How to Reduce Garbage Collection Pauses in Java
Vikas Singh

Vikas Singh @viksingh

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How to Reduce Garbage Collection Pauses in Java

Publish Date: Aug 11
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Java is widely used for building everything from small tools to large scale enterprise systems. One reason for its popularity is that developers do not need to manually manage memory. Java uses garbage collection to automatically free memory that is no longer in use.

While this makes development easier, garbage collection can sometimes pause the application while it reclaims memory. These pauses may be short, but in systems that need high responsiveness even small delays can affect performance.

This post focuses on ways to reduce garbage collection pause times so your Java applications can run smoothly without unexpected slowdowns.

Understand Garbage Collection in Java

Garbage collection in Java is the process of finding and removing objects from memory that are no longer reachable by the application. The JVM does this automatically, which helps avoid memory leaks and makes development simpler.

However, this process is not free. When the garbage collector runs, it may stop the application threads to safely free memory. These pauses are called stop the world events. The goal is to reduce the time these pauses take.

Key points about GC in Java

  • Heap memory is divided into different regions such as the young generation, old generation, and sometimes a permanent or metaspace area.

  • Objects are first allocated in the young generation. If they survive multiple collections, they are moved to the old generation.

  • Most pauses happen during collections of the old generation because they involve more data.

  • Different garbage collectors handle this process differently, which impacts pause times and throughput.

Common garbage collectors in modern Java

  • Serial GC – Simple and single threaded, best for small heaps.

  • Parallel GC – Uses multiple threads to speed up collections, good for throughput oriented workloads.

  • Concurrent Mark Sweep (CMS) – Reduces pauses by collecting most of the old generation concurrently with the application.

  • G1 GC – Splits the heap into regions and collects them incrementally, balancing low pauses with high throughput.

  • ZGC and Shenandoah – Designed for very low pause times even on large heaps.

Understanding how each collector works and how your application uses memory is the first step to reducing pause times.

Identify GC Pause Problems

Before you try to tune garbage collection, you need to confirm whether GC pauses are actually affecting your application. Long pauses can look like random slowdowns, unresponsive user interfaces, or delayed request processing.

Signs that GC pauses are an issue

  • Increased response times under load

  • Gaps in application logs where no requests are processed

  • Spikes in CPU usage caused by GC activity

  • Users experiencing delays or timeouts without other clear causes

Ways to detect GC pauses

Enable GC logging

Use JVM flags such as

-Xlog:gc*

or in older JVM versions

-XX:+PrintGCDetails -XX:+PrintGCDateStamps

These logs will show how often GC runs, how long it takes, and which memory areas are collected.

Monitor with tools

  • Java Mission Control and Flight Recorder can give detailed insights into GC events

  • JVisualVM offers real-time heap usage graphs

  • Application performance monitoring tools like New Relic or AppDynamics can correlate GC pauses with request delays

The more data you collect, the easier it becomes to spot patterns, such as pauses happening at predictable intervals or after certain actions. This helps you decide whether tuning or code changes are needed.

Tuning the Garbage Collector

Once you know GC pauses are an issue, the next step is to choose the right garbage collector and configure it for your workload. Java offers several collectors, each with different trade offs between pause time, throughput, and memory footprint.

Pick the right GC for your needs

  • G1 GC works well for most modern applications with medium to large heaps. It aims to keep pauses short while maintaining good throughput.

  • ZGC and Shenandoah are best for applications that need extremely low pause times, even with very large heaps.

  • Parallel GC can be effective for batch processing or workloads that can tolerate longer pauses in exchange for higher throughput.

Adjust heap size

  • A heap that is too small will trigger frequent collections, causing more pauses.

  • A heap that is too large can increase pause times, especially in collectors that scan large areas at once.

  • Use tools or testing to find a balance based on your application’s memory usage patterns.

Set GC specific flags

Each collector has options that affect how it runs. For example, with G1 GC you can target a maximum pause time:

-XX:MaxGCPauseMillis=200

This tells the JVM to aim for pauses no longer than 200 milliseconds, adjusting collection work as needed.

Test changes under realistic loads

Tuning in a development environment is not enough. GC behavior changes with traffic, data size, and runtime conditions, so always validate settings in staging or production like environments.

Reduce Object Creation and Promote Efficient Memory Usage

The more objects your application creates, the more work the garbage collector has to do. This can increase both the frequency and length of pauses. Reducing object churn is one of the simplest ways to keep GC activity low.

One approach is to reuse objects when it makes sense. For example, instead of creating new objects in tight loops, keep them in memory and update their values. Also, avoid unnecessary temporary objects in methods that run often.

You can help the GC by releasing references to large objects as soon as they are no longer needed. Choosing the right data structures matters too. For example, set the initial size of collections to match your expected usage so they do not constantly resize and allocate more memory.

Small optimizations like these make a difference over time, especially in applications that run continuously or handle a high number of requests.

Optimize Data Structures and Algorithms

Memory use is not only about how much data you store but also how you store and process it. Choosing the right data structures and algorithms can reduce memory pressure and cut down on garbage collection work.

If you use a data structure that holds more information than you need, you are wasting memory. For example, a HashMap with millions of entries will consume more space than a more compact map implementation, even if you rarely access most of the data. Likewise, an algorithm that creates large intermediate collections during processing will cause unnecessary object allocation.

A good practice is to measure memory usage for different structures and pick the smallest one that meets your requirements. Also, prefer algorithms that work in place rather than building many temporary copies of data. This reduces both heap usage and the number of objects the GC needs to collect.

These choices matter most in high throughput or long running applications where even small inefficiencies build up over time.

Use Monitoring and Profiling Tools

You need visibility into how memory is used and how garbage collection behaves before you can reduce pause times. Monitoring and profiling tools provide that visibility and help you make data driven changes.

Useful tools for tracking GC and memory

  • Java Mission Control and Flight Recorder come with the JDK and show GC events, heap usage, and object allocation over time.

  • JVisualVM is a simple visual tool that displays live memory graphs and allows heap dump analysis.

  • New Relic, AppDynamics, and Dynatrace offer detailed GC metrics along with application performance data to spot slowdowns caused by pauses.

These tools help you see patterns, such as pauses occurring after specific jobs or requests. Once you know the trigger, you can focus your fixes where they will have the most effect.

Best Practices for Long Term Performance

Reducing garbage collection pauses is not a one time fix. It requires good habits in how you write and maintain code.

  • Keep object lifecycles clear so unused references are released quickly

  • Limit large object creation unless absolutely necessary

  • Choose GC algorithms wisely and test them under real workloads before deploying

  • Regularly review heap usage with profiling tools to catch problems early

  • Refactor code that creates excessive temporary objects during critical operations

  • Test performance changes in staging to see how they affect both GC and application speed

When these practices become part of your development process, you avoid building up memory issues that lead to long pauses later.

Final Thoughts

Garbage collection is a key part of Java’s memory management, but poorly tuned GC can cause unwanted pauses that slow down your application. Reducing these pauses is about writing efficient code, choosing the right data structures, monitoring memory usage, and adjusting GC settings based on real performance data.

Treat GC optimization as an ongoing process, not a one time task. The more you measure and refine, the smoother your Java applications will run. For complex projects or performance critical systems, it can be worthwhile to hire java developers who have experience fine tuning JVM behavior and application memory usage.

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