Java applications utilize two types of memory: Java Heap and Native Memory. The Java Heap stores application objects and is managed by the Garbage Collector, while Native Memory contains essential runtime structures. Understanding these differences aids in diagnosing performance issues and resolving memory-related errors effectively, enhancing application performance and stability.
Native memory leaks in Java are infrequent but challenging to address. This post outlines methods for identifying and troubleshooting leaks, highlighting native memory regions like Metaspace, Threads, and Direct Buffers. By employing tools such as Native Memory Tracking (NMT), developers can effectively diagnose and manage these potential problems.
jPrime is a conference focused on Java and related technologies, organized by the Bulgarian Java User Group with support from major companies. Notable was a workshop by architect Ram Lakshmanan on "GC TUNING: A MASTERPIECE IN PERFORMANCE ENGINEERING" Here is... Continue Reading →
This post discusses the importance of analyzing Garbage Collection (GC) behavior in production environments for application performance, memory troubleshooting, and capacity planning. It addresses challenges in managing numerous JVMs and presents GCeasy's REST API as a solution for automating GC log analysis, offering insightful metrics and secure data handling options.
The JVM offers various garbage collection (GC) algorithms, with the Mark-Sweep-Compact algorithm being fundamental. This method identifies and frees unused memory through three phases: Mark, Sweep, and Compact. Monitoring GC performance is crucial as inefficient tuning can hinder application performance, making tools like GCeasy valuable for analysis and diagnostics.
Automatic Garbage Collection in Java enhances application performance by providing insights through GC Logs. These logs reveal vital details about each GC event, aiding optimization and debugging. Various GC algorithms exist, each with distinct log formats. Tools like GCeasy simplify log analysis, offering metrics, graphs, and recommendations to improve GC efficiency.
Automatic Garbage Collection, introduced in 1962 with Lisp and popularized by Java in 1995, has evolved significantly. Key trends include pause-less GC to eliminate application downtime, improved performance metrics like throughput and latency, self-tuning capabilities for better goal adherence, and AI-assisted tuning tools for enhanced optimization. Future advancements promise substantial improvements.
The post explores the Java Virtual Machine (JVM) and its internal components, focusing on the Heap, Stack, and Garbage Collection (GC). It explains their functions, configuration, and common errors. Additionally, it outlines JVM memory regions and emphasizes the significance of choosing the right GC algorithm to optimize application performance.
The Shenandoah Garbage Collector, introduced by Red Hat for OpenJDK, enhances Java performance through low-pause-time collection. This post details how to analyze Shenandoah GC log files, which provide insights into GC events, timings, and memory reclamation. Tools like GCeasy help interpret these logs for performance optimization and debugging.