Architecture Overview 🏗️
This document provides a high-level architectural overview of ShopVerse, explaining how the system is structured, how services interact, and why specific design decisions were made.
ShopVerse follows a microservices + event-driven architecture, designed to be scalable, secure, and extensible.
🧩 Architectural Style
ShopVerse is built using the following architectural patterns:
- Microservices Architecture
- API Gateway Pattern
- Event-Driven Architecture (EDA)
- Database per Service
- Centralized Authentication
Each pattern is intentionally chosen to reflect real-world backend systems.
🗺️ High-Level System View
Client (Web / Mobile / API)
|
v
API Gateway
(Auth, RBAC, Routing)
|
v
-
## | Auth | User | Product | Order | Payment |
|
v
Apache Kafka
|
v
---
## | Notification | Analytics | Recommendation |
🔐 API Gateway Layer
The API Gateway acts as the single entry point to the system.
Responsibilities:
- JWT validation
- Role-based access control (RBAC)
- Request routing
- Header enrichment (user identity & role)
- Centralized security enforcement
Why Gateway-Based Security?
- Authentication happens once
- Downstream services remain lightweight
- Security logic is not duplicated
- Easier to evolve authentication strategy
⚙️ Core Microservices
Each core service owns:
- A specific business domain
- Its own database
- Its own API contract
Core Services:
- Auth Service – Authentication & token issuance
- User Service – User profiles & addresses
- Product Service – Products, categories, inventory
- Order Service – Order lifecycle management
- Payment Service – Payment processing & status tracking
These services communicate synchronously when required using REST APIs.
📡 Event-Driven Services
ShopVerse uses Apache Kafka for asynchronous communication.
Event-Driven Services:
- Notification Service
- Analytics Service
- Recommendation Service
Why Event-Driven?
- Loose coupling between services
- No cascading failures
- Improved scalability
- Easy to add new consumers
Services publish domain events instead of directly invoking downstream logic.
🗄️ Data Management Strategy
ShopVerse follows the Database-per-Service pattern.
| Service Type | Database |
|---|---|
| Core Services | PostgreSQL |
| Event Consumers | MongoDB |
| Analytics | ClickHouse |
Benefits:
- Data isolation
- Independent scaling
- Clear ownership
- Technology flexibility
🔄 Communication Patterns
| Type | Usage |
|---|---|
| REST | Synchronous operations |
| Kafka | Asynchronous events |
| Eureka | Service discovery |
The system avoids direct database sharing between services.
🧠 Fault Tolerance & Resilience
ShopVerse is designed to handle failures gracefully:
- Services fail independently
- Kafka buffers events during outages
- Retry & idempotency mechanisms
- Centralized exception handling
- Graceful degradation for non-critical flows
📈 Scalability Considerations
- Stateless services allow horizontal scaling
- Kafka consumer groups enable parallel processing
- Databases can be scaled independently
- Gateway handles traffic shaping
🔍 Observability & Debugging
- Structured logging
- Correlation via request tracing
- Centralized error handling
- Actuator health endpoints
🎯 Why This Architecture Works
This architecture ensures:
- Security – centralized and consistent
- Scalability – services scale independently
- Maintainability – clear boundaries
- Extensibility – easy to add new services
- Interview readiness – explainable design decisions
📌 Summary
ShopVerse demonstrates how a real-world e-commerce backend can be designed using modern architectural principles.
Every component exists for a reason, and every interaction is intentional.