Modern AI Workflows, Reimagined

To successfully deploy AI projects in production environments your infrastructure must be able to process very large data sets rapidly as well ingest structured and unstructured data from a wide variety of sources. Legacy high-performance processing storage architectures are constantly moving data from one storage system to another, (object storage for archival data, NAS for persistent storage, parallel file systems for fast storage) increasing complexity and management and slowing results with expanding data transfer times.

80-85% Enterprises are running into the “last mile” problem with ML model deployment and management.

Sumit Pal, Sr. Director Analyst, Gartner
“Don’t Stumble at the Last Mile: Leveraging MLOps and DataOps to Operationalize AI and ML“

AI Project Challenges

Putting AI Models Into Operation is as Critical as Building Them

Key technical challenges to operationalizing AI projects are how to efficiently fill a pipeline, how to easily integrate across systems, and how to manage rapid change.


Data Pipelines Are Complex and Hard to Keep Filled

Each step of an AI pipeline usually has a completely different IO profile for data, which results in complexity, siloing of storage and data stalls in the pipeline


Workloads and Data Sprawl Across Disparate Systems

Data needs to be ingested from multiple sources and via multiple protocols. Today’s AI workloads need to run on premises and in the cloud


Infrastructure is Slow, Science Is Fast

Traditional infrastructure can take months to years to change, however, science changes much faster, and infrastructure needs to be able to adapt in weeks


Benefits of WEKA

Cloud Native, Datacenter Ready

Seamlessly run on-premises, in the cloud and burst between platforms

Faster than Local Storage

Accelerate large scale data pipelines with reduced epoch times, the fastest inferencing and highest images/secs benchmarks.

Multi Protocol Support

Supports Native NVIDIA GPUDirect Storage, POSIX, NFS, SMB, and S3 access to data

Zero Copy Architecture

Run entire pipeline on the same storage backend and eliminate the cost and stalls of copies.

Zero Tuning Mixed Workload Support

World's fastest filesystem, supporting high I/O, low latency, small files, mixed workloads & data portability.

Fully Software Defined

Run on your choice of hardware and support new server technologies as soon as they are available

Practical Implication

Supported Hardware

“WEKA IO was the clear choice for our DNN training…standard NAS would not scale and WEKA was the most performant of all the parallel file systems we evaluated…we really liked that it was hardware-independent allowing us better control over our infrastructure costs.”

Dr. Xiaodi Hou, Co-Founder And CTO


WEKA Architectural Whitepaper


WEKA Distributed Data Protection


Selecting Scalable Storage Solutions

Buyers Guide

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