Daniel Oh

Supercharging Static Code Analysis: Konveyor AI & LLMs

What if your static analysis tool could rewrite legacy code for you? See how Konveyor AI uses LLMs to accelerate application modernization.

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

How Konveyor AI automates code generation with LLMs
18:56 MIN

How Konveyor AI automates code generation with LLMs

Application Modernization Leveraging Gen-AI for Automated Code Transformation

Performing static code analysis with Konveyor.io
10:33 MIN

Performing static code analysis with Konveyor.io

Application Modernization Leveraging Gen-AI for Automated Code Transformation

Key differentiators of the Konveyor AI approach
37:58 MIN

Key differentiators of the Konveyor AI approach

Application Modernization Leveraging Gen-AI for Automated Code Transformation

How Konveyor AI uses RAG and agents for code generation
20:05 MIN

How Konveyor AI uses RAG and agents for code generation

Navigating Application Modernization - Leveraging Gen-AI

Demo: Migrating a JMS message driven bean to reactive
07:23 MIN

Demo: Migrating a JMS message driven bean to reactive

Navigating Application Modernization - Leveraging Gen-AI

Demo of automated code transformation with Kai
24:46 MIN

Demo of automated code transformation with Kai

Application Modernization Leveraging Gen-AI for Automated Code Transformation

Using AI to manage legacy code and technical debt
39:20 MIN

Using AI to manage legacy code and technical debt

Transforming Software Development: The Role of AI and Developer Tools

Modernizing legacy codebases like COBOL with AI
39:08 MIN

Modernizing legacy codebases like COBOL with AI

Developer Productivity Using AI Tools and Services - Ryan J Salva

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