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Contemporary software often becomes vastly complex, and we are required to use a variety of technologies and different programming languages for its development. As interoperability between programming languages could cause high overhead resulting in a performance loss, it is important to examine how a current polyglot virtual machine with a compiler written in a high-level object-oriented language deals with it. OpenJDK's Project Metropolis presented the GraalVM, an open-source, high-performance polyglot virtual machine, mostly written in Java. This paper presents GraalVM's architecture and its features; furthermore, examining how it resolves common interoperability and performance problems. GraalVM makes software ecosystem productive when combining various programming languages, for example, Java, JavaScript, C/C++, Python, Ruby, R, and others. The vital part of GraalVM is the Graal compiler written in Java, which allows developers to maintain and optimize code faster, simpler, and more efficient, in comparison to traditional compilers in C/C++ languages. Graal can be used as a justin-time (JIT) or as static, ahead-of-time (AOT) compiler. Graal is an aggressively optimizing compiler implementing common compiler optimizations, with emphasis on outstanding inlining and escape analysis algorithms. This paper compares Graal with some of the best-specialized competitors, and presents our results tested within an academic environment.

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Increased complexity of network-based software solutions and the ever-rising number of concurrent users forced a shift of the IT industry to cloud computing. Conventional network software systems commonly based on monolithic application stack running on costly physical single-purpose servers are affected by significant problems of resource management, computing power distribution, and scalability. Such implementation is restricting applications to be reduced to smaller, independent services that can be more easily deployed, managed, and scaled dynamically; therefore, embellishing environmental uniformity across development, testing, and production. Current cloud-based infrastructure frequently runs on containers placed in Kubernetes or Docker-based cluster, and the system configuration is considerably different compared to the environment prevailed with common virtualizations. This paper discusses the usage of GraalVM, a polyglot high-performance virtual machine for JVM-based and other languages, combined with new Kubernetes native Java tailored stacked framework named Quarkus, formed from enhanced Java libraries. Moreover, our research explores GraalVM's creation of native images using Ahead-Of-Time (AOT) compilation and Quarkus' deployment to Kubernetes. Furthermore, we examined the architectures of given systems, various performance variables, and differing memory usage cases within our academic testing environment and presented the comparison results of selected performance measures with other traditional and contemporary solutions.

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