Building a Spring Boot Microservices Project: Architecture, Workflow, and Learnings

Source: Dev.to

Introduction

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 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 the project.

System 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, reinforcing service boundaries, data isolation, and loose coupling.

Core Services

Each service is a standalone Spring Boot application with its own database schema, deployed and run independently.

Supporting Infrastructure

Request Flow Through the API Gateway

All client requests first hit the API Gateway, which handles routing and forwards requests to the appropriate microservice based on the request path. This hides multiple service URLs/ports from the client, simplifying client‑side logic and improving security.

1. The gateway queries Eureka Server to discover an available instance of the target service.
2. The request is routed to the correct microservice (Job, Company, or Review Service).
3. Each microservice processes the request independently and interacts only with its own database.

Example: Fetching Job Details with Company Information

1. The client calls the Job API through the gateway.
2. Job Service retrieves job data from its database.
3. Using OpenFeign, Job Service synchronously calls Company Service to fetch company details.
4. The aggregated response is returned to the client.

Asynchronous Communication with RabbitMQ

To explore event‑driven architecture, certain actions (e.g., creating or updating core entities) publish events to RabbitMQ. Other services can consume these events without being tightly coupled to the producer, improving resilience, scalability, and reducing direct dependencies. This implementation helped me understand:

• Message queues, producers, and consumers
• Eventual consistency

Centralized Configuration

Spring Cloud Config Server stores all application properties centrally. Each microservice fetches its configuration from the config server at startup, making configuration changes easier and more consistent across the ecosystem.

Observability

For debugging and monitoring in a distributed setup, I explored:

• Centralized logging
• Distributed tracing (using Zipkin‑compatible tracing configuration)

These tools simplify tracing requests as they move across multiple services.

Containerization & Orchestration

All microservices are Dockerized, allowing the system to run consistently across environments. Kubernetes manifests were created to:

• Deploy services and expose them internally
• Manage scaling
• Handle pods, services, port mapping, and service discovery

Working with Kubernetes provided hands‑on experience with deploying multiple microservices within a single cluster.

Repository

The full source code is available at:

Key Takeaways

• Designing proper service boundaries avoids tight coupling.
• Understanding the difference between synchronous (OpenFeign) and asynchronous (RabbitMQ) communication.
• An API Gateway is critical for simplifying client interaction and enhancing security.
• Service discovery enables dynamic environments.
• Centralized configuration simplifies management in distributed systems.
• Challenges such as inter‑service latency, debugging, and configuration management become evident in practice.

Building this project gave me a solid foundation in modern backend architecture using Spring Boot and Spring Cloud, and clarified why certain tools and patterns exist—not just how to use them.