JVM Tuning with Machine Learning on Garbage Collection Logs – Inside.java
My name is Yagmur, and I recently completed my master’s degree in ICT Innovation—Embedded Systems at KTH. I had a great thesis opportunity at Oracle Stockholm during the Spring 2024 semester. I am truly grateful for this opportunity and all my colleagues at Oracle, especially my supervisors, Ponam Parhar and Marina Shimchenko. In this blog, I highlight the key points of my thesis. I hope you find it engaging!
As a developer or system administrator, you know how crucial the performance of Java applications can be. It’s not just about writing efficient code; the runtime performance, governed by the Java Virtual Machine (JVM), plays a significant role, too. Optimizing the JVM can be difficult, often requiring extensive expertise and effort. But what if machine learning (ML) could help us in this process?
In my thesis project, I explored a novel approach to JVM auto-tuning using ML algorithms by training them with the information gathered from Garbage Collection (GC) logs. This blog will walk you through my thesis project’s key concepts, methodology, and exciting outcomes.
