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Clean up

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This document is for an unreleased version of Modelplane.

This document applies to the Modelplane main branch and not to the latest release v0.4.

Delete the model resources, the gateway, the clusters, and finally the control plane.

Delete model resources

Delete model resources before clusters. Deleting a cluster first leaves the deployments reconciling against infrastructure that no longer exists.

bash
kubectl delete md --all -n ml-team
kubectl delete ms --all -n ml-team

Wait for all model replicas to finish:

bash
kubectl get modelreplica -n ml-team --watch

Delete the gateway

Delete the gateway before its cluster. The InferenceGateway runs a load balancer on the cluster it names; deleting it while that cluster is still up lets the load balancer be removed, rather than leaking it when the cluster goes.

bash
kubectl delete ig --all

Delete the clusters

Delete all clusters with foreground cascading deletion. The serving stack on each workload cluster must uninstall while that cluster’s API server is still reachable. Foreground deletion holds each cluster object until its stack finishes. Background deletion can orphan cloud resources.

bash
kubectl delete ic --all --cascade=foreground

Wait until all clusters are deleted:

bash
kubectl get ic --watch

Delete the control plane

Delete the kind cluster:

bash
kind delete cluster --name modelplane