0 views collected around this technical thread.
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.
This article explains the six Java thread states defined in Thread.State, demonstrates how to use the Arthas diagnostic tool to identify blocked, waiting, or timed‑waiting threads, and provides practical strategies for diagnosing and optimizing thread‑blocking issues in Java applications.
This page compiles a comprehensive collection of tutorial links and video resources covering Chrome extension development, Java performance testing, interface testing, Groovy scripting, various utility videos, and the Arthas diagnostic tool, providing developers with organized references for learning and practice.
This guide introduces Alibaba's open‑source Arthas Java diagnostic tool, explains its installation, outlines common troubleshooting scenarios, and provides detailed examples of core commands such as stack, jad, sc, watch, trace, jobs, logger, dashboard, and redefine for live JVM debugging.
This guide introduces the open‑source Meteor Console, a non‑intrusive Java application diagnostic tool built on Arthas, covering its architecture, installation steps, core features like class querying, method monitoring, thread management, and links to the full microservice project and video tutorials.
The article details a step‑by‑step investigation of an unexpected ~100 ms latency in a Spring Boot‑based channel system, covering network checks, curl measurements, Arthas trace and watch commands, identification of TomcatJarInputStream’s repeated jar‑resource loading caused by Swagger dependencies, and the final fix by upgrading the embedded Tomcat version.
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.
This article details a step‑by‑step investigation of an OutOfMemoryError in a Spring Boot social app, revealing that frequent initialization of a script engine caused massive StringSequence instances via SPI loading, and shows how consolidating the engine eliminated the OOM issue.
This article introduces the open‑source Java diagnostic tool Arthas, explains how to install and run it, showcases common use cases such as CPU spike detection, thread‑pool monitoring, deadlock analysis, and provides practical command examples and code snippets for effective production debugging.
This article documents the step‑by‑step investigation of an unexpected ~100 ms response delay in a Spring Boot channel service, showing how network checks, curl tests, Arthas trace/stack commands, and source analysis revealed a Tomcat‑embed bug caused by Swagger‑ui resources and how upgrading Tomcat resolved the issue.
Java developers must master performance optimization by using tools like Skywalking and Arthas, which leverage Java agents, class-loading and bytecode manipulation (via ByteBuddy/ByteKit) to locate bottlenecks, filter data with OGNL, and fine-tune interface response times in real-time.
This article introduces Arthas, an open‑source Java diagnostic tool from Alibaba, explains its key features, shows how to install it via Maven, and provides step‑by‑step commands for entering the shell, monitoring JVM status, tracing method calls, observing system resources, dynamically redefining code, and connecting to applications using default or Telnet modes.
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 article documents how the Helios scoring service, which originally took several seconds to retrieve a day's worth of data, was optimized from hundreds of milliseconds down to tens of milliseconds by analyzing Arthas trace data and applying multiple code and algorithm improvements.
This tutorial demonstrates how to employ the open‑source Java diagnostic tool Arthas to quickly locate and analyze a high‑CPU problem in a running JVM by leveraging commands such as dashboard, thread, jad, watch, and ognl, complete with code examples and step‑by‑step instructions.
This article shares a Java developer’s six‑year experience with Arthas, detailing how vmtool, hot‑swap, OGNL filtering and various Arthas commands can dramatically improve problem‑diagnosis, reduce log noise, and accelerate debugging in production environments.
The article details a week‑long investigation of a sandbox environment where Spring Boot APIs became unresponsive due to Redis connection pool blocking, describing the use of system tools, JVM thread analysis, and code inspection to identify mis‑configured pool settings and recommending proper connection handling with Spring's RedisTemplate.
This article documents how the Helios scoring service, which processes hundreds of thousands of data points per day, was progressively optimized from several seconds to tens of milliseconds by analyzing Arthas trace data, refactoring loops, reducing object creation, and improving date handling, ultimately revealing that database access becomes the remaining bottleneck.
This article details how a hidden 100 ms delay in a Spring Boot channel system was traced to Tomcat‑embed’s handling of Swagger‑UI resources, diagnosed with Arthas, and resolved by upgrading the embedded Tomcat version.
This article demonstrates how to use Alibaba's open‑source Java diagnostic tool Arthas to quickly locate and fix high CPU usage in a Java application, covering installation, attaching to a JVM, using dashboard, thread, jad, watch, and ognl commands, and interpreting the results.