This guide explains why Java developers need profiling, introduces IntelliJ IDEA’s built‑in Profiler (powered by Async Profiler and JFR), and provides step‑by‑step instructions with screenshots for CPU, memory, and thread analysis to diagnose slow endpoints, high CPU usage, memory leaks, and concurrency bottlenecks.
The article explains how CPU scheduling works, why tasks can overload the processor, outlines common pitfalls such as dead loops, lock contention, memory leaks, priority inversion and context‑switch overload, and provides a step‑by‑step troubleshooting and remediation guide for Linux systems.
This article analyzes the CPU spikes that occur within minutes after a Java service restart, explains how excessive Runnable threads, frequent context switches, and JIT compiler activity cause the overload, and presents step‑by‑step diagnostics and mitigation strategies such as traffic greying, cache pre‑warming, request‑parameter cleanup, and JVM warm‑up.
This article explains why traditional monitoring tools often fail in production, introduces Arthas as a lightweight, non‑intrusive Java diagnostic solution, and walks through five real‑world scenarios—slow interfaces, thread blockage, memory leaks, hot‑fixes, and data inconsistency—showing exact commands, code snippets, and visualizations to quickly locate and resolve root causes.
This guide explains how to identify the root causes of a server's CPU hitting 100%—whether on a database or an application server—by using cloud monitoring, Linux top commands, thread analysis with jstack, and practical Java code fixes such as limiting loops, optimizing locks, and handling GC pressure.
This article details the optimization of cold startup times in Android applications using ASM and method tracing techniques to improve performance and user experience.
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 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.
This article explains the role of APM in automated operations, outlines the challenges of manual thread diagnostics, and presents a one‑click thread analysis solution with a five‑stage architecture—capture, aggregation, storage, query, and deep analysis—illustrated through multiple real‑world scenarios.
This article walks through a real‑world MySQL 5.7 memory‑leak case, showing how to use performance_schema, pmap, and thread analysis to identify runaway threads and fix the issue by closing unclosed cursors.
