Application Modernization and Migration

with Konveyor

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The ultimate Open Source toolkit to help organizations safely migrate and modernize their application portfolio to leverage Kubernetes and Cloud-Native technologies, providing differential value on each stage of the adoption process

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Konveyor Workflow

Stages and personas in the modernization journey

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Konveyor Hub

Assets Generation

Reporting

Assessment

Code Transformation

Planning

Analysis

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An overview of Konveyor 0.3.0

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Konveyor Operator

Install Konveyor in your Kubernetes cluster with almost no effort

• Can be installed in all Kubernetes distributions
• Available in operatorhub.io
• Requires Operator Lifecycle Manager on upstream Kubernetes distributions
• Provides a tackle CR to provision all components
• Capability Level II

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Application Inventory

Manage your Application Portfolio

• Used to maintain a portfolio of applications
• It is the hub, and natural integration point for all Konveyor projects in the future
• Applications can be linked to the business services that they support
• Application interdependencies can be defined and managed
• Through the use of tags extensible metadata can be added to describe and categorize the applications in multiple dimensions

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• Integration with source code and binaries repositories:
• Git
• Subversion
• Maven Artifact repositories
• Secure store for multiple credential types:
• Source control
• Maven settings files
• Proxy
• Credentials are managed by administrators and assigned by architects to applications.

Application Inventory

Integration with repositories

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Archetypes

Enhanced classification of applications

• Store information about the different application types in the organization based on their taxonomy.
• Technology stack.
• Maintainers.
• Automatically classify applications based on their associated tags.
• Simplify the assessment process

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Application Assessment

Assess your Application Portfolio for containerization suitability

• A questionnaire based tool that assesses the suitability of applications for deployment in containers within an enterprise Kubernetes platform
• The reports provide information about the suitability of the applications for containerization, highlighting risks and producing an adoption plan informed by effort, priority and dependencies

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Application Assessment

Questionnaire management

• Import and export questionnaires.
• Render existing questionnaires.
• Define which questionnaires are required for the assessment: which questionnaires should be presented to the users and answered by the for an application to be considered assessed?

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Application Assessment

YAML syntax

• Enable questionnaire authoring and versioning through a YAML syntax.
• Enhanced capabilities:
• Conditional questions.
• Autotagging of applications based on answers.
• Automated answers based on tags present on the assessed application or archetype.

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• Analyzes application source code and binaries and helps estimating the migration effort for different targets or paths.
• Analyzes applications executing an extensible set of rules to identify issues.
• Support numerous migration paths and creates a rich set of reports.
• Currently supports Java and Go.
• Subsequent minor releases will include support for .NET, Typescript and Python. More languages to come.

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Application Analysis

Get precise data about your Application Portfolio and estimate migration cost

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• Support multiple languages for analysis by abstracting away the analysis engine and delegating the complexity of each language to a Language Server Protocol implementation.
• Language Providers will integrate with the implementation of a given language and translate rules conditions into LSP queries.

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Multi Language Analysis

Overview

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Dynamic reports

Identify trends across the whole application portfolio

• Users are able to get aggregated information about issues and dependencies across the entire application portfolio.
• Identify portfolio-wide trends or drill down to the single line of source code.
• Analysis results are now fully integrated with the main Konveyor UI, without requiring dedicated reports.
• Downloading static reports or analysis results files for individual applications is still available.

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Application Analysis

Issue type analysis and support for effort estimation

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Application Analysis

Issue identification and guidance for developers

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Application Analysis

Technology identification

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Application Analysis

Dependencies identification

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Application Analysis

Migration paths matrix

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Application Analysis

Custom rules

• For your own Frameworks
• “If you encounter this - here is how you migrate”.
• Also great for large engagements, once you have built your “cookbook”.
• Provide your internal guidance and link directly to your documentation.
• Fully documented YAML syntax aimed at simplifying rules authoring.

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• Simplify analysis configuration and execution
• Lower the barrier for the usage of custom rules at scale.
• Architects can maintain custom rules in their own, and make sure third party developers use them in a straightforward way.

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Custom Migration Targets

Encapsulate custom rules for analysis configuration

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Custom Migration Targets

Streamline knowledge sharing abstracting migration teams from the complexity

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Migration Waves

Planning modernization across the application portfolio

• Allows modernization leads to break the portfolio into different waves and execute the adoption effort in an iterative fashion.
• Brings a new target persona for the Konveyor project: managers leading the migration initiative that need to plan the different iterations required to execute the project.

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Migration Waves

Integration with issue trackers

• Provides a way to keep track of the overall progress of the modernization initiative at migration wave or individual application level.
• Allows third party migrators to work with their usual issue tracker/task manager while their progress is reflected in Konveyor.
• First implemented integration: Atlassian Jira.
• Applications in a migration wave are created in Jira as issues.
• Compatible with all Jira flavors.

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Kantra CLI

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• Runs application analysis locally.
• Generates static HTML reports for analysis results.
• Helps testing custom rules easily.
• Leverages Podman to avoid complex installations.
• Provides flexibility for automation and enables simple integration with CI/CD pipelines.
• Transforms legacy XML rules into the new YAML syntax.

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Kantra CLI

Features

Kantra analyze --input /home/user/myapp --output /home/user/reports --target eap7

--target cloud-readiness --source weblogic

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Kantra CLI

Automated source code changes

• Leverages OpenRewrite to automate source code changes
• Integrated with the CLI, dedicated openrewrite flag to run recipes
• OpenRewrite recipes included out of the box:
• Java EE to Jakarta EE
• Spring Boot to Quarkus

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Konveyor Roadmap

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Disclaimer

Due to the constant changes in the cloud ecosystem

Roadmaps are subject to change

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Q2 2024

Q1 2025

Konveyor 0.5: Typescript support for analysis. Analysis history. Quality of life improvements.

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Konveyor 0.4: .NET and Python support for analysis. Quality of life improvements.

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Q3 2024

Konveyor 1.0:

Platform awareness, assets generation and Kai GenAI

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Roadmap

Tentative milestones for upcoming Konveyor releases

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Upcoming Initiatives

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Platform Awareness

Integration with platforms to gather application insights

• Enable Konveyor to retrieve information about applications directly from the platform in which they are running:
• Deployment configuration
• Runtime configuration
• Flexible enough to obtain information from multiple platform types:
• Container platforms
• Application servers
• Hypervisors and VMs
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Assets Generation

Generate custom tailored deployment and configuration assets

• Flexible enough to generate all assets required to deploy an application on k8s (and potentially other platforms in the future)
• Provide opinionated best practices out of the box.
• Allow organizations to create their own corporate assets easily:
• Use templating as much as possible.
• Build on industry standards
• Avoid having to learn new programming languages or proprietary APIs.

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Kai

Leverage GenAI for application modernization and migration

• Short for Konveyor AI
• Goal: Automate source code changes as much as possible, even when applications use custom corporate technologies and frameworks.
• Leverage the structured migration data stored in Konveyor to enhance commercial LLMs via prompt engineering.
• RAG approach to provide additional context and increase accuracy.
• Avoid the need for fine tuning even with custom technologies.

Thank you!

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