08 May 2026

feedDZone Java Zone

How AI Is Rewriting Full-Stack Java Systems: Practical Patterns with Spring Boot, Kafka and WebSockets

Building real-time applications means balancing user responsiveness with heavy backend processing. A proven solution is to decouple heavy workloads using events and asynchronous processing. In this approach, a Spring Boot application quickly publishes events to Kafka instead of processing requests inline. Then Kafka consumers (with AI/ML logic) handle the data in the background, and the results are pushed to clients in real time via WebSockets. This article highlights three key patterns enabling this architecture:

  1. Event Production with Spring Boot and Kafka
  2. AI-Driven Processing in Kafka Consumers
  3. Real-Time WebSocket Delivery to the Frontend

Event Production with Spring Boot and Kafka

The first step is capturing an event and publishing it to Kafka. By offloading work to Kafka the application can respond immediately to the user without waiting for processing. Spring Boot's integration with Apache Kafka provides a KafkaTemplate to send messages to topics.

08 May 2026 2:00pm GMT

07 May 2026

feedDZone Java Zone

How to Test PUT API Request Using REST-Assured Java

PUT requests are typically used for updating an existing resource. This means replacing the current data for the target resource with the data sent in the API request body.

Just like POST requests, the content-type header is important because it tells the server how to interpret the data we're sending.

07 May 2026 2:30pm GMT

Comparing Top Gen AI Frameworks for Java in 2026

Java has always been a serious language for production systems, and in 2026, the Generative AI ecosystem has finally caught up. For years, Java developers watched from the sidelines as Python and TypeScript accumulated framework after framework for building LLM-powered applications. Today, the picture is very different. Java has multiple mature, actively maintained AI frameworks, each with its own philosophy and trade-offs.

This article covers the four frameworks I have personally used to ship Java AI applications: Genkit Java, Spring AI, LangChain4j, and Google ADK Java. Each one represents a meaningfully different bet on what a Java AI framework should be, and understanding those differences will save you from picking the wrong tool.

07 May 2026 12:30pm GMT