JavaOne 2026 Session

Summary

Memory-related issues remain a common challenge in Java-based applications, leading to heap exhaustion, performance degradation, and even system failures. Out-of-memory errors are particularly devastating, causing costly downtime.

This session aims to uncover the diagnostic tools and troubleshooting techniques to tackle these issues. We’ll discuss how to collect and analyze different forms of diagnostic data, including heap dumps, GC logs, NMT output, as well as other critical troubleshooting information. We’ll then explore how AI-powered agents, built with LangChain4j, can revolutionize JVM memory troubleshooting. Discover how these agents can rapidly analyze diagnostic data, correlate errors, and suggest actionable steps to resolve issues faster. Concrete examples will show how AI can assist in quickly pinpointing memory issues, reducing downtime, and enhancing performance.

Join us to dive into strategies to troubleshoot memory problems in Java applications.