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 Compute Pool is a group of shared Compute resources used to create Kubernetes clusters where your AI/ML applications run. In the hub-spoke architecture, each Compute Pool becomes a spoke cluster on which applications and models are deployed.
This section covers the core concepts you need to understand when working with PaletteAI. Whether you are a platform engineer setting up infrastructure or a data scientist deploying workloads, these concepts explain how PaletteAI organizes resources and manages AI/ML deployments.
Profile Bundles are reusable bundles that package infrastructure and application configurations for consistent, repeatable deployments across Compute Pools. Instead of manually configuring each deployment's software components, you define it once in a Profile Bundle and reuse them wherever needed.