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Flash economics

Flash pricing is volatile.
Your AI infrastructure should not be.

Analysis shows SSD pricing volatility is now a structural risk for AI and HPC infrastructure planning.

This analysis is based on transparent hardware cost assumptions and current, publicly published industry pricing benchmarks.
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What changed

Flash cost predictability broke

AI demand and NAND supply cycles are making multi-year storage planning harder than most teams expect.

What matters

Economics, not just performance

Performance is solvable. The risk is budget drift and forced architecture compromises over time.

What to do

Architect for volatility

Separate performance data from retention data without losing a single namespace or parallel speed.

About the researcher

Erik Salo, SVP at VDURA

Erik Salo leads products, markets, and operations at VDURA for AI data infrastructure, while publishing analysis on how storage architecture and economics affect performance, scalability, and long-term risk.

Erik’s knowledge base includes decades of experience spanning semiconductors, storage systems, and global enterprise deployments.

The hidden risk in AI infrastructure economics

AI infrastructure planning often assumes flash pricing is stable. It is not. Volatility shows up as budget drift, refresh constraints, and forced tradeoffs at scale.

THE ASSUMPTION

“We can forecast SSD cost over 3 years.”
  • Procurement cycles assume predictable unit economics
  • AI programs assume storage cost curves look like last year
  • All-flash architectures assume pricing remains favorable

THE REALITY

NAND cycles and AI demand are making SSD pricing less predictable.
  • Pricing variability becomes a planning risk
  • Cost spikes force retention data onto premium tiers
  • Teams delay capacity adds or compromise performance

Model the real cost of flash over time

Use the SSD Pricing Volatility Calculator to understand how flash pricing variability impacts your environment across multiple years. Updates reflect the latest research as it evolves.

Want full methodology and assumptions? View the whitepaper →

SSD pricing volatility research

Analysis tracked SSD pricing behavior across multiple NAND cycles to quantify the economic risk introduced by flash volatility. The conclusion is clear: architectures that assume flat flash pricing expose organizations to unpredictable cost expansion over time.

Read the Technical Bulletin →

Why architecture matters more than ever

AI workloads are not uniform. Training and inference demand NVMe flash. Retention, checkpoints, and long-term datasets do not. If everything is forced onto flash, pricing volatility becomes systemic risk.

Architect for volatility

Separate performance data from retention data without sacrificing a single namespace or parallel performance.
  • Flash-first NVMe performance where it matters most
  • Cost-efficient capacity tiers for retention and growth
  • Single global namespace across data tiers
  • True parallel file system architecture

Built for performance and economic resilience

VDURA was designed to decouple performance from long-term storage economics. That design choice matters more today than ever.
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