Access the Developer Sandbox for Red Hat OpenShift to learn with guidance the basics of powering applications with AI. The sandbox is a free-to-use environment that includes OpenShift AI, where you can create and deploy models and connect services using Apache Camel as our integration Swiss Army knife to build AI-enabled APIs.
This is not your usual, read-fast-retain-little article. We want to make a difference by welcoming you to experience first-hand how to train a model with your own data set, make it consumable, and show you how to create applications that expose and enrich the capability.
You’ll need no local environment to set up and no preparation time or effort. It all happens in our Developer Sandbox which automatically provisions the tutorial on demand. This guide is designed to be very easy to follow and is rich in well-explained and illustrated concepts.
Tutorial highlights
The track will show you how to create an AI project, navigate and use the model factory, and even execute the training cycles to generate your custom model. The environment provides the computational power you need and more to continue your journey with new technologies to discover.
After you create and deploy your bespoke model suited for your enterprise needs, you will switch roles and become the application developer using OpenShift Dev Spaces, a web-based, cloud-native development environment ready with all the required resources. Figure 1 shows both workflows.
Figure 1: Tutorial workflows to create and deploy models and applications.
First, you’ll play the role of an AI developer to produce a model you can deploy. And then, you will impersonate the application developer planning to create a smart application powered by AI.
After delivering both artifacts, you will deploy, connect and test them out.
Start your journey
If you are accessing the Developer Sandbox for the first time, you’ll have to create a Red Hat account. Other than that, you are one click away from kicking off this unique experience. Click the link below to get started.
After Dev Spaces finishes preparing your workspace and opens VS Code in your browser tab, the Readme file might not appear by default. If so, follow the actions illustrated in Figure 2.
Figure 2: Mouse actions in VS Code to open the tutorial.
In summary, unfold the ENDPOINTS group at the bottom-left corner, on the left panel of VS Code, and reveal and open the tutorial documentation link to get started, as per the actions shown in Figure 2.
Watch the intro video
To help you get started and get a glimpse of the tutorial, watch the video below to see how to provision your sandbox environment and some of its highlights.
Take your learnings further
What you’ll learn following the learning track just covers the basics. Its material is tightly related to the Solution Pattern “Edge to Core Data Pipelines for AI/ML”, from where the core of the source code originates.
To further broaden your knowledge on this fascinating topic, I strongly recommend following the link below to continue the journey:
And finally, find below a list of resources you might find useful:
- Find the Solution Pattern home page on which the tutorial is based.
- Explore other Solution Patterns also available.
- Read the Apache Camel page in Red Hat Developers to learn more about the capabilities of Apache Camel.
- Play with more tutorials in the Developer Sandbox for Red Hat OpenShift.
