Section 1.1: Neglecting Spring Boot Starters

Common Mistake: A frequent error is overlooking Spring Boot Starters, which are essential dependency descriptors that simplify project setup.

Best Practice: Always investigate the available Spring Boot Starters for your project. For instance, when developing a web application, utilizing spring-boot-starter-web can automatically handle all necessary dependencies, thus saving you considerable time and effort in configuring your project.

Without Spring Boot Starter:

// Manual dependency management required

With Spring Boot Starter:

dependencies {

implementation 'org.springframework.boot:spring-boot-starter-web'

}

Section 1.2: Misusing Spring Profiles

Common Mistake: Improper configuration or failure to use Spring Profiles can complicate the management of application settings across various environments.

Best Practice: Employ Spring Profiles to differentiate configuration data for different environments (development, testing, production). This approach helps maintain organized application properties and ensures that the correct configurations are activated at the appropriate times.

# application-dev.yml

server:

port: 8081

spring:

datasource:

url: jdbc:h2:mem:testdb

username: sa

password: password

Section 1.3: Overlooking Database Connection Pooling

Ignoring database connection pooling can severely affect the performance and scalability of applications crafted with Spring Boot or any other framework. Connection pooling is a method that manages a collection of database connections, allowing multiple clients to share connections rather than opening and closing them for each request.

Common Mistake: Relying excessively on auto-configuration may lead to unanticipated behavior or performance issues, especially when the defaults do not fit your specific requirements.

Some issues you may face include:

• Performance Decline: Opening and closing a database connection for each user request can significantly hinder application speed. Each connection setup entails network overhead, authentication, and transaction initiation, which can add considerable latency.
• Resource Drain: Databases have a cap on the number of concurrent connections they can support. Without connection pooling, your application might exhaust database resources during high load, potentially causing server crashes or rejections of new connections.
• Scalability Limitations: As your application expands and the number of requests increases, managing individual connections for each request will hinder your application's scalability, leading to poor user experiences.

Best Practice: Grasp the auto-configurations that Spring Boot applies and override them when necessary. Spring Boot facilitates connection pooling configuration through its auto-configuration capabilities and support for popular connection pool implementations, such as HikariCP (the default pool provider in Spring Boot 2.x-3.x). To employ HikariCP or another connection pool provider, simply include the relevant dependency in your pom.xml or build.gradle file and configure the pool settings in your application.properties or application.yml file.

spring.datasource.hikari.maximum-pool-size=10

spring.datasource.hikari.minimum-idle=5

spring.datasource.hikari.idle-timeout=10000

Section 1.4: Ignoring Security Measures

Common Mistake: Neglecting to implement appropriate security protocols can expose your application to vulnerabilities.

Best Practice: Integrate Spring Security from the onset. Use it to configure authentication, authorization, and other security aspects per your application’s requirements.

@EnableWebSecurity

public class WebSecurityConfig extends WebSecurityConfigurerAdapter {

@Override

protected void configure(HttpSecurity http) throws Exception {

http

.authorizeRequests()

.antMatchers("/", "/home").permitAll()

.anyRequest().authenticated()

.and()

.formLogin()

.loginPage("/login")

.permitAll()

.and()

.logout()

.permitAll();

}

}

Section 1.5: Failing to Handle Exceptions Properly

Common Mistake: A common error in Spring applications is the inappropriate or excessive catching of exceptions, often through broad try-catch blocks that capture all exceptions indiscriminately, complicating debugging efforts.

Best Practice: To avoid the pitfalls of ineffective exception handling, leverage annotations such as @ControllerAdvice and @ExceptionHandler for appropriate and centralized exception management. These annotations allow developers to establish global exception handlers that catch and process specific exceptions throughout the application, ensuring consistent and informative client responses.

