Daniel Oh
Supercharging Static Code Analysis: Konveyor AI & LLMs
#1about 2 minutes
Understanding the challenges of application modernization
Migrating legacy monolith applications to modern microservices architectures presents significant challenges that often involve a cycle of trial and error.
#2about 7 minutes
Exploring the benefits and strategies for modernization
Modernization improves security, reliability, and scalability, and can be approached using strategies like rehosting, replatforming, or refactoring.
#3about 2 minutes
Using Konveyor for rules-based code analysis
Konveyor is a CNCF open source project that analyzes source code and artifacts using a customizable rules engine to identify migration issues.
#4about 2 minutes
Supercharging analysis with Konveyor AI and LLMs
Konveyor AI enhances static analysis by connecting to large language models (LLMs) to automatically generate complete code solutions for migration issues.
#5about 6 minutes
Setting up the local Konveyor AI demo environment
A live demonstration shows how to set up the local environment, including a Postgres database and LLM server, and configure an analysis in VS Code.
#6about 5 minutes
How Konveyor AI uses RAG for accurate results
Konveyor AI uses Retrieval-Augmented Generation (RAG) to overcome LLM context limits and improve accuracy by leveraging a database of previously solved migration patterns.
#7about 5 minutes
Fixing migration issues with AI-generated code
The analysis report is reviewed in VS Code, where AI-generated code snippets for fixing issues like namespace changes and API refactoring can be accepted with a single click.
#8about 3 minutes
Running the fully modernized Quarkus application
After applying all AI-suggested fixes, the legacy application is successfully migrated and runs on the modern Quarkus stack, complete with its dependencies.
#9about 1 minute
How Konveyor AI differs from GitHub Copilot
Unlike developer-centric tools like Copilot, Konveyor AI is designed for organization-wide analysis across multiple repositories, creating a shared knowledge base of migration solutions.
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Matching moments
05:50 MIN
How Konveyor AI automates code generation with LLMs
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08:23 MIN
Performing static code analysis with Konveyor.io
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02:31 MIN
Key differentiators of the Konveyor AI approach
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05:42 MIN
How Konveyor AI uses RAG and agents for code generation
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09:24 MIN
Demo: Migrating a JMS message driven bean to reactive
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10:56 MIN
Demo of automated code transformation with Kai
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02:40 MIN
Using AI to manage legacy code and technical debt
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