problem within the computing environment can be received by a data processing system external to a computing environment. Based on the indication of the problem within the computing environment, the data processing system can select a data log filter. The data log filter can be configured to access, from each of a plurality of data logs, a respective data set comprising log entries that are candidate indicators of the problem. Each of the plurality of data logs can be generated by a respective electronic device that is a member of the computing environment. The data processing system can access the respective data sets from the plurality of data logs using the data log filter, and output each respective data set.

Abstract: A method, computer system, and computer program product for determining whether data compression should be performed at a storage virtualization layer or a backend layer, within a storage area network, including assessing a volume of data to decide whether the volume of data should be compressed or is already compressed, and in response to deciding that the volume of data should be compressed: checking whether a restriction exists on the volume of data, and in response to deciding that the volume of data is already compressed: determining that the volume of data already compressed should be uncompressed based on at least one metric.

Abstract: An indication of a problem within the computing environment can be received by a data processing system external to a computing environment. Based on the indication of the problem within the computing environment, the data processing system can select a data log filter. The data log filter can be configured to access, from each of a plurality of data logs, a respective data set comprising log entries that are candidate indicators of the problem. Each of the plurality of data logs can be generated by a respective electronic device that is a member of the computing environment. The data processing system can access the respective data sets from the plurality of data logs using the data log filter, and output each respective data set.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining information of first through Nth storage volumes and based on the examining providing for each storage volume of the first through Nth storage volumes a predicted storage space savings value, the predicted storage space savings value indicating a predicted terabyte volume of storage space savings producible by performance of data compression of data stored on the storage volume; predicting a per terabyte compression cost savings associated with compressing one or more storage volume of the first through Nth storage volumes, and providing a ranking of storage volumes of the first through Nth storage volumes based on the examining and the predicting; and scheduling a compression of storage volumes of the first through Nth storage volumes based on the ranking of storage volumes of the first through Nth storage volumes.

Abstract: An indication of a problem within the computing environment can be received by a data processing system external to a computing environment. Based on the indication of the problem within the computing environment, the data processing system can select a data log filter. The data log filter can be configured to access, from each of a plurality of data logs, a respective data set comprising log entries that are candidate indicators of the problem. Each of the plurality of data logs can be generated by a respective electronic device that is a member of the computing environment. The data processing system can access the respective data sets from the plurality of data logs using the data log filter, and output each respective data set.

Abstract: An indication of a problem within the computing environment can be received by a data processing system external to a computing environment. Based on the indication of the problem within the computing environment, the data processing system can select a data log filter. The data log filter can be configured to access, from each of a plurality of data logs, a respective data set comprising log entries that are candidate indicators of the problem. Each of the plurality of data logs can be generated by a respective electronic device that is a member of the computing environment. The data processing system can access the respective data sets from the plurality of data logs using the data log filter, and output each respective data set.

Abstract: A method and system. In response to a request for a proposed additional data transfer from a source storage system to a target storage system, an estimate is made of utilization of one or more data transfer components of the source storage system and the target storage system that would occur during the proposed additional data transfer combined with other scheduled data transfers involving the source storage system and the target storage system, based in part on (i) an I/O request rate for recent actual data transfers involving the source storage system and the target storage system combined with (ii) an estimated I/O request rate for the proposed additional data transfer. It is ascertained whether the estimated utilization exceeds a corresponding utilization threshold. If so, execution of the proposed additional data transfer is postponed. If not, execution of the proposed additional data transfer is initiated.

Abstract: A method and system. In response to a request for a proposed additional data transfer from a source storage system to a target storage system, an estimate is made of utilization of one or more data transfer components of the source storage system and the target storage system that would occur during the proposed additional data transfer combined with other scheduled data transfers involving the source storage system and the target storage system, based in part on (i) an I/O request rate for recent actual data transfers involving the source storage system and the target storage system combined with (ii) an estimated I/O request rate for the proposed additional data transfer. It is ascertained whether the estimated utilization exceeds a corresponding utilization threshold. If so, execution of the proposed additional data transfer is postponed. If not, execution of the proposed additional data transfer is initiated.

Abstract: A method for controlling the storage of data among multiple regional storage centers coupled through a network in a global storage system is provided. The method includes steps of: defining at least one dataset comprising at least a subset of the data stored in the global storage system; defining at least one ruleset for determining where to store the dataset; obtaining information regarding a demand for the dataset through one or more data requesting entities operating in the global storage system; and determining, as a function of the ruleset, information regarding a location for storing the dataset among regional storage centers having available resources that reduces the total distance traversed by the dataset in serving at least a given one of the data requesting entities and/or reduces the latency of delivery of the dataset to the given one of the data requesting entities.

Abstract: A method for controlling the storage of data among multiple regional storage centers coupled through a network in a global storage system is provided. The method includes steps of: defining at least one dataset comprising at least a subset of the data stored in the global storage system; defining at least one ruleset for determining where to store the dataset; obtaining information regarding a demand for the dataset through one or more data requesting entities operating in the global storage system; and determining, as a function of the ruleset, information regarding a location for storing the dataset among regional storage centers having available resources that reduces the total distance traversed by the dataset in serving at least a given one of the data requesting entities and/or reduces the latency of delivery of the dataset to the given one of the data requesting entities.

Abstract: Scheduling a proposed additional data transfer from one or more source storage devices to one or more target storage devices. A computer receives a request for the proposed additional data transfer, and in response, determines a measure of the proposed additional data transfer. The computer determines a measure of recent actual data transfers. The recent actual data transfers involve one or more of the source storage devices and one or more of the target storage devices. In response to the request for the proposed additional data transfer, the computer estimates performance of one or more of the source storage devices and one or more of the target storage devices that would occur during the proposed additional data transfer based on the measure of recent actual data transfers combined with the measure of the proposed additional data transfer.

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.