Upgrading to Java 25: How Project Valhalla and Structured Concurrency Redefine Enterprise Performance
Introduction
As we navigate February 2026, Java 25 stands firmly as the current Long-Term Support (LTS) release, marking a pivotal moment for enterprise development. This version isn't just another incremental update; it's a profound leap forward, integrating mature, production-ready features from Project Valhalla and Project Loom that fundamentally redefine how we approach performance, memory management, and concurrent programming. For organizations looking to future-proof their systems, enhance responsiveness, and dramatically reduce operational costs, understanding and adopting the new Java 25 LTS features is no longer optional—it's imperative.
The enterprise landscape of 2026 demands applications that are not only robust and scalable but also exceptionally efficient. Traditional Java object models and concurrency patterns, while powerful, have inherent overheads that can bottleneck high-throughput systems. Java 25 addresses these challenges head-on, offering groundbreaking solutions like Value Objects and Structured Concurrency that promise to unlock new levels of efficiency and developer productivity. This tutorial will guide you through the essentials of upgrading to Java 25, highlighting how these innovations translate into tangible enterprise benefits.
By embracing Java 25, developers gain access to tools that allow them to write clearer, safer, and significantly faster code. We'll explore how Project Valhalla's Value Objects optimize memory layouts and reduce garbage collection pressure, and how Project Loom's Structured Concurrency, paired with Scoped Values, simplifies complex asynchronous operations and improves debugging. Prepare to dive deep into the architectural shifts that make high-performance Java 2026 a reality, ensuring your enterprise applications are ready for the demands of the modern digital world.
Understanding Java 25 LTS features
Java 25 LTS represents the culmination of years of research and development, primarily from Project Valhalla and Project Loom. At its core, Java 25 is designed to address two fundamental challenges in modern enterprise applications: the overhead of object identity and the complexity of concurrent programming. By tackling these, it paves the way for applications that consume less memory, perform computations faster, and are easier to reason about and debug, even under heavy load.
Project Valhalla introduces the concept of "value types" (now formalized as Value Objects in Java 25), which allows developers to define classes whose instances are treated purely by their value, rather than their object identity. This seemingly subtle change has profound implications for memory layout and CPU cache efficiency. Instead of allocating individual objects on the heap with associated metadata and pointers, Value Objects can be laid out "inline" within their containing objects or arrays, much like primitive types. This reduces memory footprint, improves data locality, and significantly lessens the burden on the garbage collector, leading to substantial performance gains, especially in data-intensive applications.
Concurrently, Project Loom’s contributions, specifically Structured Concurrency and Scoped Values, revolutionize how Java handles concurrent tasks. Traditional Java concurrency often leads to "thread leaks," difficult error propagation, and complex cancellation logic. Structured Concurrency, through the StructuredTaskScope API, introduces a hierarchical structure for concurrent operations. Child tasks are bound to a parent scope, ensuring that their lifecycle is managed collectively. This simplifies error handling, guarantees proper resource cleanup, and makes concurrent code far more robust and understandable. Complementing this, Scoped Values offer a safer, more performant alternative to ThreadLocal for passing immutable data down a hierarchy of tasks, crucial for contextual information in microservices and asynchronous processing. These features are critical for any Java structured concurrency tutorial, demonstrating how modern Java tackles the complexities of parallel execution.
Key Features and Concepts
Feature 1: Project Valhalla (Value Objects)
Project Valhalla's Value Objects are a game-changer for memory efficiency and performance. Historically, every instance of a Java class, no matter how simple (e.g., a coordinate pair or an RGB color), has been an object with an identity. This means it resides on the heap, consumes memory for its header, and is accessed via a reference. While flexible, this model can lead to significant overhead when dealing with millions of small, data-only objects. Value Objects, introduced in their finalized form in Java 25, eliminate this overhead for specific types of data.
A Value Object is a class whose instances are defined solely by their state, not by their identity. They are immutable, final, and do not have a separate object header or monitor. This allows the JVM to perform "inline" allocations, where the fields of a Value Object are stored directly within the memory space of its containing object or array, rather than as a separate reference on the heap. This flattening of data structures drastically improves cache locality, reduces memory consumption, and lessens the frequency and duration of garbage collection cycles.
