Creating agentic AI to deploy ARO cluster using Terraform with Red Hat OpenShift AI on ARO and Azure OpenAI

Learn how to create an artificial intelligence (AI) that can deploy Microsoft Azure Red Hat® OpenShift® clusters using Terraform. Explore prompt-based infrastructure and how it can be used to maintain clusters in your own environment.

This learning path is for operations teams or system administrators

Developers may want to check out Getting started with Red Hat OpenShift AI on developers.redhat.com. 

Get started on developers.redhat.com

Creating agentic AI to deploy ARO cluster using Terraform with Red Hat OpenShift AI on ARO and Azure OpenAI

Agentic AI can be defined as systems that are capable of interpreting natural language instructions, in this case users' prompts, making decisions based on those prompts, and then autonomously executing tasks on behalf of users. In this guide, you will create one that is intelligent enough that not only can it understand/parse users' prompts, but it can also take action upon it by deploying (and destroying) Microsoft Azure Red Hat OpenShift cluster using Terraform.

Disclaimers: Please note that this guide references Terraform repositories that are actively maintained by the Managed OpenShift Black Belt (MOBB) team and may change over time. Always check the repository documentation for the latest syntax, variables, and best practices before deployment. In addition, when using this agentic AI, please be aware that while the system is designed to interpret natural language instructions and autonomously execute infrastructure configurations, it is not infallible. 

The agentic AI may occasionally misinterpret requirements or generate suboptimal configurations. It is your responsibility to review all generated Terraform configurations before applying them to your cloud environment. Neither the author of this implementation nor the service providers can be held responsible for any unexpected infrastructure deployments, service disruptions, or cloud usage charges resulting from configurations executed by the agentic AI. Lastly, please note that user interfaces may change over time as the products evolve. Some screenshots and instructions may not exactly match what you see.

What is included in this learning path?

  • Prerequisites
  • Setting up the files needed for agentic AI creation
  • Creating deployment agents for agentic AI
  • Notebook integration for agentic AI
     

What will you get?

  • A working agentic AI model for your environment
  • Clusters created and/or destroyed using the model
  • Working knowledge of setting up agentic AI within Azure Red Hat OpenShift and using Red Hat OpenShift AI
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