Vtrace’s new continuous profiling feature fills previous Trace blind spots by sampling method‑level execution via JMX, delivering detailed intra‑service insights comparable to leading APM tools while keeping CPU overhead under five percent even at high transaction rates.
This article explains JMX (Java Management Extensions), outlines its typical monitoring and configuration scenarios, details its three‑layer architecture, and provides a practical guide with code examples on defining MBeans, implementing them, and using JConsole to modify bean properties at runtime.
This case study details how Qunar’s engineering team analyzed and resolved severe Kafka production bottlenecks during peak traffic by adding targeted monitoring, tuning thread and filebeat parameters, and validating changes through gray‑scale tests, ultimately saving 2000 CPU cores across three clusters.
This guide shows how to activate Spring Boot's admin features via configuration, customize application shutdown with exit codes and DisposableBean, and monitor startup performance using ApplicationStartup and Actuator endpoints, all illustrated with practical code snippets and screenshots.
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 article explains how to enable JMX for Kafka, retrieve and interpret key metrics such as UnderReplicatedPartitions, and troubleshoot common issues like broker failures, disk outages, and replica lag by examining metric values and related logs.
Learn how to enable and use Spring Boot Actuator's monitoring features—including HTTP and JMX endpoints—configure built‑in endpoints, expose custom metrics, dynamically adjust log levels, and manually register JMX MBeans, with code examples and integration tips for Prometheus and Grafana.
This article explains how to monitor SpringBoot applications using built‑in HTTP actuator endpoints and JMX, demonstrates enabling and exposing specific endpoints, shows how to customize health, loggers, and metrics, and provides step‑by‑step code examples for creating custom monitoring endpoints and manually registering JMX MBeans.
This article provides a comprehensive overview of popular Kafka monitoring solutions—including JMX, Kafka Manager (CMAK), Kafka Eagle, and Logi‑KafkaManager—detailing their features, installation steps, configuration examples, and comparative advantages, while also mentioning custom setups using JMXTrans, InfluxDB, and Grafana.
JVisualVM, bundled with JDK, provides a visual interface to monitor JVM threads, memory, and CPU usage, allowing installation of plugins for GC, thread, and memory analysis, demonstrating how to simulate memory leaks, capture heap dumps, compare snapshots, trace object references, and set up remote Tomcat monitoring via JMX.
This guide explains how to embed the Arthas Java diagnostic console into Spring Boot Admin, covering project setup, Maven resource configuration, external view linking, custom Spring MVC controllers, Arthas Spring Boot plugin adjustments, and JMX exposure via Spring Actuator, along with practical usage notes and known limitations.
This article introduces JVisualVM, explains how to install and use its plugins for monitoring threads, CPU, memory and GC, demonstrates a Java memory‑leak simulation with code and JVM options, shows step‑by‑step analysis of heap dumps, and describes remote Tomcat monitoring via JMX.
This guide introduces JVisualVM, explains its installation and plugin system, demonstrates how to create a memory‑leak example, use VisualGC and sampling tools to identify leaking objects, and shows step‑by‑step remote monitoring of a Tomcat server via JMX, providing practical screenshots and code snippets.
This article introduces JVisualVM, explains its installation and plugin system, demonstrates how to create a memory‑leak test program and analyze the leak using VisualGC and heap dumps, and shows how to configure remote JMX monitoring for a Tomcat server.
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 presents a comprehensive guide to monitoring Hadoop Distributed File System (HDFS) on JD Cloud, covering challenges, recommended toolchains, essential metrics, configuration tips, and real‑world case studies to help engineers ensure reliability and performance of large‑scale data clusters.
To mitigate startup latency spikes in Java-based query services caused by class loading, JIT warm‑up, and lazy resource loading, the article presents a generic, low‑cost pre‑warming component that parses local Dubbo and HTTP logs, filters, samples, and replays traffic, detailing its design, implementation, and performance optimizations.
