fidzu : Java

04 Nov 2025 1:00pm GMT

Migrating from a monolithic Java 8 system to a reactive microservice architecture on Kubernetes allowed us to dramatically improve performance and maintainability. In this article, I'll share our journey, key Spring Cloud Kubernetes features we adopted, the challenges we faced during development, and the lessons we learned along the way.

Business Logic

We have a data processing logic that streams information into S3 storage using Kafka, Spark Streaming, and Iceberg. Initially, we encountered multiple challenges, such as file optimization issues and Spark's unpredictable memory behavior. After addressing these issues, we achieved significant cost savings. Once the insert service was completed, we needed to select an appropriate search engine service. We chose Trino as it fulfilled the needs of our data science department. We also serve customers who perform operations on our S3 data, which can result in high system load. Before this modernization, our platform ran on an old monolithic architecture built with Java 8, which created several performance and maintenance challenges.

30 Oct 2025 2:00pm GMT

Kilo is an open-source project for creating and consuming RESTful and REST-like web services in Java. Among other things, it includes the Collections and Optionals classes, which are designed to help simplify code that depends on collection types and optional values, respectively. Both are discussed in more detail below.

Collections

Kilo's Collections class provides a set of static utility methods for declaratively instantiating list, map, and set values:

27 Oct 2025 7:00pm GMT

Recently, I wrote the Introduction to Spring Data Elasticsearch 5.5 article about Spring Data Elasticsearch usage as a NoSQL database. The article covered just the setup of the unsecured Elasticsearch. However, we need to be able to connect to the secured Elasticsearch as well. Let's follow the previous article and see the needed changes to run and connect to the secured Elasticsearch.

In This Article, You Will Learn

• How to create a secure Elasticsearch
• How to connect to the secured Elasticsearch with Spring Data Elasticsearch
• How to change the password in Elasticsearch

Set Up Secured Elasticsearch

The setup for creating a secure Elasticsearch is pretty similar to the steps in the already-mentioned article. The technologies used in this article, compliant with the compatibility matrix, are:

27 Oct 2025 5:00pm GMT

While running a synthetic benchmark that pre-warmed the cache, we noticed an abnormal performance impact on Ampere CPUs. Digging deeper, we found that there were many more page faults happening with Ampere CPUs when compared to x86 CPUs. We isolated the issue to the use of certain atomic instructions like ldadd, which load a register, add a value to it, and store data in a register in a single instruction. This triggered two "page faults" under certain conditions, even though this is logically an all-or-nothing operation, which is guaranteed to be completed in one step.

In this article, we will summarize how to qualify this kind of problem, how memory management in Linux works in general, explain how an atomic Arm64 instruction can generate multiple page faults, and show how to avoid performance slowdowns related to this behavior.

24 Oct 2025 12:00pm GMT

In a previous article, we explored how to implement full-text search in PostgreSQL using Hibernate 6 and the posjsonhelper library. We built queries with to_tsvector, to_tsquery, and their simpler wrappers for the plainto_tsquery, phraseto_tsquery, and websearch_to_tsquery functions.

This time, we'll extend that foundation and explore how to rank search results based on their relevance using PostgreSQL's built-in ranking functions like ts_rank and ts_rank_cd.

23 Oct 2025 2:00pm GMT

When it comes to software development, one of the biggest mistakes is delivering precisely what the client wants. While this may sound cliché, the problem persists even after decades in the industry. A more effective approach is to begin testing with a focus on business needs.

Behavior-driven development (BDD) is a software development methodology that emphasizes behavior and domain terminology, also known as ubiquitous language. It uses a shared, natural language to define and test software behaviors from the user's perspective. BDD builds on test-driven development (TDD) by concentrating on scenarios that are relevant to the business. These scenarios are written as plain-language specifications that can be automated into tests, which also serve as living documentation.

23 Oct 2025 1:00pm GMT

According to a 2024 Gartner report, more than 92% of large enterprises now operate in multi-cloud environments. This reflects strategic priorities such as geographic scalability, high availability, regulatory compliance, and cost optimization.

But with these benefits comes significant complexity. Each provider - AWS, GCP, Alibaba Cloud, and others - exposes its own APIs, semantics, and SDKs. As a result, development teams must reconcile divergent models for storage, databases, identity, and more. The outcome is often fragmented codebases filled with conditional logic, code forking, duplicated workflows, and costly rewrites when onboarding new providers. For large organizations, this slows delivery, increases operational risk, and erodes the developer experience.

20 Oct 2025 5:00pm GMT

Artificial intelligence (AI) is becoming increasingly pervasive. As an Enterprise Java developer, you might be wondering what value AI can add to your business applications, what tools Java provides to easily do that, and what skills and knowledge you might need to learn. In this article, we equip you with the basic knowledge and skills that you need to start exploring the capabilities of AI to build intelligent and responsive Enterprise Java applications.

