System and ai pattern model for actionable alerts for events within a chatops platform

Abstract

In an approach for building a machine learning model that predicts the appropriate action to resolve a malfunction or system error, a processor receives an alert that a malfunction or a system error has occurred. A processor creates a workspace on a ChatOps platform integrated with a chatbot and one or more tools. A processor inputs data relating to the alert in a natural language format. A processor processes the data using a natural language processing algorithm. Responsive to determining a pre-set threshold for outputting the appropriate action is not met, a processor establishes a conversation between two or more support service agents in the workspace. A processor monitors the conversation using the natural language processing algorithm. A processor analyzes a transcript of the conversation using text analytics or pattern matching. A processor creates and trains a machine learning model to predict the appropriate action in future iterations.