PaletteAI abstracts away the complexity of deploying AI and ML application stacks on Kubernetes. Built on proven orchestration technologies, PaletteAI enables data science teams to deploy and manage their own AI and ML application stacks while platform engineering teams maintain control over infrastructure, security, and more.
PaletteAI uses a hub-spoke architecture to separate the control plane from the data plane. The hub cluster is where you manage and configure applications. Spoke clusters are where your AI/ML applications actually run. This separation allows a single control plane to orchestrate workloads across many environments.
PaletteAI uses OCI (Open Container Initiative) registries to store and distribute workload artifacts between hub and spoke clusters. When you create an App Deployment or Model Deployment, the spoke cluster's Workload controller renders your Workload Profile into Kubernetes manifests, packages them as OCI artifacts, and stores them in the spoke's OCI registry. Flux controllers on the spoke then pull these artifacts and apply them.