Skip to content

RedHat-Middleware-Workshops/devsandbox-catalog-ai-labs

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

23 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Catalogue of tutorials for the Developer Sandbox

Note
This content was auto-generated from a git template.
Update its contents accordingly.

Introduction

This repository represents the parent entity (Catalogue) hosting a series (categories) of labs and tutorials of different topics/technologies.

Available labs

The table below collects the labs currently available and the articles in Red Hat Developers they're based on.

Follow the link to the article to run the lab you're interested in.

Lab Name Preview in GitHub Article
​​Try OpenShift AI and integrate with Apache Camel preview link
Tool Up your LLM with Apache Camel on OpenShift preview link

Running the Catalogue

You can run the catalogue from Red Hat's Developer Sandbox, a free OpenShift environment that lets you build and deploy cloud-native applications using only your web browser.

To launch this catalogue first you need to access the Developer Sandbox, read the article below to help you enter the environment:

From the Developer Sandbox, follow the steps shown in the animated image below:

Open the catalogue in Dev Spaces

  1. From OpenShift's web console, click the Applications icon as shown above (marked 1).
  2. Select Red Hat OpenShift Dev Spaces (2).
    You will be prompted to log in and Authorize Access; select the "Allow selected permissions" option.
  3. When the Create Workspace dashboard in OpenShift Dev Spaces opens, copy the URL address of this Git repository.
    Then, paste it into the Git Repo URL field (3).
  4. Click Create & Open (4).
  5. When the workspace finishes provisioning and the IDE opens, click the deployable Endpoints accordion (5).
  6. Then, click on the icon (6), which opens the tutorial in a new browser tab.
  7. You can then choose a tutorial from the catalogue to start working.

About

AI learning labs applied to App Dev

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published