Abstract: According to one or more embodiments of the present invention a computer-implemented method includes receiving a transaction-data for a transaction that occurs in a particular time-interval. The method further includes comparing a set of parameters from the transaction-data with a performance profile associated with the particular time-interval. The method further includes based on determining that the transaction is a deviant transaction, forwarding the transaction-data to a first data collector. The method further includes based on determining that the transaction is a conventional transaction, forwarding the transaction-data to a second data collector.

Abstract: A computer-implemented method for recommending a monitoring interval in provided. A non-limiting example of the computer-implemented method includes receiving, by a processor, monitoring data at an initial monitoring interval and calculating, by the processor, a set of aggregation data from the monitoring data including a first subset of aggregation data at a first interval of the initial monitoring interval. The method calculates, by the processor, a first density score for the first subset of aggregation data and a first indicator score for the first subset of aggregation data and provides, by the processor, the first interval as a recommended interval when the first density score does not exceed a density threshold and the first indicator threshold does not exceed an indicator threshold.

Abstract: A computer system to detect data alerts includes a data preprocessing system and a data analysis system. The data preprocessing system obtains system data of the computer system, generates predicted data based on the system data, and generates differential data indicating a difference between the system data and the predicted data. The data analysis is in signal communication with the data preprocessing system and determines that the differential data is one of expected event or an anomaly event in response to adding at least one new value from the differential data to the predicted data.

Abstract: Methods, systems, and computer program products for identifying relationships among a group of indicators are provided. Aspects include obtaining the group of indicators, including a number of indicators relating to an operation of a computing system. Aspects also include creating pairs of indicators, wherein the pairs of indicators includes all possible combination of the group of indicators. Aspects further include, for each pair of indicators, calculating a linear correlation score, calculating a fitting function score, determining a final correlation score based at least in part on one of the linear correlation score and the fitting function score and storing the final correlation score in a relationship database. Aspects also include creating a graphical display based on the relationship database, wherein the graphical display is configured to convey a strength relationships among the group of indicators.

Abstract: A computer-implemented method for recommending a monitoring interval in provided. A non-limiting example of the computer-implemented method includes receiving, by a processor, monitoring data at an initial monitoring interval and calculating, by the processor, a set of aggregation data from the monitoring data including a first subset of aggregation data at a first interval of the initial monitoring interval. The method calculates, by the processor, a first density score for the first subset of aggregation data and a first indicator score for the first subset of aggregation data and provides, by the processor, the first interval as a recommended interval when the first density score does not exceed a density threshold and the first indicator threshold does not exceed an indicator threshold.

Abstract: According to one or more embodiments of the present invention a computer-implemented method includes receiving a transaction-data for a transaction that occurs in a particular time-interval. The method further includes comparing a set of parameters from the transaction-data with a performance profile associated with the particular time-interval. The method further includes based on determining that the transaction is a deviant transaction, forwarding the transaction-data to a first data collector. The method further includes based on determining that the transaction is a conventional transaction, forwarding the transaction-data to a second data collector.

Abstract: A computer system to detect data alerts includes a data preprocessing system and a data analysis system. The data preprocessing system obtains system data of the computer system, generates predicted data based on the system data, and generates differential data indicating a difference between the system data and the predicted data. The data analysis is in signal communication with the data preprocessing system and determines that the differential data is one of expected event or an anomaly event in response to adding at least one new value from the differential data to the predicted data.

Abstract: Methods, systems, and computer program products for identifying relationships among a group of indicators are provided. Aspects include obtaining the group of indicators, including a number of indicators relating to an operation of a computing system. Aspects also include creating pairs of indicators, wherein the pairs of indicators includes all possible combination of the group of indicators. Aspects further include, for each pair of indicators, calculating a linear correlation score, calculating a fitting function score, determining a final correlation score based at least in part on one of the linear correlation score and the fitting function score and storing the final correlation score in a relationship database. Aspects also include creating a graphical display based on the relationship database, wherein the graphical display is configured to convey a strength relationships among the group of indicators.