Core

Parallel Filesystems vs Object Storage

Choose storage by access semantics, working-set reuse and failure protection. Trace a shared read/checkpoint budget, distinguish local completion from durable export, and learn when a second storage tier earns its cost.

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RELATED CONCEPTS

Data Loading Pipelines for Training Checkpoint I/O GPUDirect RDMA and GPUDirect Storage Training Cluster Design at 10k GPUs Capacity Planning and Utilization TCO: Buy vs Rent

LESSONS THAT TEACH THIS

Fleet and ReliabilitySize storage for bytes, operations, concurrency and durability14 min→Fleet and ReliabilitySpecify isolation by resource and validate the end-to-end promise30 min→

PRACTICE THIS IN REAL QUESTIONS

AI Infrastructure System DesignDesign the checkpoint store for a lab running several large training jobs: write bursts, retention, resharding and lineage.→Networking, Interconnects & StorageParallel filesystem or object storage for training data? Make the call and explain the two-tier pattern most clusters end up with.→Networking, Interconnects & StorageWhy does object storage behave badly for random reads, and what does a training pipeline do about it?→Napkin Math, Cost & CapacityEstimate how long it takes to write a checkpoint for a 405B training run→AI Infrastructure System DesignDesign the eval pipeline for a frontier model: thousands of evals per checkpoint, sharded inference, caching, reproducible results.→AI Infrastructure System DesignDesign the runtime for long-running agents: sessions, tool sandboxes, KV that lives for hours, and checkpoints.→