VDURA Flash Relief Program: Beat Vast, Weka, or All-Flash cost by 50%

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Velocity • Durability

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Flash Volatility Index and Storage Economics Optimizer tool

The Flash Volatility Index tracks SSD price volatility and shows how it impacts real-world infrastructure costs compared to HDD. The Storage Economics Optimizer models total system cost across architectures and media mixes so teams can evaluate trade-offs before committing capital.

VDURA Flash Relief Program
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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 →

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.

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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Revisit the problem

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

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 →