A Transformative Solution Framework for Accelerated DataOps
WEKA is a solutions ecosystem engineered to solve Accelerated DataOps challenges, delivering Reference Architectures and Software Development Kits with leading AI solutions partners. It provides a production-ready storage solution where the entire data pipeline workflow—ingest data, to batch feature extraction, to hyperparameter optimization, and finally to inferencing and versioning—can be run on the same platform, whether running on-prem or in the public cloud. Direct access to data for training and inferencing eliminates data staging at the compute layer and storage silos which results in shorter Epoch and Wall Clock time.
Reference Architectures And Technical Briefs
DataOps Workflow And Related Storage Challenges
Different stages within AI data pipelines have distinct storage requirements for massive ingest bandwidth, need mixed read/write handling and ultra-low latency, often resulting in storage silos, for each stage. This means business and IT leaders must reconsider how they architect their storage stacks and make purchasing decisions for these new workloads.


Ingest
Needs massive concurrency, write (WR) throughput
Enrich
Needs labelling, index, search, and cloud bursting
Train
Needs massive read (RD) throughput
Validate
Needs large number of streams replay
Infer
Needs low latency access
Retain
Needs lifecycle, management, versioning, and reproducibility