Monitoring

Don’t just be a tool user! Let’s build a frontend error monitoring SDK from scratch. This hands-on guide will walk you through creating your own error tracking system. Why Build Your Own SDK? While there are excellent error monitoring services like Sentry, Rollbar, and Bugsnag, building your own SDK helps you: Understand how error monitoring works under the hood Customize error tracking to your specific needs Learn valuable debugging and monitoring concepts Reduce dependency on third-party services Core Features Our SDK will include: ...

This article summarizes the DEV post “Key Performance Metrics for Web Apps and How to Measure Them,” focusing on the most important signals and how to capture them. Core metrics LCP (Largest Contentful Paint): loading speed; target < 2.5s p75. INP/TTI (Interaction to Next Paint / Time to Interactive): interactivity; target INP < 200ms p75. FCP (First Contentful Paint): first visual response. TTFB (Time to First Byte): server responsiveness. Bundle size & request count: total transferred bytes and requests. Measurement toolbox Lighthouse: automated audits; budgets and suggestions. WebPageTest: multi-location runs, filmstrips, waterfalls. RUM (GA or custom): real-user timing for live traffic. React profiler & perf tools: find slow renders/update frequency. Webpack/Vite bundle analyzer: visualize bundle composition and dead weight. Optimization reminders Ship less JS/CSS; enable tree shaking/code splitting. Compress and cache static assets; serve modern image formats. Trim request count; inline critical CSS for hero; defer non-critical JS. Watch layout stability; reserve space to avoid CLS hits. Set and enforce budgets (JS gz < 200KB, LCP < 2.5s p75, INP < 200ms). Takeaway: Track a small, high-signal set of metrics with both lab (Lighthouse/WPT) and field (RUM) data, then enforce budgets so regressions fail fast.