Red Hat Trusted Application Pipeline for AI applications

Interactive demo•5 mins• Red Hat OpenShift AI

Fecha de publicación November 20, 2024 por Ricardo Garcia Cavero

This interactive demo helps developers accelerate the creation and deployment of AI-powered applications using standardized templates. It walks through the full application development and MLOps workflow from initial setup to model serving.
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What you'll learn in this interactive demo

• Signing into Red Hat Developer Hub and creating an AI application from a template.
• Configuring a Large Language Model (LLM) and reviewing the application deployment pipeline with OpenShift GitOps.
• Monitoring model serving status and accessing a Jupyter Notebook workbench in Red Hat OpenShift AI.
• Modifying chatbot code in OpenShift DevSpaces with Quarkus live dev mode and committing changes.
• Running LLM response quality tests and an MLOps pipeline based on Kubeflow.
• Exploring data connections and object storage for models and pipeline artifacts in MinIO.

Next steps

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About the author of this page

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Ricardo Garcia Cavero

Principal Portfolio Architect

Ricardo Garcia Cavero joined Red Hat in October 2019 as a Senior Architect focused on SAP. In this role, he developed solutions with Red Hat's portfolio to help customers in their SAP journey. Cavero now works for as a Principal Portfolio Architect for the Portfolio Architecture team. ...