In one aspect of tape repositioning management in accordance with the present description, in response to loading a tape in a tape drive, mounting the tape linear tape file system (LTFS) is initiated including reading an index partition on the tape to extract metadata for mounting the tape LTFS, and prior to accessing a data area of the tape in response to any application access request, the tape is repositioned within a data partition to read a vHRTD (virtual High Resolution Tape Directory) recorded in an EOD (End of Data) portion such as an EOD data set, for example, of the data partition. The EOD portion is read to retrieve the vHRTD to facilitate application requested accesses to the tape. In one embodiment, repositioning and stopping the tape at the beginning of the data partition after reading the index partition containing metadata is bypassed.

In some embodiments, a user enters a search term (or a portion thereof) in a search field associated with one or more resource types that may be searched. The user may be presented with a pop-up menu containing a list of likely matches. The user selects the desired preference control from the pop-up menu, and the corresponding preference pane, or other container, containing the selected data item, control, or other resource is displayed. In one aspect, as the user enters the search term (or portion thereof), certain icons are highlighted. Specifically, those icons that represent containers containing matching data items (such as preference panes having controls that match the search term) are highlighted. Different types of highlighting can be used depending on the degree of certainty as to which container is likely to contain the correct match.

In some embodiments, a user enters a search term (or a portion thereof) in a search field associated with one or more resource types that may be searched. The user may be presented with a pop-up menu containing a list of likely matches. The user selects the desired preference control from the pop-up menu, and the corresponding preference pane, or other container, containing the selected data item, control, or other resource is displayed. In one aspect, as the user enters the search term (or portion thereof), certain icons are highlighted. Specifically, those icons that represent containers containing matching data items (such as preference panes having controls that match the search term) are highlighted. Different types of highlighting can be used depending on the degree of certainty as to which container is likely to contain the correct match.

Indexing preferences generally associate each data source with a type of indexing technology and/or with an index/catalog and/or with a computing device that hosts the index/catalog for tracking backup data generated from the source data. Indexing preferences govern which index/catalog receives transaction logs for a given storage operation. Thus, indexing destinations are defined granularly and flexibly in reference to the source data. Load balancing without user intervention assures that the various index/catalogs are fairly distributed in the illustrative backup systems by autonomously initiating migration jobs. Criteria for initiating migration jobs are based on past usage and going-forward trends. An illustrative migration job re-associates data sources with a different destination media agent and/or index/catalog, including transferring some or all relevant transaction logs and/or indexing information from the old host to the new host.

Indexing preferences generally associate each data source with a type of indexing technology and/or with an index/catalog and/or with a computing device that hosts the index/catalog for tracking backup data generated from the source data. Indexing preferences govern which index/catalog receives transaction logs for a given storage operation. Thus, indexing destinations are defined granularly and flexibly in reference to the source data. Load balancing without user intervention assures that the various index/catalogs are fairly distributed in the illustrative backup systems by autonomously initiating migration jobs. Criteria for initiating migration jobs are based on past usage and going-forward trends. An illustrative migration job re-associates data sources with a different destination media agent and/or index/catalog, including transferring some or all relevant transaction logs and/or indexing information from the old host to the new host.

Storage cluster configuration for computing resources of a storage system is disclosed. A cluster configuration can be based on client indicated cluster criteria. Further, a cluster configuration can be based on non-client indicated criteria, such as, system requirements, regulatory compliance, industry best practices, etc. Determined candidate cluster configurations that can satisfy client criteria can be organized according to a selection preference, to enable selection of a preferred cluster configuration from the candidate cluster configurations. Candidate cluster configurations can result from recursive combinatorial searching, with pruning, of an entity space resulting from an ontological analysis of storage system computing resources. Pruning can be accelerated based on heuristic selection of a fork attribute. A K-D tree subjected to dimensional normalization can be employed to interpolate an attribute value. Interpolation can be performed from predetermined sets of data, for example from storage system models or historical storage system performance.

Techniques for adjusting storage space involve: receiving a request for adjusting available storage space of a user in a filesystem from a first size to a second size; determining whether to allow to adjust the available storage space based on the request; and in response to allowing to adjust the available storage space, adjusting the available storage space to the second size. Accordingly, not only operations that an administrator needs to perform for adjusting the available storage space of a user is reduced, but also a quick and correct response for a request from a user of adjusting the available storage space is guaranteed.

Disclosed are various embodiments for triggering a processing of a data object stored in a bucket in a data store. In one embodiment, a cloud computing resource comprising one or more processors in communication with a data store receives a notification event generated in response to a modification of a data object in one or more buckets. The cloud computing resource determines, responsive to the received notification event, that a data object stored in a bucket in the data store has been modified. The cloud computing resource triggers a processing of the data object by executable code associated with the data object. The executable code causes a notification message, processing of the modified data object, or other user specified processes within a platform as a service cloud computing offering.

Disclosed are various embodiments for triggering a processing of a data object stored in a bucket in a data store. In one embodiment, a cloud computing resource comprising one or more processors in communication with a data store receives a notification event generated in response to a modification of a data object in one or more buckets. The cloud computing resource determines, responsive to the received notification event, that a data object stored in a bucket in the data store has been modified. The cloud computing resource triggers a processing of the data object by executable code associated with the data object. The executable code causes a notification message, processing of the modified data object, or other user specified processes within a platform as a service cloud computing offering.

A lightweight always-on monitoring, collecting, diagnosing, and correcting utility operates in an enhanced storage manager that manages a data storage managements system. The always-on utility provides a comprehensive and pro-active approach, which is intended to reduce, if not altogether eliminate, the need for after-the-fact diagnostics. The always-on utility also enforces so-called best practices and other heuristics, which include pro-actively activating certain database settings that are not enabled by default; manipulating certain aspects of the database to improve performance; and reporting aspects that are outside best-practice parameters to the trouble report system so that system administrators and/or developers may intervene before a catastrophic failure occurs. In some cases, the best-practice parameters represent heuristics designed by the present inventors to improve the performance and general health of the management database.