International Business Machines Corporation

Benjamin J Randall

Steven M Kern

Jeffrey R Placer

Jacob A Stevens

Teresa Shen Swingler

Ryan D McNair

Stephen A Byrd

John A Bowers

Andrew J Laforteza

David Randall Blea

John Jay Wolfgang

Sumant Padbidri

Christian Bolik

Errol Jay Calder

Todd Benjamin Schlomer

Scott Joseph Colbeck

William D Olsen

Andres F Holguin

Kristen N Muramoto

Tiffany P Tsai

A method, system and computer product for performing storage maintenance is described. A training set for storage volume reclamation is received. The training set for storage volume reclamation contains sets of storage parameters for storage volumes and corresponding user decisions whether the storage volumes are reclaimable. The training set is used to train a machine learning system to recognize reclaimable candidate storage volumes. The trained machine learning system is used to determine that a candidate storage volume for reclamation is likely a reclaimable storage volume.

Machine learning for determining confidence for reclamation of storage volumes

A method, system and computer product for performing storage maintenance is described. A training set for storage volume reclamation is received. The training set includes a set of storage parameters, each set of storage parameters corresponds to a respective candidate storage volume of a set of candidate storage volumes. The training set also includes a set of user decisions made whether a respective candidate storage volume is reclaimable. The training set is used to train a machine learning system to recognize common features of reclaimable candidate storage volumes. A set of candidate storage volumes is provided for potential reclamation, each with a set of storage parameters. A graphical user interface presents respective members of the set of candidate storage volumes for reclamation if a confidence level is calculated that the respective candidate storage volume is reclaimable exceeds a threshold.

A method, computer program product, and system for determining an optimal volume placement on a storage system. The method includes acquiring at least a desired response time range for each storage volume associated with an application. The degree of optimization of volume placement is evaluated utilizing numeric scores assigned by a fitness function, and a recommendation is provided for storage volumes that should be moved to different storage pools, such that desired response times are met.

Optimizing volume placement based upon desired response time and priority

Display screen with graphical user interface for network topology display

For logging browser data, the method compiles a string representing metadata of an operating environment for a browser displaying webpage content from a Web server. The method further compiles a Document Object Model (DOM) string representing at least one DOM element of the webpage content. In addition, the method logs the metadata string and the DOM string within a data store accessible by the web server.

Logging browser data

A mechanism is provided in a data processing system for volume placement across remote replication relationships. Responsive to applying a volume placement optimization to a source storage pool having at least one volume with a replication target in a target storage pool, the mechanism determines whether the source storage pool and the target storage pool have identical storage volume membership. Responsive to determining the source storage pool and the target storage pool not having the same storage volume membership, the mechanism generates workload performance data for each non-shared storage volume in the target storage pool that does not have a corresponding member of the source storage pool. The mechanism generates a hardware profile for hardware of the target storage pool. The mechanism generates a volume placement optimization for the storage volumes in the target storage pool based on the workload performance data for each non-shared storage volume in the target storage pool and the hardware profile for the hardware of the target storage pool.

Optimal volume placement across remote replication relationships

One aspect of the present invention includes capturing a client browser state and communicating this captured browser state within markup text for logging at a web server. In one embodiment, the contents of the DOM (Document Object Model) of a webpage accessed by a client are traversed and written as markup text in a string of characters, such as HTML. This markup, in addition to metadata specific to identify the browser display environment, is transmitted from the client to the server as text within a HTTP request. The server may then log the markup text and the metadata for later access. The logged markup text and the metadata can be used to recreate the exact display which occurred within the client browser, and therefore provide details useful for webpage problem determination, testing, and development.

Method for server-side logging of client browser state through markup language

A method for replicating a volume of data including selecting a target storage box to receive a physical copy of the actual volume of data stored on the source storage box for replication of the actual volume of data, selecting a point in time storage box to receive a physical copy of actual data stored on the target storage box, physically copying actual data stored on the target storage box to the point in time storage box, performing the replication of the actual volume of data by initiating the physical copying on the target storage box of the actual volume of data, and selectively undoing the physical copying on the target storage box of the actual volume of data by replacing the current actual data stored on the target storage box with the physical copy of actual target storage box data stored on the point in time storage box.

Replication management with undo and redo capabilities

Growing community of inventors

Fort Collins, CO, United States of America

Benjamin J Randall