Cache-Billed Versus Capacity-Billed Filesystems for AI Agent Workloads
Provider cache eviction forces agents onto storage that survives restarts and forks.
Provider cache eviction forces agents onto storage that survives restarts and forks.
Access your S3 bucket as a filesystem without moving data.
Unified mount lets AI agents access cloud storage buckets like local directories without migration.
Incomplete planning and hidden data turn migrations into data loss and compliance disasters.
Agents share cloud storage buckets as filesystems while preserving S3 access and POSIX semantics.
Decouple applications from storage vendors using four architectural patterns.
Pretraining gives AI agents an edge with familiar filesystem interfaces over custom APIs.
Multiple nodes writing to the same bucket require coordination the object store won't provide.
Multi-cloud GPU training demands storage that spans AWS, GCP, and Azure without egress penalties.
Hole punching recovers wasted disk space in Linux files through deliberate deallocation.
Checkpoint speed and cost determine whether a parallel filesystem or object-storage layer wins.
Metadata operations, not bandwidth, bottleneck distributed AI training systems.