Quarkus Roadmap Quarkus 3.20 Release Highlights The Quarkus 3.20 release, which was released at the end of April, brings several significant improvements: Enhanced WebSocket handling with full Jakarta EE WebSocket support Default container images updated to UBI9 (for runtime and core components) MicroProfile REST Client updated to version 4.0 Added OpenTelemetry logging support Future Roadmap: Quarkus 3.27 The upcoming 3.27 release is targeted for Q4 2025 (around October), though this is considered an aggressive timeline. Key points: ...

Why is OpenJDK 8 supported by Red Hat for longer than OpenJDK 11? The OpenJDK Lifecycle shows that OpenJDK 8 will be supported until Nov 2026, nearly 2 years after OpenJDK 11 support will end in October 2024. That sounds strange. Why was OpenJDK 8 supported extended from June 2023 to Nov 2026? Why does support for OpenJDK 11 end before OpenJDK 8? There’s a Red Hat article, solving these questions. tl;dr: Migration from Java 8 to 11 is a way more complicated step involving bigger changes than the migration past Java 11. ...

Modelcars from Red Hat Last week I wrote about model cars and how you can build them yourself. Following on from this, there are also some existing modelcars that are provided by the Red Hat AI Business Unit and can be used without further ado: https://quay.io/repository/redhat-ai-services/modelcar-catalog Just do step 5 from last week with the image you want and you’re done. CPU models I am currently working on an OpenShift AI PoC and one of the requirements is to deploy an LLM that only runs on CPU. The team can’t use GPUs at the beginning, but they know that LLMs can only reach their full potential on them. Later, the production system will also have GPUs and be able to use other more common models. A good CPU solution should therefore be found. ...

Cool things from the Open Practice Library The Open Practice Library is a community-driven, open-source collection of proven practices designed to support teams in delivering better outcomes. It includes tools like Event Storming, User Story Mapping, and Affinity Mapping, which help teams align on goals, prioritize work, and iterate effectively. Developed by Red Hat’s Open Innovation Labs, the library serves as a valuable resource for teams seeking to adopt agile and DevOps methodologies in a structured, collaborative way. ...

Tech journey promo There are some tech journey events coming up soon that I would like to share here. It is a series of Webinars, in german, all remote. If you are interested, you should register immediately. 04.06. - Storage integration in OpenShift Virtualization 11.06. - Erste Schritte mit Gen AI auf Red Hat OpenShift 27.08. - OpenShift Virtualization 201: Day 2 Operations in der Praxis On top of that, there’ll be a dedicated AI Roadshow, in Person. Here are the dates (subject to change): ...

OpenShift AI custom workbenches This week I’ve learned about custom notebooks in OpenShift AI. The use is quite similar to Dev Spaces, at the end it’s just an image you’ll have to build and provide somewhere. Here’s a useful link on how to get easily started and get it done. OpenShift AI and it’s upstream project OpenDataHub have a image repo with a lot of pre-built images you can use as a base for your own implementation, here’s the link. If you already know how to use custom Devfiles in Dev Spaces, that should sound familiar to you because there you probably use one of the universal developer images as a base. ...

Team meetings This week I had a lot of in-person team meetings (Volkswagen & BMW, Manufacturing and Enterprise) and a lot of talks. I also presented my Agentic AI and Konveyor AI Slides from last week and we’ve had several discussions. It’s always interesting when many Red Hatters come together and learn how different people in different positions see things from their perspectives. OpenShift AI Proof of Concept I’m participating in two proof of concepts from the manufacturing industry, both different for different reasons. One is an OpenShift PoC without GPUs (although GPUs are available in general) and is intended to explore the extent to which this might still make sense on a production line. The other is about replacing and standardizing existing ClearML workflows while avoiding vendor lock-in and deploy also on a production line on lower-performance computers. Both aim to be more independent in terms of deployment in the hyperscalers’ clouds, deploying their models both on-premises and across multiple clouds. ...

Quarkus Meetup Frankfurt recap It was nice. Good reviews. Unfortunately, few people. We need to do more marketing. The main topic was migration to Quarkus and the Konveyor project. For the second talk, I talked about Agentic AI: Why it exists, what it’s supposed to solve, and a bit about the implementation in Quarkus. There’s a very good GitHub repo that explains this, by my colleague Mario Fusco. Everything is linked in the slides. ...

Quarkus Meetup next week Next week I will talk at the Quarkus Meetup in Frankfurt. If you want to attend, here’s the registration link. It will take place at CodeCentric, a place where we have already held the Quarkus Meetup Frankfurt and had a good time. My topics will be Konveyor and a little bit of the currently developed Konveyor AI. In general we will see how to easily migrate a Java Application to Quarkus with static code analysis and guidance. And discuss what the roadmap is and where the journey goes. ...

Agentic AI & MCP So that week I was in munich and worked with a colleague on the topics Agentic AI and MCP. Mostly we did research and didn’t create own things. Goal was to gain so much knowledge in that topics to be able to talk with people about that. I will publish an article when I’m ready and had the time to pipeline my thoughts, but here’s a short journey through these topics: ...