The Ultimate Guide to Garbage Collection in Java: Boosting Performance and Scalability

In the world of software development, memory management is a fundamental concern. For developers working with languages like C or C++, it’s a manual, often perilous task where a single mistake can lead to memory leaks, dangling pointers, and system instability. Java, however, revolutionized this with its automatic Garbage Collection (GC), a process managed by the Java Virtual Machine (JVM) that automatically reclaims memory occupied by objects that are no longer in use. While often seen as a black box or even a source of performance issues, a deep understanding of Garbage Collection is a superpower for any serious Java developer.

Contrary to some beliefs, GC is not inherently slow. In fact, for many allocation-heavy workloads typical of modern Java Microservices and Java Web Development, a well-tuned, modern garbage collector can outperform manual memory management in both speed and safety. This article will demystify Garbage Collection, taking you from core concepts and classic algorithms to the advanced, low-latency collectors in Java 17 and Java 21. We’ll explore practical JVM Tuning techniques, best practices for writing GC-friendly code, and how to build robust, high-performance applications on the JVM.

The Fundamentals of Automatic Memory Management

To appreciate Garbage Collection, it’s essential to understand the problem it solves. Automatic memory management abstracts away the complexity of memory deallocation, allowing developers to focus on business logic rather than low-level memory operations.

Manual vs. Automatic Memory Management

In languages without GC, the developer is responsible for every byte of memory. You allocate it, use it, and then you must explicitly free it. This gives you fine-grained control but introduces significant risks. Forgetting to free memory leads to a “memory leak,” where the application’s memory footprint grows indefinitely until it crashes. Freeing memory too early creates a “dangling pointer,” which can lead to unpredictable behavior and security vulnerabilities.

Java’s GC eliminates these problems. The developer creates objects using the new keyword, and the JVM’s garbage collector takes care of the rest. The core principle it uses to determine if an object can be deleted is called reachability.

Key Concepts: The Heap, The Stack, and Reachability

The JVM organizes memory into a few key areas, but for GC, the two most important are the Stack and the Heap.

• The Stack: Each thread in a Java application has its own stack. The stack stores primitive local variables and references to objects on the heap. When a method is called, a new frame is pushed onto the stack; when it returns, the frame is popped. This memory is managed automatically and is very fast.
• The Heap: This is the main memory pool shared by all threads where all Java objects live. It’s the region that the Garbage Collector manages.

An object is considered “garbage” and eligible for collection if it is no longer reachable. Reachability is determined by tracing a graph of object references starting from a set of “GC Roots.” GC Roots are special references that are always considered reachable, such as:

• Local variables on the current thread’s stack.
• Active threads themselves.
• Static variables of any loaded class.
• References from JNI (Java Native Interface).

If there is no path of references from any GC Root to an object, that object is unreachable and its memory can be reclaimed.

public class GcExample {

    public static void main(String[] args) {
        // 'user1' is a GC Root (local variable on the main thread's stack)
        // It references a new User object on the heap. This object is reachable.
        User user1 = new User("Alice");

        // 'user2' is another GC Root referencing another User object.
        User user2 = new User("Bob");

        // Now, user1 references the same object as user2.
        // The original "Alice" object on the heap no longer has any
        // references pointing to it from a GC Root. It is now unreachable.
        user1 = user2;

        // The "Alice" object is now eligible for garbage collection.
        // We can suggest a GC run, but it's not guaranteed.
        System.gc();

        System.out.println("End of program.");
    }
}

class User {
    private String name;

    public User(String name) {
        this.name = name;
        System.out.println("User '" + this.name + "' created.");
    }

    @Override
    protected void finalize() throws Throwable {
        // Finalize is deprecated and should be avoided, but useful for demonstrating GC.
        System.out.println("User '" + this.name + "' is being finalized and collected.");
        super.finalize();
    }
}

How Garbage Collectors Work: Classic Algorithms

Over the years, several core algorithms have been developed to implement Garbage Collection. Understanding them provides a foundation for appreciating the sophistication of modern collectors. A key concept across many older GCs is the “Stop-The-World” (STW) pause, where the application threads are completely frozen while the GC does its work.

