backend-patterns

Provide standardized Node.js patterns for REST and GraphQL API design.

Updated Mar 31, 2026

Search Tags:#architecture #caching #database #backend #patterns #nodejs #api-design

Ready to run

npx skills add https://github.com/GGEdu/claude-god-mode-template --skill backend-patterns-ggedu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: backend-patterns
Source: https://github.com/GGEdu/claude-god-mode-template/tree/main/skills/backend-patterns
Command: npx skills add https://github.com/GGEdu/claude-god-mode-template --skill backend-patterns-ggedu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Backend development patterns help teams design scalable, maintainable server-side systems by codifying proven patterns and best practices for API design, data access, caching, error handling, and deployment.

Core Features & Use Cases

RESTful and GraphQL API structure templates
Repository, Service, and Middleware patterns for clean architecture
Database query optimization, N+1 prevention, indexing strategies
Caching strategies (Redis, cache-aside)
Error handling, authentication, authorization patterns
Middleware, rate limiting, background jobs, logging and monitoring
Real-world use case: designing a scalable e-commerce API with clean separation layers

Quick Start

Apply these patterns to implement scalable API structures in your Node.js/Next.js project.

Frequently Asked Questions about backend-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I structure a scalable Node.js backend API with clean architecture?▼

Structure a scalable Node.js backend by separating concerns into repository, service, and middleware layers. This clean architecture ensures robust validation, isolated data access, and maintainable REST or GraphQL services.

What is the best way to prevent N+1 query problems in backend database design?▼

Prevent N+1 query problems by applying repository layer patterns with optimized database indexing strategies. These backend patterns ensure efficient data access and reduce redundant queries across distributed or monolithic systems.

How does cache-aside strategy work with Redis for backend APIs?▼

Cache-aside strategy with Redis works by having the backend check the cache before querying the database. If data is missing, the service layer fetches it, stores it in Redis, and returns it to optimize API response times.

Can I use these backend patterns for both monolithic and distributed architectures?▼

You can use these backend patterns for both monolithic and distributed architectures. They specify standardized requirements for service layering, authentication, and observable logging that adapt across different deployment scales.

Where should I handle authentication and error handling in a layered backend?▼

Handle authentication and error handling in the middleware and service layers of a backend. This layered approach standardizes authorization checks and centralizes observable logging across your API endpoints.

What's the best way to design rate limiting and background jobs for e-commerce APIs?▼

Design rate limiting and background jobs by applying standardized middleware patterns within your service architecture. These patterns manage API traffic flow and asynchronous tasks to build scalable e-commerce backends.