Modern artificial intelligence (AI) and machine learning (ML) workloads require the utmost flexibility and speed. They also need data—the more, the better. For the best results, you need a solution that can unify your data pipeline across edge, core, and cloud. NetApp and Iguazio have been partners for over 2 years, simplifying the life of data scientist teams and allowing them to bring AI projects to market much faster through automation and deploying data pipelines that scale.
The Iguazio Data Science platform is a fully integrated and secure data science platform as a service (PaaS) that simplifies development, accelerates performance, facilitates collaboration, and automates ML pipelines. It provides a complete workflow in a single ready-to-use platform that includes all the required building blocks for creating data science applications from research to production. One of the managed services is Jupyter Notebooks. Each developer gets a deployment of a Notebook container with the resources they need for development.
Amazon FSx for NetApp ONTAP is fully integrated managed storage built on the popular NetApp® ONTAP® file system. FSx for ONTAP brings the full capabilities of ONTAP to a native Amazon Web Services (AWS) managed service, delivering a consistent hybrid cloud experience. The Iguazio Jupyter Notebook takes advantage of the data protection available in Amazon FSx for ONTAP by mounting the FSx ONTAP volumes to the Jupyter Notebook, or by mounting them as a data directory for the training jobs. The Amazon FSx for ONTAP file system has tight integration with the NetApp DataOps Toolkit, a Python library that makes it easy for developers and data scientists to perform numerous data management tasks.
Figure 1) Iguazio integrating with NFS file share running in Amazon FSx for ONTAP.
The solution integration from NetApp and Iguazio provides seamless integration of NetApp storage, Amazon Web Service cloud services, and Iguazio MLOps automation. The customer uses the data in their machine learning and deep learning workflows, generating automated, reproducible pipelines that accelerate the deployment of AI in production and enable the continuous rollout of new AI services. The customer receives the managed services directly from their Amazon Web Services account in a few clicks, and they save time, effort, and resources to focus on the data science.
This simple end-to-end solution for deploying and managing large-scale AI applications in hybrid and real-time environments brings automation of the data science process and acceleration in the deployment of AI products. To learn more about this joint solution with Iguazio, read this technical report.
Mike McNamara is a senior product and solution marketing leader at NetApp with over 25 years of data management and cloud storage marketing experience. Before joining NetApp over ten years ago, Mike worked at Adaptec, Dell EMC, and HPE. Mike was a key team leader driving the launch of a first-party cloud storage offering and the industry’s first cloud-connected AI/ML solution (NetApp), unified scale-out and hybrid cloud storage system and software (NetApp), iSCSI and SAS storage system and software (Adaptec), and Fibre Channel storage system (EMC CLARiiON).
In addition to his past role as marketing chairperson for the Fibre Channel Industry Association, he is a member of the Ethernet Technology Summit Conference Advisory Board, a member of the Ethernet Alliance, a regular contributor to industry journals, and a frequent event speaker. Mike also published a book through FriesenPress titled "Scale-Out Storage - The Next Frontier in Enterprise Data Management" and was listed as a top 50 B2B product marketer to watch by Kapos.