This epic is to capture requirements and work efforts for the initial phase of model explainability, which will focus on initial functionality for model fairness and bias detection. 

Reqs doc: https://docs.google.com/document/d/1plV2df_tttn0N6l6wH9bYKCKNp1rZt8ejl2ImrOBs4E/edit?usp=sharing

Things to consider and add to the below branches as needed:

• Implement component testing framework (for new components)
• Add tutorials and documentation to ODH website
• Implement Monitoring
• All new features/components must have an upgrade strategy:
• Base language version (e.g. golang versions will be aligned with openshift core components or only use LTS).
• Dependencies

• Write standard operating procedures for new feature for SRE

• Static analysis for new repos
  • For static analysis, we are working with QE on what framework is best. 
• Blog post about new feature and component
• Record new feature and post to youtube
• What open source projects could come out of this work
• Does it impact any Tier 2 component integration that we need to make the owners of those components aware of?
• For new components:
  • Work withe DevOps Team and reference https://docs.google.com/document/d/1crPEEsZkJByBpMPXAAGahChLGR2OtLyo-lyd8G9LRXk/edit
  • Update/create a standard operating procedures document for MT-SRE.  Example SOP .  Check with SRE team and AI services managers.
  • Update/create training material.  Dave Mulford is a good contact for this.
  • Update the architectural document: https://docs.google.com/document/d/1iZMPWcqj4G6D6t72jUg_m0ueU0aRdiF5VLRr30Aw85E/edit#heading=h.lrchm1vhf7fh