Consider a simple Point class. Before Valhalla, even a point with just two integer coordinates would be a full-fledged object. With Value Objects, it can behave much like a primitive type.
// Traditional class (pre-Valhalla)
public final class PointIdentity {
private final int x;
private final int y;
public PointIdentity(int x, int y) {
this.x = x;
this.y = y;
}
public int x() { return x; }
public int y() { return y; }
// Equals and hashCode based on value
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
PointIdentity that = (PointIdentity) o;
return x == that.x && y == that.y;
}
@Override
public int hashCode() {
return java.util.Objects.hash(x, y);
}
}
// Value Object (Java 25+)
public value class PointValue {
private final int x;
private final int y;
public PointValue(int x, int y) {
this.x = x;
this.y = y;
}
public int x() { return x; }
public int y() { return y; }
// Value Objects implicitly provide value-based equals/hashCode and are final.
// They are also implicitly immutable.
}
The value class keyword signifies to the JVM that instances of PointValue are not distinct entities with unique identities in memory. Instead, their data can be embedded directly. For instance, an array of PointValue objects would be a contiguous block of memory containing x and y coordinates directly, rather than an array of references pointing to separate PointIdentity objects scattered across the heap. This difference is critical for high-performance Java 2026 applications, especially those dealing with large datasets or numerical computations, offering a significant advantage over Java 25 vs Java 21 in terms of memory layout and performance.
Feature 2: Structured Concurrency and Scoped Values
The challenge of writing correct, observable, and debuggable concurrent code has long been a pain point in Java. Traditional approaches, relying on raw threads, CompletableFuture, or ExecutorService, often lead to "unstructured" concurrency where child tasks can outlive their parent, making error propagation, cancellation, and debugging exceedingly difficult. Java 25, building on Project Loom, introduces Structured Concurrency, a paradigm shift that simplifies concurrent programming by treating a group of related tasks as a single unit of work.
Structured Concurrency is primarily implemented through the StructuredTaskScope API. When you create a StructuredTaskScope, any virtual threads (or platform threads) started within that scope are considered children of the scope. The scope acts as a supervisor, ensuring that all child tasks complete (either successfully or with an exception) before the parent task can proceed. This provides a clear, hierarchical structure, making it much easier to reason about the lifecycle of concurrent operations. Error handling becomes localized – if any child task fails, the scope can terminate other running children and propagate the error to the parent. Similarly, if the parent task is cancelled, the scope can automatically cancel its children.
Here’s a conceptual example of StructuredTaskScope:
import java.time.Duration;
import java.util.concurrent.StructuredTaskScope;
import java.util.concurrent.Future;
import java.util.concurrent.Executors;
public class DataAggregator {
public record UserProfile(String userId, String name, int age) {}
public record OrderHistory(String userId, int totalOrders) {}
public UserProfile fetchUserProfile(String userId) throws InterruptedException {
// Simulate network call or database lookup
Thread.sleep(Duration.ofMillis(200));
return new UserProfile(userId, "John Doe", 30);
}
public OrderHistory fetchOrderHistory(String userId) throws InterruptedException {
// Simulate another network call
Thread.sleep(Duration.ofMillis(300));
return new OrderHistory(userId, 5);
}
public String aggregateUserData(String userId) throws Exception {
try (var scope = new StructuredTaskScope.ShutdownOnFailure()) {
Future userFuture = scope.fork(() -> fetchUserProfile(userId));
Future orderFuture = scope.fork(() -> fetchOrderHistory(userId));
scope.join(); // Wait for all subtasks to complete or for one to fail
scope.throwIfFailed(); // Propagate any exception from subtasks
UserProfile profile = userFuture.resultNow();
OrderHistory history = orderFuture.resultNow();
return "User: " + profile.name() + ", Age: " + profile.age() + ", Orders: " + history.totalOrders();
}
}
public static void main(String[] args) throws Exception {
DataAggregator aggregator = new DataAggregator();
System.out.println(aggregator.aggregateUserData("user123"));
}
}
In this example, aggregateUserData concurrently fetches user profile and order history. If either subtask fails, ShutdownOnFailure ensures the other is cancelled, and the exception is propagated to the aggregateUserData caller. This is a core aspect of any Java structured concurrency tutorial.
