The article explains the JVM's core components, execution workflow, garbage collection fundamentals—including GC roots and Stop-The-World pauses—and introduces basic tuning tools like VisualVM and Arthas, helping readers grasp where performance optimizations should focus.
This guide introduces JVM performance monitoring by explaining built‑in tools like JConsole and VisualVM, showcasing third‑party solutions such as Arthas, and providing step‑by‑step commands and screenshots to help developers quickly visualize and troubleshoot Java applications.
This article demonstrates how to quickly locate and resolve frequent full GC and CPU spikes in Java backend services by combining Arthas‑integrated async‑profiler flame graphs with VisualVM, GCEasy analysis, and practical step‑by‑step deployment procedures.
This guide explains why frequent garbage collection and heap memory overflow occur in Java applications, demonstrates how to reproduce the issue with a sample program, and walks through various techniques—including jmap histograms, heap dumps, VisualVM analysis, and remote JMX monitoring—to diagnose and resolve out‑of‑memory errors.
A June 15 Full GC alert in a Spring Data Elasticsearch service led to a deep investigation using jstat, jmap, VisualVM, and OQL, revealing massive class loading from ES PO packages caused by per‑request ElasticsearchRestTemplate instances, which exhausted metaspace and triggered repeated garbage collections.
This article introduces VisualVM, a Java profiling tool bundled with the JDK, explains how to install and use its plugins for monitoring CPU, memory, threads, and garbage collection, and demonstrates step‑by‑step memory‑leak detection and remote Tomcat monitoring with code examples.
This tutorial walks Java developers through using VisualVM to monitor JVM threads, memory, and CPU, demonstrates how to create a memory‑leak scenario, generate heap dumps, and interpret VisualVM and Visual GC data to pinpoint memory‑leak root causes.
This article introduces nine Java performance profiling tools—including NetBeans Profiler, JProfiler, GC Viewer, VisualVM, Patty, JRockit Mission Control, Eclipse Memory Analyzer, Java Interactive Profiler, and Profiler4J—explaining their features, usage scenarios, and how they can help developers improve Java application efficiency.
