Limitation Of Springboot

1. High Memory Consumption & Startup Time

• Spring Boot applications can consume more memory compared to traditional Java applications due to embedded servers and extra dependencies.
• Startup time may be slower, especially for large applications with many beans and configurations.

2. Large Deployment Size

• Spring Boot packages dependencies and an embedded server (Tomcat, Jetty, etc.), leading to larger artifact sizes compared to traditional deployments.

3. Complexity in Large-Scale Applications

• While great for microservices, large monolithic applications using Spring Boot can become difficult to manage due to excessive auto-configuration.

4. Limited Control Over Auto-Configuration

• The framework provides auto-configuration, which is convenient but can sometimes lead to unexpected behavior. Fine-tuning and debugging can be tricky.

5. Performance Overhead

• Since Spring Boot comes with many features enabled by default, it may introduce performance overhead. Unused dependencies and auto-configurations should be explicitly excluded.

6. Learning Curve

• While Spring Boot simplifies Spring configuration, new developers may struggle with understanding auto-configuration, dependency management, and Spring ecosystem components.

7. Limited Support for Serverless & Cloud-Native Features

• Compared to frameworks like Quarkus or Micronaut, Spring Boot is not as optimized for serverless or cloud-native applications, leading to longer cold starts in environments like AWS Lambda.

8. Vendor Lock-in with Spring Ecosystem

• Spring Boot works best within the Spring ecosystem, making it harder to migrate to other frameworks without significant code changes.

9. Debugging & Memory Leaks

• Memory leaks and circular dependencies can occur due to incorrect bean management, making debugging challenging in large applications.