Abstract: A cognitive automation engine receives notice that an unexpected event has occurred in a computing environment. The engine tries to address any resulting problems by running a previously generated automation script, customizing the script as required through cognitive means. If this fails, the engine forwards the script to a human expert for customization. In either case, the engine records any customization activities, extracts parameters from the recording that identify each customization step, cognitively assigns a level of risk to each step based on historical precedent, and determines whether running the customized script presents an unacceptable risk of adverse results. The system adds the revisions, other script-related information, and any results of running the revised script Loin a training corpus. The corpus is then incorporated into a machine-learning procedure that teaches the automation engine how to more intelligently customize a script the next time a similar event occurs.

Abstract: A cognitive automation engine receives notice that an unexpected event has occurred in a computing environment. The engine tries to address any resulting problems by running a previously generated automation script, customizing the script as required through cognitive means. If this fails, the engine forwards the script to a human expert for customization. In either case, the engine records any customization activities, extracts parameters from the recording that identify each customization step, cognitively assigns a level of risk to each step based on historical precedent, and determines whether running the customized script presents an unacceptable risk of adverse results. The system adds the revisions, other script-related information, and any results of running the revised script in a training corpus. The corpus is then incorporated into a machine-learning procedure that teaches the automation engine how to more intelligently customize a script the next time a similar event occurs.