performance

Rails Performance Guide

Core Philosophy

• Measure before optimizing
• Optimize for the common case
• Keep solutions simple and maintainable
• Use Rails built-in performance features
• Monitor performance in production

Database Optimization Principles

• Design efficient schemas from the start
• Index foreign keys and queried columns
• Use database-specific features wisely
• Keep queries simple and focused
• Monitor slow query logs

Query Optimization

• Eliminate N+1 queries with includes
• Use select to limit returned columns
• Implement pagination for large datasets
• Use pluck for single column queries
• Batch process large operations

Indexing Strategy

• Index all foreign keys
• Create composite indexes for multi-column queries
• Use partial indexes for filtered queries
• Monitor index usage and effectiveness
• Remove unused indexes

Caching Principles

• Cache at multiple levels
• Use Russian doll caching for nested content
• Implement fragment caching for expensive views
• Cache database queries appropriately
• Monitor cache hit rates

Rails Cache Store

• Use Solid Cache for database-backed caching
• Configure Redis for high-traffic applications
• Set appropriate cache expiration
• Use cache keys that auto-expire
• Monitor cache memory usage

Fragment Caching

• Cache expensive view partials
• Use cache digests for automatic expiration
• Implement conditional caching
• Cache user-specific content carefully
• Profile view rendering times

Query Caching

• Leverage Rails query cache
• Use low-level caching for expensive calculations
• Cache aggregated data
• Implement counter caches
• Update caches strategically

Asset Optimization

• Use Propshaft for simple asset handling
• Implement CDN for asset delivery
• Compress assets appropriately
• Set proper cache headers
• Optimize image sizes

Background Job Performance

• Process heavy operations asynchronously
• Use appropriate queue priorities
• Batch similar operations
• Monitor job queue depth
• Implement job timeouts