Top 10 Mistakes in Spring Boot Microservices and How to Avoid Them (With Examples)

Spring Boot has become the de facto standard for building microservices due to its simplicity, powerful features, and seamless integration with cloud environments. However, developers often make critical mistakes when designing, implementing, and deploying Spring Boot microservices. These mistakes can lead to performance bottlenecks, scalability issues, security vulnerabilities, and maintainability challenges.

In this article, we will explore the top 10 most common mistakes in Spring Boot microservices and how to avoid them with bad and good code examples.

1️⃣ Not Using API Gateway Properly

In microservices architecture, an API Gateway acts as a single entry point for handling client requests. Many developers skip API gateways, leading to tight coupling and security vulnerabilities.

❌ Bad Approach (Direct Communication)

Client → Service A → Service B → Service C

🔹 Issues:

• Clients directly communicate with multiple services.
• Difficult to manage authentication and authorization.
• Hard to implement logging, monitoring, and rate-limiting.

✅ Good Approach (Using API Gateway - Spring Cloud Gateway)

Spring Cloud Gateway provides centralized routing, security, and monitoring.

@SpringBootApplication
@EnableDiscoveryClient
public class ApiGatewayApplication {
    public static void main(String[] args) {
        SpringApplication.run(ApiGatewayApplication.class, args);
    }
}

application.yml:

spring:
  cloud:
    gateway:
      routes:
        - id: user-service
          uri: lb://USER-SERVICE
          predicates:
            - Path=/users/**

🔹 Benefits:
✔️ Centralized API management.
✔️ Load balancing and rate-limiting.
✔️ Easier security implementation.

2️⃣ Not Handling Circuit Breakers (Service Failure Handling)

A circuit breaker prevents cascading failures when a microservice is down.

❌ Bad Code (No Circuit Breaker)

public String getUsers() {
    return restTemplate.getForObject("http://USER-SERVICE/users", String.class);
}

🔹 Issue: If USER-SERVICE is down, requests keep failing, consuming resources.

✅ Good Code (Using Resilience4j Circuit Breaker)

@CircuitBreaker(name = "userService", fallbackMethod = "fallbackGetUsers")
public String getUsers() {
    return restTemplate.getForObject("http://USER-SERVICE/users", String.class);
}

public String fallbackGetUsers(Exception e) {
    return "User service is currently unavailable. Please try again later.";
}

🔹 Benefits:
✔️ Prevents cascading failures.
✔️ Improves system resilience.

3️⃣ Ignoring Service Discovery (Hardcoding URLs)

Hardcoding service URLs leads to maintenance nightmares.

❌ Bad Code (Hardcoded URLs)

restTemplate.getForObject("http://localhost:8081/users", String.class);

🔹 Issue: If service moves to another port, all clients break.

✅ Good Code (Using Eureka Service Discovery)

@LoadBalanced
@Bean
public RestTemplate restTemplate() {
    return new RestTemplate();
}

public String getUsers() {
    return restTemplate.getForObject("http://USER-SERVICE/users", String.class);
}

🔹 Benefits:
✔️ Dynamic service registration.
✔️ Automatically discovers available instances.

4️⃣ Poor API Versioning Strategy

APIs evolve over time, but many developers ignore proper versioning.

❌ Bad Approach (No Versioning)

@GetMapping("/users")
public List<User> getUsers() { return userService.getAllUsers(); }

🔹 Issue: If API changes, old clients may break.

✅ Good Approach (URI Versioning)

@RestController
@RequestMapping("/api/v1/users")
public class UserController {
    @GetMapping
    public List<User> getUsers() { return userService.getAllUsers(); }
}

🔹 Other Versioning Approaches:
✔️ Header-based (Accept: application/vnd.api.v1+json)
✔️ Query Parameter (/users?version=1)

5️⃣ Not Securing Microservices Properly

Security is often an afterthought in microservices architecture, leading to unauthorized access, data leaks, and security vulnerabilities. It's crucial to implement proper authentication and authorization.

❌ Bad Code (No Authentication)

@GetMapping("/users")
public List<User> getUsers() { 
    return userService.getAllUsers(); 
}

🔹 Issue:

• Any client can access the API without authentication.
• Sensitive data can be exposed, leading to security breaches.

✅ Good Code (Using Spring Security with OAuth2 + JWT)

With the latest Spring Security 6, WebSecurityConfigurerAdapter is deprecated. The correct way to implement security now is by using SecurityFilterChain.

