Abstract: An amount of data change associated with a version of a content file with respect to one or more previous versions of the content file is determined. The amount of change associated with the version of the content file is determined using a tree data structure associated with the content file that is stored on a storage cluster. One or more statistics associated with backup snapshot are provided to a server. The server is configured to determine that the amount of data change associated with the version of the content file is anomalous based in part on the one or more statistics associated with the backup snapshot. A notification that data associated with the backup snapshot is potentially infected by malicious software is received from the server. The version of the content file is indicated as being potentially infected by malicious software.

Abstract: An amount of data change associated with a version of a content file with respect to one or more previous versions of the content file is determined. The amount of change associated with the version of the content file is determined using a tree data structure associated with the content file that is stored on a storage cluster. One or more statistics associated with backup snapshot are provided to a server. The server is configured to determine that the amount of data change associated with the version of the content file is anomalous based in part on the one or more statistics associated with the backup snapshot. A notification that data associated with the backup snapshot is potentially infected by malicious software is received from the server. The version of the content file is indicated as being potentially infected by malicious software.

Abstract: An embodiment of the invention may include a method, computer program product and system for data storage management. The embodiment may include receiving a request from a second container runtime for access to a first container runtime volume by the second container runtime. The embodiment may include determining whether the first container runtime volume exists within a shared unified volume listing. Based on determining that the first container runtime volume exists within the shared unified volume listing, the embodiment may include transforming volume information of the first container runtime volume from a unified volume listing schema to a second container runtime volume listing schema. The embodiment may include returning the volume information of the first container runtime volume to the second container runtime.

Abstract: An embodiment of the invention may include a method, computer program product and system for data storage management. The embodiment may include receiving a request from a second container runtime for access to a first container runtime volume by the second container runtime. The embodiment may include determining whether the first container runtime volume exists within a shared unified volume listing. Based on determining that the first container runtime volume exists within the shared unified volume listing, the embodiment may include transforming volume information of the first container runtime volume from a unified volume listing schema to a second container runtime volume listing schema. The embodiment may include returning the volume information of the first container runtime volume to the second container runtime.

Abstract: A method and system for optimizing power consumption of a data center by dynamic workload adjustment. Workload of the data center is dynamically adjusted from a current workload distribution to an optimal workload solution. The optimal workload solution is a candidate workload solution of at least one candidate workload solution having a lowest sum of a respective power cost and a respective migration cost. Each candidate workload solution represents a respective application map that specifies a respective workload distribution among application programs of the data center. Dynamically adjusting the workload of the data center includes: estimating a respective overall cost of each candidate workload solution, selecting the optimal workload solution that has a lowest overall cost as determined from the estimating, and transferring the optimal workload solution to devices of a computer system for deployment.

Abstract: Methods, systems, and articles of manufacture for identifying compatible system configurations are provided herein. A method includes generating a second graph from a first graph of multiple devices in a network and a set of one or more network compatibility rules, wherein said generating comprises dividing each device in the first graph into multiple nodes in the second graph, and wherein each node in the second graph represents a valid configuration of a device in the first graph; identifying a sub-graph of two or more linked nodes in the second graph that is isomorphic to at least a portion of the first graph, wherein the two or more linked nodes in the second graph represent two or more configurations that are compatible based on the set of one or more network compatibility rules; and determining each of one or more changes needed to convert a current configuration in the network to a target configuration specified by the sub-graph.

Abstract: A method and system for optimizing power consumption of a data center by dynamic workload adjustment. Workload of the data center is dynamically adjusted from a current workload distribution to an optimal workload solution. The optimal workload solution is a candidate workload solution of at least one candidate workload solution having a lowest sum of a respective power cost and a respective migration cost. Each candidate workload solution represents a respective application map that specifies a respective workload distribution among application programs of the data center. Dynamically adjusting the workload of the data center includes: estimating a respective overall cost of each candidate workload solution, selecting the optimal workload solution that has a lowest overall cost as determined from the estimating, and transferring the optimal workload solution to devices of a computer system for deployment.

Abstract: A method and system for optimizing power consumption of a data center by dynamic workload adjustment. At least one candidate workload solution for the data center is generated. Each candidate workload solution represents a respective application map that specifies a respective workload distribution among application programs of the data center. Workload of the data center is dynamically adjusted from a current workload distribution to an optimal workload solution. The optimal workload solution is a candidate workload solution of the at least one candidate workload solution having a lowest sum of a respective power cost and a respective migration cost. Dynamically adjusting the workload of the data center includes: estimating a respective overall cost of each candidate workload solution, selecting the optimal workload solution that has a lowest overall cost as determined from the estimating, and transferring the optimal workload solution to devices of a computer system for deployment.

Abstract: Methods, systems, and articles of manufacture for identifying compatible system configurations are provided herein. A method includes generating a second graph from a first graph of multiple devices in a network and a set of one or more network compatibility rules, wherein said generating comprises dividing each device in the first graph into multiple nodes in the second graph, and wherein each node in the second graph represents a valid configuration of a device in the first graph; identifying a sub-graph of two or more linked nodes in the second graph that is isomorphic to at least a portion of the first graph, wherein the two or more linked nodes in the second graph represent two or more configurations that are compatible based on the set of one or more network compatibility rules; and determining each of one or more changes needed to convert a current configuration in the network to a target configuration specified by the sub-graph.

Abstract: A method and system for optimizing power consumption of a data center by dynamic workload adjustment. At least one candidate workload solution for the data center is generated. Each candidate workload solution represents a respective application map that specifies a respective workload distribution among application programs of the data center. Workload of the data center is dynamically adjusted from a current workload distribution to an optimal workload solution. The optimal workload solution is a candidate workload solution of the at least one candidate workload solution having a lowest sum of a respective power cost and a respective migration cost. Dynamically adjusting the workload of the data center includes: estimating a respective overall cost of each candidate workload solution, selecting the optimal workload solution that has a lowest overall cost as determined from the estimating, and transferring the optimal workload solution to devices of a computer system for deployment.

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 data center power cost accounting system uses server and storage and cooling power consumption models and device maps, together with runtime application maps, to estimate the equipment power consumption and cooling power consumption of individual applications. An approximation of the cooling cost over a period of time, for any given application, can be pieced together by adding up the equipment utilized by the application and applying the cooling estimates obtained from computational fluid dynamics (CFD) simulations. The cooling estimates can further account for changes or variability in resource usage over time since the cooling estimates are based directly on utilization. The per application power consumption costs are obtained without having to install or depend on power measurement instruments or other hardware in the datacenters.

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: 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 data center power cost accounting system uses server and storage and cooling power consumption models and device maps, together with runtime application maps, to estimate the equipment power consumption and cooling power consumption of individual applications. An approximation of the cooling cost over a period of time, for any given application, can be pieced together by adding up the equipment utilized by the application and applying the cooling estimates obtained from computational fluid dynamics (CFD) simulations. The cooling estimates can further account for changes or variability in resource usage over time since the cooling estimates are based directly on utilization. The per application power consumption costs are obtained without having to install or depend on power measurement instruments or other hardware in the datacenters.

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.