Backend Development

mrgoonie's avatarfrom mrgoonie
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[Architecture Design]

When & Why to Use This Skill

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 (REST/GraphQL), database optimization (PostgreSQL/Redis), and cloud-native DevOps patterns.

Use Cases

  • Architecting scalable microservices: Designing distributed systems with event-driven patterns, containerization via Docker, and orchestration using Kubernetes.
  • Implementing secure authentication systems: Building robust identity management using OAuth 2.1, JWT, and RBAC while mitigating OWASP Top 10 vulnerabilities.
  • Database performance tuning: Optimizing complex queries, implementing efficient caching strategies with Redis, and designing ACID-compliant schemas in PostgreSQL.
  • Automating CI/CD pipelines: Setting up automated testing (unit, integration, E2E) and deployment workflows to ensure high code quality and rapid delivery.
  • API Development and Documentation: Designing high-performance internal gRPC services or public-facing REST/GraphQL APIs with strict input validation and rate limiting.
namebackend-development
descriptionBuild 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.
licenseMIT
version1.0.0

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

Reference Navigation

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

Resources