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This article explains how to replace invasive manual timing code with Java Instrumentation, demonstrating both premain and agentmain approaches, building and attaching agents, using ASM and Bytekit for bytecode enhancement, and leveraging Arthas for runtime tracing and debugging.
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 demonstrates how to replace invasive manual timing code with Java Agent‑based instrumentation, covering the use of java.lang.instrument, premain and agentmain methods, dynamic class retransformation via the Attach API, and practical examples including method‑level timing, runtime class modification, and integration with Arthas for tracing.
The article presents MyPerf4J, a Java‑agent based, low‑overhead performance monitoring library that provides real‑time metrics such as method latency, QPS, memory usage, GC statistics, and class loading, along with quick‑start instructions, configuration details, and open‑source links for Java backend services.
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The article walks through building a custom OpenTelemetry Java‑agent extension for Pulsar client metrics—migrating from SkyWalking, setting up a Gradle project, using ByteBuddy to instrument methods with advice, registering gauge metrics, packaging the jar, handling common class‑loader pitfalls, and configuring deployment via the OpenTelemetry operator.
This article explains the background, principles, loading mechanisms, usage workflow, testing considerations, and advantages of JavaAgent technology for dynamic Java bytecode instrumentation and runtime protection.
MyPerf4J is a Java‑agent based, low‑overhead performance monitoring library that provides real‑time method, memory, GC and class metrics for high‑concurrency, low‑latency applications, offering quick start, configurable properties, and detailed statistical reports for both development and production environments.
This article details the investigation of a SkyWalking thread‑pool plugin enhancement failure caused by multiple AgentClassLoader instances, explains the debugging steps, class‑loading behavior, and provides two practical solutions to ensure proper bytecode instrumentation for ThreadPoolExecutor in Java applications.
MyPerf4J is a Java‑agent based, low‑overhead monitoring solution that provides real‑time method, memory, GC and class metrics, enabling developers to quickly locate performance bottlenecks and assess service capacity in both development and production environments.
This article explains the principles of Interactive Application Security Testing (IAST), details the JavaAgent-based agent instrumentation approach, and provides a step‑by‑step guide to building a Java IAST agent using Javassist, custom class loaders, ThreadLocal tracing, and Maven packaging.
This article describes the background, technology selection, architecture design, data flow, monitoring, logging, and trace collection mechanisms of Qunar's self‑built distributed tracing system, analyzes major performance problems such as Flume interruptions, Kafka bottlenecks, Flink back‑pressure, and presents concrete solutions including sliding‑window throttling, CGroup limits, and JavaAgent instrumentation, ultimately improving trace connectivity and system observability.
This article explains how to use Java bytecode instrumentation with ASM and a JavaAgent to automatically monitor, capture, and report exceptions across a backend system, covering exception fundamentals, best‑practice handling, and practical implementation steps.
This article explains the Java parent‑delegation model, shows how to implement a custom ClassLoader for class hot‑swap and jar hot‑deployment, demonstrates Java SPI for dynamic service loading, and details building a plugin framework using Java Agent and Javassist for runtime bytecode enhancement.
This article explains Java exception fundamentals, best‑practice handling, and demonstrates how to use ASM bytecode enhancement together with a JavaAgent to automatically capture, monitor, and report exception information in a non‑intrusive way for backend services.
This article explains the Java parent‑delegation model, shows how to implement custom ClassLoaders for class hot‑swap and jar hot‑deployment, demonstrates SPI‑based class replacement, introduces Java Agent premain/agentmain mechanisms, and presents a plugin framework that combines SPI, Java Agent, and Javassist for dynamic enhancement.
The 2017‑initiated vivo distributed tracing system leverages a JavaAgent‑based micro‑kernel architecture, using ByteBuddy for non‑intrusive bytecode instrumentation, a Disruptor lock‑free queue, and Kafka to capture Trace/Span data—including cross‑thread propagation—while employing sampling, degradation, and JVM metrics to ensure 94% adoption stability.
The article explains how to enhance Java bytecode using a javaagent, covering bytecode fundamentals, agent loading during JVM startup, implementation steps, transformation via ClassFileTransformer, and popular tools such as ASM, Javassist, and ByteBuddy for non‑intrusive runtime instrumentation and monitoring.