Conclusion

What You’ve Learned

Congratulations! You’ve completed the AI-assisted application modernization workshop with Red Hat Developer Lightspeed for MTA.

Throughout this workshop, you’ve gained hands-on experience with the complete modernization workflow:

Module 1: Analyzing Legacy Applications with MTA

  • Used Migration Toolkit for Applications to assess and analyze legacy Java applications

  • Identified migration risks and opportunities using AI-powered analysis

  • Configured archetypes and questionnaires to categorize applications for modernization

Module 2: AI-Assisted Code Modernization

  • Leveraged Red Hat Developer Lightspeed to generate code fixes for migration issues

  • Applied AI-powered recommendations to transform legacy code into cloud-native patterns

  • Validated AI-generated changes and understood the review workflow

Module 3: Incorporating Policy and Tribal Knowledge

  • Configured Solution Server to capture organizational best practices

  • Integrated company-specific policies and patterns into AI-assisted code generation

  • Ensured consistent application of ACME Corp standards across migration waves

Module 4: Deploying to OpenShift

  • Containerized modernized applications using Quarkus

  • Created and deployed applications to OpenShift clusters

  • Verified end-to-end migration from legacy to cloud-native deployment

Key Takeaways

For ACME Corp’s modernization initiative, you’ve demonstrated:

  • AI-assisted tools can significantly reduce migration time from weeks to days

  • Organizational knowledge can be codified and systematically applied

  • The complete workflow from legacy assessment to OpenShift deployment is achievable

  • Developer Lightspeed for MTA provides the tooling needed for large-scale portfolio migrations

Technical skills acquired:

  • Application assessment and analysis with MTA

  • AI-assisted code modernization workflows

  • Solution Server configuration for organizational patterns

  • Cloud-native deployment to OpenShift

Business impact:

  • Faster migration velocity supports business expansion timelines

  • Consistent code quality reduces technical debt

  • Knowledge capture improves team scalability

  • Proven approach can be presented to stakeholders for portfolio-wide adoption

Next Steps

Continue your AI-assisted modernization journey:

  1. Apply to your applications: Use the techniques from this workshop on your organization’s legacy applications

  2. Capture your patterns: Document your team’s best practices in Solution Server

  3. Scale the approach: Extend the workflow to additional applications in your portfolio

  4. Measure impact: Track migration time and quality improvements to demonstrate ROI

Explore related Red Hat technologies:

  • Red Hat OpenShift GitOps for automated deployments

  • Red Hat OpenShift Pipelines for CI/CD automation

  • Red Hat Advanced Cluster Security for runtime security

  • Red Hat Developer Hub for developer productivity

References

Red Hat Developer Lightspeed

Migration Toolkit for Applications

Red Hat OpenShift

Quarkus

AI and Application Modernization

Community and Support

Thank You

Thank you for participating in this workshop. We hope the hands-on experience with Red Hat Developer Lightspeed for MTA has provided valuable insights for your application modernization journey.

For questions, feedback, or to share your modernization success stories, connect with the Red Hat Developer community.