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FlexPod for your full-stack AI and complete AI lifecycle

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Ketan Mota

It’s no surprise that artificial intelligence, machine learning, and deep learning (AI/ML/DL) are among organizations’ top initiatives for becoming more innovative and competitive. The main reasons for this trend are:

  • A data explosion, producing much of the data that’s a key requirement for AI training
  • Faster computing with technologies such as GPUs
  • Availability of software frameworks and tools to develop and operationalize AI algorithms

No more silos—complete AI lifecycle with FlexPod

With FlexPod®, advancing your AI/ML/DL initiatives is simpler than you might think. You don’t need to invest in a separate dedicated infrastructure platform to get started. There’s no need to create another silo, and it’s easy to kickstart your AI/ML/DL initiatives by applying your existing FlexPod investments.

chart for innovation

Alternatively, you can start experimenting with AI in the public cloud, and then bring the model on premises to refine it with the data that resides there. No matter what your preference is, the cloud-connected FlexPod platform makes it easier for you. With FlexPod, you get a complete solution to manage your whole AI lifecycle:

  • Use FlexPod Datacenter solutions for AI training and exploration.
  • Use FlexPod Express solutions for inferencing at the edge and remote locations.
  • Use FlexPod cloud connectivity to build several hybrid cloud use cases for AI across multiple public cloud providers.
AI lifecycle chart

FlexPod AI white paper

We just published a white paper, WP-7345 Build an AI ecosystem with FlexPod AI, that describes several aspects of the FlexPod platform for AI/ ML/ DL:

  • FlexPod now supports the NVIDIA A100 GPU with PCIe connectivity, broadening the server acceleration options to choose from.
  • The NetApp® AI Control Plane simplifies the user experience for data scientists with Kubeflow integration. Kubeflow makes it easier to deploy ML workflows and execute ML pipelines.
  • With the NetApp Data Science Toolkit, data scientists and data engineers can easily carry out several data management tasks from their familiar workspaces without having to learn the storage infrastructure constructs.
  • NetApp ONTAP® capabilities allow data scientists to collaborate and work on multiple versions of datasets efficiently.
  • A data fabric powered by NetApp technology enables you to easily manage and move the data and model between your on-premises and public cloud infrastructures.

FlexPod offers a full-stack AI, ML, and DL solution

Geared toward data scientists and MLOps engineers, FlexPod with the NetApp AI Control Plane offers a complete AI, ML, and DL solution that includes Kubeflow, and it enables rapid deployment of the entire stack. Kubeflow makes the deployment of ML workflows on Kubernetes simple, portable, and scalable.

With NetApp Trident and the data fabric enabled by NetApp, data volumes in ONTAP can be presented to Kubernetes in a Kubernetes-native format. Powered by ONTAP, FlexPod with NetApp AI Control Plane makes it easier for multiple data scientists to share datasets. FlexPod also facilitates collaboration and optimizes data storage while data scientists work on multiple versions.

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FlexPod AI overview video

This short video from Arvind Ramakrishnan, senior solutions architect, summarizes the overall FlexPod AI capabilities.

Customer success

Several customers have already benefited from FlexPod AI capabilities. Here are few:

  • A large insurance provider has expanded its FlexPod environment to use AI to automate the underwriting of insurance applications The company loves the cooperative support model that FlexPod offers.
  • A leader in specialty chemicals that has standardized on FlexPod architecture has expanded its FlexPod investments for AI initiatives and complex calculations. By failing fast and learning faster, the company can accelerate its time to market.
  • A well-known service provider has selected FlexPod for the past several years because it’s easy to manage and scale independently. The provider has also expanded its offerings to include AI/ML services.
  • A large financial services organization depends on FlexPod for its rock-solid reliability and performance. With FlexPod, the company can innovate quickly, using strategies that include AI/ML initiatives.

To learn more about FlexPod, take a virtual tour.

Ketan Mota

Ketan is a solutions product manager at NetApp managing a broad portfolio of FlexPod converged infrastructure solutions in partnership with Cisco. His focus areas include Enterprise Databases, AI/ML, Virtual Desktop Infrastructure (VDI) and Healthcare offerings. He has been in the Hi-Tech industry for 20+ years focusing on the cloud, storage and security technology domains. His diverse professional career includes Software Engineering, Professional Services and Product Management experience.

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