A comprehensive microservices architecture for PyAirtable, built with Go and Python, designed for scalability, maintainability, and cloud-native deployment.
PyAirtable is built using a microservices architecture pattern with the following core principles:
- Domain-Driven Design: Each service owns its domain and data
- API-First: RESTful APIs with OpenAPI documentation
- Cloud-Native: Kubernetes-ready with Docker containers
- Observability: Comprehensive logging, metrics, and tracing
- Security: JWT-based authentication with RBAC authorization
| Service | Repository | Language | Purpose |
|---|---|---|---|
| API Gateway | pyairtable-api-gateway-go | Go | Entry point, routing, rate limiting |
| Auth Service | pyairtable-auth-service-go | Go | Authentication, authorization, JWT |
| User Service | pyairtable-user-service-go | Go | User management, profiles |
| Tenant Service | pyairtable-tenant-service-go | Go | Multi-tenancy, organization management |
| Workspace Service | pyairtable-workspace-service-go | Go | Workspace creation, management |
| Permission Service | pyairtable-permission-service-go | Go | RBAC, access control |
| Service | Repository | Language | Purpose |
|---|---|---|---|
| Webhook Service | pyairtable-webhook-service-go | Go | Webhook management, delivery |
| Notification Service | pyairtable-notification-service-go | Go | Email, SMS, push notifications |
| File Service | pyairtable-file-service-go | Go | File upload, storage, processing |
| Library | Repository | Language | Purpose |
|---|---|---|---|
| Go Shared | pyairtable-go-shared | Go | Common Go utilities, middleware |
| Python Shared | pyairtable-python-shared | Python | Common Python utilities, helpers |
- Docker & Docker Compose
- Kubernetes cluster (local or cloud)
- Go 1.21+ (for development)
- Python 3.11+ (for Python services)
-
Clone this repository:
git clone https://github.com/Reg-Kris/pyairtable-microservices.git cd pyairtable-microservices -
Clone all service repositories:
./scripts/clone-all-repos.sh
-
Start local development environment:
docker-compose up -d
-
Run database migrations:
./scripts/run-migrations.sh
For production deployment using Kubernetes:
# Deploy to Kubernetes
kubectl apply -f k8s/
# Or use Helm
helm install pyairtable ./helm/pyairtable-stackEach microservice follows these standards:
- Structure: Standard Go project layout
- Configuration: Environment-based config with validation
- Database: PostgreSQL with migrations
- Caching: Redis for performance
- Monitoring: Prometheus metrics, structured logging
- Testing: Unit tests, integration tests, benchmark tests
- Documentation: OpenAPI/Swagger specifications
- RESTful endpoints following OpenAPI 3.0
- Consistent error responses
- Request/response validation
- Rate limiting and throttling
- API versioning support
- JWT-based authentication
- Role-based access control (RBAC)
- Input validation and sanitization
- SQL injection prevention
- Rate limiting and DDoS protection
graph TB
Client[Client Applications] --> Gateway[API Gateway]
Gateway --> Auth[Auth Service]
Gateway --> User[User Service]
Gateway --> Tenant[Tenant Service]
Gateway --> Workspace[Workspace Service]
Gateway --> Permission[Permission Service]
Gateway --> Webhook[Webhook Service]
Gateway --> Notification[Notification Service]
Gateway --> File[File Service]
Auth --> DB[(PostgreSQL)]
User --> DB
Tenant --> DB
Workspace --> DB
Permission --> DB
Auth --> Cache[(Redis)]
Permission --> Cache
Webhook --> Queue[Message Queue]
Notification --> Queue
- Language: Go 1.21+
- Framework: Gin (HTTP), GORM (ORM)
- Database: PostgreSQL 15+
- Cache: Redis 7+
- Message Queue: Redis Streams / RabbitMQ
- Containerization: Docker
- Orchestration: Kubernetes
- Service Mesh: Istio (optional)
- Load Balancer: NGINX / Traefik
- Monitoring: Prometheus + Grafana
- Logging: ELK Stack / Loki
- CI/CD: GitHub Actions
- Testing: Go testing, Testify
- Documentation: Swagger/OpenAPI
- Code Quality: golangci-lint, SonarQube
- Application metrics via Prometheus
- Business metrics and KPIs
- Infrastructure monitoring
- Custom dashboards in Grafana
- Structured logging with consistent format
- Centralized log aggregation
- Log correlation with trace IDs
- Error tracking and alerting
- Distributed tracing with OpenTelemetry
- Request flow visualization
- Performance bottleneck identification
- Fork the relevant service repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Follow Go conventions and best practices
- Write comprehensive tests (aim for >80% coverage)
- Update documentation for API changes
- Use conventional commit messages
- Ensure all CI checks pass
# Run unit tests
make test
# Run integration tests
make test-integration
# Run benchmarks
make benchmark
# Generate coverage report
make coverage- Issues: Use GitHub Issues in relevant repositories
- Discussions: GitHub Discussions in this repository
- Security: Email [email protected] for security concerns
This project is licensed under the MIT License - see the LICENSE file for details.
Built with modern microservices patterns and cloud-native technologies. Special thanks to the Go and Kubernetes communities for excellent tooling and documentation.
🤖 Generated with Claude Code