NetApp Deploys Iguazio's Data Science Platform to Optimize Storage Management

By Tiera Oliver

Associate Editor

Embedded Computing Design

June 11, 2020


Data Science Platform boosts infrastructure behind NetApp's Active IQ solution, providing actionable intelligence for predictive maintenance and optimal data management.

Iguazio announced a new strategic customer, NetApp, which is using its platform to analyze 10 trillion data points per month, to automate the support and optimization of storage. NetApp’s Active IQ uses predictive analytics to automate the proactive care and optimization of storage controllers owned by customers around the world.

NetApp turned to Iguazio to replace their traditional data warehouse and Hadoop-based data lake with a Kubernetes-powered, cloud-native, serverless data science platform which can analyze massive amounts of data in real-time.

According to the company, the platform is deployed both in the cloud and on-premises on NetApp’s Cloud Volumes and NetApp’s All Flash Storage, driving the following gains in cost reduction and accelerated time to market:

  • 50% reduction in operating costs 
  • 16x storage capacity reduction 
  • 3-6x fewer compute nodes 
  • 6-12x improvement in time to develop and deploy new AI services 

NetApp wanted to build a digital advisor that uses AI at scale and in real-time to continually gain insights on these devices and conduct predictive maintenance on storage.

Previously built on Hadoop, NetApp was also looking to modernize the service infrastructure to reduce the complexities of deploying new AI services and the costs of running large-scale analytics. In addition, the shift was needed to enable real-time predictive AI, and to abstract deployment, allowing the technology to run on multi-cloud or on premises seamlessly. 

Iguazio’s platform integrates with NetApp’s Trident technology, hooking up a Kubernetes cluster to its NFS (Network File System) and Cloud Volumes Storage.  Last month, Iguazio announced its partnership with NetApp, offering their joint data science and MLOps (machine learning operations) solution on NetApp’s ONTAP AI product.

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Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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