The article details a week‑long investigation of unresponsive APIs in a sandbox environment, tracing the root cause to Redis connection pool blocking in a Spring Boot service, and presents step‑by‑step debugging, code analysis, configuration fixes, and best‑practice recommendations for proper Redis usage.
A Spring Boot channel service suffered an unexplained 100 ms extra latency, which was traced using Arthas to Tomcat’s handling of META‑INF resources from Swagger’s JAR, and the issue was resolved by upgrading the embedded Tomcat version.
This article shares practical Java performance‑optimization techniques, covering UI and non‑UI latency metrics, baseline data collection, bottleneck discovery with tools like Arthas, chronic issue handling, and a comprehensive set of governance measures ranging from network‑level caching to code‑level refactoring, asynchronous processing, and service splitting to achieve stable sub‑200 ms response times.
This article walks through a real‑world Java logging slowdown, explains how to benchmark the code with JMH, and shows step‑by‑step usage of Arthas commands like monitor, trace, and watch to pinpoint the exact cause of the performance regression.
This article introduces Arthas, a Java online diagnostic tool, explains its instrumentation‑based runtime principle, guides installation on various platforms, and provides a comprehensive command reference—including basic, system, class, and enhancement commands—for effective debugging, monitoring, and performance analysis of Java applications.
This article introduces Alibaba's open‑source Java diagnostic tool Arthas and demonstrates how to address eight common production issues—including locating class JARs, verifying code changes, online debugging without redeployment, monitoring JVM health, generating flame graphs, and finding class instances—through practical command‑line examples and code snippets.
This article describes how a hidden 100 ms latency in a Spring Boot channel service was traced with Arthas, revealing a Tomcat‑embed bug caused by repeated loading of Swagger UI resources, and explains how upgrading Tomcat or Spring Boot eliminates the delay.
This article walks through diagnosing a hidden Excel parsing exception using Arthas, identifies the root cause in header mapping logic, and then explains Java Agent fundamentals before providing a step‑by‑step demo that injects custom code into a running JVM.
A week‑long API freeze in a sandbox environment was traced to Redis connection pool deadlocks caused by missing pool configuration and improper connection handling, and the article walks through the diagnosis with top, jstack, Arthas, and the code changes needed to fix it.
This article explains how Java object behavior is stored in the JVM method area, explores dynamic bytecode manipulation using java.lang.instrument.Instrumentation, demonstrates practical tracing with BTrace, and introduces Arthas as a user‑friendly diagnostic tool for runtime debugging and monitoring.
This guide demonstrates how to replace traditional debugging with Arthas, covering installation of IDEA plugins, quick 5‑minute problem resolution, hot‑deployment using ArthasHotSwap, and advanced time‑tunnel commands for recording and replaying method executions.
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 reviews Arthas’s rapid growth to over 25,000 GitHub stars, highlighting its technical advancements, release highlights, community contributions, usage statistics, and future roadmap, while providing code examples and links to its open‑source repositories and documentation.
This guide explains how to set up Alibaba's open‑source Java diagnostic tool Arthas using four methods—running the jar locally, accessing the Web Console, adding it as a Maven dependency, and deploying via Docker—so developers can quickly troubleshoot bugs in production environments.
This article walks through the step‑by‑step investigation of an unexpected ~100 ms latency in a Spring Boot channel service, using network checks, curl timing, Arthas trace and watch commands to pinpoint a Tomcat‑embed bug caused by Swagger‑UI JAR loading, and then shows how upgrading Tomcat resolves the issue.
After upgrading an internal framework, a company’s UAT environment saw throughput drop from 53.9/s to 6.4/s due to abnormal Feign latency, prompting a deep dive with Arthas profiling, code tracing, and class‑loader analysis that uncovered costly JodaModule loading and class‑loader overhead, leading to targeted fixes that restored and even improved performance.
This guide explains why multiple Netty jar versions cause runtime errors, shows how to use the Arthas tool to inspect loaded classes and methods, and provides Maven commands and pom.xml techniques to locate and eliminate version conflicts in Java backend projects.
Faced with a legacy Dubbo service needing both Dubbo and HTTP protocols and a new Spring Cloud project requiring seamless Feign calls, this article details the challenges, the solution using Dubbo’s SPI Container extension, and how Arthas was employed to diagnose and resolve hidden loading errors.
