Optimizing the JVM can be a difficult task, often requiring extensive expertise and effort. In my thesis project, I explored a novel approach to JVM auto-tuning using machine learning (ML) algorithms, by training them with the information gathered f…

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Optimizing Java Virtual Machine (JVM) performance can significantly enhance Java applications. This research explores automating JVM tuning using machine learning (ML) models trained on garbage collection (GC) logs. The study demonstrated that ML could contribute to a 20% improvement in application throughput by adjusting JVM memory-related flags, specifically focusing on young generation size. The promising results suggest ML can simplify and improve JVM tuning even for those without in-depth JVM knowledge.

JVM Tuning with Machine Learning on Garbage Collection Logs – Inside.java

JVM Tuning with Machine Learning on Garbage Collection Logs