What is backend-development?

This Claude skill provides a comprehensive framework for building production-ready backend systems using modern technologies like Node.js, Python, Go, and Rust. It focuses on creating scalable, secure, and high-performance architectures by implementing industry best practices in API design, database management, microservices, and DevOps integration.

When should I use backend-development?

backend-development is useful in the following scenarios: • Designing and implementing secure RESTful, GraphQL, or gRPC APIs with robust input validation and error handling. • Architecting scalable microservices and event-driven systems using Docker, Kubernetes, and message queues like Kafka. • Optimizing database performance through schema design, indexing strategies, and caching layers with Redis or PostgreSQL. • Implementing advanced security protocols including OAuth 2.1, JWT authentication, and OWASP Top 10 mitigation strategies. • Establishing automated CI/CD pipelines and observability stacks (Prometheus/Grafana) to ensure seamless production deployments and monitoring.

name	backend-development
description	Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
license	MIT
version	1.0.0

Backend Development Skill

Production-ready backend development with modern technologies, best practices, and proven patterns.

When to Use

Designing RESTful, GraphQL, or gRPC APIs
Building authentication/authorization systems
Optimizing database queries and schemas
Implementing caching and performance optimization
OWASP Top 10 security mitigation
Designing scalable microservices
Testing strategies (unit, integration, E2E)
CI/CD pipelines and deployment
Monitoring and debugging production systems

Technology Selection Guide

Languages: Node.js/TypeScript (full-stack), Python (data/ML), Go (concurrency), Rust (performance) Frameworks: NestJS, FastAPI, Django, Express, Gin Databases: PostgreSQL (ACID), MongoDB (flexible schema), Redis (caching) APIs: REST (simple), GraphQL (flexible), gRPC (performance)

See: references/backend-technologies.md for detailed comparisons

Core Technologies:

backend-technologies.md - Languages, frameworks, databases, message queues, ORMs
backend-api-design.md - REST, GraphQL, gRPC patterns and best practices

Security & Authentication:

backend-security.md - OWASP Top 10 2025, security best practices, input validation
backend-authentication.md - OAuth 2.1, JWT, RBAC, MFA, session management

Performance & Architecture:

backend-performance.md - Caching, query optimization, load balancing, scaling
backend-architecture.md - Microservices, event-driven, CQRS, saga patterns

Quality & Operations:

backend-testing.md - Testing strategies, frameworks, tools, CI/CD testing
backend-code-quality.md - SOLID principles, design patterns, clean code
backend-devops.md - Docker, Kubernetes, deployment strategies, monitoring
backend-debugging.md - Debugging strategies, profiling, logging, production debugging
backend-mindset.md - Problem-solving, architectural thinking, collaboration

Key Best Practices (2025)

Security: Argon2id passwords, parameterized queries (98% SQL injection reduction), OAuth 2.1 + PKCE, rate limiting, security headers

Performance: Redis caching (90% DB load reduction), database indexing (30% I/O reduction), CDN (50%+ latency cut), connection pooling

Testing: 70-20-10 pyramid (unit-integration-E2E), Vitest 50% faster than Jest, contract testing for microservices, 83% migrations fail without tests

DevOps: Blue-green/canary deployments, feature flags (90% fewer failures), Kubernetes 84% adoption, Prometheus/Grafana monitoring, OpenTelemetry tracing

Quick Decision Matrix

Need	Choose
Fast development	Node.js + NestJS
Data/ML integration	Python + FastAPI
High concurrency	Go + Gin
Max performance	Rust + Axum
ACID transactions	PostgreSQL
Flexible schema	MongoDB
Caching	Redis
Internal services	gRPC
Public APIs	GraphQL/REST
Real-time events	Kafka

Implementation Checklist

API: Choose style → Design schema → Validate input → Add auth → Rate limiting → Documentation → Error handling

Database: Choose DB → Design schema → Create indexes → Connection pooling → Migration strategy → Backup/restore → Test performance

Security: OWASP Top 10 → Parameterized queries → OAuth 2.1 + JWT → Security headers → Rate limiting → Input validation → Argon2id passwords

Testing: Unit 70% → Integration 20% → E2E 10% → Load tests → Migration tests → Contract tests (microservices)

Deployment: Docker → CI/CD → Blue-green/canary → Feature flags → Monitoring → Logging → Health checks

Implementation Principles

Avoid over-engineering. Only make changes directly requested or clearly necessary. Keep solutions simple and focused. Do not add features, refactor code, or make improvements beyond what was asked. Start with a monolith and split to microservices only when needed.

Read and understand relevant files before proposing code edits. Do not speculate about code you have not inspected.

Resources

OWASP Top 10: https://owasp.org/www-project-top-ten/
OAuth 2.1: https://oauth.net/2.1/
OpenTelemetry: https://opentelemetry.io/

backend-development

When & Why to Use This Skill

Use Cases