Performance Optimization

Performance Optimization

Overview

Premature optimization wastes effort. Always measure, identify the real bottleneck, then improve it with the simplest effective change.

When to Use

• Users report slowness
• Performance budgets or SLOs exist
• Profiling shows hotspots
• Scaling concerns arise

Core Process

1. Define the goal – What latency, throughput, or resource target?
2. Measure – Establish a reliable baseline with realistic load/data.
3. Locate the bottleneck – Profile; do not guess.
4. Improve – Make the smallest change that meaningfully moves the metric.
5. Re-measure – Confirm the improvement and check for regressions.
6. Guard – Add monitoring or tests if the area is critical.

Common Hotspots

• N+1 queries / missing indexes
• Unbounded data fetching
• Excessive serialization or memory allocation
• Synchronous work that can be async or cached
• Frontend re-renders or large bundles
• Lock contention

Principles

• Optimize for the common case
• Prefer algorithmic improvements over micro-optimizations
• Keep changes measurable and reversible
• Document non-obvious performance decisions

Verification

• Before/after numbers exist
• No significant regression in correctness or other metrics
• Monitoring covers the improved path if it is critical