An AIWorkload is the custom resource that represents an App Deployment or Model Deployment on the PaletteAI hub cluster. When you complete the App Deployment or Model Deployment workflow, PaletteAI creates an AIWorkload resource in your Project namespace. The resource captures everything the deployment needs: the Profile Bundles to deploy, the workloads to generate from them, and the Compute Pool that runs them.
An App Deployment represents an AI/ML application deployed using a Profile Bundle; the Profile Bundle must contain a Workload Profile with the type Application. An App Deployment is the primary method that data scientists and ML engineers use to deploy their workloads onto Compute Pools.
A Model Deployment deploys AI/ML models to a Compute Pool for inference. It abstracts the infrastructure required to host and serve models, simplifying the user experience for data scientists by eliminating direct infrastructure management. It is implemented as an AIWorkload resource with the palette.ai/aiworkload-type: model label.