Kubernetes Deployment

Spice.ai runs on any Kubernetes cluster — managed (EKS, GKE, AKS) or self-hosted (kubeadm, k3s, Kind, RKE2). The official Spice Helm chart is the foundation for all three deployment paths covered here.

Choose the workflow that matches the operating model:

Path	When to use
Helm	Direct, imperative deploys with helm install / helm upgrade. Simplest path for getting started or CI-driven pipelines that already invoke Helm.
Argo CD	GitOps with continuous reconciliation. Define the desired state in Git; Argo CD applies and self-heals.
Flux	GitOps with native Kubernetes-style controllers (HelmRelease, HelmRepository, Kustomization). Lightweight alternative to Argo CD.

All three options consume the same chart and values.yaml, so configuration learned in one path transfers directly to the others.

Spice.ai Enterprise Operator

For production lifecycle management beyond what the Helm chart provides, the Spice.ai Enterprise Kubernetes Operator introduces two custom resources:

• SpicepodSet — declarative replica management with automatic PVC resizing, rolling/parallel update strategies, crashloop protection, and per-replica StatefulSets when persistent volumes are configured. Use it instead of the chart's stateful mode for stateful workloads.
• SpicepodCluster — distributed query clusters with dedicated scheduler and executor nodes, automatic mTLS, and shared object-store-backed state. Use it for horizontally scaled query execution and high availability.

The operator works alongside Helm, Argo CD, and Flux — install the operator chart and manage SpicepodSet / SpicepodCluster resources from the same GitOps pipeline.

Prerequisites

• Access to a Kubernetes cluster (v1.25+ recommended).
• kubectl configured for the target cluster. See the Kubernetes documentation.
• For local testing, Kind or k3d provide a quick single-node cluster.

Cookbook

• Running Spice.ai in Kubernetes