Abstract: An approach is described that enables the reception of multiple client requests directed to a mainframe computer system from various transaction origination points external to the mainframe. It involves computing time-based performance metrics, including transaction times from these origination points to the mainframe. By capturing and analyzing transaction times from diverse external sources, the system evaluates mainframe performance holistically, reflecting the complete duration of transactions from their initiation outside the mainframe to their processing completion within it. This approach provides comprehensive insights into transaction efficiency across different user environments, enhancing the system’s ability to measure, optimize, and maintain performance standards under varied operating conditions.

Abstract: Computer-implemented methods for a gateway health monitoring system. Aspects include generating a mapping between entity utilization metrics and an application of a mainframe of a hybrid cloud system. Aspects also include determining a correlation between the entity utilization metrics and information technology (IT) performance metrics. Aspects further include defining a relationship between an entity utilization driver and the IT performance metrics using the mapping and the correlation. Aspects also include generating forecasted values using the relationship between the entity utilization driver and the IT performance metrics. Aspects further include generating a proposed infrastructure configuration based on the forecasted values.

Abstract: A computer-implemented method includes: monitoring, by a computing device, a data set format of all files in a computing system to determine a list of data sets in a first format which are accessed greater than a predetermined number of times; gathering, by the computing device, the list of data sets in the first format within the computing system; and converting, by the computing device, the list of data sets in the first format within the computing system to a second format which is different from the first format.

Abstract: A computer-implemented method includes: monitoring, by a computing device, a data set format of all files in a computing system to determine a list of data sets in a first format which are accessed greater than a predetermined number of times; gathering, by the computing device, the list of data sets in the first format within the computing system; and converting, by the computing device, the list of data sets in the first format within the computing system to a second format which is different from the first format.

Abstract: Computer-implemented methods for a gateway health monitoring system. Aspects include generating a mapping between entity utilization metrics and an application of a mainframe of a hybrid cloud system. Aspects also include determining a correlation between the entity utilization metrics and information technology (IT) performance metrics. Aspects further include defining a relationship between an entity utilization driver and the IT performance metrics using the mapping and the correlation. Aspects also include generating forecasted values using the relationship between the entity utilization driver and the IT performance metrics. Aspects further include generating a proposed infrastructure configuration based on the forecasted values.

Abstract: Embodiments relate to enhancing a virtual storage mechanism to optimize fetch performance of named objects in enterprise systems. A technique includes receiving from a requester a request to retrieve an object and determining that the object is available for retrieval in a virtual data space, where a machine learning model is configured to cause the object to be placed in the virtual data space, the machine learning model being trained on fetch data for objects. The technique includes retrieving the object from the virtual data space instead of a storage system and providing the object to the requester for execution.

Abstract: A computer-implemented method includes: monitoring, by a computing device, a data set format of all files in a computing system to determine a list of data sets in a first format which are accessed greater than a predetermined number of times; gathering, by the computing device, the list of data sets in the first format within the computing system; and converting, by the computing device, the list of data sets in the first format within the computing system to a second format which is different from the first format.

Abstract: A computer-implemented method for optimize memory configuration of a computer system. The computer-implemented method includes determining available online real storage assigned to the computer system. The method further includes computing, using a machine learning model, a Large Frame Area (LFAREA) value to support large pages used by one or more applications executing on the computer system, wherein the large pages are memory pages larger than a predetermined value. The method further includes dynamically updating the LFAREA value of the computer system to the determined LFAREA value to support the large pages of the computer system.