Java’s concurrency model just got a major upgrade with virtual threads. Think of virtual threads as Java’s equivalent of switching from a family van to a sports car — suddenly, you’re handling concurrency with ease and style. Gone are the days of clunky, resource-gobbling threads that make scaling feel like wrestling an octopus. Now, with Project Loom, we’ve got virtual threads: fast, lightweight, and ready to transform your code.

Let’s take a look at how this new feature changes everything you thought you knew about concurrency in Java.

So, What’s the Big Deal with Virtual Threads?

Virtual threads are a new type of thread that doesn’t take over all system resources. If traditional threads are like waiting for a table at a busy restaurant, virtual threads are more like sitting at a self-serve café: you slide right in, get started immediately, and avoid the wait entirely. This means you can spin up thousands, even millions, of virtual threads without sending your server into a tailspin.

And here’s where it gets really exciting — virtual threads can make even synchronous-looking code handle massive concurrency without much effort. Let’s dive in and see what makes them tick.

The Old Way: Traditional Threads

Before virtual threads, writing concurrent Java code meant working with OS threads, each with a big memory footprint. If you tried to create too many, you’d quickly run into memory issues, like a party where you’ve invited too many guests, and now people are sitting on the floor.

Here’s how the code used to look:

for (int i = 0; i < 1000; i++) {
    new Thread(() -> {
        System.out.println("Running in thread: " + Thread.currentThread().getName());
    }).start();
}

This version is fine if you have a limited number of threads. But try scaling it up — imagine trying to handle a large number of simultaneous connections — and your app’s memory usage balloons, dragging down performance and possibly leading to a dreaded OutOfMemoryError.

Enter Virtual Threads: Java’s Concurrency Makeover

With the JDK 21, we now have virtual threads fully integrated and supported. They’re like traditional threads but without all the baggage. Virtual threads are managed by the JVM instead of the OS, allowing you to create thousands of threads without needing a huge amount of memory.

Here’s how the same code looks with virtual threads:

for (int i = 0; i < 100000; i++) {
    Thread.startVirtualThread(() -> {
        System.out.println("Running in virtual thread: " + Thread.currentThread().getName());
    });
}

See the difference? Not only does this code look simpler, but it’s also handling a much larger number of threads without turning your app into a memory guzzler. Virtual threads make it possible to handle massive concurrency without breaking a sweat, letting you scale up without stressing about resource limits.

Blocking I/O: Virtual Threads vs. Traditional Threads

One of the biggest headaches in concurrency is handling blocking I/O operations, like reading files or fetching data from a network. In the past, blocking meant your thread was out of commission, sitting idly while it waited for data.

With virtual threads, though, blocking is no big deal. When a virtual thread encounters a blocking operation, it’s paused by the JVM and picks up right where it left off once the operation finishes. This means you can handle lots of blocking operations without bottlenecking your server.

Here’s a look at the old approach:

new Thread(() -> {
    try (BufferedReader reader = new BufferedReader(new FileReader("file.txt"))) {
        System.out.println("Read line: " + reader.readLine());
    } catch (IOException e) {
        e.printStackTrace();
    }
}).start();

And now, with virtual threads: Thread.startVirtualThread(() -> { try (BufferedReader reader = new BufferedReader(new FileReader("file.txt"))) { System.out.println("Read line: " + reader.readLine()); } catch (IOException e) { e.printStackTrace(); } });

In both cases, the code is nearly identical. The big difference is in performance: the virtual thread version can handle many more I/O-bound tasks without requiring extra resources or complex asynchronous code.

But Wait, Isn’t Async the Way to Go?

Before virtual threads, Java developers often leaned on CompletableFuture and other async frameworks to handle concurrency without blocking threads. But async code can be tricky, leading to what’s often called “callback hell” — the programming equivalent of a spaghetti disaster.

// Running an asynchronous task with CompletableFuture
CompletableFuture<Void> future = CompletableFuture.runAsync(() -> {
     System.out.println("Async task with CompletableFuture");
});

// Waiting for the task to complete
future.join(); 

Virtual threads, however, make it possible to handle async tasks in a synchronous style, eliminating the need for complex workarounds. Here’s an example using virtual threads instead of CompletableFuture:

Thread.startVirtualThread(() -> {
    System.out.println("Async task with virtual thread");
});

It’s clean, it’s readable, and it doesn’t require a callback pyramid.

But, before you unleash virtual threads everywhere, let’s talk limitations. While these threads are a superhero squad for I/O-bound tasks and high-concurrency needs, they’re not exactly built for CPU-bound tasks. Think of virtual threads as the ultimate waiters: they’re efficient at handling lots of tasks that sit idle most of the time, like database calls or web requests. But for CPU-heavy jobs? They don’t shine as brightly.

Why Not CPU-Bound?

Here’s the deal. Virtual threads thrive on managing tasks that spend more time waiting than doing — they’re champs at suspending and resuming without consuming resources. But CPU-bound tasks are a different beast altogether. These jobs demand the CPU’s full attention, processing continuously without taking a break.

The Resource Competition

For CPU-bound work, virtual threads don’t get the same advantage they do with I/O tasks. Since CPU-bound tasks need steady processing, the lightweight nature of virtual threads isn’t as helpful here. Each task is actively chewing through CPU time, so it’s like trying to fit as many people as possible into a fast-food line — they’re all hungry and want attention, and there are only so many burgers to go around!

The Context Switching Factor

Sure, virtual threads reduce context-switching overhead compared to OS threads, but for CPU-bound work, there’s still a performance cost. If you’ve got a crowd of CPU-intensive tasks in virtual threads, they start competing fiercely for CPU resources, which can cause a bottleneck, bringing us right back to the resource crunch we were trying to avoid.

The Better Fit for CPU-Bound Work

“The real challenge of multithreading is not doing things concurrently, but rather doing things concurrently safely.” — Herb Sutter

When it comes to crunching numbers, processing big datasets, or running computations, OS threads (good old-fashioned threads) are often a better fit. A fixed pool of threads — typically matching the number of CPU cores — can make full use of the available CPU power without unnecessary overhead. These OS threads work harmoniously with the CPU, letting each task chug along without the need for extra suspensions or interruptions.

Virtual threads are best for high-concurrency, I/O-heavy tasks, like handling web requests, file I/O, or database interactions where they can wait on I/O without consuming resources. For pure, CPU-bound tasks, though, OS threads often have the upper hand because they’re optimized to keep every core busy, especially with data-heavy, compute-intensive tasks like simulations or scientific calculations.

Virtual Threads: A Game-Changer for Java’s Future

With virtual threads, Java’s concurrency model finally has the power, flexibility, and simplicity it needs to thrive in modern, scalable applications. From handling web requests to managing real-time data, virtual threads make Java a serious contender in high-concurrency applications. It’s a huge step forward for anyone building apps that need to handle thousands of users without a hitch.