Quarkus: Modernizing Java for the Cloud Era

Although relatively new, Quarkus is causing a stir in the Java and application development world. The project, born in the open source community, is a full-stack Kubernetes-native Java framework, designed to work with popular Java standards, frameworks, and libraries. For this reason, it is an excellent option for new cloud-native technologies, such as serverless and microservices.

According to IDC data, Java is still the leading programming language in the market. According to the survey, 9.3 million of the 13.5 million professional developers worldwide identify themselves as "moderate to frequent" users of the platform. The arrival of Quarkus helps modernize this language for the cloud era, allowing professionals to use it to build new cloud-native structures.

In a recent IDC validation report, sponsored by Red Hat, a global leader in developing open source solutions, Quarkus's performance was evaluated against another Java framework widely used for cloud-native development, identified as Framework A. The comparison is based on attributes important to developers and their experience, as well as characteristics important for containers, Kubernetes, and cloud deployments.

Resource Savings

One of the main benefits of Quarkus is resource savings, as attested by the IDC Validation Report. Both Quarkus JVM and Quarkus Native enable lower memory consumption, as well as faster startup times, leading to higher Kubernetes pod deployment density.

Quarkus also has a lower operating cost. Compared to Framework A, savings from Quarkus operating in native mode (using GraalVM to create a standalone, optimized executable that does not run on a traditional Java Virtual Machine, or JVM) can reach up to 64%, while when running on a JVM, it reaches 37%.

Developer Productivity

Quarkus streamlines developers' everyday work, improving productivity and speeding up time to market for products. Compared to Framework A, Quarkus reduced the number of operational steps required to update applications from six to two. Using Quarkus, a developer making and testing changes to source code has to go through two steps: change the code and save.

Development using Framework A, on the other hand, requires six steps: make the change in the project, pause the service, start the service, test the change, run the Framework A application, and test the application again. The reduction in steps provided by Quarkus also makes code compilation easier and more efficient.

The reduction in the number of processes is possible thanks to live coding. Application updates using live coding are seen immediately, improving developers' operational efficiency and leading to more efficient testing when searching for problems.

Quarkus also unifies imperative and reactive programming, giving developers the option to combine them freely. By allowing for a smaller number of projects and source files, professionals can reduce the time needed to maintain their code, as well as the number of projects they need to manage.

Deployment Density

Developers using Quarkus can spin up a larger number of pods than with Framework A. Those using Quarkus native can spin up 8x more pods, while those using Quarkus JVM can spin up 1.5x more pods. This means that, with Quarkus, customers can do more with the same amount of resources, and more applications can be developed using the same amount of memory. Deployment density and reduced memory usage are among the main ways Quarkus optimizes Java for containers.

Overall Performance

It was traditionally said that Java used too much memory at startup, making it unsuitable for lightweight applications. Quarkus debunks this view. Its native version reduced startup memory usage by 90, while Quarkus JVM reduced it by 20%. The savings result in greater processing capacity for the same memory footprint in both JVM and native modes, meaning it's possible to do more with the same amount of memory.

Quarkus is also much faster at startup than Framework A. Quarkus Native is 12x faster, while Quarkus JVM is 2x quicker. This makes the application more responsive to workload changes and more reliable during operations that require significant scaling (for example, serverless), boosting innovation and offering an advantage over competitors.