Spring Boot simplifies Java development, but even experienced developers can make mistakes that lead to production crashes. These errors, often overlooked during development, can cause downtime, performance issues, or even data loss. In this article, we’ll explore 10 Spring Boot mistakes that can crash production, explain why they happen, and provide practical solutions with code examples. By understanding these pitfalls, you can build robust applications and avoid costly errors.
This guide is designed for intermediate to advanced developers who want to ensure their Spring Boot applications run smoothly in production. Let’s dive into the mistakes and how to fix them.
1. Ignoring Resource Management in Production
Resource leaks, such as unclosed database connections or thread pool exhaustion, are common Spring Boot mistakes that can crash production systems. For example, failing to close resources properly can overwhelm your server, leading to slowdowns or crashes.
Why It Happens: Developers often assume Spring Boot’s auto-configuration handles all resource cleanup. However, improper use of components like RestTemplate or JdbcTemplate can lead to leaks.
Solution: Always manage resources explicitly. Use try-with-resources or ensure proper cleanup in your code. Moreover, configure connection pools like HikariCP correctly to avoid exhaustion.
Code Example: Proper Resource Management
// Bad practice: Not closing resources
JdbcTemplate jdbcTemplate = new JdbcTemplate(dataSource);
jdbcTemplate.execute("SELECT * FROM users");
// Good practice: Using try-with-resources
try (Connection conn = dataSource.getConnection()) {
PreparedStatement stmt = conn.prepareStatement("SELECT * FROM users");
ResultSet rs = stmt.executeQuery();
while (rs.next()) {
// Process results
}
}
Fix: Configure your connection pool in application.properties to limit connections and avoid leaks. For instance:
spring.datasource.hikari.maximum-pool-size=10
spring.datasource.hikari.minimum-idle=5
By managing resources effectively, you prevent crashes caused by resource exhaustion.
2. Misconfiguring Spring Boot’s Auto-Configuration
Spring Boot’s auto-configuration is powerful, but relying on it blindly is a mistake that can crash production. For example, default settings for database connections or thread pools may not suit high-traffic applications.
Why It Happens: Developers often leave auto-configuration untouched, assuming it’s optimized for production. However, defaults like an unlimited thread pool or unoptimized database settings can lead to bottlenecks.
Solution: Customize configurations in application.properties or application.yml. For instance, adjust the server thread pool to handle peak loads.
Code Example: Customizing Tomcat Thread Pool
server.tomcat.threads.max=200
server.tomcat.threads.min-spare=20
External Resource: For more on Spring Boot configuration, check the official Spring Boot documentation.
Fix: Review and override default settings to match your production environment’s needs. As a result, your application will handle traffic spikes without crashing.
3. Neglecting Exception Handling
Failing to handle exceptions properly is a critical Spring Boot mistake that can crash production. Uncaught exceptions can halt request processing or expose sensitive information to users.
Why It Happens: Developers may focus on happy-path scenarios and overlook edge cases. For example, a database timeout or null pointer exception can crash an endpoint if not handled.
Solution: Use global exception handling with @ControllerAdvice to catch and manage errors gracefully. Additionally, log exceptions for debugging.
Code Example: Global Exception Handling
@ControllerAdvice
public class GlobalExceptionHandler {
@ExceptionHandler(Exception.class)
public ResponseEntity<String> handleException(Exception ex) {
// Log the error
log.error("Unexpected error occurred: ", ex);
return new ResponseEntity<>("An error occurred. Please try again.", HttpStatus.INTERNAL_SERVER_ERROR);
}
}
Fix: Implement specific exception handlers for common issues like SQLException or NullPointerException. This approach prevents crashes and improves user experience.
4. Overloading the Database with Inefficient Queries
Inefficient database queries are a common Spring Boot mistake that can crash production by overwhelming your database. For example, fetching large datasets without pagination or running unoptimized joins can cause performance issues.
Why It Happens: Developers may write queries that work in development but fail under production load. Moreover, not using indexes or batch processing exacerbates the problem.
Solution: Use pagination, optimize queries with indexes, and leverage Spring Data JPA’s features like @Query for efficient data access.
Code Example: Paginated Query
@Repository
public interface UserRepository extends JpaRepository<User, Long> {
Page<User> findByActiveTrue(Pageable pageable);
}
// Controller
@RestController
public class UserController {
@Autowired
private UserRepository userRepository;
@GetMapping("/users")
public Page<User> getUsers(@RequestParam(defaultValue = "0") int page,
@RequestParam(defaultValue = "10") int size) {
return userRepository.findByActiveTrue(PageRequest.of(page, size));
}
}
Fix: Always test queries under production-like conditions. On the other hand, consider using tools like EXPLAIN to analyze query performance.
5. Ignoring Logging Best Practices
Poor logging practices can make it hard to diagnose issues, indirectly leading to production crashes. For instance, excessive logging can slow down your application, while insufficient logging leaves you blind to errors.
Why It Happens: Developers may not configure logging levels or use inappropriate logging frameworks, causing performance issues or missing critical logs.
Solution: Use SLF4J with Logback and configure logging levels in application.properties. Moreover, avoid logging sensitive data.
Code Example: Configuring Logging
logging.level.org.springframework=INFO
logging.level.com.yourpackage=DEBUG
logging.file.name=app.log
Fix: Set appropriate logging levels (e.g., INFO for production, DEBUG for development) and use asynchronous logging to minimize performance impact.