Complementing Structured Concurrency are Scoped Values. These provide a safe and efficient mechanism for sharing immutable data across a tree of concurrently executing tasks, specifically within the context of a StructuredTaskScope or any virtual thread hierarchy. Unlike ThreadLocal, which is mutable and can lead to memory leaks or unexpected side effects across virtual threads that might be reused by different tasks, ScopedValue is immutable and tied to the dynamic extent of a computation. Once a ScopedValue is bound, its value remains constant for all child tasks for the duration of its binding. This makes it ideal for passing contextual information like correlation IDs, security principals, or transaction IDs in a request-response cycle through a complex call stack without explicit parameter passing.
import java.time.Duration;
import java.util.concurrent.ScopedValue;
import java.util.concurrent.StructuredTaskScope;
import java.util.concurrent.Future;
public class ScopedValueExample {
// Define a ScopedValue to hold the request ID
private static final ScopedValue REQUEST_ID = ScopedValue.newInstance();
public String processSubTaskA() throws InterruptedException {
// Access the request ID shared via ScopedValue
System.out.println("SubTask A processing for Request ID: " + REQUEST_ID.get());
Thread.sleep(Duration.ofMillis(100));
return "Result from A";
}
public String processSubTaskB() throws InterruptedException {
System.out.println("SubTask B processing for Request ID: " + REQUEST_ID.get());
Thread.sleep(Duration.ofMillis(150));
return "Result from B";
}
public String processRequest(String requestId) throws Exception {
// Bind the requestId to the ScopedValue for the duration of this computation
return REQUEST_ID.where(requestId, () -> {
try (var scope = new StructuredTaskScope.ShutdownOnFailure()) {
Future futureA = scope.fork(this::processSubTaskA);
Future futureB = scope.fork(this::processSubTaskB);
scope.join();
scope.throwIfFailed();
return "Main processing for Request ID: " + REQUEST_ID.get() +
" -> A: " + futureA.resultNow() + ", B: " + futureB.resultNow();
}
});
}
public static void main(String[] args) throws Exception {
ScopedValueExample app = new ScopedValueExample();
System.out.println(app.processRequest("REQ-1001"));
System.out.println(app.processRequest("REQ-1002")); // Another request, another binding
}
}
This example demonstrates how REQUEST_ID is bound once at the processRequest level and then safely accessed by processSubTaskA and processSubTaskB without being passed explicitly as a method argument. This significantly cleans up method signatures and prevents accidental mutable state sharing, crucial for robust microservices architecture and efficient Java 25 LTS features.
Implementation Guide
Migrating to Java 25 and leveraging its new features effectively involves a few key steps, from project configuration to applying the new paradigms in your code. Here, we'll walk through a practical example of building a high-performance backend service that uses both Project Valhalla's Value Objects and Structured Concurrency with Scoped Values to handle incoming requests. This scenario often arises in Jakarta EE migration contexts where performance and clarity are paramount.
Step 1: Configure Your Project for Java 25
First, ensure your build system (Maven or Gradle) is configured to use Java 25.
# Ensure you have Java 25 SDK installed and configured
java -version
# Expected output similar to: openjdk version "25" 2026-09-19 LTS
For Maven users, update your pom.xml:
...
25
25
org.apache.maven.plugins
maven-compiler-plugin
3.13.0
25
--enable-preview
...
For Gradle users, update your build.gradle:
// build.gradle
plugins {
id 'java'
}
java {
toolchain {
languageVersion = JavaLanguageVersion.of(25)
}
}
tasks.withType(JavaCompile) {
options.compilerArgs.add('--enable-preview') // If any features are still in preview
}
// For running applications with preview features
tasks.withType(JavaExec) {
jvmArgs '--enable-preview'
}
Note: By February 2026, Value Objects and Structured Concurrency are finalized, so --enable-preview might not be strictly necessary for these features, but it's good practice for any new language features you might experiment with.
