Konveyor AI: Changing app modernization with open-source innovation
Modernizing applications is an intimidating task for enterprises, yet increasingly essential. Enter Konveyor AI, an open-source marvel leveraging retrieval-augmented generation to seamlessly integrate large language models. This innovative tool is poised to transform the landscape of app modernization, according to James Falkner (pictured), director of product marketing for Runtimes at Red Hat Inc.
“The challenge that we face is the economics of really essentially changing an app, burning it down, rewriting it,” Falkner said. “We have championed an open-source upstream project called Konveyor, designed to facilitate onboarding applications to Kubernetes. What we’re doing here with Konveyor is introducing a new tool called Konveyor AI. This takes advantage of the groundswell underneath AI and brings a different and novel way of doing this modernization.”
Falkner spoke with theCUBE Research’s Rob Strechay and Paul Gillin at Red Hat Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed why Konveyor AI is a game-changer in application modernization. (* Disclosure below.)
Konveyor AI fills the app modernization void
Since many organizations intend to jump on the application modernization bandwagon in the near future, Konveyor AI streamlines this process through cloud-native capabilities. As a result, enterprises are saved from the hustle of having to rewrite apps, Falkner pointed out.
“We’ve done research recently that shows 80% of those we surveyed are going to modernize over half of their apps in the next two years … the other interesting piece that came out of this survey is that over 75% of them intend to use AI,” he noted. “You can take an application and just ask an LLM, ‘What’s the next best thing I should do?’ With Konveyor AI, we’re able to take advantage of a lot of the history of an application modernization and not just ask it for the next best action.”
By merging Konveyor AI with IBM watsonx Code Assistant, RAG is improved because of enhanced prompts. As a result, this is also a novel innovation in the application modernization journey, according to Falkner.
“IBM Research is actually one of the partners in the Konveyor community,” he said. “Konveyor AI can use watsonx Code Assistant underneath as that foundational model. What we are also doing, which is very new, is taking corporation data … historical data about other fixes that have happened through things like GitHub pull requests, JIRA issues, the static code analysis, and we’re taking all of that and using the RAG pattern.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Red Hat Summit:
(* Disclosure: Red Hat Inc. sponsored this segment of theCUBE. Neither Red Hat nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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