International Business Machines Corporation

Billy S Brewer

Ramani Ranjan Routray

Nagapramod S Mandagere

Kavita Chavda

Bernhard Julius Klingenberg

Steven Pantridge

Patrick B Heywood

A method and associated systems for backing up a target computer application that comprises identifying and backing up databases and other information repositories upon which the target application depends. The target application is identified and related to a backup requirement that specifies a minimum application-backup frequency. The application's 'dependencies' are automatically identified from sources that include configuration files, where each dependency identifies one or more databases or other information repositories that store information upon which the application directly or indirectly depends. If any of these databases or repositories is associated with a backup frequency less than the application's minimum backup frequency, the database or repository is flagged. Each flagged entity's backup schedule is then revised so that the flagged entity's backup frequency is equal to or greater than the application's minimum backup frequency.

Enhancing robustness of a database application

An approach for managing replicated data is presented. A current usage of resources in a system and a threshold usage of the resources are determined. Based on inter-replica correlation(s) and inter-data correlation(s) specified by a unified replication metadata model, a proper subset of replicas included in a plurality of replicas is indexed by (i) if the current usage is less than the threshold usage, determining an expected additional resource usage due to performing an indexing task online and based on the expected additional resource usage, determining a resource affinity score for performing the indexing task online, or (ii) if the current usage is greater than or equal to the threshold usage, determining an expected resource usage due to performing the indexing task offline and based on the expected resource usage, determining a resource affinity score for performing the indexing task offline.

Managing replicated data

Backing up a computer application

An approach for managing replicated data is presented. Metadata is received specifying inter-data correlation(s), inter-replica correlation(s), and data-replica correlation(s) among replicas generated for a system. A unified replication metadata model specifying the correlations is generated. Based on the inter-replica correlation(s), a proper subset of the replicas is selected. Based on the inter-replica and inter-data correlation(s), the selected proper subset of replicas is indexed to generate a unified content index. Based on a current usage of resources, an expected usage and an affinity score for performing an indexing task online or offline are determined. A query is received to locate a data item in at least one of the replicas. Based on the unified content index, the unified replication metadata model, and the query, candidate replica(s) and confidence score(s) indicating likelihood(s) that the candidate replica(s) include the data item are determined.

An approach for managing replicated data is presented. Metadata is received specifying inter-data correlation(s), inter-replica correlation(s), and data-replica correlation(s) among replicas generated for a system. A unified replication metadata model specifying the correlations is generated. Based on the inter-replica correlation(s), a proper subset of the replicas is selected. Based on the inter-replica and inter-data correlation(s), the selected proper subset of replicas is indexed to generate a unified content index. A query is received to locate a data item in at least one of the replicas. Based on the unified content index, the unified replication metadata model, and the query, candidate replica(s) and confidence score(s) indicating likelihood(s) that the candidate replica(s) include the data item are determined. Based on temporal distance(s) and percent change(s) between first and second replica(s), confidence score(s) of the second replica(s) are determined.

An approach for managing replicated data is presented. Metadata is received specifying inter-data correlation(s), inter-replica correlation(s), and data-replica correlation(s) among replicas generated for a system. A unified replication metadata model specifying the correlations is generated. Based on the inter-replica correlation(s), a proper subset of the replicas is selected. Based on the inter-replica and inter-data correlation(s), the selected proper subset of replicas is indexed to generate a unified content index. A query is received to locate a data item in at least one of the replicas. Based on the unified content index, the unified replication metadata model, and the query, candidate replica(s) and corresponding confidence score(s) are determined. The confidence score(s) indicate respective likelihood(s) that the candidate replica(s) include the data item.

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Kailua, HI, United States of America

Billy S Brewer