🚀 Introduction

Spring Boot has become the backbone of modern Java development. With Spring Boot 3.5 arriving and Spring Boot 4 on the horizon, developers are exploring cutting-edge features like Virtual Threads, GraalVM native images, reactive APIs, and observability tooling.

In this blog, we will deep dive into advanced technical aspects of Java and Spring Boot in 2025, complete with code snippets, configuration tips, and performance optimization strategies.

⚡ 1. Java 21 + Spring Boot 3.5 = Next-Gen Development

Spring Boot now supports Java 21 LTS. The combination of Project Loom Virtual Threads and structured concurrency allows developers to write scalable APIs with minimal complexity.

Example: REST API with Virtual Threads


@RestController
@RequestMapping("/orders")
public class OrderController {

    @GetMapping("/{id}")
    public String getOrder(@PathVariable String id) {
        try (var executor = Executors.newVirtualThreadPerTaskExecutor()) {
            return executor.submit(() -> processOrder(id)).get();
        } catch (Exception e) {
            throw new RuntimeException(e);
        }
    }

    private String processOrder(String id) {
        return "Order processed: " + id;
    }
}

✅ Why this matters:

Each request runs on a lightweight virtual thread, scaling to millions of concurrent requests.
Less boilerplate, better CPU utilization.

🏗️ 2. GraalVM Native Images for Spring Boot

Microservices often need fast startup time and low memory usage. GraalVM Native Image support in Spring Boot 3.5 delivers exactly that.

Example: Build Native Image


./mvnw -Pnative native:compile
./target/demo

Performance Comparison:

JVM startup: ~1.5s, Memory: 250MB
GraalVM Native: ~0.05s, Memory: 40MB

This makes Spring Boot serverless-ready for AWS Lambda, Azure Functions, and GCP Cloud Run.

🔄 3. Reactive Programming with Spring WebFlux

When building real-time applications, blocking I/O is a bottleneck. Enter Spring WebFlux + Project Reactor.

Example: Reactive REST Endpoint


@RestController
@RequestMapping("/stream")
public class StreamController {

    @GetMapping(produces = MediaType.TEXT_EVENT_STREAM_VALUE)
    public Flux<String> streamEvents() {
        return Flux.interval(Duration.ofSeconds(1))
                   .map(seq -> "Event " + seq);
    }
}

✅ This produces Server-Sent Events (SSE), streaming data reactively to clients.

Use cases:

Live dashboards
Stock tickers
Chat applications

🛡️ 4. Advanced Security in Spring Boot 3.5

Security remains a top concern. Spring Security has introduced OAuth2.1, JWT improvements, and fine-grained authorization.

Example: Securing APIs with JWT


@Bean
SecurityFilterChain security(HttpSecurity http) throws Exception {
    return http
        .csrf().disable()
        .authorizeHttpRequests(auth -> auth
            .requestMatchers("/public/**").permitAll()
            .anyRequest().authenticated()
        )
        .oauth2ResourceServer(oauth2 -> oauth2.jwt())
        .build();
}

Now, any API request must include a valid JWT in the Authorization header.

📊 5. Observability with Micrometer + OpenTelemetry

Modern apps need metrics, tracing, and logs. Spring Boot integrates Micrometer and OpenTelemetry out of the box.

Example: Prometheus Metrics


management:
  endpoints:
    web:
      exposure:
        include: health, metrics, prometheus

Access metrics at:


http://localhost:8080/actuator/prometheus

✅ Export to Grafana dashboards for performance monitoring.

☁️ 6. Microservices with Spring Cloud 2025

Spring Cloud simplifies service discovery, centralized config, and resilience.

Eureka / Consul → Service discovery
Spring Cloud Config → Centralized configs
Resilience4j → Circuit breakers, retries

Example: Circuit Breaker with Resilience4j


@CircuitBreaker(name = "orderService", fallbackMethod = "fallbackOrder")
public String getOrder(String id) {
    return restTemplate.getForObject("http://order-service/orders/" + id, String.class);
}

public String fallbackOrder(String id, Throwable ex) {
    return "Order Service is down. Please try again later!";
}

🤖 7. AI & Spring Boot: The Future

The Spring AI project (experimental) allows integration with LLMs (Large Language Models) like OpenAI, HuggingFace, and Anthropic directly into Spring applications.

Example: Calling AI from Spring


@Autowired
private ChatClient chatClient;

public String askAI(String question) {
    return chatClient.prompt("Explain in simple terms: " + question).call().getResult();
}

✅ Imagine building chatbots, code review assistants, or predictive analytics APIs natively in Spring Boot.

📝 Conclusion

In 2025, Java + Spring Boot is evolving rapidly:

Virtual Threads & GraalVM → high-performance microservices
Reactive WebFlux → real-time APIs
Spring Security + JWT → robust authentication
Observability + OpenTelemetry → production-grade monitoring
Spring AI → bringing machine learning into enterprise apps

If you’re a Java developer, now is the time to embrace these new Spring Boot features and stay ahead of the curve.

🔥 Mastering Spring Boot in 2025: Advanced Java Features, Native Images, and Microservices Best Practices