Performance Optimization

Performance Optimization for Rails 8

Overview

Performance optimization focuses on:

• N+1 query detection and prevention
• Query optimization
• Memory management
• Response time improvements
• Database indexing

Quick Start

# Gemfile
group :development, :test do
  gem 'bullet'           # N+1 detection
  gem 'rack-mini-profiler' # Request profiling
  gem 'memory_profiler'  # Memory analysis
end

N+1 Query Detection and Prevention

N+1 queries occur when code loads a collection then makes a separate query for each associated record. The Bullet gem detects these automatically. Fix them with eager loading via includes, preload, or eager_load.

Eager Loading Decision Table

| Method | Use When | |--------|----------| | includes | Most cases (Rails chooses best strategy) | | preload | Forcing separate queries, large datasets | | eager_load | Filtering on association, need single query | | joins | Only need to filter, don't need association data |

Key patterns: Bullet configuration, eager loading methods, scoped eager loading, counter caches, N+1 specs with query count assertions.

See [references/n-plus-one.md](references/n-plus-one.md) for all code examples and patterns.

Query Optimization

Optimize queries by selecting only needed columns, using batch processing for large datasets, and choosing efficient existence checks.

Key Patterns

| Pattern | Bad | Good | |---------|-----|------| | Column selection | User.all.map(&:name) | User.pluck(:name) | | Large iterations | Event.all.each { ... } | Event.find_each { ... } | | Existence checks | .any? / .present? | .exists? | | Collection size | .length (loads all) | .size (smart) |

Database Indexing

Add indexes for: foreign keys, columns in WHERE/ORDER BY/JOIN clauses, and unique constraints. Use composite indexes for multi-column queries. Use partial indexes for filtered subsets.

Query Analysis

Use Event.where(...).explain(:analyze) to inspect query plans. Set up slow query logging via ActiveSupport::Notifications to catch queries over a threshold.

See [references/query-optimization.md](references/query-optimization.md) for all code examples and patterns.

Memory Management and Profiling

Use memory_profiler to detect memory issues. Prefer pluck over loading full AR objects, use find_each for streaming, and use update_all / in_batches for bulk operations.

Rack Mini Profiler

Provides per-request profiling in development. Shows query count, timing, and flamegraphs (with stackprof gem). Access via the profiler badge or ?pp=flamegraph.

See [references/memory-and-profiling.md](references/memory-and-profiling.md) for all code examples and patterns.

Quick Fixes Reference

| Problem | Solution | |---------|----------| | N+1 on belongsto | includes(:association) | | N+1 on hasmany | includes(:association) | | Slow COUNT | Add counter_cache | | Loading all columns | Use select or pluck | | Large dataset iteration | Use find_each | | Missing index on FK | Add index on *_id columns | | Slow WHERE clause | Add index on filtered column | | Loading unused associations | Remove from includes |

Performance Checklist

• [ ] Bullet enabled in development/test
• [ ] No N+1 queries in critical paths
• [ ] Foreign keys have indexes
• [ ] Counter caches for frequent counts
• [ ] Eager loading in controllers
• [ ] Batch processing for large datasets
• [ ] Query analysis for slow endpoints

Workflow

1. Detect -- Enable Bullet, run specs, check Rack Mini Profiler
2. Analyze -- Use explain(:analyze), check slow query logs, profile memory
3. Fix -- Apply the appropriate pattern from the reference files
4. Verify -- Re-run specs, confirm query counts, check profiler

Reference Files

• [references/n-plus-one.md](references/n-plus-one.md) -- N+1 detection, eager loading methods, Bullet config, counter caches, testing patterns
• [references/query-optimization.md](references/query-optimization.md) -- Column selection, batch processing, indexing strategies, EXPLAIN analysis, slow query logging
• [references/memory-and-profiling.md](references/memory-and-profiling.md) -- Memory profiler usage, memory-efficient patterns, Rack Mini Profiler setup, deployment checklist

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ThibautBaissac
• Source: ThibautBaissac/railsai_agents
• License: MIT
• Homepage: https://thibautbaissac.github.io/

Install and usage instructions live in the source repository linked above.