6. Not Securing Endpoints Properly
Failing to secure endpoints is a dangerous Spring Boot mistake that can crash production by exposing vulnerabilities. For example, unauthenticated endpoints can allow malicious access, leading to data breaches or system overload.
Why It Happens: Developers may skip security configurations during prototyping and forget to secure them later. As a result, production systems become vulnerable.
Solution: Use Spring Security to enforce authentication and authorization. Additionally, validate all user inputs to prevent injection attacks.
Code Example: Basic Spring Security Configuration
@Configuration
@EnableWebSecurity
public class SecurityConfig {
@Bean
public SecurityFilterChain securityFilterChain(HttpSecurity http) throws Exception {
http
.authorizeHttpRequests((requests) -> requests
.requestMatchers("/public/**").permitAll()
.anyRequest().authenticated()
)
.formLogin((form) -> form
.loginPage("/login")
.permitAll()
)
.logout((logout) -> logout.permitAll());
return http.build();
}
}
Fix: Always secure sensitive endpoints and use HTTPS in production to protect data in transit.
7. Hardcoding Configuration Values
Hardcoding values like database URLs or API keys is a Spring Boot mistake that can crash production when environments change. For instance, a hardcoded database URL will fail if the production database moves.
Why It Happens: Developers may hardcode values for convenience during development, forgetting to externalize them later.
Solution: Use environment variables or application.properties to manage configurations. Moreover, use Spring’s @Value annotation to inject values.
Code Example: Externalizing Configuration
# application.properties
database.url=jdbc:mysql://localhost:3306/mydb
database.username=admin
database.password=${DB_PASSWORD}
@Service
public class DatabaseService {
@Value("${database.url}")
private String dbUrl;
@Autowired
private DataSource dataSource;
public void connect() {
// Use dbUrl for connection
}
}
Fix: Store sensitive data in environment variables or a secure vault to prevent crashes and improve security.
8. Not Handling Concurrent Requests Properly
Ignoring concurrency issues is a Spring Boot mistake that can crash production during high traffic. For example, race conditions in shared resources can lead to data corruption or crashes.
Why It Happens: Developers may not test for concurrent scenarios, assuming single-threaded behavior. However, production environments often face multiple simultaneous requests.
Solution: Use Spring’s @Transactional for database operations and synchronize critical sections when necessary.
Code Example: Handling Concurrency
@Service
public class OrderService {
@Autowired
private OrderRepository orderRepository;
@Transactional
public void processOrder(Order order) {
// Ensure atomic updates
orderRepository.save(order);
}
}
Fix: Test your application under concurrent loads and use locking mechanisms or optimistic concurrency control to prevent issues.
9. Overusing Synchronous Calls in REST APIs
Making synchronous calls to external services can slow down your Spring Boot application, potentially crashing production under load. For instance, a slow third-party API can block threads and cause timeouts.
Why It Happens: Developers may use RestTemplate for simplicity, not realizing it blocks threads. As a result, the application becomes unresponsive during high traffic.
Solution: Use asynchronous clients like WebClient for non-blocking calls. Additionally, implement timeouts and circuit breakers.
Code Example: Asynchronous API Call with WebClient
@Service
public class ApiService {
@Autowired
private WebClient webClient;
public Mono<String> fetchData() {
return webClient.get()
.uri("https://api.example.com/data")
.retrieve()
.bodyToMono(String.class)
.timeout(Duration.ofSeconds(5));
}
}
Fix: Use reactive programming with Spring WebFlux for high-performance APIs and configure circuit breakers with tools like Resilience4j.
10. Skipping Load Testing Before Production
Deploying a Spring Boot application without load testing is a mistake that can crash production when traffic spikes. For example, untested applications may fail under heavy loads due to unoptimized resources.
Why It Happens: Developers may assume development tests are sufficient, but production environments face different challenges. Consequently, untested applications crash under real-world conditions.
Solution: Use tools like JMeter or Gatling to simulate production traffic. Moreover, monitor performance with tools like Spring Actuator.
Code Example: Enabling Spring Actuator
management.endpoints.web.exposure.include=health,metrics
management.endpoint.health.show-details=always
Fix: Perform load testing with realistic scenarios and monitor key metrics like CPU usage, memory, and response times.
Summary of Spring Boot Mistakes and Fixes
| Mistake | Impact | Fix |
|---|---|---|
| Ignoring Resource Management | Resource exhaustion | Use try-with-resources, configure connection pools |
| Misconfiguring Auto-Configuration | Performance bottlenecks | Customize settings in application.properties |
| Neglecting Exception Handling | Uncaught errors crash system | Implement @ControllerAdvice |
| Inefficient Database Queries | Database overload | Use pagination, optimize queries |
| Poor Logging Practices | Hard to diagnose issues | Configure SLF4J with Logback |
| Not Securing Endpoints | Security breaches | Use Spring Security |
| Hardcoding Configurations | Environment-specific failures | Externalize with application.properties |
| Ignoring Concurrency | Data corruption | Use @Transactional, synchronize resources |
| Overusing Synchronous Calls | Slow responses | Use WebClient for async calls |
| Skipping Load Testing | Crashes under load | Use JMeter, monitor with Actuator |
Conclusion
Avoiding these 10 Spring Boot mistakes that can crash production is crucial for building reliable applications. By managing resources, configuring settings, handling exceptions, and testing thoroughly, you can prevent costly downtime. Moreover, adopting best practices like securing endpoints and optimizing queries ensures your application scales effectively. Start implementing these fixes today to keep your Spring Boot applications running smoothly in production.
For further reading, explore the Spring Boot Reference Documentation for detailed configuration options and best practices.