Abstract: Described are techniques for identifying an optimal AIOps solution for resolving issues. An alert to resolve a software development and/or information technology problem is routed to a secondary responder to handle after a primary responder failed to resolve the alert. Key performance indicators in handling the alert for both the primary and secondary responders may then determined. A determination is then made as to how the secondary responder performed in handling the alert in comparison to the primary responder based on the key performance indicators. The results of such a determination are stored as metadata. Furthermore, the matching portions of the runbooks used by the primary and secondary responders are identified and stored as metadata. The machine learning model is then trained to select the best runbook to be used by the secondary responder to handle future alerts based on the saved metadata and the metadata of the corresponding alerts.

Abstract: Described are techniques for identifying an optimal AIOps solution for resolving issues. An alert to resolve a software development and/or information technology problem is routed to a secondary responder to handle after a primary responder failed to resolve the alert. Key performance indicators in handling the alert for both the primary and secondary responders may then determined. A determination is then made as to how the secondary responder performed in handling the alert in comparison to the primary responder based on the key performance indicators. The results of such a determination are stored as metadata. Furthermore, the matching portions of the runbooks used by the primary and secondary responders are identified and stored as metadata. The machine learning model is then trained to select the best runbook to be used by the secondary responder to handle future alerts based on the saved metadata and the metadata of the corresponding alerts.