Performance Optimization and Profiling of Go Services Using pprof and trace
The article outlines why high‑load Go services need performance tuning and presents a systematic workflow—preparation, analysis with Linux tools and Go’s pprof/trace, targeted optimizations such as goroutine pooling, Redis MSET, efficient JSON handling and slice resizing—demonstrating how these changes boost throughput, lower latency, and stabilize memory usage while offering broader Go‑specific best‑practice recommendations.
