The News: Weka has announced a new integrated appliance offering for its Weka Data Platform solution, named WEKApod. The WEKApod solution is certified for NVIDIA DGX SuperPOD systems and is designed to offer streamlined deployment of storage for AI. More about the release of WEKApod can be found in Weka’s blog post.
Weka Announces WEKApod Solution for Streamlined AI Deployments
Analyst Take: Weka has introduced a new integrated appliance solution, dubbed WEKApod, for deploying its Weka Data Platform. The WEKApod offering introduces a new turnkey appliance solution, alongside Weka’s existing software offering, providing flexibility for customers, and ultimately offering streamlined deployment of data storage for AI.
WEKApod is designed specifically to support NVIDIA-based AI deployments and the solution is certified for NVIDIA DGX SuperPOD. WEKApod also notably integrates with NVIDIA Base Command Manager for management and observability.
Configurations of WEKApod begin at 8 nodes and can expand in 4-node increments up to hundreds of nodes. Weka states an 8-node WEKApod configuration is capable of providing the performance required to support 128 NVIDIA DGX H100 systems. Weka has stated the following specifications for an initial 8-node deployment:
- 1 PB storage capacity
- 18.3 million IOPs
- 720 GB/s read bandwidth
- 186 GB/s write bandwidth
WEKApod offers the same software and features as the standard Weka Data Platform software, but in an easily deployable hardware offering. This offering provides greater flexibility for Weka customers and a streamlined approach for organizations to deploy infrastructure for AI workloads.
Traditionally, the HPC market has gravitated toward a do-it-yourself approach to parallel file systems, opting for software-only offerings. This trend stems in part from a desire to flexibly deploy the solutions as they choose, as well as having the knowledge base and dedicated staff required to do so. In the race to deploy AI applications, however, organizations appear to be taking a different approach, prioritizing more streamlined methods and opting for integrated appliance offerings that offer quicker deployment or less configuration. With the announcement of WEKApod, Weka can provide this streamlined deployment approach, simplifying the deployment of AI data infrastructure for organizations running AI workloads on NVIDIA systems.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Image Credit: Weka
Author Information
Mitch comes to The Futurum Group through the acquisition of the Evaluator Group and is focused on the fast-paced and rapidly evolving areas of cloud computing and data storage. Mitch joined Evaluator Group in 2019 as a Research Associate covering numerous storage technologies and emerging IT trends.
With a passion for all things tech, Mitch brings deep technical knowledge and insight to The Futurum Group’s research by highlighting the latest in data center and information management solutions. Mitch’s coverage has spanned topics including primary and secondary storage, private and public clouds, networking fabrics, and more. With ever changing data technologies and rapidly emerging trends in today’s digital world, Mitch provides valuable insights into the IT landscape for enterprises, IT professionals, and technology enthusiasts alike.
