Beyond SpringBoot - Newer Ways of Developing Microservices in Java

As microservices architecture continues to evolve, Java developers are exploring alternatives to SpringBoot. This blog post delves into modern approaches and frameworks for building efficient, scalable, and robust microservices.

The Shift in Microservices Development

When developing microservices, consider: fault-tolerance, observability, fast startup time, lower memory consumption, and statelessness.
New frameworks beyond Spring Boot are emerging to address these considerations.
MicroProfile has been developed to standardize Java Specifications for microservices development.

What is MicroProfile?

MicroProfile is an open-source project under the Eclipse Foundation that aims to optimize Enterprise Java for microservices architecture. It provides a collection of specifications, APIs, and technologies designed to help developers build cloud-native microservices using Java.

Key Features and Specifications

          
              Telemetry 2.0: Monitoring and logging
              microservices
            
              Fault Tolerance 4.1: Building resilient
              microservices
            
OpenAPI 4.0: Defining RESTful APIs

              Rest Client 4.0: Building type-safe REST clients
            
              JWT Auth 3.0: JSON Web Token-based authentication
            
              Config 3.1: Externalized configuration management
            
              Metrics 5.1: Collecting and exposing metrics

MicroProfile Implementations

MicroProfile is implemented in various Java-based runtimes, including:

Quarkus
WildFly Swarm
Open Liberty
Apache TomEE
Thorntail
Micronaut (Not 100% MicroProfile compliant)

Native Images: The Next Step in Optimization

          
              Consider using GraalVM to generate native images for your
              microservices.
            
              Benefits: Smaller size, lower CPU and memory consumption, and
              faster startup time.
            
              Note: While GraalVM offers advantages, it's not as mature as
              Classic JVM. JIT compilation can outperform AOT in certain
              scenarios.

Distributed Tracing (APM): Observability in Action

Distributed tracing observes requests as they propagate through distributed cloud environments, collecting data across services. It records each segment as a span, combining them into a single trace.

Popular Distributed Tracing Tools:

Sentry: End-to-end distributed tracing
SigNoz: Open-source observability platform
Uptrace: OpenTelemetry-native APM
OpenTelemetry: Vendor-agnostic observability framework
Zipkin: Open-source distributed tracing system
Jaeger: End-to-end distributed tracing