IBM Corp.’s Red Hat subsidiary today is using the Kubecon + Cloudnativecon Europe conference in London to announce updates to its Developer Hub and new features for the Konveyor AI application modernization project.

Both moves are intended to streamline the development and transformation of applications to cloud environments.

Release 1.5 of Developer Hub includes Adoption Insights, an analytical dashboard that shows how teams are using the portal. Platform engineers can see metrics about templates, plugins, visits and usage patterns. Red Hat stated that the goal is to help organizations identify areas where developers are succeeding and where they may require additional support or new features.

A new Extensions Catalog, available in a developer preview, offers access to more than 60 community and Red Hat-verified plugins that enable organizations to customize Developer Hub. Development teams can manage and add plugins at runtime without having to rebuild or redeploy the portal.

There’s also a new local, lightweight, self-contained version of the Developer Hub, called RHDH Local, that can run on a local machine. Now in developer preview, it’s intended to let platform engineers test and customize the portal without installing it on a Kubernetes cluster. Red Hat said use of RHDH Local speeds development cycles by making it easier to test new tools, troubleshoot issues and work on templates before rolling out changes to production.

Red Hat Developer Hub 1.5 is now generally available.

AI-based modernization

Konveyor is an open-source community project designed to help organizations modernize applications for cloud-native environments. Version 0.1 of Konveyor AI, which is being released today, integrates generative artificial intelligence with static code analysis to simplify modernization tasks. It uses retrieval-augmented generation to combine large language models with migration data, allowing developers to automate source code changes without fine-tuning their own AI models, review past transformations and reduce the manual effort required for large-scale migrations.

Key enhancements in this version include static code analysis, which flags potential issues when moving to new frameworks or containers. Issue tracking logs and retains a history of resolved modernization challenges. The release contains 2,400 built-in rules for various migration paths, with the option to define custom rules.

A Visual Studio code extension provides code change suggestions from within the integrated development environment. Users can work with any large language model and choose which issues generative AI handles based on estimated effort.

The Konveyor project is also adding features for re-platforming applications to Kubernetes, including automated generation of deployment artifacts. Red Hat said it plans to bring these AI-driven capabilities into its own migration toolkit for applications, with the aim of making large-scale modernization more efficient.

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