Analytics and Data Summit 2020

This session focuses on how Oracle is applying various machine learning technologies to the area of AI Ops to prevent performance issues and maintain availability. Details about the architectures and algorithms used for autonomous operations will be covered for both cloud and on-premise database deployments. Specific operational use cases will be covered detailing the strategies and algorithms used to proactively detect performance degradation through the phases of detection, root-cause analysis and targeted corrective actions. The first section focuses on detection based upon data from the operating system and software layers and how normality can be determined and deviations detected in real-time with the goal of preserving session, database, and infrastructure availability. The second section focuses on detection using log and trace file data were the analysis is based on anomalous events or log record signatures. The final section will cover integration into operations.