The Generational Hypothesis

Most modern JVM GCs are “generational.” This approach is based on the empirical observation that most objects in an application die young. To optimize for this, the heap is divided into two main areas:

• Young Generation: Where all new objects are allocated. It is further divided into an Eden space and two Survivor spaces (S0 and S1). Minor GCs run frequently here and are typically very fast.
• Old Generation (Tenured): Objects that survive several Minor GCs are “promoted” to the Old Generation. Major GCs (or Full GCs) run here, are less frequent, but can take longer as they scan the entire heap.

Mark-and-Sweep

This is one of the simplest GC algorithms. It works in two phases:

1. Mark Phase: The collector starts at the GC Roots and traverses the entire object graph, marking every reachable object as “live.”
2. Sweep Phase: The collector scans the entire heap from start to finish. Any object that was not marked is considered garbage, and its memory is reclaimed.

While effective, Mark-and-Sweep can lead to memory fragmentation, where the free memory is scattered in small chunks, making it difficult to allocate larger objects later.

Mark-Compact

The Mark-Compact algorithm builds on Mark-and-Sweep to solve the fragmentation problem. It adds a third phase:

1. Mark Phase: Same as above, identify all live objects.
2. Compact Phase: All live objects are moved to one contiguous block at the beginning of the heap. This updates all references to them, which is an expensive operation.
3. Sweep Phase: The memory after the compacted block is now one large free chunk.

This algorithm is often used for the Old Generation, where pauses are more acceptable and fragmentation is a bigger concern.

import java.util.ArrayList;
import java.util.List;

public class MinorGcSimulation {

    // This simulates a workload that creates many short-lived objects,
    // common in a Spring Boot REST API handling many requests.
    public static void main(String[] args) {
        System.out.println("Starting simulation of high allocation rate...");

        // Run for 20 seconds
        long startTime = System.currentTimeMillis();
        while (System.currentTimeMillis() - startTime < 20000) {
            // In each iteration, create a list and populate it.
            // The list and its contents become unreachable at the end of the loop.
            // This will trigger frequent Minor GCs in the Young Generation.
            createShortLivedObjects();
            try {
                // Small pause to avoid overwhelming the CPU completely
                Thread.sleep(5);
            } catch (InterruptedException e) {
                Thread.currentThread().interrupt();
            }
        }

        System.out.println("Simulation finished.");
    }

    private static void createShortLivedObjects() {
        List<String> shortLivedList = new ArrayList<>();
        for (int i = 0; i < 1000; i++) {
            shortLivedList.add("Object-" + i + "-" + System.nanoTime());
        }
        // At the end of this method, 'shortLivedList' goes out of scope.
        // The List and all its String objects become eligible for GC.
    }
}

The Evolution of GC: Modern Low-Pause Collectors in Java 17 and Java 21

The primary goal for modern garbage collectors has shifted from maximizing application throughput to minimizing pause times. For interactive applications, Java REST APIs, and systems within a Java Microservices architecture, long STW pauses are unacceptable. This has led to the development of highly concurrent and low-latency collectors.

The G1 (Garbage-First) Collector

G1 has been the default collector since Java 9 and represents a major leap forward. Instead of fixed Young and Old generations, G1 divides the heap into a large number of small, equal-sized regions. It can dynamically assign a role (Eden, Survivor, Old) to each region.

During a collection cycle, G1 concurrently marks live objects across the heap. When it performs a collection pause, it focuses on collecting from the regions that contain the most garbage—hence the name “Garbage-First.” This allows it to meet user-defined pause time goals with high probability, making it a great all-around collector for Java Enterprise applications.

ZGC (The Z Garbage Collector)

Introduced as production-ready in Java 15, ZGC is a scalable, ultra-low-latency collector designed for applications with massive heaps (from gigabytes to terabytes) and strict pause time requirements. ZGC’s design goal is to keep pause times under 10ms, and often achieves sub-millisecond pauses, regardless of heap size. It achieves this by performing nearly all its work concurrently with the application threads, using advanced techniques like colored pointers and load barriers. ZGC is an excellent choice for latency-sensitive services in a Java Cloud environment, deployed with Docker Java and Kubernetes Java.

Shenandoah

Shenandoah is another ultra-low-latency collector with similar goals to ZGC. It also performs most of its work concurrently, including the compaction phase, which is a significant achievement. While ZGC is part of the standard OpenJDK, Shenandoah was initially developed by Red Hat and is available in builds like Red Hat’s OpenJDK and Adoptium. The choice between ZGC and Shenandoah often comes down to the specific workload and JVM distribution being used.