This article explains how to install and use the Arthas Java diagnostic tool to perform hot‑code updates in the dble middleware, covering environment preparation, decompiling classes, modifying source, recompiling with memory‑compile, and applying the changes via both interactive and non‑interactive commands.
Tracing a large method with Arthas caused a Metaspace OOM because constant‑pool rewrites inflated the Non‑Class space, each rewrite copying a massive StackMapTable, but preserving the original constant‑pool layout in Arthas stops the growth, and exposing off‑heap metrics aids production monitoring.
This article details the step‑by‑step investigation of an unexpected ~100 ms response delay in a Spring Boot‑based channel system, showing how network checks, curl measurements, and deep tracing with the Arthas Java diagnostic tool pinpointed a Tomcat‑embed bug caused by Swagger‑UI resources and how upgrading Tomcat resolved the problem.
This article explains how Java objects store behavior and attributes, describes the JVM method area where method bytecode resides, and demonstrates practical dynamic tracing techniques using java.lang.instrument.Instrumentation, BTrace scripts, and the Arthas diagnostic tool.
This article details ICBC's development of an online diagnostic platform using Arthas, covering the challenges of traditional Java debugging, the architectural design of the platform, gateway, and diagnostic process, as well as real‑world usage results and future outlook.
This article explains how to reproduce a slow‑response SpringBoot service using JMeter, then quickly locate the bottleneck in production by leveraging Alibaba's open‑source Arthas tool and its trace command to analyze the full call chain.
This article demonstrates how the open‑source Java diagnostic tool Arthas can be employed in various production scenarios—such as CPU spikes, class‑loading conflicts, method‑level monitoring, performance bottlenecks, and hot‑code replacement—to rapidly locate and resolve runtime problems without restarting services.
After an AWS network jitter caused lingering slow Redis requests in a Java project using Redisson sentinel, the team traced the issue through source code inspection, custom Prometheus metrics, chaos‑blade testing, and Arthas debugging, ultimately identifying a connection‑pool bug and submitting a fix to Redisson's master branch.
This article explains how Java object behavior is stored in the JVM method area, explores the java.lang.instrument.Instrumentation API for redefining and retransformation of classes, and demonstrates practical dynamic tracing and bytecode manipulation using tools like ASM, BTrace, and Arthas to inject logging and diagnostics at runtime.
This article provides a comprehensive guide to using Arthas for Java backend debugging, covering installation, core trace and watch commands, OGNL expression syntax, practical examples for inspecting method calls, accessing static fields, and integrating with Spring context via advanced command techniques.
The article explains how a Druid 1.1.20 connection pool was throttled to ~10k RPS by fair‑locking in recycle(), and how enabling the unfair lock (setUseUnfairLock(true)) doubled single‑machine TPS, raised CPU usage to near 100 % and boosted cluster throughput by about 70 %.
This article introduces Alibaba’s open‑source Java diagnostic tool Arthas, explains how to install and use it for JVM monitoring, class loading inspection, and performing hot code updates via memory compilation and the redefine command, while noting its limitations.
Using the open‑source Arthas tool, the author traced a Java server’s 99 % CPU usage to two runaway threads, inspected their stack traces, discovered a cyclic bucket in a HashBiMap caused by unsynchronized cache updates, and resolved the issue by adding a synchronized keyword to the cache‑sync method.
This article explains how to use Arthas's tt (TimeTunnel) command to record method parameters, return values, timestamps, and execution details, compare it with the watch command, and replay recorded calls, accompanied by field definitions and a practical Java demo.
This guide explains how to use Arthas's trace command to capture Java method call paths, measure execution time for each node, handle class and method patterns, and highlights its limitations with lambda expressions, providing practical code examples and output analysis.
This tutorial demonstrates how to use Arthas' watch command to monitor Java method entry parameters and return values in real time, explains the required OGNL syntax, shows a practical demo code, and notes performance considerations for online debugging.
This article introduces the Arthas watch command, explains its four observation points and main parameters, and shows how to use OGNL expressions to monitor Java method invocations, including arguments, return values, and exceptions.
The article explains how to safely stop ongoing performance tests without losing data by using JVM termination flags, Arthas to modify static variables or invoke stop(), and provides sample Java code for implementing a graceful termination interface that still records results for reporting.
This article explains how the open‑source Java diagnostic tool Arthas can monitor method execution with the monitor command, describes each monitoring metric, shows how to configure the sampling interval, and demonstrates the impact on response time using a concrete code example.
