performance-profiling

Performance profiling collects metrics across backend APIs, Lambda functions, database queries, and frontend rendering to pinpoint where latency occurs. Profile your application to measure p95 latency, cold start times, query duration, and bundle size, then compare against target thresholds to locate optimization opportunities.

Lambda performance profiling captures duration, memory usage, and invocation patterns to identify slow functions. Collect these metrics, analyze execution logs, and apply code optimizations to the hot paths identified in your profiling results.

Query and API profiling captures timing and logs for database calls and API routes in a single workflow. Profile your application end-to-end to correlate slow API responses with expensive database operations, then implement targeted optimizations based on the results.

Yes, performance profiling covers frontend rendering metrics and bundle size adjustments across client layers. Collect TTFB and rendering data, enforce target thresholds for these metrics, and receive actionable guidance for frontend optimization.

Performance profiling supports setting and enforcing target thresholds for p95 latency, TTFB, memory, and error rates. Profile your application, collect metrics against these targets, and generate reports to track compliance over time.

Performance profiling captures memory usage, invocation counts, and latency metrics applicable to both cloud and client layers. Monitor these metrics to reduce resource consumption and identify optimization opportunities across your entire stack.