product updates, company news, and insights on building and optimizing your data pipelines.
EBS, EFS, FSx, object storage, CSI drivers — Kubernetes gives you many options for ML storage and all the wrong defaults. Here's the pattern that actually works for training workloads.
POSIX semantics on top of object storage is an old and messy problem. Here's what's possible, what's impossible, and what ML teams should actually demand from a storage layer.
A caching gateway colocated with your GPUs is the biggest single lever for training throughput. Here's how the architecture works and why it produces such dramatic speedups.