backend-development-index

Backend Development Master Index

🎯 COMPLETE BACKEND DEVELOPMENT GUIDE

This index provides comprehensive guidance for backend development based on proven patterns from ingestion_orchestration_fastapi_app and ml_inference_fastapi_app.

📋 RULE SELECTION GUIDE - Choose Your Path:

🚀 New Service Development

START HERE: fastapi-microservice-patterns.mdc

• Complete service lifecycle management patterns
• Lifespan context managers for startup/shutdown
• Background task orchestration
• Service health monitoring
• Production deployment patterns

🤖 ML/AI Service Development

START HERE: ml-service-integration.mdc

• GPU resource management patterns
• Model loading and inference optimization
• Async ML processing workflows
• Memory-efficient batch processing
• CUDA acceleration patterns

🔌 API Design & Data Modeling

START HERE: api-design-patterns.mdc

• RESTful endpoint design patterns
• Pydantic model organization
• Request/response validation
• Error handling strategies
• API versioning approaches

🔗 Dependency Management & Architecture

START HERE: fastapi-dependency-injection.mdc

• Circular import prevention
• Dependency injection patterns
• Shared resource management
• Application state management
• Testing with dependencies

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🏗️ ARCHITECTURE DECISION FLOWCHART

Step 1: Service Type Classification

Is your service primarily for:
├── Data Processing/Ingestion → Use `fastapi-microservice-patterns.mdc`
├── ML Inference/Training → Use `ml-service-integration.mdc`  
├── API Gateway/CRUD → Use `api-design-patterns.mdc`
└── Complex Multi-Service → Use ALL rules in sequence

Step 2: Implementation Pattern Selection

For Data Processing:
├── Background Tasks → Celery + Redis patterns (microservice-patterns)
├── Real-time Processing → WebSocket patterns (api-design-patterns)
├── Batch Processing → Job queue patterns (microservice-patterns)
└── File Processing → Async file handling (microservice-patterns)

For ML Services:
├── GPU Inference → Lock patterns (ml-service-integration)
├── Model Serving → FastAPI + torch patterns (ml-service-integration)
├── Batch Inference → Queue patterns (microservice-patterns + ml-integration)
└── Real-time Inference → Streaming patterns (ml-service-integration)

For API Services:
├── CRUD Operations → Repository patterns (api-design-patterns)
├── Complex Queries → Query builder patterns (api-design-patterns)
├── File Uploads → Streaming upload patterns (api-design-patterns)
└── Authentication → JWT patterns (api-design-patterns)