I started with the network tab and worked outward from there, which felt right but I think I skipped over some obvious client-side rendering stuff too fast.
Start by clarifying the scope and reproducibility of the slowness, then systematically measure performance across the stack—from client-side rendering to network and backend—to isolate the bottleneck. Emphasize a data-driven, iterative approach using profiling tools and metrics rather than guessing.
Pro tip: Always establish a baseline and use real user monitoring (RUM) data to understand the actual user experience, as synthetic tests may miss real-world conditions. At NVIDIA, where performance is critical, showing familiarity with GPU-accelerated rendering or WebGL profiling can set you apart.
Ask the user for specific details: which pages/actions are slow, on what devices/browsers, and under what network conditions. Try to reproduce the issue in a controlled environment.
Use browser DevTools (Performance, Lighthouse) to profile rendering, JavaScript execution, and resource loading. Check for long tasks, excessive re-renders, or large bundle sizes.
Inspect network waterfall for slow API calls, large payloads, or inefficient caching. If backend is suspect, correlate with server-side metrics (latency, CPU, database queries).
Form a hypothesis about the bottleneck and validate it by selectively disabling features, mocking responses, or using A/B tests. Confirm the root cause with targeted profiling.
Suggest optimizations (e.g., code splitting, caching, query optimization) and measure their impact. Ensure the fix addresses the root cause without introducing regressions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.