This article explains how Arthas's redefine command enables hot‑updating of Java classes at runtime, outlines scenarios where redefinition fails, offers tips for uploading compiled .class files, and provides a concrete code example demonstrating the process.
This article introduces the Arthas Java diagnostic tool, explains the powerful ognl command with basic usage examples for inspecting static fields and invoking static methods, and provides a sample Java code snippet illustrating how to apply these techniques in practice.
This article explains the Arthas "sc" (Search‑Class) and "sm" (Search‑Method) commands, showing how they list loaded classes and their methods in a JVM, when they are useful, and why they can often be skipped if source code is available.
This guide explains how to use the Arthas logger command to change Java logger levels on‑the‑fly without restarting the JVM, demonstrates a complete Log4j2 XML configuration, and provides a runnable Java example that continuously emits logs at various levels.
This article compiles Arthas video tutorials and explains the four basic commands—JVM, sysprop, sysenv, and vmoption—detailing what they display, their differences from built‑in JVM tools, and where to find further resources for deeper JVM parameter tuning.
This article explains how the Arthas thread command can reveal detailed JVM thread information—including states, CPU usage, stack traces, and lock status—and provides a practical code demo to help Java developers monitor and diagnose performance issues effectively.
Learn how to install and launch Alibaba’s open‑source Arthas tool, explore its dashboard, run essential commands like thread and watch, and see a practical Java demo, all in a concise step‑by‑step tutorial that gets you debugging Java processes fast.
The author plans to study Arthas, a highly recommended Java diagnostic tool praised by colleagues for its ability to capture method execution details, thread states, and overall performance dashboards, and intends to share an introductory video on a public platform soon.
This article introduces Arthas, an open‑source Java diagnostic tool, explains its key features, demonstrates four practical troubleshooting scenarios with command examples, and shows how to start using it via an IDE plugin or direct download.
This article explains Java thread lifecycle, compares OS generic thread states with Java’s six states, shows how to query thread state via getState(), and introduces debugging tools like jstack and Arthas, helping developers master state transitions and write robust concurrent code.
A Spring Boot channel service suffered an unexplained ~100 ms delay per request, which was traced through network checks, curl timings, and deep Arthas analysis to reveal a Tomcat‑embed bug caused by repeated loading of Swagger static resources, ultimately fixed by upgrading Tomcat.
This guide explains how to use Alibaba's Arthas tool to attach to a running Java process, inspect JVM metrics, execute hot code updates, and troubleshoot production issues without redeploying, covering download, common commands, and step‑by‑step hot‑swap procedures.
This article explains why Dubbo's default thread pool can become exhausted, demonstrates how to reproduce the issue, and shows how to use Arthas's dashboard and thread commands to pinpoint and resolve thread‑pool problems in Java services.
This tutorial demonstrates how to use Alibaba's open‑source Java diagnostic tool Arthas to decompile, modify, and hot‑replace a running class in a production environment, covering the jad, mc, and redefine commands, practical steps, and common pitfalls.
This article explains how Java objects store behavior and state, describes the JVM method area where method bytecode resides, and demonstrates runtime class modification using java.lang.instrument.Instrumentation, BTrace scripts, and the Arthas diagnostic tool to solve real‑world debugging problems.
This article introduces fifteen Alibaba open‑source and cloud tools—including Arthas, Cloud Toolkit, ChaosBlade, and many others—detailing their core features, typical usage scenarios, tutorial resources, and where to obtain them, helping backend developers boost productivity and reliability.
This article explains how to diagnose and manually re‑execute a Spring @Scheduled task that fails to send notifications by using Arthas to obtain the ApplicationContext, invoke the bean method, and reveals that a missing timeout in Hutool caused the original hang.
This article walks Java developers through diagnosing and fixing common problems such as deadlocks and CPU usage spikes, explaining the underlying concepts, showing practical code examples, and demonstrating how to use tools like jps, jstack, JConsole, JVisualVM, and Arthas to pinpoint and prevent performance bottlenecks.
This article walks through using Alibaba Cloud's Cloud Toolkit IDE plugin to configure, package, and deploy a SpringBoot application from IntelliJ IDEA to any server, compares its workflow with native IDEA deployment, and evaluates its core features such as Deploy to Host, Deploy to ECS, file upload, remote terminal, and built‑in Arthas diagnostics.
