A deep-dive tutorial that shows advanced techniques for using the PerformanceObserver API: feature-detection, buffering, batching and serializing entries, offloading processing to workers, correlating long tasks with frame drops and LCP, production best practices and privacy considerations.
Learn how to use the PerformanceObserver API to capture real-time performance signals (LCP, CLS, long tasks, and more), instrument production apps safely, and turn observations into actionable improvements with concrete examples and case studies.
Learn how to use the PerformanceObserver API to capture real, user-centric performance metrics (LCP, FCP, CLS, FID/INP, long tasks), send them for analysis, set SLOs, and iterate on improvements with code examples, percentile calculations, and real-world optimizations.