Advancing safe deployment with AIOps--introducing Gandalf

"Changes to Azure services and the Azure platform itself are both inevitable and beneficial, to ensure continuous delivery of updates, new features, and security enhancements. However, change is also a primary cause of service regressions that can contribute towards reliability issues--for hyperscale cloud providers, indeed for any IT service provider. As such, it is critical to catch any such problems as early as possible during the development and deployment rollout, to minimize any impact on the customer experience. As part of our ongoing Advancing Reliability blog series, today I've asked Principal Program Manager Jian Zhang from our AIOps team to introduce how we're increasingly leveraging machine learning to de-risk these changes, ultimately to improve the reliability of Azure."--Mark This post includes contributions from Principal Data Scientists Ken Hsieh and Ze Li, Principal Data Scientist Manager Yingnong Dang, and Partner Group Software Engineering Manager Murali Chintalapati.