Improving schema issue advisor in the Azure SQL database

Abstract

An analysis of the telemetry data in the Azure SQL database reveals that the most frequent anomalies are due to the schema inconsistency errors which impairs normal functioning of the customer applications. We assumed that direct e-mail notifications to the customers could shorten time to resolve the problems. The benefits are first validated by sending e-mail recommendations manually. Then, an improved schema advisor which detects anomalies and automatically sends the appropriate notifications to the customers. Implementation which respects the feedback from the users was accompanied by continuous testing process as a modern way of a new feature development. Evaluation in a prolonged period confirmed the expected benefits.