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ROADMAP.md

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Roadmap

Overview

This document outlines the future directions and plans for the Cloud Native AI Model Format Specification project. Our goal is to develop a comprehensive specification that facilitates seamless integration of AI models with the cloud-native ecosystem.

Phases

Phase 1: Model Image Packaging and Distribution

  • Goal: Define a standardized approach for packaging and distributing AI model images.
  • Tasks:
    • Develop a model image format specification.
    • Create tools and libraries to support the packaging process.
    • Collaborate with the broader CNCF community to gather feedback and ensure alignment with other cloud-native projects.
    • Promote the adoption of the specification through community engagement, presentations, and workshops.

Phase 2: Community Engagement and Adoption

  • Goal: Gain attention and support from the broader CNCF community and other relevant projects.
  • Tasks:
    • Identify key stakeholders and projects within the CNCF community.
    • Establish communication channels and partnerships with these stakeholders.
    • Organize community events, discussion panels, and presentations to showcase the benefits of our specification.
    • Collect feedback and iterate on the specification based on community input.

Phase 3: Define Runtime Specification

  • Goal: Create a runtime specification that supports the integration of various inference engines with the cloud-native ecosystem.
  • Tasks:
    • Research and analyze popular inference engines and their applicability to AI model deployment.
    • Define a set of requirements and features for the runtime specification.
    • Develop a draft runtime specification and share it with the community for feedback.
    • Implement reference implementations and tools to facilitate the adoption of the runtime specification.

Phase 4: Integration and Testing

  • Goal: Ensure that the model packaging, distribution, and runtime specifications work seamlessly together.
  • Tasks:
    • Conduct thorough testing of the model packaging and runtime specifications.
    • Integrate the specifications with popular inference engines and cloud-native platforms.
    • Address any issues or gaps identified during the testing phase.
    • Release stable versions of the specifications and supporting tools.

Future Directions

  • Explore additional features and enhancements based on community feedback and technological advancements.
  • Continue to engage with the CNCF community and other relevant projects to promote the adoption and evolution of the specifications.
  • Maintain and improve the tools and libraries supporting the specifications.

Conclusion

We are excited about the future of the Cloud Native AI Model Format Specification project and look forward to collaborating with the community to build a robust and widely adopted standard for AI model deployment in the cloud-native ecosystem.