Why S3FS Fails in AI/ML — and How to Achieve Scalable POSIX Access Anyway
Mounting S3-compatible storage via S3FS seems like an easy way to enable POSIX-like access in Kubernetes. But in real AI/ML workloads—e.g., training with PyTorch or TensorFlow—we hit major issues: crashes from incomplete writes, vanished checkpoints, inconsistent metadata, and unpredictable I/O latency.