Storage Configuration¶
AIM Engine uses persistent volumes for model caching. This guide covers storage setup and sizing.
Requirements¶
Model caching requires ReadWriteMany (RWX) persistent volumes so that multiple pods can mount the same cached model data. You need a CSI driver that supports RWX access mode, such as:
Default Storage Class¶
Set the default storage class for all AIM PVCs via cluster runtime configuration:
apiVersion: aim.eai.amd.com/v1alpha1
kind: AIMClusterRuntimeConfig
metadata:
name: default
spec:
storage:
defaultStorageClassName: longhorn
Without this setting, AIM Engine uses the cluster's default storage class.
PVC Headroom¶
AIM Engine sizes PVCs based on discovered model sizes plus a configurable headroom percentage. This accounts for filesystem overhead and temporary files during downloads.
apiVersion: aim.eai.amd.com/v1alpha1
kind: AIMClusterRuntimeConfig
metadata:
name: default
spec:
storage:
pvcHeadroomPercent: 15
The default headroom is 10%. The final PVC size is rounded up to the nearest GiB.
Storage Sizing Guidelines¶
Model storage requirements vary significantly:
| Model Size Category | Approximate Storage | Example |
|---|---|---|
| Small (7-8B params) | 15-20 GiB | Qwen3 8B |
| Medium (30-70B params) | 60-140 GiB | Qwen3 32B, DeepSeek R1 70B |
| Large (100B+ params) | 200+ GiB | Mixtral 8x22B |
These are per-model estimates. A template cache PVC holds all model sources for that template.
Monitoring Storage¶
Check PVC usage:
# List AIM-related PVCs
kubectl get pvc -l aim.eai.amd.com/artifact -n <namespace>
# Check artifact download status
kubectl get aimartifact -n <namespace>
Cleanup¶
Template cache PVCs are owned by AIMTemplateCache resources, which are owned by templates. When a template is deleted, its caches and PVCs are cleaned up automatically.
To manually reclaim storage:
# Delete a template cache (also deletes its PVCs and artifacts)
kubectl delete aimtemplatecache <name> -n <namespace>
Next Steps¶
- Model Caching Guide — Caching modes and configuration
- Model Caching Concepts — Cache hierarchy and ownership