Use Machine Learning and Topology Hotspots to Isolate Cause of Issues in Minutes Instead of Hours
Project and Program:
Enterprise Data Center,
Data Center Management
Tags:
Proceedings,
2019,
SHARE Pittsburgh 2019
A system issue arises that appears to involve your mainframe, due to the complexity and inter-relationships between subsystems and applications – this often triggers the process of multiple experts, looking at multiple tools, debating over a bridge call to determine the source of the problem. What if there was a way you could automatically scope down the mass of infrastructure data to only that which is relevant for a given issue, then within minutes determine the likely root cause? In this session you will learn how you can use CA Mainframe Operational Intelligence to leverage your system data, such as SMF records, with machine learning algorithms and a new topology hotspot visualizer to automatically surface relevant elements of your infrastructure and associate those with generated insights such as performance anomalies. See how you can quickly visualize your infrastructure from multiple scopes – such as elements within an LPAR or a named application – to reduce RCA from hours to minutes and protect your high value mainframe resources.-David Helsley-Broadcom
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