The SSD Shortage Is Exposing a Deeper Architectural Failure

Constrained NAND wafer production and surging demand from hyperscale AI buildouts. Industry estimates project supply tightness for 18–24 months. For most enterprises, however, the impact is amplified by architectural inefficiency: replication alone consumes 50–66% of raw flash capacity before procurement is ever a factor.

Full replication burns two-thirds of raw flash on redundant copies (50–66% consumed), and even legacy erasure coding gives up 20–25% of capacity. VAST splits data into k data fragments and m parity fragments; any m failures rebuild from surviving data. Because parity is a small fraction of total data, overhead drops to under 3%. Its locally decodable design keeps enterprise fault tolerance and low-latency random reads, ending the trade-off that forced architects to accept protection overhead.

DASE (Disaggregated Shared Everything) is the architectural foundation behind VAST Amplify. Instead of dividing data across isolated storage nodes, DASE allows every storage node to see all data, enabling global data reduction across the entire system. This eliminates many of the inefficiencies that consume flash capacity in traditional architectures and allows organizations to unlock significantly more usable capacity from the SSDs they already own.

Capacity-weighted median of nearly 2:1 across production deployments, validated across exabytes of fleet data. Raw LLM training datasets (multimodal) achieve 3.0–8.0:1. Log stores and enterprise backups exceed 3.0:1. Scientific datasets range from 1.5–3.0:1. Results are dataset-dependent; these ranges reflect observed production values.

KV cache is the attention state an LLM generates during the prompt-processing phase of inference. Reusing it eliminates redundant computation, reducing inference costs and accelerating response times. As memory prices rise and customers shift to inference at scale, KV cache is driving significant, previously unforecasted demand for flash. VAST provides a persistent, high-performance KV cache tier with built-in data reduction to store and manage large KV cache repositories at enterprise scale.

Total data overhead is the aggregate percentage of raw flash consumed by protection, operational reserves, write buffers, and structural metadata before workloads occupy any space. Shared-nothing competitors lose 21–28% of raw capacity to architecture overhead; add replication on top and the majority of deployed flash is inaccessible. VAST achieves under 12% (3% parity + 9% system reserve), validated across exabytes of production deployments.

Amplify allows you to leverage existing SSD assets, while replacing your current SW with VAST, immediately unlocking significant new capacity without adding HW. During the assessment phase of the engagement, VAST works with each customer to create a phased transition plan to minimize disruption. In many cases, downtime can be avoided entirely by gradually failing out nodes as they are added to a new cluster.

Workloads generating large data volumes with structural similarity patterns, where global deduplication and compression extract significant savings, combined with high I/O demand requiring flash-speed access: AI/ML training, LLM inference and KV cache, log and telemetry analytics, genomics sequencing, financial time-series, and media. Organizations running multiple workload types on a unified VAST platform achieve compounding efficiency.

Flash scarcity is a structural constraint on enterprise NVMe SSD availability caused by constrained NAND manufacturing capacity and unprecedented hyperscale demand, resulting in extended lead times, price escalation, and procurement rationing. But the supply chain is only half the problem. Conventional storage architectures lose the majority of raw flash to replication and overprovisioning. Organizations that fix the architecture recover most of that capacity without buying additional hardware.

Capacity amplification allows you to store more logical data on the same physical assets, without purchasing additional hardware. Three mechanisms: erasure coding that reduces protection overhead from 50–66% (replication) to under 3%, global similarity-based data reduction (1.87:1 median, higher for AI and telemetry workloads), and consolidation of stranded, siloed storage into a single shared namespace. VAST Amplify applies DASE architecture to existing deployments to deliver capacity amplification.