This page describes Google Cloud products that are integrated with Cloud Storage FUSE.
For a list of Google Cloud products that are integrated with Cloud Storage generally, see Integration with Google Cloud services and tools.
| Product | How Cloud Storage FUSE is integrated |
|---|---|
| Google Kubernetes Engine (GKE) | The Cloud Storage FUSE CSI driver manages the integration of Cloud Storage FUSE with the Kubernetes API to consume pre-existing storage buckets as volumes. You can use the Cloud Storage FUSE CSI driver to mount buckets as file systems on Google Kubernetes Engine nodes. |
| Vertex AI | When you perform custom training on Vertex AI, Vertex AI uses Cloud Storage FUSE to mount your storage buckets as file systems to store your training data. For more information on how Vertex AI uses Cloud Storage FUSE, see Read and write Cloud Storage files with Cloud Storage FUSE in the Vertex AI documentation or the blog Cloud Storage as a file system in AI training. |
| Deep Learning VM Images | Cloud Storage FUSE comes pre-installed with Deep Learning VM Images. |
| Deep Learning Containers | To mount storage buckets for Deep Learning Containers, you can either use the Cloud Storage FUSE CSI driver (recommended) or install Cloud Storage FUSE. |
Cloud Storage FUSE for machine learning
Cloud Storage FUSE is a common choice for developers looking to store and access machine learning (ML) training and model data as objects in Cloud Storage. Cloud Storage FUSE provides several benefits for developing ML projects:
Cloud Storage FUSE lets you mount Cloud Storage buckets as a local file system so your applications can access training and model data using standard file system semantics. This means that you can avoid the cost of rewriting or refactoring your application's code when using Cloud Storage to store ML data.
From training to inference, Cloud Storage FUSE lets you leverage the native high scalability, performance, and cost effectiveness of Cloud Storage, so you can run your ML workloads at scale.
Cloud Storage FUSE allows you to start training jobs quickly by providing compute resources with direct access to data in Cloud Storage, so you don't need to download training data to the compute resource.
For more information, see ML frameworks supported by Cloud Storage FUSE.