Over the past few weeks, I worked on a backend microservices project to deeply understand how real-world distributed systems are designed and built using Spring Boot and Spring Cloud. Instead of creating a single monolithic application, the goal of this project was to break the system into smaller, independent services that can evolve, scale, and fail independently. This article walks through the architecture, overall workflow, and the key technical learnings I gained while building this project.
Project Overview
The system is designed as a Job Portal–style backend consisting of multiple microservices. Each microservice owns its own database and is responsible for a single business capability. This strict separation helped me understand service boundaries, data isolation, and loose coupling—core principles of microservice architecture.
The main services in the project are:
- Job Service – Manages job listings (create, update, fetch jobs)
- Company Service – Manages company profiles and company-related data
- Review Service – Handles company reviews and ratings
Each service is a standalone Spring Boot application with its own database schema, deployed and run independently.
System Architecture
To support communication, scalability, and maintainability, I used several Spring Cloud components and supporting tools:
- Spring Cloud Gateway as a single entry point for all client requests
- Eureka Server for service discovery
- OpenFeign for synchronous inter-service communication
- RabbitMQ for asynchronous, event-driven communication
- Spring Cloud Config Server for centralized configuration management
- Docker for containerizing each microservice
- Kubernetes (K8s) manifests for container orchestration
This combination helped me understand how individual tools fit together to form a complete microservices ecosystem.
Request Flow and Workflow
All client requests first hit the API Gateway. The gateway handles routing and forwards requests to the appropriate microservice based on the request path. Instead of exposing multiple service URLs and ports, the client interacts with a single base URL, which simplifies client-side logic and improves security.
When a request arrives at the gateway:
- The gateway queries Eureka Server to discover the available instance of the target service.
- The request is routed to the correct microservice (Job, Company, or Review Service).
- Each microservice processes the request independently and interacts only with its own database.
For example, when fetching job details along with company information:
- The client calls the Job API through the gateway.
- The Job Service fetches job data from its database.
- Using OpenFeign, the Job Service synchronously calls the Company Service to fetch company details.
- The aggregated response is returned to the client.
Event-Driven Communication with RabbitMQ
In addition to synchronous communication, I introduced RabbitMQ to understand asynchronous, event-driven architecture. Certain actions—such as creating or updating core entities—publish events to RabbitMQ.
Other services can consume these events without tightly coupling themselves to the producer. This approach improves system resilience and scalability, and it reduces direct dependencies between services. Implementing RabbitMQ helped me understand concepts like message queues, producers, consumers, and eventual consistency.
Configuration and Observability
To avoid duplicating configuration across services, I used Spring Cloud Config Server to centralize application properties. Each microservice fetches its configuration from the config server at startup, making configuration changes easier and more consistent.
For observability and debugging in a distributed setup, I explored:
- Centralized logging
- Distributed tracing (using Zipkin-compatible tracing configuration)
These tools made it easier to trace requests as they moved across multiple services.
Containerization and Deployment
Each microservice is Dockerized, allowing the entire system to run consistently across environments. After containerization, I created Kubernetes manifests to deploy services, expose them internally, and manage scaling.
Working with Kubernetes gave me hands-on experience with:
- Pods and Services
- Port mapping and service discovery
- Deploying multiple microservices under a single cluster
Github Repository: https://github.com/nirmalravidas/Spring-Boot-Job-List-Microservice-Application
Key Learnings
This project helped me move beyond theory and truly understand how microservices work in practice. Some of the most important takeaways include:
- How to design proper service boundaries and avoid tight coupling
- The difference between synchronous (OpenFeign) and asynchronous (RabbitMQ) communication
- Why an API Gateway is critical in microservice systems
- How service discovery works in dynamic environments
- The importance of centralized configuration in distributed systems
- Challenges like inter-service latency, debugging, and configuration management
Conclusion
Building this microservices project gave me a solid foundation in modern backend architecture using Spring Boot and Spring Cloud. More importantly, it clarified why certain tools and patterns exist, not just how to use them. This project is a learning-focused implementation, but it closely mirrors real-world system design patterns and has significantly strengthened my understanding of backend and distributed system development.
Top comments (0)