When we talk about AI in this article, we mean getting responses from a large language model (LLM) based on a request that the Java application sends to the LLM. In our article's example, we create a simple chatbot that customers can ask for planetary tourist destination recommendations, and then use to book a spaceship to visit them. We demonstrate using Java frameworks like LangChain4j with Quarkus to efficiently interact with LLMs and create satisfying applications for end-users.

10 Oct 2025 7:00pm GMT

So, I've been deep in the trenches with JNI lately (yeah, that Java Native Interface stuff) while working on a project where we had to plug a C++ AI assistant into our Android app. At first, it felt like stepping into a weird twilight zone - half Java, half C++, and all these random edge cases you never think about until you hit them. I remember staring at the stack trace for what felt like hours, realizing that one tiny missed DeleteLocalRef was enough to crash the whole app. Thought I'd share what actually tripped me up, what worked, and some ways to make life a little less miserable if you ever have to do this.

What the Hell Is JNI Anyway?

JNI is basically the bridge that lets Java (or Kotlin) talk to C/C++ code and vice versa. On Android, it's the only real way to get heavy lifting done efficiently or access low-level APIs that Java/Kotlin just can't reach. Honestly, the first time I tried to wrap my head around it, I felt like I was learning a new language on top of Java and C++ at the same time.

10 Oct 2025 6:00pm GMT

It's been a while since my first article dedicated to Spring Data Elasticsearch usage as a NoSQL database was published. A couple of articles with configuration changes or hints followed the first article. Therefore, the main goal of this article is to define a new baseline for the full Elasticsearch setup.

Note: All previous articles are listed at the end.

10 Oct 2025 4:00pm GMT

There's something that every backend or API developer faces sooner or later: the need for good fake data.

Whether you're testing a new API, populating a database for demos, or simply trying to make your unit tests less "boring", fake data is part of your daily routine. The problem? Most fake data feels… fake. You end up with "John Doe" and "123 Main Street" repeated over and over, which doesn't look great when showing a prototype to your team or client.

10 Oct 2025 12:00pm GMT

If you are a developer, regardless of the technologies you use, at some point, you will face the challenge of handling large Excel files.

Most commonly, you will see the "out of memory" error when handling these files.

09 Oct 2025 12:00pm GMT

Advanced Technical Approach

Some Java frameworks have taken on the complexity of supporting both javax and jakarta package namespaces simultaneously. This approach makes sense for frameworks and platform services, such as Jetty and ActiveMQ, where the core development team needs to move the code base forward to support newer JDKs, while also providing a way for application developers to adopt Jakarta EE gradually. This simplifies the support for open-source frameworks, as there are fewer releases to manage, and in the event of a security bug, being able to release one mainline branch vs having to go back and backport across past versions.

However, supporting both javax and jakarta namespaces simultaneously in a single application is complicated and time-consuming. Additionally, it opens additional scenarios that may lead to errors and security gaps for enterprise applications. This limits the ability to set up verification checks and source code scanning to block pre-Jakarta libraries from being used or accidentally pulled in through transitive dependencies. It creates a lot of ambiguity and reduces the effectiveness of DevOps teams in providing pre-approved SDKs to be used by enterprise developers. With the pitfalls outweighing the benefits, enterprise projects should not need to support both javax and jakarta namespaces simultaneously in most scenarios.

08 Oct 2025 4:00pm GMT

If you've ever tried to scale your organization's data infrastructure beyond a few teams, you know how fast a carefully planned "data lake" can degenerate into an unruly "data swamp." Pipelines are pushing files nonstop, tables sprout like mushrooms after a rainy day, and no one is quite sure who owns which dataset. Meanwhile, your real-time consumers are impatient for fresh data, your batch pipelines crumble on every schema change, and governance is an afterthought at best.

At that point, someone in a meeting inevitably utters the magic word: data mesh. Decentralized data ownership, domain-oriented pipelines, and self-service access all sound perfect on paper. But in practice, it can feel like you're trying to build an interstate highway system while traffic is already barreling down dirt roads at full speed.

26 Sep 2025 12:00pm GMT

JavaFX is a versatile tool for creating rich enterprise-grade GUI applications. Testing these applications is an integral part of the development lifecycle. However, Internet sources are very scarce when it comes to defining best practices and guidelines for testing JavaFX apps. Therefore, developers must rely on commercial offerings for JavaFX testing services or write their test suites following trial-and-error approaches.

This article summarises the seven most common mistakes programmers make when testing JavaFX applications and ways to avoid them.

24 Sep 2025 11:00am GMT