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.security.config.annotation.web.builders.HttpSecurity;
import org.springframework.security.config.http.SessionCreationPolicy;
import org.springframework.security.web.SecurityFilterChain;

@Configuration
public class SecurityConfig {

    @Bean
    public SecurityFilterChain securityFilterChain(HttpSecurity http) throws Exception {
        http
            .csrf(csrf -> csrf.disable())  // Disable CSRF for stateless APIs
            .authorizeHttpRequests(auth -> auth
                .requestMatchers("/api/public/**").permitAll() // Public endpoints
                .anyRequest().authenticated()  // Secure all other endpoints
            )
            .oauth2ResourceServer(oauth2 -> oauth2.jwt()); // Enable JWT authentication

        return http.build();
    }
}

🔹 Benefits:
✔️ Protects API endpoints by enforcing authentication.
✔️ Uses OAuth2 with JWT for secure token-based authentication.
✔️ Stateless authentication, making it scalable for microservices.

By implementing this, your Spring Boot microservices will be secured against unauthorized access, ensuring only authenticated clients can access protected endpoints. 🚀

6️⃣ Not Implementing Centralized Logging

Each microservice logs separately, making debugging hard.

❌ Bad Approach (Local Logs)

Each microservice logs independently, making correlation difficult.

✅ Good Approach (Using ELK - Elasticsearch, Logstash, Kibana)

1. Configure Logstash to collect logs.
2. Store logs in Elasticsearch.
3. Visualize logs in Kibana.

7️⃣ Poor Database Management (One Database for All Services)

Microservices should have separate databases, but many developers share a single database.

❌ Bad Approach (Shared Database)

User Service → Shared DB ← Order Service

🔹 Issue:

• Services are tightly coupled.
• Schema changes affect multiple services.

✅ Good Approach (Database Per Service)

User Service → User DB
Order Service → Order DB

🔹 Benefits:
✔️ Scalability and independence.
✔️ Decentralized data management.

8️⃣ Not Using Asynchronous Communication

Microservices should communicate asynchronously when possible.

❌ Bad Code (Synchronous REST Calls)

restTemplate.getForObject("http://PAYMENT-SERVICE/pay", String.class);

🔹 Issue: If PAYMENT-SERVICE is slow, response time increases.

✅ Good Code (Using Kafka for Asynchronous Messaging)

kafkaTemplate.send("payment-topic", paymentEvent);

🔹 Benefits:
✔️ Decouples microservices.
✔️ Improves scalability.

9️⃣ Ignoring Rate Limiting (Denial-of-Service Vulnerability)

Without rate-limiting, APIs are vulnerable to DDoS attacks.

❌ Bad Code (No Rate Limiting)

@GetMapping("/users")
public List<User> getUsers() { return userService.getAllUsers(); }

🔹 Issue: No protection against high request volumes.

✅ Good Code (Using Resilience4j Rate Limiter)

@RateLimiter(name = "userRateLimiter", fallbackMethod = "rateLimitFallback")
public List<User> getUsers() { return userService.getAllUsers(); }

public List<User> rateLimitFallback(Exception e) {
    return List.of();
}

🔹 Benefits:
✔️ Prevents abuse.
✔️ Ensures service availability.

🔟 Ignoring Containerization & Orchestration

Many developers deploy microservices manually, making scaling difficult.

❌ Bad Approach (Manual Deployment)

JAR files deployed manually on VMs.

🔹 Issue: Difficult to scale and manage.

✅ Good Approach (Docker + Kubernetes)

FROM openjdk:11
COPY target/app.jar app.jar
ENTRYPOINT ["java", "-jar", "/app.jar"]

🔹 Benefits:
✔️ Easier deployment & scaling.
✔️ Better resource utilization.

📌 Conclusion: Build Robust Microservices

By avoiding these top 10 mistakes, you can build scalable, secure, and high-performing Spring Boot microservices.

✔️ Use API gateways for centralized management.
✔️ Implement circuit breakers to prevent failures.
✔️ Use service discovery for dynamic scaling.
✔️ Secure microservices using OAuth2 and JWT.
✔️ Enable centralized logging for better monitoring.
✔️ Adopt asynchronous messaging for better scalability.
✔️ Implement rate limiting to prevent abuse.
✔️ Use containerization (Docker + Kubernetes) for easy deployment.

By following these best practices, you will design microservices that are resilient, maintainable, and scalable! 🚀

📌 Suggested Keywords

🔹 Spring Boot Microservices Mistakes
🔹 Microservices Best Practices
🔹 Spring Cloud Gateway
🔹 Circuit Breaker in Microservices
🔹 Service Discovery in Spring Boot
🔹 OAuth2 Security for Microservices
🔹 Docker & Kubernetes for Microservices
🔹 Asynchronous Messaging in Microservices