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‘Revolutionizing JFR Analysis with AI’ Webinar
Java Flight Recorder (JFR) captures essential Java application events but analyzing vast JFR recordings can be challenging. In a webinar, Ram Lakshmanan discusses how Deterministic AI enhances JFR analysis by converting complex data into structured facts, facilitating quicker and more accurate troubleshooting of JVM performance issues while ensuring data privacy.
‘Deterministic AI for Java Thread Dump Analysis’ Webinar
Java thread dumps are one of the most powerful diagnostic artifacts for understanding application freezes, deadlocks, CPU spikes, and JVM unresponsiveness, but interpreting them accurately is rarely straightforward. Their size, complexity, and sheer volume can make manual analysis overwhelming, especially when troubleshooting production incidents under time pressure. In this webinar, Ram Lakshmanan, Founder of fastThread... Continue Reading →
Restoration Service: Rapid Recovery for Production Incidents
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“GC Log Analysis Using Deterministic AI” webinar
GC logs are essential for JVM performance analysis, but their complexity complicates interpretation. In a recent webinar, Ram Lakshmanan discussed how Deterministic AI can refine GC log analysis, enhancing accuracy and safety while addressing the limitations of traditional AI methods. This approach enables faster, reliable insights for troubleshooting performance issues.
JAX MAINZ 2026 – JAVA NATIVE MEMORY LEAKS & HOW TO FIX THEM
Every May, JAX MAINZ hosts a five-day conference focused on Java and Software Architecture for professionals. This year, architect Ram Lakshmanan discussed "JAVA NATIVE MEMORY LEAKS & HOW TO FIX THEM," addressing the challenges of detecting native memory leaks in Java, providing tools and techniques to identify and resolve these issues effectively.
JAX MAINZ 2026 – MACHINE LEARNING & MICROMETRICS TO FORECAST PRODUCTION PROBLEMS
Every May, JAX MAINZ hosts a five-day conference for Java and Software Architecture professionals. This year, architect Ram Lakshmanan presented on using machine learning and micro-metrics to forecast production issues. His approach highlights nine critical metrics, promoting proactive problem detection and effective root cause analysis through advanced observability techniques.