Fluidstack and VAST Data Partnership: Elevating AI Workload Performance with Advanced Storage Solutions

In the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML), infrastructure performance is paramount. Fluidstack, a leader in distributed cloud compute, has strategically partnered with VAST Data, a pioneer in next-generation storage architectures, to deliver a transformative solution that significantly enhances AI workload performance. This collaboration addresses the critical bottlenecks in AI data pipelines by combining Fluidstack’s scalable compute platform with VAST Data’s revolutionary storage technology, enabling enterprises to accelerate AI model training, inference, and data analytics at unprecedented scale and efficiency.

1. Product Overview

The Fluidstack and VAST Data partnership integrates two cutting-edge technologies to create a unified platform optimized for AI workloads. Fluidstack provides a distributed cloud compute environment that leverages idle compute resources across global data centers, offering elastic, cost-effective GPU and CPU compute power. VAST Data complements this by delivering a high-performance, scalable storage solution designed specifically for data-intensive AI applications.

At its core, the joint solution addresses the challenges of AI infrastructure: massive data ingestion, ultra-low latency access, and seamless scalability. VAST Data’s Universal Storage architecture eliminates traditional storage bottlenecks by combining NVMe flash, Intel Optane persistent memory, and advanced erasure coding to deliver petabyte-scale capacity with sub-millisecond latency. Fluidstack’s platform dynamically provisions compute resources close to the data, reducing data movement and network overhead, which is critical for AI training and inference workflows.

This partnership is particularly impactful for enterprises running large-scale AI workloads such as natural language processing (NLP), computer vision, autonomous systems, and recommendation engines. By integrating Fluidstack’s distributed compute fabric with VAST Data’s storage, organizations can achieve faster time-to-insight, improved model accuracy through larger datasets, and reduced total cost of ownership (TCO) for AI infrastructure.

Fluidstack Distributed Compute Platform

Fluidstack’s platform aggregates underutilized compute resources from data centers worldwide, creating a global, elastic compute pool. This approach enables AI practitioners to access GPU-accelerated compute on demand without the capital expense of dedicated hardware. The platform supports Kubernetes orchestration, containerized AI workloads, and integrates with popular ML frameworks such as TensorFlow, PyTorch, and MXNet.

VAST Data Universal Storage Architecture

VAST Data’s Universal Storage is architected to overcome the limitations of traditional storage systems that rely on spinning disks or tiered flash. It uses a disaggregated architecture where compute and storage are decoupled, enabling independent scaling. The system employs a patented erasure coding scheme that provides enterprise-grade data protection with minimal overhead. Its use of NVMe over Fabrics (NVMe-oF) ensures high throughput and low latency, critical for AI data pipelines.

2. Product Specifications

Fluidstack Compute Specifications

• Compute Resources: Access to NVIDIA A100, A40, and RTX 6000 GPUs; Intel Xeon Scalable CPUs
• Compute Model: Distributed cloud compute with Kubernetes orchestration
• Network: High-speed 10/25/40/100 Gbps connectivity with low-latency peering
• Storage Integration: Native integration with VAST Data Universal Storage via NVMe-oF
• Security: End-to-end encryption, zero-trust architecture, and compliance with SOC 2 and GDPR
• APIs & SDKs: RESTful APIs, Python SDKs for seamless integration with AI pipelines

VAST Data Storage Specifications

• Storage Media: NVMe flash drives combined with Intel Optane persistent memory
• Capacity: Scalable from tens of terabytes to multiple petabytes in a single namespace
• Performance: Up to 10 million IOPS per cluster; sub-millisecond read/write latency
• Data Protection: Advanced erasure coding with 6+2 or 8+3 configurations for fault tolerance
• Protocol Support: NVMe-oF, NFSv3/v4, SMB 3.0, S3-compatible object storage
• Scalability: Linear scaling of performance and capacity without downtime
• Management: AI-driven analytics and predictive maintenance via VAST Data Insights

3. Features and Benefits

Seamless Scalability for AI Workloads

The Fluidstack and VAST Data solution enables organizations to scale compute and storage independently and elastically. This flexibility is crucial for AI workloads that experience variable demand during model training and inference phases. Enterprises can dynamically provision additional GPU resources from Fluidstack’s global pool while expanding storage capacity with VAST Data’s universal storage without service interruption.

Ultra-Low Latency Data Access

AI workloads are highly sensitive to data access latency. VAST Data’s NVMe-oF architecture delivers sub-millisecond latency, ensuring that GPUs and CPUs receive data at line rate without bottlenecks. This reduces idle compute cycles and accelerates model training times significantly. Fluidstack’s compute nodes are strategically located to minimize network hops, further reducing latency.

Cost Efficiency and Resource Optimization

By leveraging Fluidstack’s distributed compute model, organizations avoid the capital expenditure associated with purchasing and maintaining dedicated AI hardware. The pay-as-you-go model aligns costs with actual usage. VAST Data’s architecture reduces storage overhead by eliminating the need for multiple