0 views collected around this technical thread.
This tutorial explains Java Agent technology, shows how to implement a custom agent using the Instrumentation API and Javassist, integrates it with a Spring Boot 3 application to log API execution time, and provides step‑by‑step packaging and execution instructions.
This article explains the concept of Java Agent, compares it with AOP, and provides step‑by‑step implementations of both premain and agentmain modes, including Maven packaging, VM attachment, class transformation, redefinition, retransformation, and a Javassist example for method timing.
The article introduces Joylive Agent, a Java bytecode‑enhancement framework that implements a proxyless service‑mesh architecture for microservice governance, detailing its background, design principles, plugin system, bytecode manipulation techniques, traffic‑control strategies, multi‑active models, and deployment practices on Kubernetes.
Spring AOP cannot advise non‑bean, static, or internally‑called methods, limiting its use for the Diagnose framework, so the article proposes a Java Agent that transforms bytecode at startup, bypasses proxy constraints, and reliably intercepts private, static, and self‑invoked methods across separate class loaders.
Explore three Spring AOP implementation methods—dynamic proxy, Java Agent, and AspectJ Maven plugin—by setting up a sample Service, defining aspects, configuring aop.xml and JVM arguments, and comparing their flexibility, performance impact, and compile‑time weaving within a Spring Boot 2.7 environment.
AREX is an open‑source traffic recording and replay platform created by Ctrip that enables comprehensive testing—from performance and regression to rapid issue fixing—by capturing real traffic across complex micro‑service environments, addressing challenges such as async context, non‑idempotent calls, authentication, time‑sensitivity, and cache consistency, and offering easy CI/CD integration and large‑scale deployment.
The article introduces AREX, Ctrip’s open‑source traffic recording and replay platform, detailing its background, design decisions, technical challenges such as cross‑thread collection and non‑idempotent interfaces, deployment strategies, best‑practice integration with CI/CD pipelines, and the measurable benefits achieved across thousands of applications.
This article introduces the design and implementation of a remote hot‑deployment component (Mark42/Jarvis) built on Java Agent and an IDEA plugin, analyzes the challenges of dynamic compilation in Spring‑Boot fat‑jar environments, presents solution choices, and shares practical experiences and future directions.
This article explains the background, concepts, implementation details, and practical deployment considerations of Alibaba's open‑source Repeater tool, which enables low‑impact traffic recording and replay in Java backend services using JVM‑Sandbox bytecode enhancement.
This article presents the design, implementation, and operational experience of AREX, a Java‑agent based record‑and‑replay testing platform that captures real production traffic and data to enable fast, cost‑effective automated regression testing for complex backend services.
This article explains how to replace invasive manual timing code with a lightweight Java Agent that leverages the java.lang.instrument API, ASM bytecode manipulation, and the Attach API to measure method execution time, perform dynamic class redefinition, and integrate with tools like Arthas for runtime tracing.
This article describes how the ZhiZhuan B2C backend team built a standardized logging, custom Apollo‑based log agent, Prometheus‑driven alerting service, and first‑responsible‑person mechanism to quickly locate and resolve service timeouts, exceptions, and other production issues, even when working off‑site.
This article describes Qunar's use of traffic recording and replay technology for fault isolation, performance optimization, and upgrade migration, detailing the evolution of their Java‑based agents, the end‑to‑end testing workflow, full‑link stress‑test integration, and the measurable business and performance outcomes.
This article explains the challenges of full‑chain load testing in microservice environments, compares component modification versus bytecode enhancement, selects ByteBuddy as the preferred bytecode library, describes the design and execution of a Java Agent (Sftc‑Agent), and discusses module architecture, class‑loader isolation, and future improvements.
This guide explains how to integrate the open‑source Pyroscope platform with Rainbond to continuously profile microservices, detect CPU bottlenecks and memory leaks, and visualize performance data through its UI and various view modes.
vivo’s “Moonlight Treasure Box” platform records and replays production traffic using a customized Jvm‑Sandbox‑Repeater Java‑Agent, handling GC limits, thread‑pool tracing, data desensitization, deduplication, timestamp alignment, noise reduction and sub‑call matching, while providing plugins, visual call‑chain analysis and coverage metrics that have integrated 200 services, executed over 10 000 sessions, and boosted testing efficiency by more than 80 %.
The stability‑assurance squad built an online load‑testing framework that injects global TraceIds via a Java‑agent, records real‑traffic, routes test writes to shadow databases and caches, enforces automatic stop‑rules, and provides a UI platform, reducing cost, improving capacity insight, and enabling safe fault‑injection drills.
This article explains how to build a Java Agent that leverages bytecode instrumentation, class‑loader mechanisms, and AOP techniques to provide lightweight, configurable performance profiling and monitoring for Java services, covering requirements, technical foundations, implementation steps, and testing procedures.
Youzan’s full‑link tracing system combines a multi‑language SDK, Java Agent dynamic attachment, transparent upgrades, asynchronous context propagation, and a Spark‑based data pipeline that indexes traces in Elasticsearch and stores them in HBase, enabling real‑time diagnostics, log correlation, and future container‑level tracing expansion.
This article explains how to implement Java Instrumentation using a custom Java agent to achieve AOP‑style method timing without Spring, covering Instrument concepts, Maven manifest configuration, Agent entry points, JDK Attach API loading, class file transformers, annotation processing, and integration with QTrace for full‑stack tracing.