Profile bundles are reusable bundles that package infrastructure and application configurations for consistent, repeatable deployments across compute pools. You can create profile bundles through the PaletteAI user interface (UI) or import them from Palette AI Studio using the PaletteAI CLI.
Workload profiles are reusable templates that define how an application should be configured, decoupling the modeling and deployment phases of the application lifecycle. You build workload profiles from definitions (components, traits, and policies) and use them when creating profile bundles and deploying applications and models with those profile bundles.
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.
A Workload represents an application or task running on your infrastructure. Workloads are Kubernetes resources automatically created by AIWorkloads, which are built from three types of building blocks called Definitions: