The IT Nerd

VDURA and Wasabi Technologies, the hot cloud storage company, have announced a technology alliance to connect GPU-adjacent AI data infrastructure with predictably priced S3-compatible cloud storage. 

Through the alliance, the companies will collaborate to help AI factories, neoclouds and enterprise HPC environments place active datasets and checkpoints close to GPUs while extending long-term retention, protection and data reuse into the cloud.

The alliance is anchored by a simple operating principle: keep AI data close when it is being used and move it freely when it is not. AI infrastructure teams routinely keep far more inactive data on performance infrastructure than they need to, because moving it has meant operational complexity, access delays or unpredictable cloud costs. The result is performance capacity consumed by data that no longer requires it, and retained data that is harder to protect, govern and reuse than it should be. 

VDURA’s high-performance data storage serves the active phase of the AI data lifecycle: dataset staging, model loading, training, checkpointing and inference. VDURA provides GPU-adjacent parallel file system storage performance with RDMA data paths and full POSIX workflows, spanning NVMe flash, HDD capacity and a native S3 interface within a single global namespace.

Wasabi extends the environment with S3-compatible cloud object storage serving as an active archive and long-term retention layer. Datasets, checkpoints, model versions and derived artifacts that are no longer in active use move to Wasabi for protection, compliance, disaster recovery and distribution to other sites or compute environments, and remain readily accessible for retraining, model comparison and governance. Wasabi’s predictable pricing, with no per-GB egress or API request charges under its standard terms, allows teams to plan retention and reuse costs in advance rather than discovering them on an invoice.

Tiered data placement is a practice long proven by the largest cloud operators, who pair lean performance infrastructure with deep, low-cost capacity. The alliance brings a comparable design pattern to organizations building their own AI infrastructure, using two independent, specialized platforms connected through open interfaces rather than a single closed stack.

The joint technology alliance will be present at Ai4 2026, August 4 to 6 at The Venetian in Las Vegas, where Wasabi will exhibit at booth #935. Ai4 is North America’s largest artificial intelligence industry event, gathering more than 12,000 attendees across enterprise AI, infrastructure and research.

VDURA today announced three major advances for ISC High-Performance 2026: a next-generation multi-tenant control plane, significant S3 performance improvements and native S3 object tagging. Together, these capabilities are designed to simplify operations and accelerate data-intensive workloads at scale for AI and HPC organizations worldwide.

Planned for general availability in the second half of 2026, these advances continue VDURA’s mission to deliver the world’s most powerful data infrastructure platform for AI and HPC.

Next-Generation Control Plane: Simplified, Multi-Tenant Management for AI and HPC Environments

VDURA’s next-generation control plane, planned for general availability later this year, is purpose-built for the operational demands of modern AI and HPC environments. It introduces a modern management interface that delivers a streamlined tenant administration model, enabling platform and tenant operators to manage complex multi-tenant storage environments from an intuitive dashboard. Alongside the new UI, a REST API for key platform operations gives operators and integrators a foundation for automation and tooling workflows. Together, they significantly reduce operational overhead while preserving the depth of control that enterprise and research organizations require.

S3 Performance Improvements: Sustained Throughput for Cloud-Native AI Pipelines

VDURA is delivering targeted S3 performance improvements designed to sustain high throughput across cloud-native AI pipelines, including AI model checkpointing, inference serving, and large-scale dataset ingestion. These improvements reduce latency for S3-native operations and increase aggregate throughput for concurrent read and write workloads, ensuring the VDURA Data Platform continues to deliver the performance AI operators demand as workloads scale.

S3 Tags: Metadata-Driven Control Across the Data Lifecycle

Building on enhanced S3 performance, VDURA is also introducing native S3 object tagging support, enabling organizations to attach rich metadata to objects stored on the VDURA platform. S3 Tags unlock policy-based data lifecycle management, automated tiering workflows, and fine-grained access controls across AI training datasets, model artifacts, and scientific data collections. For HPC and AI operators managing petabyte-scale object stores, S3 Tags provide the metadata infrastructure required to enforce governance policies and manage data across its full lifecycle.

Availability

The Next-Generation Control Plane, S3 Performance Improvements, and S3 Tags are planned for general availability in the second half of 2026 for all V5000 class systems. Existing customers can upgrade in place via an online software update. Customers interested in early access are encouraged to visit VDURA at ISC 2026 or contact the VDURA sales team at vdura.com.

