7 docs tagged with "profile bundles"

PaletteAI's definition playground is where you can create and edit Definitions. It provides a three-pane user experience similar to the Helm Playground. Each pane in the playground plays a specific purpose:

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.

This page covers how to reference outputs and user variables using PaletteAI's macro system in workload profiles. The different source types for macros include:

Components and traits are rendered into Kubernetes resources when a Workload is deployed. There are three types of outputs that can be referenced via workload profile macros:

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.

PaletteAI renders CUE templates using a modified version of the KubeVela rendering engine. For a comprehensive introduction to CUE syntax, refer to CUE Basic.