Learn to identify JVM memory leaks in production by monitoring heap usage, analyzing GC logs, using heap dumps and runtime profiling, and applying prevention patterns such as bounded caches, proper resource cleanup, and safe reference handling to avoid OutOfMemoryError crashes.
During a midnight promotion launch, a forgotten TODO caused thread‑pool exhaustion and frequent Full GC, bringing down an e‑commerce service; the article presents a five‑step end‑to‑end JVM tuning methodology, from data collection to root‑cause verification and code fix, showing how to diagnose and resolve such incidents.
This guide explains the fundamentals of memory leaks in Java, outlines common causes in Spring Boot, and provides step‑by‑step techniques—including GC log analysis, JConsole, VisualVM, MAT, Actuator, custom endpoints, jstack, BTrace, and best‑practice recommendations—to identify, diagnose, and prevent memory leaks for stable long‑running services.
When a production Java service repeatedly restarts and triggers full GC and OutOfMemoryError alerts, this guide shows how to capture heap dumps using JVM flags, install and configure Eclipse Memory Analyzer (MAT), and systematically analyze the dump to pinpoint memory leaks, high usage, and problematic code.
This article explains the various forms of Java OutOfMemoryError, their underlying causes such as heap exhaustion, GC overhead, metaspace limits, and native allocation failures, and provides practical solutions and code snippets to diagnose and resolve each scenario.
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.
This article demonstrates how to use Eclipse Memory Analyzer (MAT) together with heap dump files to diagnose Java OutOfMemoryError issues, covering heap dump generation, histogram and dominator tree analysis, reference chain inspection, OQL queries, and a concrete Spring Boot example.
This guide explains essential Node.js diagnostic techniques—including generating core dumps, capturing heap snapshots, profiling CPU usage, leveraging trace events, and using Diagnostic Reports—providing step‑by‑step commands, flag configurations, and example code to help developers troubleshoot crashes and performance issues in production environments.
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.
In 2020 Tencent's KonaJDK team enhanced Java memory analysis by parallelizing jmap heap scans across multiple garbage collectors, achieving 2‑8× speedups, adding gzipped heap dump support, and contributing dozens of patches and commits to the OpenJDK community.
Learn how to export a live heap dump from a Java service, use JProfiler 9.x to open the .hprof file, identify large objects such as Zipkin's InMemoryReporterMetrics, and pinpoint memory leaks that can consume gigabytes of RAM.
JVisualVM, bundled with JDK, offers a visual interface to monitor JVM threads, memory, CPU usage, and perform heap dumps, enabling developers to detect memory leaks, analyze object references, and remotely monitor applications such as Tomcat, with step-by-step installation, plugin usage, and code examples.
This article explains how to generate a heap dump with jmap, import it into Eclipse Memory Analyzer (MAT), and interpret the various reports such as Histogram, Dominator Tree, Top Consumers, and Leak Suspects to identify memory leaks or insufficient heap sizing in Java applications.
jcmd, introduced in JDK 7, is a powerful built‑in Java diagnostic tool that lets you send commands to running JVMs, replace utilities like jstack and jmap, and perform tasks such as listing processes, printing thread stacks, retrieving heap information, and using Java Flight Recorder.
Learn how to optimize Java applications by configuring six critical JVM parameters—including heap size, Metaspace limits, GC algorithm selection, logging, heap dumps, thread stack size, and network timeouts—while understanding their impact on performance, memory usage, and troubleshooting common out‑of‑memory issues.
This article explains how to avoid thread‑unsafe statistics collection by copying objects per thread, explores Java deep and shallow copying concepts, provides a concrete test program, and uses JConsole and heap dumps to verify the number of object instances created by each copying method.
During a rewrite of a performance testing framework, the author explores Java deep and shallow copying, demonstrates memory analysis using heap dumps and JConsole to visualize object instances, and provides sample code illustrating how to clone objects safely across multiple threads.
This guide shows how to programmatically generate a JVM heap dump using HotSpotDiagnosticMXBean, retrieve the binary file, and analyze it offline with the jhat tool, including code snippets, usage notes, and visualization of memory usage.
This guide explains multiple ways to capture Java heap dumps—including jmap, JVM flags, jcmd, JVisualVM, JMX, and programmatic methods—detailing command syntax, best‑practice options, and step‑by‑step procedures for effective memory‑issue diagnosis.
This article explains Java heap dump files, detailing the concepts of shallow and retained heap, leading sets, dominator trees, and various types of garbage collection roots to help developers analyze memory usage and diagnose OutOfMemoryError issues.
A production Elasticsearch 5.3.2 cluster showed a persistent 80% heap usage due to a hidden memory leak caused by Log4j thread‑local objects retaining large bulk request data, and the article walks through the investigation, heap‑dump analysis, source‑code tracing, and a practical fix using a JVM flag.
This article introduces the Sieve Android memory analysis system, explains why existing tools like LeakCanary and MAT fall short, describes how heap dump files are parsed, GC Roots identified, dominator trees generated, retained sizes calculated, and reference chains constructed to help developers locate memory leaks and OOM causes.
