AIOUG-NIC Tech Day (RAC Internals & Machine Learning by Sandesh Rao)

Date & Venue: Feb 18^th, 2018 @ Fidelity Gurugram

Key Speaker: Sandesh Rao

Speaker's Profile:- 

Sandesh Rao is a VP running the RAC Assurance Team within RAC Development at Oracle Corporation specializing in performance tuning , high availability , disaster recovery and architecting cloud based solutions using the Oracle Stack. With more than 14 years of experience working in the HA space and having worked on several versions of Oracle with different application stacks he is a recognized expert in RAC , Database Internals , PaaS , SaaS and IaaS solutions , solving Big Data related problems . Most of his work involves working with customers in the implementation of public and hybrid cloud projects in the financial , retailing , scientific , insurance , biotech and the tech space. His current position involves running a team that develops best practices for the Oracle Grid Infrastructure 12c including products like RAC (Real Application Clusters) , Storage (ASM , ACFS)More details at http://bit.ly/1UCL46K 

Session 1: Diagnostics and details on RAC internals

Learn about new diagnostic features in the 12.2 database product, tools on how to read trace and log files, automatically troubleshoot hangs, perform best practices on your stack automatically and how to act on the recommendations. We will cover RAC, ASM basics, the newest features of the diagnostic tools like Trace File Analyzer Collector, orachk, exachk, OSWatcher, Procwatcher, Hang Manager, Cluster Health Monitor and Cluster Health Analyzer. You can use Trace File Analyzer Collector to do all your first failure diagnostic collections and reduce the amount of back and forth with Oracle Support due to 90% of all the files Support needs being included by default.

Session 2: Top 10 new diagnostic features in the 12.2 database product

Session 3: Machine learning in general and different frameworks available, the algorithms we use.

The session will begin on the basics of machine learning and will talk about usecases
like analyzing logfiles using Machine Learning and others. This can also be an open session with questions which people can have. We will also touchbase some of the products and algorithms mentioned here in the blog post below and also cover the algorithms we use, test for analyzing massive amounts of log data using the Autonomous health framework.