CoreWeave Data Handling

Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.

Overview

CoreWeave GPU cloud workloads involve large-scale data artifacts: model weights (multi-GB safetensors/GGUF), training datasets (parquet, TFRecord, WebDataset), checkpoint snapshots, and inference cache volumes. Data flows through Kubernetes PersistentVolumeClaims backed by region-specific storage classes. Compliance requires encryption at rest via the storage driver, namespace-scoped RBAC for volume access, and audit logging for any data egress from GPU nodes.

Prerequisites

• Approved data classification, retention schedule, and region for the artifact.
• A namespace-scoped service account, encrypted storage class, and approved destination.
• Expected artifact size and SHA-256 from a trusted source before import.

Instructions