Shaaf's blog

Consider a web application that needs to store user-generated content, such as images, videos, and documents. Instead of storing them in a file systems or using a database, the web application can use an object store. An object store can handle objects as a single unit, providing metadata about each object and abstracting away from the underlying storage which can be local or distributed. In this blog post I will explain a local setup for minio using docker.

Konveyor AI is a tool used to migrate Java applications to different Java frameworks, such as from JavaEE to Quarkus or Spring or from Spring 5 to 6, using Generative AI and static code analysis. I wrote a detailed post about this last year for the Java Advent Calendar. Most recently, we have all been hard at work, bringing a preview for our community of users. In this post, I will outline how you can install and configure Konveyor AI using OpenAI and make meaningful generations.

Java is an amazing language to work with. Millions of developers use it for daily work routines, and many mission-critical applications run on Java today. Whether we talk about banks, stock exchanges, or space, Java is prevalent and a language of choice. With the advent of Large Language Models(LLM), new opportunities are at play. While Python has been the dominating language runtime for apparent reasons, there is a misconception that creating applications, agents, or other components for LLMs should also be done in Python.

Konveyor’s main strength lies in its comprehensive approach to migration and modernization. At the core of Konveyor’s functionality is its powerful analysis engine. This engine performs static source code analysis, identifying anti-patterns and issues that might hinder the application’s operation on a target platform. Utilizing community standards like the Language Server Protocol, Konveyor’s analysis engine uses rules designed to aid in various migration scenarios. Users can also create custom rules to address specific migration needs, enhancing Konveyor’s flexibility and adaptability.

The article is a comprehensive guide on creating, deploying, and managing the coolstore cart service using Quarkus and Infinispan. The guide details building the cart-service with Quarkus, packaging it, and deploying it to OpenShift. It covers single-site deployment with Infinispan cache configuration and extends to cross-site clustering for data replication and fault tolerance across multiple data centers. The article also addresses schema management and implementing fault tolerance with Smallrye Fault Tolerance for fallback mechanisms acorss multiple site deployments.