CartFlow: Microservice eCommerce Backend

Overview

CartFlow is a backend-focused project built to deeply understand how microservice-based systems work in real-world scenarios. Instead of building a full frontend product, the focus was on designing and implementing independent backend services that could scale, communicate, and evolve separately.

The system was designed around a typical eCommerce domain, with separate services responsible for carts, orders, and products, mimicking how large-scale platforms structure their backend systems.

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What the System Handles

• Product Service: Manages product data, availability, and pricing.
• Cart Service: Handles cart creation, item management, and cart state.
• Order Service: Processes order creation and lifecycle management.
• Caching Layer: Uses Redis to reduce database load and improve response times.
• Inter-Service Communication: Services communicate using APIs.
• API Security: Structured and secure REST APIs designed for service consumption.
• AI Agent: Utilizes Langchain for product fetching & suggestion & adding product into cart.

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Why I Built This

I built CartFlow to go beyond CRUD-based backend projects and understand:

• How large systems split responsibilities across services.
• How services communicate without becoming tightly coupled.
• The real complexity introduced by microservices.
• How caching and messaging affect performance and reliability.

This project was intentionally backend-only, with the goal of learning system design through implementation, not building a market-ready product.

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Tech Stack

• Node.js
• Express.js
• MongoDB
• Redis
• Langchain
• React
• Tailwind CSS

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Why It Was Not Deployed

CartFlow was never meant to be deployed as a production product, and that decision was intentional.

• The microservice setup felt over-engineered without a real business use case.
• Managing multiple services locally highlighted the operational complexity of microservices.
• Without real users or traffic patterns, further scaling would have been artificial.
• A monolithic approach would have been more practical for an actual MVP.

Rather than forcing deployment, I chose to treat CartFlow as a learning-focused system design project, extracting the architectural insights instead of polishing unused infrastructure.

This decision helped me better understand when microservices make sense — and when they don’t.

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Key Takeaways

• Microservices introduce real operational overhead.
• Clear service boundaries are critical for maintainability.
• Caching and async communication significantly improve performance.
• Not every problem needs a distributed architecture.
• Architectural decisions should be driven by real use cases, not trends.

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After Build & Impact

• Gained hands-on experience with microservice architecture.
• Developed a strong intuition for backend scalability tradeoffs.
• Applied learnings to later projects with more practical architectures.
• Improved confidence in backend system design discussions.
• Built a solid foundation for working on platform-level backend systems.

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Future Possibilities

• Convert the system into a modular monolith.
• Add real-world use cases and traffic simulation.
• Introduce service discovery and monitoring.
• Explore containerization and orchestration (Docker, Kubernetes).
• Apply the architecture selectively to suitable projects.