Abstract: Embodiments of the invention relate to performing on-demand data deduplication for managing data and storage space. Redundant data in a system is detected. Availability of data storage space in the system is periodically evaluated. Performance parameters of the system are evaluated. Detected redundant data is selected based on the data storage availability and performance parameters of the system. If at least a portion of the selected redundant data is to be deduplicated is determined.

Abstract: The present invention proactively identifies hotspots in a cloud computing environment through cloud resource usage models that use workload parameters as inputs. In some embodiments the cloud resource usage models are based upon performance data from cloud resources and time series based workload trend models. Hotspots may occur and can be detected at any layer of the cloud computing environment, including the server, storage, and network level. In a typical embodiment, parameters for a workload are identified in the cloud computing environment and inputted into a cloud resource usage model. The model is run with the inputted workload parameters to identify potential hotspots, and resources are then provisioned for the workload so as to avoid these hotspots.

Abstract: A computer-implemented method for determining, from a system including a plurality of data center resources, at least one configuration of data center resources for an implementation of an application. The method includes receiving application information and receiving information regarding known internal features up the data center resources. The method also includes provisioning the system of data center resources and creating possible configurations of data center resources for implementing application. The method also includes correlating models and data center resources to create an interrelated representation of the models and the data center resources. The models predict a relationship of parameters for the possible configurations.

Abstract: One embodiment retrieves a first portion of a plurality of stored objects from at least one storage device. The embodiment further performs a base type deduplication estimation process on the first portion of stored objects. The embodiment still further categorizes the first portion of the plurality of stored objects into deduplication sets based on a deduplication relationship of each object of the plurality of stored objects with each of the estimated first plurality of deduplication chunk portions. The embodiment further combines deduplication sets into broad classes based on deduplication characteristics of the objects in the deduplication sets. The embodiment still further classifies a second portion of the plurality of stored objects into broad classes using classifiers. The embodiment further selects an appropriate deduplication approach for each categorized class.

Abstract: Embodiments of the invention relate to testing a storage system point-in-time copy of data for consistency. An aspect of the invention includes receiving system and application event information from systems and applications associated with point-in-time copies of data. The system and application event information is associated with each of point-in-time copies of data. At least one point-in-time copy of data is selected for testing. The system and application event information is compared with inconsistency classes to determine tests for testing the point-in-time copy of data. The point-in-time copy of data is tested.

Abstract: Embodiments of the invention detect inadvertent or malicious data corruption and for recovering data including receiving a query specifying corrupted application data; analyzing transaction logs to find update operations related to the data; determining where the data are stored, by mapping the table data to locations within the file system and mapping the file system locations to volume logical blocks; and analyzing snapshot volume bitmaps to determine if the bitmaps show changes to the table data stored in the volume logical blocks. Changes which are reflected in the bitmaps for the data, but which do not have corresponding entries in the transaction logs are flagged as unauthorized changes. Snapshots of the data, from a time prior to the time at which a flagged snapshot was taken, are identified for use in restoring data to its status prior to the unauthorized change.

Abstract: A system and associated method for replicating data based on capacity optimization. A local node receives the data associated with a key. The local node within a local domain communicates with nodes of remote domains in a system through a communication network. Each domain has its own distributed hash table that partitions key space and assigns a certain key range to an owner node within the domain. For new data, the local node queries owner nodes of domains in the system progressively from the local domain to remote domains for a duplicate of the new data. Depending on a result returned by owner nodes and factors for replication strategies, the local node determines a replication strategy and records the new data in the local node pursuant to the replication strategy.

Abstract: A method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions. The programming instructions are operable to determine one or more optimal mappings between a server layer and a storage layer through a network layer based on performance metrics of one or more ports of at least one of the server layer, the storage layer and the network layer.

Abstract: A system and associated method for optimizing power consumption of a data center by dynamic workload adjustment. A current workload distribution of the data center is shifted to an optimal workload solution that provides acceptable level of service with the least amount of power consumption. The sum of power cost and migration cost that corresponds to the optimal workload solution is the lowest among all sums that correspond to respective candidate workload solutions. The power cost is determined by a maximum temperature of the data center and accompanying cooling cost for each candidate workload solution. The migration cost is determined by performance degradation that occurs during shifting a workload distribution of the data center from the current workload distribution to each candidate workload solution.

