WAG Management API Service v4

This service provides a comprehensive API for managing WAG (Wide Area Gateway) systems. It handles configuration, monitoring, and control operations for WAG devices in the network infrastructure.

Quick Start

To run the tests using Docker Compose:

docker compose -f docker-compose.test.yml up --build

Project Structure

Core Services and Components

• Services/ - Core service implementations

  • PostgresDb/ - PostgreSQL database operations and models
  • MongoDb/ - MongoDB operations and document models
  • Redis/ - Redis caching and session management
  • Email/ - Email notification service

• ApiValidations/ - Request validation and data sanitization

  • Input validation rules
  • Data sanitization filters
  • Schema validation middleware

• ApiLibrary/ - Common utilities and helper functions

  • Shared functions and utilities
  • Common constants and configurations
  • Helper classes and decorators

Configuration and Settings

• AllConfigs/ - Configuration management

  • Database configurations
  • Service settings
  • Environment-specific configs

• Schemas/ - Data models and schema definitions

  • Request/Response models
  • Database schemas
  • API contract definitions

Docker and Deployment

• DockerApiServices/ - API service Docker configurations

  • API service Dockerfile
  • Service dependencies

• DockerStoreServices/ - Storage service Docker configurations

  • Database service Dockerfiles
  • Storage service dependencies

Error Handling and Events

• ErrorHandlers/ - Error handling and exception management

  • Custom exceptions
  • Error handlers
  • Exception middleware

• ApiEvents/ - Event handling and processing

  • Event listeners
  • Event dispatchers
  • Message queue handlers

Language and Testing

• LanguageModels/ - Localization and language support

  • Language files
  • Translation models
  • i18n configurations

• Ztest/ - Test suite

  • Unit tests
  • Integration tests
  • Test fixtures and utilities

Additional Components

• scripts/ - Utility scripts and tools
  • Deployment scripts
  • Database migrations
  • Maintenance utilities

use arcjet @frontend

Architecture Overview

This project follows a layered architecture with three core services:

Core Services

1. AuthServiceApi: Authentication and authorization
2. EventServiceApi: Event processing and management
3. ValidationServiceApi: Input and schema validation

System Layers

• Dependencies Layer: External dependencies and requirements
• Application Layer: Core business logic
• Service Layer: API implementations
• Test Layer: Testing infrastructure
• Dev Layer: Development utilities
• Root Layer: Configuration and documentation

For detailed architecture documentation, see System Architecture.

Suggested Improvements

The following improvements have been identified to enhance the system:

Infrastructure & Deployment

• Service Isolation: Containerize core services (Auth, Event, Validation)
• API Gateway: Add gateway layer for rate limiting, versioning, and security
• Monitoring: Implement distributed tracing and metrics collection
• Configuration: Move to centralized configuration service with feature flags

Performance & Scaling

• Caching Strategy: Enhance Redis implementation with invalidation patterns
• Database: Implement sharding and read replicas
• Event System: Add message queue (RabbitMQ/Kafka) for event handling
• Background Jobs: Implement job processing and connection pooling

Security & Reliability

• API Security: Implement key rotation and rate limiting
• Error Handling: Add centralized tracking and circuit breakers
• Testing: Add integration tests and performance benchmarks
• Audit: Implement comprehensive audit logging

Development Experience

• Code Organization: Move to domain-driven design
• Documentation: Add OpenAPI/Swagger docs and ADRs
• Internationalization: Create translation management system
• Developer Tools: Enhance debugging and monitoring capabilities

For implementation details of these improvements, see:

• Architecture Documentation
• Detailed Improvement Plan with code examples and implementation timeline

Development Notes with AI-Windsurf

This project uses AI-Windsurf's intelligent note-taking system to maintain comprehensive development documentation. Notes are automatically organized and stored in the /docs/notes/ directory.

Note Structure

• Topic-based Organization: Notes are categorized by topics (architecture, features, bugs, etc.)
• Date Tracking: All notes include creation and modification dates
• Automatic Linking: Related components and documentation are automatically cross-referenced
• Action Items: Tasks and next steps are tracked within notes

Accessing Notes

1. Browse the /docs/notes/ directory
2. Notes are stored in markdown format for easy reading
3. Each note follows a standard template with:
   • Overview
   • Technical details
   • Related components
   • Action items

Adding Notes

Work with AI-Windsurf to add notes by:

1. Describing what you want to document
2. Mentioning related components or previous notes
3. Specifying any action items or follow-ups

The AI will automatically:

• Create properly formatted note files
• Link related documentation
• Update existing notes when relevant
• Track development progress

For detailed documentation about specific components, refer to the corresponding files in the /docs/ directory.