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Your 4 Biggest Questions About FlexPod AI Answered

Hermann Wedlich

By now, you’ve already heard how artificial intelligence (AI) and machine learning (ML) can increase revenue and boost efficiency for your business. Analyzing patterns, detecting fraud, improving customer relationships, optimizing supply chains, automating processes—there’s almost no end to the ways AI and ML can empower you to make faster, more informed decisions.

The FlexPod® AI converged architecture stands ready to help you get started quickly and safely. To find out how, take a few moments to explore it up close.

1. Who should use FlexPod AI?

Whether you’re a data engineer, vice president of IT, or AI solution architect, FlexPod AI is designed to help handle and prepare all kinds of data. And, with the right use case, it can deliver tangible business value. That’s because FlexPod AI offers the performance, scale, operational consistency, and resilience you need to deliver results faster and more consistently. And by doing so, you can maintain your competitive edge—without making any sacrifices in security.

2. How does FlexPod AI work?

AI means that your business needs the ultimate performance in compute, network, and data management. But how do you get there? Much of this performance depends on latency. But it also depends on a balanced and validated design for AI frameworks within the processes of ingest, preprocessing, training of models, and lifecycle of the AI data training stream. That’s why FlexPod AI uses an architecture that spans from edge to core to cloud. With FlexPod AI, you can continue to collect, clean, correlate, train, and model your data even as you perform maintenance or upgrades.

3. What goes into building FlexPod AI?

FlexPod AI is based primarily on three different technologies: NetApp® all-flash arrays, Cisco UCS Servers with NVIDIA GPUs, and Cisco Nexus data center switches.

As the world’s first end-to-end NVM Express (NVMe) solution, it also takes advantage of Cisco MDS switches and Cisco Fabric Interconnects. In addition, FlexPod AI comes with eight NVIDIA Tesla V100 cards, so your business has room to scale—in case you need to add more storage or capacity.

4. What’s the best part of using this solution for AI, ML, and deep learning projects?

The data options! With FlexPod AI, you can capture your data at the edge, bring it back to your data center core, or provide direct high-speed connections to public cloud services with NetApp Private Storage for Cloud.

Are you wondering what else AI could do for you and your data center? To find out, check out our solution brief and watch this short video.

Or, if you’re just beginning your converged infrastructure journey, start with our overview of FlexPod, and then explore and

Do you have questions for us? To get them answered, send us a message.

Hermann Wedlich

Hermann focuses on developing IT business solutions and models for the digital transformation built on NetApp and eco partner offerings within the EMEA platform and solutions group. His mission is to generate and enable a momentum of positive change for NetApp customers, partners and their own sales force, towards new IT architectures and smart data services. Hermann has over 20 years of experience in IT, engineering and business development and is part of the NetApp EMEA AI and ML expert team, where he drives technologies and use cases for these new IT domains passionately.

View all Posts by Hermann Wedlich

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