Stream: Suzuka
Time: 10:00 - 10:45
This session provides a beginner-friendly introduction to System Management Facility (SMF), the foundation of performance and capacity analysis on IBM Z systems. I will explain what SMF records are, why they are collected, and how organisations use them to understand system activity, workload behaviour, resource utilisation, performance, and capacity. The session introduces key SMF concepts, including record types, system configuration, CPU utilisation, performance reporting, and how SMF data supports capacity planning, charge back, and cost allocation. Attendees will gain an understanding of common SMF record types, their characteristics, and how performance data is transformed into actionable business insights for optimisation and cost management.
There is currently no attachment for Making Sense of SMF: A Beginner's Guide to Mainframe Performance Data
Meena Chand, MBCS, is a Mainframe Performance & Capacity Graduate Analyst at SMT Data, IBM Champion 2026, and TechChannel Rising Star 2025. Her journey into mainframe began through the GS UK WAVEZ Student Scholarship, which gave her her first introduction to the world of enterprise computing and set her on the path she walks today. Growing up in Nepal, she earned full scholarships from school through to her undergraduate degree, won the National Debate Championship, and eventually made her way to the UK to build a career at the heart of enterprise technology. She holds a Postgraduate degree in Computer Science from the University of Wolverhampton and completed the Open Mainframe Project LFX Mentorship Programme (2025) with the Linux Foundation, contributing to the COBOL Crisis initiative and working to bridge the skills gap in legacy systems vital to global enterprises. At the IBM GS UK Conference 2024, Meena and her team won the prestigious Capture the Flag (CTF) competition, solving real z/OS security and performance challenges. She also holds the IBM Z Xplore All-Star badge, demonstrating advanced proficiency in mainframe technologies. Prior to joining SMT Data, Meena gained over a year of hands-on experience working across IBM i and Power Systems environments, software development, and Industrial Internet of Things (IIoT) solutions. She worked on a range of real-world projects including Smart Hydroponics Control Systems built using Node-RED and MicroPython, AI-powered plant health detection systems, and scalable modules across data analytics and education technology. This breadth of enterprise and emerging technology experience gave her a strong foundation in how critical systems are designed, integrated, and optimised across different platforms. Now specialising in mainframe performance and capacity management at SMT Data, a global leader in this field, her focus is on analysing enterprise-level performance data, supporting capacity planning, and optimising resource utilisation to help organisations make smarter, data-driven decisions. Beyond her technical work, Meena serves as Education Co-Lead at Women in AI UK and is a regular tech speaker, having presented at BCS Hertfordshire, the University of Wolverhampton, Ravensbourne University, Kathmandu University, and Broadway Infosys. She was awarded a fully funded scholarship by Black Talent & Leadership in STEM to complete the DEI Leadership Programme at Homerton College, University of Cambridge, and received the Oxford GEE Award for Technology Leadership and Community Building. She founded the Kisori Scholarship Programme, providing free education and mentorship to underprivileged girls in Nepal, the work closest to her heart. Her motto: Lead with strength. Serve with heart.
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