Abstract: A system and associated method for automated disaster recovery (DR) planning. A DR planning process receives disaster recovery requirements and a target environment configuration from a user to design DR plans for the target environment configuration that meets disaster recovery requirements. The DR planning process accesses a knowledgebase containing information on replication technologies, best practice recipes, and past deployment instances. The DR planning process creates the DR plans by analyzing the disaster recovery requirements into element risks, associating replication technologies to protect each element risks, combining associated replication technologies based on the best practice recipes, and selecting highly evaluated combination based on the past deployment instances. The DR planning process presents the DR plans as classified by replication strategy-architecture combination for each DR plans and marks how strongly each DR plans are recommended.

Abstract: A system and associated method for continuously optimizing data archive management scheduling. A job scheduler receives, from an archive management system, inputs of task information, replica placement data, infrastructure topology data, and resource performance data. The job scheduler models a flow network that represents data content, software programs, physical devices, and communication capacity of the archive management system in various levels of vertices according to the received inputs. An optimal path in the modeled flow network is computed as an initial schedule, and the archive management system performs tasks according to the initial schedule. The operations of scheduled tasks are monitored and the job scheduler produces a new schedule based on feedbacks of the monitored operations and predefined heuristics.

Abstract: The embodiments of the invention provide methods, computer program products, etc. for autonomic retention classes when retaining data within storage devices. More specifically, a method of determining whether to retain data within at least one storage device begins by storing data items in at least one storage device. Furthermore, the method maintains access statistics for each of the data items, an age of each of the data items, and an administrator-defined importance value of each of the data items. Following this, a retention value is calculated for each of the data items based on the access statistics for each of the data items, the age of each of the data items, and the administrator-defined importance value of each of the data items.

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: A method, system, and article are provided for monitoring performance of hardware devices. Each hardware device is configured with an agent, and the server is configured with a coordinator. The agent collects device data at a first modifiable frequency and communicates the collected data to the coordinator at a second dynamically modifiable frequency. The collected data is periodically monitored and the first and second frequencies are modified subject to evaluation of the collected and monitored data.

Abstract: 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.

Abstract: A method, system, and article are provided for managing performance of a computer system. Both implicit and explicit recommendations for processing of tasks are provided. System performance is tracked and evaluated based upon the actions associated with the task. Future recommendations of the same or other tasks are provided based upon implicit feedback pertaining to system performance, and explicit feedback solicited from a system administrator.

Abstract: A system and associated method for replicating data based on capacity optimization. A local node receives the data associated with a key. The local node within a local domain communicates with nodes of remote domains in a system through a communication network. Each domain has its own distributed hash table that partitions key space and assigns a certain key range to an owner node within the domain. For new data, the local node queries owner nodes of domains in the system progressively from the local domain to remote domains for a duplicate of the new data. Depending on a result returned by owner nodes and factors for replication strategies, the local node determines a replication strategy and records the new data in the local node pursuant to the replication strategy.

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: A system and associated method for automated disaster recovery (DR) planning. A DR planning process receives disaster recovery requirements and a target environment configuration from a user to design DR plans for the target environment configuration that meets disaster recovery requirements. The DR planning process accesses a knowledgebase containing information on replication technologies, best practice recipes, and past deployment instances. The DR planning process creates the DR plans by analyzing the disaster recovery requirements into element risks, associating replication technologies to protect each element risks, combining associated replication technologies based on the best practice recipes, and selecting highly evaluated combination based on the past deployment instances. The DR planning process presents the DR plans as classified by replication strategy-architecture combination for each DR plans and marks how strongly each DR plans are recommended.

Abstract: One embodiment retrieves a first portion of a plurality of stored objects from at least one storage device. The embodiment further performs a base type deduplication estimation process on the first portion of stored objects. The embodiment still further categorizes the first portion of the plurality of stored objects into deduplication sets based on a deduplication relationship of each object of the plurality of stored objects with each of the estimated first plurality of deduplication chunk portions. The embodiment further combines deduplication sets into broad classes based on deduplication characteristics of the objects in the deduplication sets. The embodiment still further classifies a second portion of the plurality of stored objects into broad classes using classifiers. The embodiment further selects an appropriate deduplication approach for each categorized class.