Dell EMC PowerScale F710 All-Flash NAS Node

The PowerScale F710 All-Flash NAS Node represents Dell EMC's latest entry into the scale-out storage segment, purpose-built for organizations requiring extreme performance combined with horizontal scalability. The F710 leverages a distributed architecture with NVMe flash storage, enabling linearly scalable throughput and capacity across multiple nodes in a single namespace. Designed for latency-sensitive workloads, the system achieves microsecond-class response times while maintaining consistent performance under sustained high-concurrency access patterns typical of AI/ML training pipelines and real-time media ingest scenarios.

The platform integrates OneFS operating system with OneFS in Kubernetes (IsiK) containerization support, enabling seamless integration into modern cloud-native and on-premises data infrastructure. The F710 targets organizations managing unstructured data at scale—particularly research institutions processing scientific datasets, streaming media providers encoding and serving content, and enterprise AI teams requiring unified storage for model training and inference workloads. The node's architecture supports multi-protocol access (NFS, SMB, HDFS, S3) while maintaining single-namespace consistency across the cluster.

Launched in Q1 2024, the F710 addresses market demand for dedicated all-flash NAS infrastructure that bridges the performance gap between enterprise SAN arrays and traditional scale-out NAS systems. The system incorporates Dell EMC's proven reliability engineering, redundant controllers, hot-swappable components, and built-in data protection mechanisms including snapshots, replication, and erasure coding.

Ideal for

• AI/ML model training pipelines requiring high-throughput random I/O and sub-millisecond latency for distributed training frameworks (TensorFlow, PyTorch)
• Real-time media ingest, transcoding, and content delivery workflows for streaming platforms and broadcast operations
• High-performance genomics and scientific research data processing supporting parallel analysis of petabyte-scale datasets
• Machine learning inference serving with synchronized access to model repositories and feature stores across multiple inference nodes
• Financial services risk modeling and quantitative analysis requiring deterministic low-latency access to large shared datasets
• Autonomous vehicle and robotics development supporting sensor data collection, processing, and model training at scale

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.