Applied Machine Learning for Database Autonomous Health

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Speaker: Mark Scardina, Director - Oracle Autonomous Health Framework at Oracle

Applied Machine Learning for Database Autonomous Health

6:00pm - 6:30pm - ODSC Intro, Pizza & Refreshments
6:30pm - 7:20pm - Talk
7:20pm - 7:30pm - Q&A
7:30pm - 8:00pm - Networking

Mark Scardina is currently the Director of Product Management responsible for Oracle Autonomous Health Framework working in the Applied Machine Learning Technologies Group. Previously, he was in charge of the development of Oracle's Trusted Information Exchange having been Oracle's XML Evangelist for Server products and the Group Product Manager for the CORE and XML Development Group. Mark has chaired the Oracle XML Standards committee and participated on the OGC, W3C XSL and DOM Working Groups. He is a frequent speaker at industry trade shows and conferences and is a co-author of 4 software patents and of several books including Oracle Database 10g XML & SQL.

This session focuses on how Oracle is applying various Machine Learning technologies to the area of AI Opts to prevent performance issues and maintain availability. Details about the architectures and algorithms used for this Autonomous Health initiative 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 realtime 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 DevOps processes.

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