@ControllerAdvice

public class GlobalExceptionHandler {

@ExceptionHandler(value = {Exception.class})

public ResponseEntity handleGenericException(Exception ex, WebRequest request) {

// Log the error details here

return new ResponseEntity<>("An error occurred", HttpStatus.INTERNAL_SERVER_ERROR);

}

@ExceptionHandler(MyException.class)

@ResponseStatus(HttpStatus.BAD_REQUEST)

public void handleMyException(MyException ex) {

// Specific handling for MyException

}

}

Improved Exception Management: By employing @ControllerAdvice, you can create a global exception handler applicable across the entire application. The @ExceptionHandler annotation specifies handlers for various exception types, eliminating the need for repetitive try-catch blocks in controllers and ensuring all exceptions are handled uniformly.

Section 1.6: Inadequate Logging Configuration

Common Mistake: Retaining the default logging setup or logging insufficient or excessive information.

Best Practice: Utilize application.properties or application.yml to set suitable log levels for different packages or classes, enhancing the application's debuggability and monitoring.

logging.level.root=WARN

logging.level.org.springframework.web=DEBUG

logging.level.com.yourapplication=INFO

Section 1.7: Inefficient JPA/Hibernate Usage

Common Mistake: Using JPA or Hibernate without a thorough understanding can lead to poor performance, as seen with the N+1 select issue during entity loading.

Best Practice: Use @EntityGraph to explicitly identify which relationships should be eagerly loaded, avoiding the N+1 issue. Familiarize yourself with lazy loading and eager loading concepts.

@Entity

public class User {

@Id

@GeneratedValue(strategy = GenerationType.AUTO)

private Long id;

@OneToMany(mappedBy = "user", fetch = FetchType.LAZY)

private Set orders;

}

@EntityGraph(attributePaths = { "orders" })

List findAllWithOrders();

Section 1.8: Misconfiguring Embedded Server Settings

Common Mistake: Failing to customize the embedded server configuration in Spring Boot can result in performance or security vulnerabilities.

Best Practice: Adequately configure the embedded server (Tomcat, Jetty, Undertow) based on your application's requirements, including thread pool size, timeouts, and security settings.

server.port=8080

server.servlet.session.timeout=20m

server.tomcat.max-threads=200

Section 1.9: Insufficient Testing Practices

Common Mistake: Not implementing sufficient tests leads to low code coverage and a potentially fragile application.

Best Practice: Spring Boot offers excellent support for various testing types: unit tests, integration tests, system tests, and acceptance tests. Below are examples for each type, utilizing Spring Boot's testing capabilities.

Unit Tests Example:

@SpringBootTest

class UserServiceTest {

@Mock

private UserRepository userRepository;

@InjectMocks

private UserService userService;

@Test

void testAddUser() {

User user = new User("Hannibal");

when(userRepository.save(any(User.class))).thenReturn(user);

User result = userService.addUser(user);

assertNotNull(result);

assertEquals("Hannibal", result.getName());

}

}

Section 1.10: Inappropriate Use of Auto-configuration

Common Mistake: Relying on Spring Boot's extensive auto-configurations without fully understanding their implications can lead to incorrect setups, especially with overlapping configurations from multiple dependencies.

Best Practice: Familiarize yourself with the auto-configurations associated with Spring Boot dependencies included in your project. Use tools like spring-boot:run with the --debug parameter to observe which auto-configurations are applied or excluded. If you identify undesired auto-configurations, exclude them explicitly using the exclude property in the @SpringBootApplication annotation or in your configuration files.

@SpringBootApplication(exclude = {DataSourceAutoConfiguration.class})

public class MyApplication {

public static void main(String[] args) {

SpringApplication.run(MyApplication.class, args);

}

}

Section 1.11: Improper Cache Utilization

Common Mistake: A frequent oversight when implementing caching is failing to manage cache logic appropriately or neglecting to clear the cache as needed, leading to data inconsistency.

Best Practice: Use the @Cacheable annotation with a unique cache key to ensure that cached data is retrieved correctly for each request. This practice prevents data inconsistencies and optimizes the caching system's effectiveness.

@Cacheable(value = "mycache", key = "#id")

public String getMyData(int id) {

return myRepository.findById(id).orElse(null);

}