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Java 26 GC: Making Data Streaming Faster and More Reliable in Containers
Imagine running a Java application that processes massive amounts of data in real time. Example financial transactions flowing through Kafka or analytics pipelines in Flink. These apps need to be fast and consistent, but there’s a built-in challenge: Garbage Collection (GC). What is…
08-2026 | JAVA Security – Special Edition
SECURE CODING & THE JAVA PLATFORM ▪️ Security in the Age of Java 25: New Language Tools for Safer Code▪️ Top Security Flaws Hiding in Your Code Right Now – and How to Fix Them API & FRAMEWORKSSECURITY▪️Mastering API Security in Java: OWASP Best Practices▪️ The Security Innovations in…
Java 26 adopts HTTP/3 with the evolution of the HttpClient
The future of communication between microservices Modern distributed architectures, such as microservices, are deeply intertwined with the evolution of network protocols. As microservice architectures have become the dominant approach for building scalable and resilient applications,…
Java 26 Is Here, And With It a Solid Foundation for the Future
JEP Overview New features HotSpot JEP 516: Ahead-of-Time Object Caching with Any GC JEP 522: G1 GC: Improve Throughput by Reducing Synchronization Core Libs JEP 517: HTTP/3 for the HTTP Client API Repreviews JEP 524: PEM Encodings of Cryptographic Objects (Second Preview) What’s Different…
Enterprise Playbook for Generative AI Adoption
Era of Generative AI and Agentic systems The use of Generative AI (GenAI) started with the basic traditional use case which is generation of content. Simple applications and wrappers were built over Large Language Models (LLMs). These facilitated users interacting with LLMs and consuming the…
From Tables to JSON: Handling Unstructured Data in RDBMS systems with Spring Boot
Most of us have built numerous Spring Boot applications that perform standard CRUD (Create, Read, Update, Delete) operations on structured data stored in relational databases such as PostgreSQL. These systems typically rely on fixed schemas and well-defined table structures. But, what…
Hexagonal Architecture for Machine Learning: Ports, Adapters, and Model Versioning in Spring Boot
Machine learning has changed enterprise software in ways many teams did not expect. In many Spring Boot systems, predictions now shape prices, quality checks, anomaly alerts, fraud decisions, recommendations, and planning. But teams still shape prediction code like a small helper function. A…
DevOps Patterns and Java 26 for On-Premises LLM Platforms in Safety-Critical Environments
The first wave of AI adoption in many organizations relied on cloud APIs – but in safety-critical and regulated environments, that approach is often a non-starter. Confidentiality requirements, data protection regulations, and the need for technically enforceable operational boundaries stand…
Building AI-Driven Java Systems with Spring AI and Java 26
Spring AI and Java 26 make building AI-powered Java applications finally practical. This article shows how developers can integrate LLMs into production systems using modern concurrency, performance improvements and clean architectures. It discusses real-world concerns such as scalability,…
Beyond REST: Rethinking APIs with GraphQL and Java
Introduktion Distributed systems need little introduction today. They form the backbone of modern software architectures, enabling independent components to communicate, coordinate, and share resources seamlessly at scale. With the industry’s shift toward microservices, the importance of…
Code at Court – Java as evidence
Software forms the foundation of numerous business models, industrial processes, and public administration structures today. It is created in complex ecosystems consisting of source code, data, interfaces, and architectures – and thus gains legal relevance far beyond traditional copyright…
Intelligent Test Automation in the Java 26 Era: Eliminating Flaky Tests with Modern Concurrency, Stability Engineering and Smart Tooling
Flaky Tests Are a RESULT of Outdated Automation Flaky tests—tests that pass or fail inconsistently without any code changes—have become one of the most expensive problems in engineering teams. Their non deterministic outcome have disturbed the automation landscape and reliability of…
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