VDURA at ISC High Performance 2026

VDURA is exhibiting at ISC High Performance 2026 in Hamburg, Germany. Visit the VDURA booth G21 to experience these new capabilities firsthand and learn more about VDURA’s full portfolio of AI and HPC storage solutions.

 VDURA today announced Version 12 of the VDURA Data Platform, a major software release that redefines scalability and resilience for AI and high-performance computing (HPC) environments. V12 increases performance on every metric and introduces a new elastic Metadata Engine, system-wide Snapshot Support, and optimized integration for hyperscale class HDD’s using Shingled Magnetic Recording (SMR) technology to deliver unprecedented performance efficiency, durability, and capacity scaling across the data lifecycle.

Building on the performance foundation established in V11, VDURA V12 Key Highlights of Data Platform V12 include:

• Elastic Metadata Engine: A next-generation, scale-out, metadata engine designed for increased performance. It dynamically scales across nodes to sustain performance as file and object counts grow, eliminating traditional bottlenecks and improving metadata operations by up to 20x.
• Snapshot Support: Enables instantaneous, space-efficient point-in-time copies of datasets for AI pipelines, model checkpoints, and operational recovery. Snapshots integrate seamlessly with support for both manual and policy-based retention.
• SMR HDD Optimization: Extends the VDURA data platform to support Shingled Magnetic Recording (SMR) drives for ultra-dense data storage. A new write-placement engine organizes sequential zones intelligently, unlocking 25–30% more capacity per rack without compromising throughput or data integrity. 

Breakthrough Performance Meets Resilient Scale

The Elastic Metadata Engine enables metadata operations to scale linearly across multiple metadata nodes, supporting billions of files and objects under active use. Combined with snapshot and SMR tier support, V12 further reduces total cost of ownership while extending VDURA’s lead in AI-scale storage economics. With aggregate throughput performance increased by more than 20%, V12 delivers unmatched efficiency for training pipelines, inference workloads, and hyperscale data movement.

Availability

VDURA Data Platform V12 will be generally available in Q2 2026 for all V5000 and V7000-class systems. Existing customers running V11 or later can upgrade in place via an online software update with zero downtime.

The Mountain vs. the Data Transfer Record at SC25

On Nov 18, 2025, at 11:30 AM CT, Hafþór “Thor” Björnsson returns to SC25 Booth #2033 with VDURA to break the AI and HPC data transfer record. Powered by Phison Pascari SSDs and the VDURA Data Platform, Thor will move hundreds of petabytes in seconds, demonstrating the next level of data performance and scalability.

Last year, Thor stunned the crowd with his World Record Data Lift, hoisting over 282 PB of capacity, the most data ever lifted. This year, it’s all about speed.

VDURA has announced the launch of its first scalable AMD Instinct™ GPU reference architecture in collaboration with AMD. The new validated blueprint defines how compute, storage and networking should be configured for efficient, repeatable large-scale GPU implementations. The design combines the VDURA V5000 storage platform with AMD Instinct™ MI300 Series Accelerators to eliminate performance bottlenecks and simplify deployment for the most demanding AI and high-performance computing (HPC) environments. 

AI and HPC pipelines are increasingly limited by storage that cannot keep pace with growing data volumes. This slows GPU utilization, increases energy costs and reduces overall efficiency. The new reference architecture is engineered to keep AMD Instinct™ GPUs fully utilized, delivering sustained performance with a design that is efficient, expandable and simple to operate. 

Following a technical evaluation, AMD selected VDURA for its AMD Instinct™ GPU-optimized performance, low client overhead and proven ability to scale. The solution has already been chosen for a U.S. federal systems integrator AI supercluster, demonstrating its readiness for mission-critical workloads. 

The reference architecture provides compute, storage and networking at scale. It supports 256 AMD Instinct™ GPUs per scalable unit, achieves throughput of up to 1.4 TB/s and 45 million IOPS in an all-flash layout, and delivers around 5 PB of usable capacity in a 3 Director and 6 V5000 node configuration. Data durability is assured through multi-level erasure coding, while networking options include dual-plane 400 GbE and optional NDR/NDR200 InfiniBand. 

Built to grow with demand, the modular design allows organizations to add Director Nodes for extra performance, expand with all-flash storage for more bandwidth, or combine flash and HDD capacity for cost-effective growth, all within a single namespace.  

For further information, the full 20-page architecture reference guide is available for download at: https://www.vdura.com/wp-content/uploads/2025/07/VDURA_AMD_AI_Reference-Architecture-2.pdf