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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.
Get started with mocking and improve your application tests using our Mockito guide:
Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:
Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.
But these can also be overused and fall into some common pitfalls.
To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:
Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:
Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.
I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.
You can explore the course here:
Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.
Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.
With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.
Try a 14-Day Free Trial of Orkes Conductor today.
Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.
Get started with Spring Data JPA through the guided reference course:
Refactor Java code safely — and automatically — with OpenRewrite.
Refactoring big codebases by hand is slow, risky, and easy to put off. That’s where OpenRewrite comes in. The open-source framework for large-scale, automated code transformations helps teams modernize safely and consistently.
Each month, the creators and maintainers of OpenRewrite at Moderne run live, hands-on training sessions — one for newcomers and one for experienced users. You’ll see how recipes work, how to apply them across projects, and how to modernize code with confidence.
Join the next session, bring your questions, and learn how to automate the kind of work that usually eats your sprint time.
Yes, we're now running our Black Friday Sale. All Access and Pro are 33% off until 2nd December, 2025:
1. Introduction
In this tutorial, we’re going to have a quick look at and learn about the JVM’s code cache memory.
2. What Is the Code Cache?
Simply put, JVM Code Cache is an area where JVM stores its bytecode compiled into native code. We call each block of the executable native code a nmethod. The nmethod might be a complete or inlined Java method.
The just-in-time (JIT) compiler is the biggest consumer of the code cache area. That’s why some developers call this memory a JIT code cache.
3. Code Cache Tuning
The code cache has a fixed size. Once it is full, the JVM won’t compile any additional code as the JIT compiler is now off. Furthermore, we will receive the “CodeCache is full… The compiler has been disabled” warning message. As a result, we’ll end up with degraded performance in our application. To avoid this, we can tune the code cache with the following size options:
- InitialCodeCacheSize – the initial code cache size, 160K default
- ReservedCodeCacheSize – the default maximum size is 48MB
- CodeCacheExpansionSize – the expansion size of the code cache, 32KB or 64KB
Increasing the ReservedCodeCacheSize can be a solution, but this is typically only a temporary workaround.
Fortunately, the JVM offers a UseCodeCacheFlushing option to control the flushing of the code cache area. Its default value is false. When we enable it, it frees the occupied area when the following conditions are met:
- the code cache is full; this area is flushed if its size exceeds a certain threshold
- the certain interval is passed since the last cleanup
- the precompiled code isn’t hot enough. For each compiled method the JVM keeps track of a special hotness counter. If the value of this counter is less than a computed threshold, the JVM frees this piece of precompiled code
4. Code Cache Usage
In order to monitor the code cache usage, we need to track the size of the memory currently in use.
To get information on code cache usage, we can specify the –XX:+PrintCodeCache JVM option. After running our application, we’ll see a similar output:
CodeCache: size=32768Kb used=542Kb max_used=542Kb free=32226Kb
Let’s see what each of these values mean:
- size in the output shows the maximum size of the memory, which is identical to ReservedCodeCacheSize
- used is the actual size of the memory that currently is in use
- max_used is the maximum size that has been in use
- free is the remaining memory which is not occupied yet
The PrintCodeCache option is very useful, as we can:
- see when the flushing happens
- determine if we reached a critical memory usage point
5. Segmented Code Cache
As of Java 9, the JVM divides the code cache into three distinct segments each of which contains a particular type of compiled code. To be more specific, there are three segments:
- The non-method segment contains JVM internal related code such as the bytecode interpreter. By default, this segment is around 5 MB. Also, it’s possible to configure the segment size via the -XX:NonNMethodCodeHeapSize tuning flag
- The profiled-code segment contains lightly optimized code with potentially short lifetimes. Even though the segment size is around 122 MB by default, we can change it via the -XX:ProfiledCodeHeapSize tuning flag
- The non-profiled segment contains fully optimized code with potentially long lifetimes. Similarly, it’s around 122 MB by default. This value is, of course, configurable via the -XX:NonProfiledCodeHeapSize tuning flag
This new structure treats various types of complied code differently, which leads to better overall performance.
For example, separating short-lived compiled code from long-lived code improves the method sweeper performance — mainly because it needs to scan a smaller region of memory.
6. Conclusion
This quick article presents a brief introduction to the JVM Code Cache.
Additionally, we presented some usage and tune-up options to monitor and diagnose this memory area.
