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.
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.
The selection of the Java Garbage Collection (GC) algorithm, particularly the Concurrent Mark-Sweep (CMS) GC, impacts application performance. This post details how to analyze CMS GC log files, emphasizing the significance of metrics, events, and phases involved in GC. Tools like GCeasy assist in effective log analysis and optimization.
The choice of Java's Parallel GC algorithm significantly affects application performance. This post covers how to analyze Parallel GC logs, detailing events like Young GC and Full GC, their log formats, and key metrics. Tools like GCeasy simplify log analysis, providing insights and recommendations to optimize garbage collection performance effectively.
ZGC is a low-pause garbage collection algorithm for large memory applications. This post explains how to read ZGC log files, detailing key events, metrics, and methods for enabling logging. It also recommends using tools like GCeasy for analysis and offers tips for tuning ZGC performance to optimize JVM efficiency and stability.