Step 2: Define Value Objects for Performance-Critical Data
Let's imagine a financial service processing transaction requests. A TransactionId or MoneyAmount can be excellent candidates for Value Objects.
// src/main/java/com/syuthd/valhalla/TransactionId.java
package com.syuthd.valhalla;
import java.util.UUID;
// A Value Object for a Transaction ID
public value class TransactionId {
private final String id;
public TransactionId(String id) {
if (id == null || id.isBlank()) {
throw new IllegalArgumentException("Transaction ID cannot be null or empty");
}
this.id = id;
}
public String id() {
return id;
}
public static TransactionId generate() {
return new TransactionId(UUID.randomUUID().toString());
}
// Value Objects implicitly provide value-based equals, hashCode, and toString.
// They are also implicitly immutable and final.
}
// src/main/java/com/syuthd/valhalla/MoneyAmount.java
package com.syuthd.valhalla;
import java.math.BigDecimal;
import java.util.Objects;
// A Value Object for a Monetary Amount
public value class MoneyAmount {
private final BigDecimal amount;
private final String currency;
public MoneyAmount(BigDecimal amount, String currency) {
this.amount = Objects.requireNonNull(amount, "Amount cannot be null");
this.currency = Objects.requireNonNull(currency, "Currency cannot be null");
if (amount.scale() > 2) { // Example: enforce 2 decimal places
throw new IllegalArgumentException("Amount must have at most 2 decimal places");
}
}
public BigDecimal amount() {
return amount;
}
public String currency() {
return currency;
}
public MoneyAmount add(MoneyAmount other) {
if (!this.currency.equals(other.currency)) {
throw new IllegalArgumentException("Cannot add amounts of different currencies");
}
return new MoneyAmount(this.amount.add(other.amount), this.currency);
}
}
These value class definitions ensure that TransactionId and MoneyAmount instances are treated as pure data. When used in collections or as fields within other objects, their memory footprint will be significantly smaller, leading to fewer heap allocations and better cache utilization, a key benefit when migrating to Java 25.
Step 3: Implement Structured Concurrency with Scoped Values for Request Processing
Now, let's create a service that processes a transaction request. This service will use StructuredTaskScope to fan out multiple sub-tasks (e.g., validating the transaction, checking user balance, notifying external systems) and ScopedValue to pass a TransactionId context down to these sub-tasks without explicit parameter passing.
// src/main/java/com/syuthd/concurrency/TransactionService.java
package com.syuthd.concurrency;
import com.syuthd.valhalla.TransactionId;
import com.syuthd.valhalla.MoneyAmount;
import java.time.Duration;
import java.util.concurrent.Future;
import java.util.concurrent.StructuredTaskScope;
import java.util.concurrent.ScopedValue;
import java.util.random.RandomGenerator;
public class TransactionService {
// ScopedValue to pass the current transaction ID down the call stack
private static final ScopedValue CURRENT_TRANSACTION_ID = ScopedValue.newInstance();
public record TransactionRequest(String senderAccount, String receiverAccount, MoneyAmount amount) {}
public record TransactionResponse(TransactionId transactionId, String status, String message) {}
// --- Sub-tasks simulating external calls ---
private String validateTransaction(TransactionRequest request) throws InterruptedException {
// Access the transaction ID from the ScopedValue
System.out.println("Validating transaction " + CURRENT_TRANSACTION_ID.get().id() +
" for amount " + request.amount().amount());
Thread.sleep(Duration.ofMillis(100 + RandomGenerator.getDefault().nextInt(50))); // Simulate work
if (RandomGenerator.getDefault().nextBoolean()) {
return "Validation successful";
} else {
throw new IllegalStateException("Validation failed for " + CURRENT_TRANSACTION_ID.get().id());
}
}
private String checkAccountBalance(TransactionRequest request) throws InterruptedException {
System.out.println("Checking balance for transaction " + CURRENT_TRANSACTION_ID.get().id());
Thread.sleep(Duration.ofMillis(120 + RandomGenerator.getDefault().nextInt(60)));
return "Balance sufficient";
}
