Java Web Development (JSP/Servlets) Services

Within the discipline of software engineering, practitioners are frequently encumbered by the monotonous ritual of initializing identical project scaffolds — configuring dependencies, establishing directory hierarchies, and reproducing boilerplate code prior to engaging in substantive problem‑solving. Although indispensable, such preliminary tasks are inherently repetitive, susceptible to human error, and inimical to efficiency. 

Maven, a cornerstone of the Java build ecosystem, furnishes an elegant mechanism to mitigate this redundancy through the construct of archetypes. An archetype functions as a canonical blueprint, enabling the instantaneous generation of standardized project structures aligned with organizational conventions. By engineering bespoke archetypes, development teams can institutionalize consistency, accelerate delivery, and reallocate intellectual effort toward innovation rather than procedural repetition.

REST Assured is a popular API test automation framework in Java. Software teams widely use it for efficiently validating RESTful web services with minimal setup. It simplifies the process of sending requests, verifying responses, and handling JSON or XML paåyloads.

With its rich syntax and integration support for tools like TestNG and Maven, REST Assured enables robust, maintainable, and scalable API testing.

Retrieval-augmented generation (RAG) is quickly becoming one of the most powerful design patterns for AI applications. It bridges the gap between general-purpose large language models (LLMs) and your specific enterprise data. In this article, we’ll walk through how to build a complete RAG pipeline in Java using Spring Boot, Vertex AI’s Gemini embeddings, Apache PDFBox, and BigQuery Vector Search.

You will see how to do the following, wrapped in a Spring Boot app with a simple web UI:

One subtle challenge in software architecture is that architectural thinking can feel detached from the codebase. We draw diagrams, define layers, identify responsibilities, and craft a coherent structure — yet the moment implementation begins, those architectural ideas fade into the background. Over time, systems drift not because developers ignore design, but because the code itself provides almost no way to express that design.

This tension is well documented. In Just Enough Software Architecture, George Fairbanks argues that programming languages lack constructs for directly representing architectural concepts. Java lets us model types, fields, methods, and packages, but offers no native way to encode ideas such as “presentation layer,” “domain logic,” “aggregate root,” or “infrastructure boundary.” Without these cues in the code, architecture becomes optional, verbal, and fragile.

In a three-article series published recently on this site (Part 1, Part 2, Part 3), I've been demonstrating the power of the AWS Cloud Development Kit (CDK) in the Infrastructure as Code (IaC) area, especially when coupled with the ubiquitous Java and its supersonic/subatomic cloud-native stack: Quarkus.

While focusing on the CDK fundamentals in Java, like Stack and Construct, together with their Quarkus implementations, this series was a bit frugal as far as the infrastructure elements were concerned. Indeed, for the sake of clarity and simplification, the infrastructure used to illustrate how to use the CDK with Java and Quarkus was inherently consensual. Hence, the idea for a new series, of which this article is the first, is a series less concerned with CDK internals and more dedicated to the infrastructure itself.