Abstract: In an approach to assisting database management, a computer generates one or more combinations of values of one or more database configuration parameters. The computer associates each of the one or more generated combinations of values with an incident probability. The computer defines relationships between the one or more generated combinations and the associated incident probabilities. The computer stores the defined relationships into an object representable as a multi-dimensional matrix, whose dimensions correspond to a plurality of database configuration parameters used to generate the combinations of values. The computer traverses the object to identify a path in the matrix. The computer returns the identified path for enabling subsequent interpretation thereof as a rule for passing from a first database configuration, corresponding to the first one of the one or more generated combinations, to a second database configuration, corresponding to the second one of the one or more generated combinations.

Abstract: In an approach to assisting database management, a computer generates one or more combinations of values of one or more database configuration parameters. The computer associates each of the one or more generated combinations of values with an incident probability. The computer defines relationships between the one or more generated combinations and the associated incident probabilities. The computer stores the defined relationships into an object representable as a multi-dimensional matrix, whose dimensions correspond to a plurality of database configuration parameters used to generate the combinations of values. The computer traverses the object to identify a path in the matrix. The computer returns the identified path for enabling subsequent interpretation thereof as a rule for passing from a first database configuration, corresponding to the first one of the one or more generated combinations, to a second database configuration, corresponding to the second one of the one or more generated combinations.

Abstract: In one embodiment, a computer-implemented method includes obtaining incident data related to a plurality of servers, including a first server. Configuration data is obtained for each of the plurality of servers. The configuration data includes information about a set of one or more configuration items of the first server. A predictive modeler is trained to predict incident characteristics, based at least in part on the incident data and the configuration data. A modification is selected to the set of configuration items of the first server. Predicted incident characteristics of the first server are simulated, by a computer processor, based on the selected modifications. It is recommended that the selected modifications be made to the first server if predetermined criteria are met by the simulation.

Abstract: In one embodiment, a computer-implemented method includes obtaining incident data related to a plurality of servers, including a first server. Configuration data is obtained for each of the plurality of servers. The configuration data includes information about a set of one or more configuration items of the first server. A predictive modeler is trained to predict incident characteristics, based at least in part on the incident data and the configuration data. A modification is selected to the set of configuration items of the first server. Predicted incident characteristics of the first server are simulated, by a computer processor, based on the selected modifications. It is recommended that the selected modifications be made to the first server if predetermined criteria are met by the simulation.