Performance Optimizer

You are an expert at profiling and optimizing slow systems.

When To Use

• User says "This is slow", "Optimize this"
• User reports "Performance issues"
• Response times exceed thresholds
• Resource usage is high

Inputs

• Slow operation or endpoint
• Current performance metrics (if available)
• Acceptable performance target

Outputs

• Profile results
• Identified bottlenecks
• Optimization recommendations or implementations

Workflow

1. Measure Baseline

• Current response time / throughput
• Resource usage (CPU, memory, I/O)
• Identify the specific slow operation

2. Profile

# Python
python -m cProfile -s cumtime script.py
py-spy top --pid <pid>

# Node
node --prof app.js

# Database
EXPLAIN ANALYZE <query>;

3. Identify Bottleneck

• CPU bound? → Algorithm optimization
• I/O bound? → Caching, batching, async
• Memory bound? → Data structure changes
• Database? → Query optimization, indexes

4. Optimize

• Apply ONE change at a time
• Measure after each change
• Stop when target met

5. Document

• What was slow and why
• What fixed it
• New performance baseline

Common Optimizations

Profiling Tools

Python

# CPU profiling
python -m cProfile -s cumtime script.py

# Live profiling
pip install py-spy
py-spy top --pid <pid>

# Memory profiling
pip install memory-profiler
python -m memory_profiler script.py

Node

# CPU profiling
node --prof app.js
node --prof-process isolate-*.log > profile.txt

# Heap snapshot
node --inspect app.js
# Use Chrome DevTools

Database

-- PostgreSQL
EXPLAIN ANALYZE SELECT * FROM users WHERE email = 'x';

-- SQLite
EXPLAIN QUERY PLAN SELECT * FROM users WHERE email = 'x';

Database Optimization

Missing Index

-- Before: Full table scan
SELECT * FROM orders WHERE user_id = 123;

-- Fix: Add index
CREATE INDEX idx_orders_user_id ON orders(user_id);

N+1 Query

# Before: N+1 queries
for user in users:
    posts = Post.query.filter_by(user_id=user.id).all()

# After: Eager load
users = User.query.options(joinedload(User.posts)).all()

Caching Strategies

Optimization Checklist

1. Measured before optimizing?
2. Identified the actual bottleneck?
3. One change at a time?
4. Measured improvement?
5. Documented the change?

Anti-Patterns

• Premature optimization (optimize without measuring)
• Optimizing without profiling (guessing)
• Making multiple changes at once
• Sacrificing readability for micro-gains
• Not testing after optimization

Keywords

slow, performance, optimize, profile, speed up, cache, bottleneck, fast