This post shares an experience in optimizing a Java application controlling warehouse robots, addressing performance issues due to long Garbage Collection (GC) pauses. By analyzing GC logs, the team identified excessive heap size and the CMS algorithm as causes. Switching to the G1 GC algorithm successfully reduced pause times, improving overall application performance.
Automatic garbage collection in programming languages like Golang, Java, and Python simplifies memory management but may lead to high CPU usage. This article discusses methods to measure CPU consumption caused by garbage collection, including GC log analysis, monitoring tools, and examining CPU usage by GC threads, enabling performance optimizations for applications.
GC log analysis offers benefits such as reduced GC pause time, cost savings in cloud computing, outage prediction, and valuable metrics for capacity planning. Key steps include enabling GC logs, measuring during peak traffic periods, and utilizing tools like GCeasy and IBM GC visualizer for effective analysis.
yCrash app is a secure and non-intrusive tool designed for instant root cause analysis during production issues. It captures various artifacts like thread dumps and GC logs in real-time and promptly analyzes them to generate a comprehensive root cause analysis report on the dashboard. A video overview is available.
