performance-optimization

To identify performance bottlenecks, establish a baseline, set a target, profile bottlenecks, and measure improvements. Focus optimization priority on algorithmic improvements, caching, I/O, and memory before attempting micro-optimizations.

Prevent premature optimization by evaluating the necessity of code changes based on the hot path, user impact, complexity cost, and data availability. Always use a measure-first approach to avoid guessing bottlenecks and optimizing the wrong things.

Performance profiling requires measuring API response time, database queries, frontend bundle size, rendering, memory, and build time. Utilize profiling tools and best practices to analyze these metrics and optimize code, databases, and frontend components.

Set performance budgets by defining thresholds for key metrics like API response time and frontend bundle size. Enforce these budgets in your CI pipeline to continuously monitor and prevent performance degradation across your application.

Yes, optimizing application performance requires a basic understanding of performance metrics and optimization techniques. You need to know how to use profiling tools to measure, analyze, and optimize code, databases, and frontend components effectively.