Google has introduced new Cloud Storage FUSE profiles on Google Kubernetes Engine (GKE) to enhance AI/ML workloads. Announced on April 20, these profiles automate performance tuning, reducing operational overhead and accelerating data access for tasks like training and inference. The profiles offer dynamic resource-aware optimization, including automatic cache size adjustments and media selection, and enable Rapid Cache to boost read performance. However, they are not compatible with CSI ephemeral volumes and do not support dynamic mounting. Additional costs apply for Cloud Storage operations and Rapid Cache usage.
Google Unveils Cloud Storage FUSE Profiles on GKE for AI/ML Efficiency
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