JVM Garbage Collectors for the Cloud

Introduction

Garbage Collection is a fundamental part of the Java Virtual Machine (JVM) that frees up memory by removing objects that are no longer needed by the application. The JVM has several garbage collectors, each with its own characteristics and performance trade-offs.

In the cloud, garbage collection is even more critical, as applications often have to deal with large amounts of data, high traffic, and run in resource-constrained environments. In addition, cloud-native applications are expected to be scalable and sometimes ephemeral. If garbage collection is not managed correctly, it can lead to performance degradation, increased latency, and even application downtime.

In this post, we will explore the different garbage collectors available in the JVM and how to choose the right one for your cloud-native applications.

What is Garbage Collection?

Garbage Collection is the process of automatically freeing up memory by removing objects that are no longer needed or in use by the application. It saves developers from having to manage memory manually, making it easier to write and maintain Java applications.

The JVM has a garbage collector that runs in the background, periodically scanning the heap for objects that are no longer needed. When it finds an object that is no longer referenced by the application, it marks it for deletion and reclaims the memory it was using.

Types of Garbage Collectors

The JVM has several garbage collectors, each with its own characteristics and performance trade-offs. The most common garbage collectors are:

Serial Garbage Collector

This is the simplest type of garbage collection algorithm. It stops all threads in the application and then scans through the heap to find any objects that are no longer being used.

Parallel Garbage Collector

This garbage collector is similar to the serial garbage collector but uses multiple threads to scan through the heap. This can improve performance by taking advantage of multiple CPU cores. It's more suitable for applications that require high throughput and can tolerate short pauses.

Concurrent Mark and Sweep (CMS) Garbage Collector

This algorithm is a more sophisticated type of parallel garbage collection. It uses two threads: a marker thread and a sweeper thread. The marker thread marks all objects that are still being used, and the sweeper thread then frees up any objects that are not marked. It's often used in applications that require low latency and can't tolerate long pauses.

G1 Garbage Collector

The Garbage First (G1) garbage collector is a newer, low-latency garbage collector that is designed to work well with large heaps. It splits the heap into regions and prioritizes collecting garbage from regions with the most garbage. It balances throughput and latency by dynamically adjusting the size of the regions based on the amount of garbage in each region.

Shenandoah Garbage Collector

This is another newer garbage collection algorithm that is designed for large heaps and ultra-low latency applications. It uses a technique called evacuation to move objects from one region of the heap to another. This can help to reduce the amount of fragmentation in the heap.

This garbage collector could be well suited for real-time applications that require low latency and can't tolerate long pauses.

Z Garbage Collector

The Z Garbage Collector is a scalable garbage collector that is designed to work well with large heaps and low-latency applications. It uses a technique called region counting to track the number of objects in each region of the heap. This can help to improve the performance of garbage collection.

Choosing the Right Garbage Collector

The best garbage collection algorithm for your application will depend on a number of factors, including the size of your heap, the amount of memory that your application uses, and the performance requirements of your application.

In addition, you should take into account the characteristics of the garbage collector, such as:

• Parallel: Whether the garbage collector uses multiple threads to scan through the heap.
• Concurrent: Whether the garbage collector can run concurrently with the application.
• Throughput: The amount of work the garbage collector can do in a given amount of time.
• Latency: The time it takes for the garbage collector to complete a collection cycle.
• Footprint: The amount of memory the garbage collector uses.

The following table summarizes the characteristics of the different garbage collectors:

When choosing a garbage collection algorithm, it is important to consider the trade-offs between different algorithms. Some algorithms, such as serial garbage collection, have low pause times but can have low throughput. Other algorithms, such as G1 garbage collection, have high throughput but can have longer pause times.

Since your applications are running in the cloud, you should also consider the resource constraints of your environment. The number of CPU cores, the amount of memory, and the network bandwidth can all affect the performance of the garbage collector.

Ultimately, the best way to choose a garbage collection algorithm is to experiment with different algorithms and see which one works best for your application.

Conclusion

Garbage collection is an important part of any cloud-native application. There are a number of different garbage collection algorithms that can be used, each with its own advantages and disadvantages.

In this post, we have explored the different garbage collectors available in the JVM and how to choose the right one for your cloud-native applications. By understanding the characteristics of each garbage collector and experimenting with different algorithms, you can optimize the performance of your applications and ensure that they run smoothly in the cloud.

References

This article was heavily inspired by the talk GC Algorithms for the Cloud by Pratik Patel at the DevBcn 2024. Make sure to check out the talk for a more in-depth look at the topic.