# How to enable different garbage collectors using JVM flags.
# This is a key part of Java Performance tuning.

# To run a Java application with the G1 GC (default on modern JVMs)
# You can explicitly set it for clarity or on older JVMs.
java -XX:+UseG1GC -jar my-spring-boot-app.jar

# To enable the Z Garbage Collector for ultra-low latency
# This requires a modern JDK (15+ for production readiness)
java -XX:+UseZGC -Xmx4g -jar my-latency-sensitive-app.jar

# To enable the Shenandoah GC (available in specific OpenJDK builds)
java -XX:+UseShenandoahGC -jar my-application.jar

# It's also good practice to enable GC logging to analyze performance.
java -XX:+UseG1GC -Xlog:gc*:file=gc.log -jar my-spring-boot-app.jar

Practical GC Tuning and Best Practices for Clean Code Java

While modern GCs are incredibly advanced, you can still improve their efficiency through monitoring, tuning, and writing GC-friendly code. This is a critical aspect of Java Performance and Java Optimization.

Monitoring Garbage Collection

You can’t optimize what you can’t measure. The first step in JVM Tuning is to monitor GC activity. Several tools are available:

• GC Logging: The most reliable source of information. Use the -Xlog:gc*:file=gc.log flag to get detailed logs.
• jstat: A command-line tool to monitor GC statistics in real-time.
• VisualVM: A graphical tool included with the JDK that provides a visual representation of heap usage and GC events.
• Application Performance Management (APM) Tools: Tools like Dynatrace, New Relic, or Datadog provide sophisticated GC monitoring and analysis for production systems.

Identifying and Fixing Memory Leaks

Even with automatic GC, memory leaks are possible in Java. A Java memory leak occurs when objects are no longer needed by the application but are still reachable from GC Roots, preventing the collector from reclaiming their memory. A classic example is a static collection that is never cleared.

import java.util.ArrayList;
import java.util.List;

// A simple cache that demonstrates a potential memory leak.
public class LeakyCache {

    // A static list holds references to all created objects.
    // Because it's static, it lives for the entire application lifetime.
    private static final List<byte[]> cache = new ArrayList<>();

    public void addToCache() {
        // Allocate a large object (1MB) and add it to the cache.
        byte[] largeObject = new byte[1024 * 1024];
        cache.add(largeObject);
        System.out.println("Added 1MB to the leaky cache. Size: " + cache.size() + "MB");
    }

    public static void main(String[] args) throws InterruptedException {
        LeakyCache leaky = new LeakyCache();
        while (true) {
            leaky.addToCache();
            Thread.sleep(1000); // Add a new object every second
        }
        // This application will eventually crash with an OutOfMemoryError
        // because the 'cache' list is never cleared, and the byte arrays
        // it holds are therefore never garbage collected.
    }
}

Writing GC-Friendly Code

Following Java Best Practices can significantly reduce GC pressure:

1. Manage Scope: Keep the scope of objects as small as possible. A variable that is only needed inside a loop should be declared inside that loop.
2. Avoid Unnecessary Allocations: Be mindful of object creation in performance-critical sections of code, such as tight loops. For example, reuse a StringBuilder instead of creating new strings with concatenation.
3. Use Primitive Types: Prefer primitives (int, long) over their boxed equivalents (Integer, Long) where possible to avoid heap allocation.
4. Beware of Finalizers: Avoid using finalize(). It’s deprecated, unpredictable, and can significantly delay object reclamation. Use try-with-resources or other explicit cleanup mechanisms instead.

Conclusion: Embracing Automatic Memory Management

Garbage Collection is one of the most powerful features of the Java platform, enabling developers to build complex, scalable, and secure applications with high productivity. We’ve journeyed from the fundamental principles of reachability and generational collection to the sophisticated, low-latency algorithms of modern collectors like G1 and ZGC. We’ve seen that rather than being a performance bottleneck, a well-configured GC is a critical component for achieving high Java Scalability and performance, especially in demanding Java Backend and cloud-native environments.

The key takeaway is that understanding GC is not just for performance experts; it’s a core competency for any professional involved in Java Development. By monitoring your application’s memory behavior, choosing the right collector for your workload, and writing memory-conscious code, you can harness the full power of the JVM. As a next step, try enabling GC logging on your own Spring Boot application, experiment with different JVM flags in a test environment, and explore the official documentation to deepen your knowledge of Java Performance tuning.