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NetApp Solutions

Solution technology

Contributors kevin-hoke
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This solution utilizes the following technologies:

  • AWS SageMaker Notebook. Offers machine learning capabilities to developers and data scientists to create, train, and deploy high-quality ML models efficiently.

  • NetApp BlueXP. Enables the discovery, deployment, and operation of storage on premises as well as on AWS, Azure, and Google Cloud. It provides data protection against data loss, cyber threats, and unplanned outages and optimizes data storage and infrastructure.

  • NetApp Cloud Volumes ONTAP. Provides enterprise-grade storage volumes with NFS, SMB/CIFS, iSCSI, and S3 protocols on AWS, Azure, and Google Cloud, giving users greater flexibility in accessing and managing their data in the cloud.

NetApp Cloud Volumes ONTAP created from BlueXP to store ML data.

The following figure shows the technical components of the solution.

This figure shows the technical components of the solution.

Use case summary

A potential use case for dual protocol access of NFS and S3 is in the fields of machine learning and data science. For example, a team of data scientists might be working on a machine learning project using AWS SageMaker, which requires access to data stored in the NFS format. However, the data might also need to be accessed and shared via S3 buckets to collaborate with other team members or to integrate with other applications that use S3.

By utilizing NetApp Cloud Volumes ONTAP, the team can store their data in a single location and have it accessible with both NFS and S3 protocols. The data scientists can access the data in NFS format directly from AWS SageMaker, while other team members or applications can access the same data via S3 buckets.

This approach enables the data to be accessed and shared easily and efficiently without the need for additional software or data migration between different storage solutions. It also allows for a more streamlined workflow and collaboration among team members, resulting in faster and more effective development of machine learning models.