private String notifyExternalSystem(TransactionRequest request) throws InterruptedException {
System.out.println("Notifying external system for transaction " + CURRENT_TRANSACTION_ID.get().id());
Thread.sleep(Duration.ofMillis(80 + RandomGenerator.getDefault().nextInt(40)));
return "External notification sent";
}
// --- Main transaction processing method ---
public TransactionResponse processTransaction(TransactionRequest request) {
TransactionId transactionId = TransactionId.generate();
// Bind the transactionId to the ScopedValue for the duration of this request processing
return CURRENT_TRANSACTION_ID.where(transactionId, () -> {
try (var scope = new StructuredTaskScope.ShutdownOnFailure()) {
Future validationFuture = scope.fork(() -> validateTransaction(request));
Future balanceFuture = scope.fork(() -> checkAccountBalance(request));
Future notificationFuture = scope.fork(() -> notifyExternalSystem(request));
scope.join(); // Wait for all subtasks to complete or for one to fail
scope.throwIfFailed(); // Propagate any exception from subtasks
// All tasks completed successfully
String validationResult = validationFuture.resultNow();
String balanceResult = balanceFuture.resultNow();
String notificationResult = notificationFuture.resultNow();
System.out.println("Transaction " + transactionId.id() + " fully processed.");
return new TransactionResponse(transactionId, "SUCCESS",
validationResult + ", " + balanceResult + ", " + notificationResult);
} catch (Exception e) {
System.err.println("Transaction " + transactionId.id() + " failed: " + e.getMessage());
// Handle specific exceptions, log, etc.
return new TransactionResponse(transactionId, "FAILED", e.getMessage());
}
});
}
public static void main(String[] args) throws Exception {
TransactionService service = new TransactionService();
RandomGenerator random = RandomGenerator.getDefault();
for (int i = 0; i < 3; i++) {
TransactionRequest req = new TransactionRequest(
"ACC" + random.nextInt(1000),
"ACC" + random.nextInt(1000),
new MoneyAmount(BigDecimal.valueOf(100.00 + random.nextDouble() * 500), "USD")
);
System.out.println("\n--- Processing new request ---");
TransactionResponse response = service.processTransaction(req);
System.out.println("Final response: " + response);
Thread.sleep(Duration.ofMillis(50)); // Small delay between requests
}
}
}
This code demonstrates how TransactionService processes requests. Each request gets a unique TransactionId (a Value Object). This ID is then bound to CURRENT_TRANSACTION_ID using ScopedValue.where(). Inside this binding, StructuredTaskScope.ShutdownOnFailure ensures that three concurrent sub-tasks (validation, balance check, notification) are run. If any of them fail, the scope automatically shuts down the others and propagates the exception, making error handling predictable. The TransactionId is accessible within each sub-task via CURRENT_TRANSACTION_ID.get() without being passed explicitly, showcasing the power of Java structured concurrency tutorial techniques. This approach leads to cleaner code, better resource management, and higher reliability, crucial for high-performance Java 2026 systems.
Best Practices
- Identify Value Object Candidates Carefully: Prioritize small, immutable, data-only classes that lack identity and are frequently instantiated. Examples include coordinates, currencies, simple DTOs, or IDs. Avoid using
value classfor objects with complex behavior, mutable state, or those requiring unique object identity. - Embrace Immutability for Value Objects: Value Objects are inherently immutable. Ensure all fields are final and that no methods allow modification of the internal state after construction. This is a fundamental principle that unlocks their performance benefits.
- Leverage Structured Concurrency for Business Transactions: Use
StructuredTaskScopeto encapsulate logical units of work that involve multiple concurrent sub-tasks. Choose the appropriateStructuredTaskScopestrategy (e.g.,ShutdownOnFailure,ShutdownOnSuccess) based on your error handling and completion requirements. - Replace
ThreadLocalwithScopedValue: For passing immutable contextual data (like request IDs, user sessions, or transaction contexts) down a call stack within a concurrent flow, always preferScopedValue. It offers