OpenShift AI gives data scientists and developers a powerful AI/ML platform for building AI-enabled applications. Data scientists and developers can collaborate to move from experiment to production in a consistent environment quickly.

It provides an AI platform with popular open source tooling. Familiar tools and libraries like Jupyter, TensorFlow, and PyTorch along with MLOps components for model serving and data science pipelines are integrated into a flexible UI.

As part of the OpenTelemetry Integrations framework delivered by the parent outcome (OBSDA-914), users shall be able to easily integrate Red Hat OpenShift AI with the OpenTelemetry ecosystem and vendors and be supported in the platform.

• Document the integration with configuration and examples
• Explore providing a dashboard in the OpenShift console related to relevant LLM info as defined in the OpenTelemetry standard.
  • Relevant info includes detecting hallucinations, text quality, length, word count... Read more here
  • Depending on the data, some of this data may be postponed to integration with TrustAI
• Enablement
  • Explore if it's possible to make RHOAI to install and/or configure an instrumentation CR
  • Explore if it's possible to make RHOAI to install and/or configure an OpenTelemetry collector to receive, process and export data inside and outside OpenShift
  • This may be a template like the one studied in this doc
• Introduce an observability section in https://ai-on-openshift.io/