17 Apr 2026

feedDZone Java Zone

Training a Neural Network Model With Java and TensorFlow

Training, exporting, and using a TensorFlow model is a great way to gain a low-level understanding of the building blocks of the LLMs fueling the AI revolution.

Since I am comfortable with using Java, I will use it to define a neural network (NN) model, train it, export it in a language-agnostic format, and then import it into a Spring Boot project. Now, doing all this from scratch would not be advisable, since there are many advances in the field of NN that would take a long time to properly understand and implementing them would be difficult and error-prone. So, to both learn about NNs and make implementation easy, we will use a proven software platform: TensorFlow.

17 Apr 2026 6:00pm GMT

Multithreading in Modern Java: Advanced Benefits and Best Practices

Multithreading has always been one of core strengths of Java over years. From the early days of the JVM, Java was designed with built-in support for concurrent programming. But for many years, writing scalable multithreaded applications required careful tuning, thread pool management and constant attention to synchronization.

In the latest Java versions, the concurrency model has evolved significantly. Modern Java introduces improvements such as Virtual Threads, better executors, improved fork-join performance and more structured concurrency approaches. These features allow developers to build highly concurrent applications with simpler code and fewer scalability limitations.

17 Apr 2026 5:00pm GMT

16 Apr 2026

feedDZone Java Zone

Optimizing Java Back-End Performance Profiling and Best Practices

The dashboard turned red at weekday. Our order processing API latency jumped from fifty milliseconds to five seconds. Customer support tickets flooded in. Users reported timeouts during checkout. The infrastructure team scaled up the Kubernetes pods, but the issue persisted. CPU usage sat at 100 percent across all nodes. We were throwing hardware at a software problem. This approach failed miserably.

In this article, I will share how we diagnosed the bottleneck. I will explain the profiling tools we used. I will detail the code changes that restored performance. This is not a theoretical guide. It is a record of a real production incident and the steps we took to resolve it.

16 Apr 2026 12:00pm GMT