Micronaut (1 of 6): Framework Features
Rob Golder - January 2025
Rob Golder - January 2025
Micronaut is a modern, JVM-based framework that has rapidly gained popularity among developers for its innovative approach to building microservices and serverless applications. This series of articles on Micronaut examines what sets this framework apart from other JVM-based frameworks, provides working examples demonstrating using Micronaut with both Kotlin and Java, integrating with Postgres and Kafka, and performing native compilation using GraalVM. This is the first article in a six part series.
Micronaut was first released in 2018 by the team behind the Grails framework, Object Computing. It was developed to address some of the shortcomings observed in other frameworks, particularly around startup time, memory usage, and the complexity associated with cloud-native application development. It represents a significant evolution in the landscape of JVM-based frameworks, offering a compelling choice for developers looking to optimise their applications for the cloud.
The key features of the framework that set it apart are its use of ahead-of-time compilation to perform dependency injection, aspect-oriented programming, and configuration management. These features greatly reduce the need for reflection and proxy generation at runtime, resulting in faster startup times and less memory consumption.
Micronaut processes annotation-based dependency injection, aspect-oriented programming, and configuration management at compile-time rather than at runtime. By doing so, it avoids the overhead associated with reflection and dynamic proxy generation that traditional frameworks encounter at runtime. This results in significantly faster startup times and reduced memory footprint since much of the work is done during the application's compilation phase.
Micronaut greatly reduces its reliance on reflection by moving the heavy lifting to the compile-time phase. This approach contrasts with the runtime reflection and proxying techniques commonly used in frameworks like Spring, which can add to startup time and increase memory usage. One example of this in Micronaut is the introduction of the Bean Introspection API, which handles bean introspection through compile-time generated metadata instead of runtime reflection.
Features such as service discovery, distributed configuration and fault tolerance are integrated directly into the framework, and optimised for minimal resource usage.
Service discovery mechanisms allow services to find and communicate with others in a distributed system without hardcoding hostnames or IP addresses. Micronaut applications running in a Kubernetes environment for example can automatically register themselves with Kubernetes Services for discovery.
Configuration can be managed centrally and distributed across multiple services and environments. This enables consistency and ease of management of the configuration. Micronaut applications integrate with configuration servers like Consul’s Key/Value store, enabling applications to dynamically load and refresh configuration without requiring a restart.
Micronaut supports common resilience patterns that enable a high availability deployment. It uses Resilience4J to provide a circuit breaker pattern so services can failover gracefully in the event of failure. Retry policies, fallback methods, rate limiting and bulkheading are similarly supported by Micronaut to provide resiliency and failover. Unlike with the Spring framework for example, much of the configuration and wiring is processed at compile-time as is the focus of Micronaut in avoiding runtime overhead. This is particularly important in cloud-native environments such as serverless computing where resources can be at a premium.
Reactive programming is a first class citizen in all parts of Micronaut providing a lightweight, natively reactive framework. It allows developers to build non-blocking applications that are scalable, resilient, and capable of handling large numbers of concurrent connections with minimal overhead. It is agnostic of the reactive library used offering developers the flexibility to choose the one that best fits their needs.
GraalVM is a high-performance polyglot virtual machine developed by Oracle. It was designed to improve the performance and efficiency of applications written in Java and other JVM-based languages, as well as languages like JavaScript, Python, and Ruby. It can compile Java bytecode to native code ahead-of-time (AOT) resulting in an executable that does not require the JVM to run. It is this feature that can significantly improve startup time and reduce the memory footprint of Java applications, factors that can otherwise be an impediment to adopting Java.
As Micronaut was designed from the ground up to be lightweight and optimised for cloud environments via the framework’s AOT compilation, it naturally aligns with GraalVM’s approach to creating native applications. While other frameworks and technologies can also be used to achieve highly optimised and performant cloud native applications, the combination of Micronaut with GraalVM is a particularly effective combination.
Micronaut is a modern, JVM-based framework designed for building microservices and serverless applications. Its emphasis on ahead-of-time compilation minimises reliance on reflection and proxy generations that would create overhead at runtime. This leads to faster startup times and reduced memory consumption. Combining Micronaut with GraalVM provides a powerful tool set for creating efficient, highly performant applications that are both scalable and perfectly tailored for cloud-native deployments.
In the second article in the series a demo Micronaut application is used to highlight some of the framework's features. There are two flavours of the application, one in Kotlin and one in Java, and the source code is available here:
Kotlin version: https://github.com/lydtechconsulting/micronaut-rest-kotlin/tree/v1.0.0
Java version: https://github.com/lydtechconsulting/micronaut-rest-java/tree/v1.0.0
View this article on our Medium Publication.
Micronaut (2 of 6): Demo Application
Micronaut (3 of 6): Testing
Microbenchmarking with JMH
Exploring JHipster
Failover and Circuit Breaker with Resilience4j
Flyway in Serverless Architectures
The Hidden Cost of AWS Lambdas
Build Only What You Need - Part 1 - Development