Automated Anomalous Performance Detection Using Machine Learning In IT

Oracle performance issues typically fall into two categories. Either "I've seen this before and it's bad!" or "I've never seen this before. We better check it out!" The good news is, a trained analyst with many years of experience can quickly do an AWR or ASH analysis. The bad news is, this manual approach DOES NOT SCALE! Even an expert can't comfortably monitor hundreds or thousands of databases. And, our rule based systems are relatively simplistic, because they can't capture the complexity and diversity of activity in production Oracle systems. One solution for this unscalable monitoring and analysis problem is to use machine learning. So, in this webinar I'm going to introduce you to the world of applied Machine Learning from an Oracle Professional (DBA/Developer/Manager) perspective. This includes understanding what ML is, why use it and why now.  But the best part is, I will demonstrate how to create an automated anomalous performance detection system! I'll be using industry standard Python with its ML libraries and Jupyter Notebooks. You will be able to download and do everything I do in this webinar! If you have ever wondered how ML can be applied in an IT environment, you don't want to miss this webinar.