Presentation
PSP: Live demo - Leveraging GenAI to Analyze Real-Time SMF Data Using Natural Language
DescriptionJoin us for an interactive demonstration showcasing how Generative AI is transforming mainframe operations, performance analysis and problem determination. This session will illustrate how natural language processing capabilities can bridge the gap between complex System Management Facilities (SMF) data and actionable insights, enabling both technical and non-technical users to query and analyze mainframe performance metrics conversationally.
During this live demo, you'll see firsthand how GenAI technology can:
- Interpret natural language queries to extract relevant SMF data in real-time
- Transform complex performance metrics into easily understandable visualizations and summaries
- Identify performance anomalies and trends without requiring deep SMF record structure knowledge
- Generate recommendations based on historical patterns and current system behavior
Whether you're a systems programmer, performance analyst, or IT manager, this demonstration will reveal practical applications for streamlining mainframe operations workflows. Attendees will learn how to leverage conversational AI to reduce the time spent parsing SMF records, accelerate problem diagnosis, and make data-driven decisions about system optimization.
Key Takeaways:
- Understanding how GenAI interprets mainframe-specific terminology and SMF record structures
- Practical use cases for natural language queries in performance management
- Integration considerations for implementing AI-powered SMF analysis in your environment
- Future possibilities for AI-assisted mainframe operations
Target Audience: Mainframe systems programmers, performance analysts, capacity planners, and IT operations managers interested in modernizing their approach to mainframe data analysis.
During this live demo, you'll see firsthand how GenAI technology can:
- Interpret natural language queries to extract relevant SMF data in real-time
- Transform complex performance metrics into easily understandable visualizations and summaries
- Identify performance anomalies and trends without requiring deep SMF record structure knowledge
- Generate recommendations based on historical patterns and current system behavior
Whether you're a systems programmer, performance analyst, or IT manager, this demonstration will reveal practical applications for streamlining mainframe operations workflows. Attendees will learn how to leverage conversational AI to reduce the time spent parsing SMF records, accelerate problem diagnosis, and make data-driven decisions about system optimization.
Key Takeaways:
- Understanding how GenAI interprets mainframe-specific terminology and SMF record structures
- Practical use cases for natural language queries in performance management
- Integration considerations for implementing AI-powered SMF analysis in your environment
- Future possibilities for AI-assisted mainframe operations
Target Audience: Mainframe systems programmers, performance analysts, capacity planners, and IT operations managers interested in modernizing their approach to mainframe data analysis.
Event Type
Sponsored Session
TimeTuesday, February 241:15pm - 2:15pm EST
LocationSalon 23
Partner Sponsored Presentation (PSP)