This guide explains SpringBoot's built‑in performance monitoring interceptors, demonstrates how to configure them with custom annotations, pointcuts, and advisors, and shows how to extend SimpleTraceInterceptor and CustomizableTraceInterceptor for detailed method‑execution logging and timing.
During high‑traffic load tests, e‑commerce services often hit performance ceilings, leading to low success rates and high latency; by combining tracing data, CPU flame‑graphs, and Alibaba Cloud’s ARMS 3.x JavaAgent features such as Code Hotspots and Adaptive Overload Protection, teams can automatically locate bottlenecks, mitigate traffic spikes, and improve stability without code changes.
This article introduces a variety of Linux command‑line tools used for stress testing and performance monitoring, covering CPU, memory, disk, network, processes, load, temperature and other utilities with brief usage examples and practical tips.
This article explains how to create a front‑end monitoring client that captures global JavaScript errors, tracks resource loading and page performance metrics, intercepts AJAX and fetch requests, gathers PV/UV statistics, and reports data using various strategies such as image beacons, POST, and IndexedDB storage.
This article explains why systematic logging is essential for production debugging, introduces a practical log classification and field schema, describes trace‑ID propagation and performance instrumentation, and walks through building an ELK‑based log collection, storage, and real‑time visualization platform for reliable observability.
After a major release, this article explains the most important Java performance metrics—response time, throughput, average load, error rate, GC pauses, business KPIs, uptime and log volume—and recommends tools to monitor them without relying on raw log files.
