Microsoft Ignite 2024 Unpacked | Lee Caswell, Nutanix

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Lee Caswell

SVP, Product & Solutions Marketing

Nutanix

Three insights you might have missed from Microsoft Ignite

Multicloud AI strategies are revolutionizing how organizations approach secure, scalable and integrated artificial intelligence solutions across complex technology landscapes. As businesses prioritize seamless connectivity and robust data access, industry leaders at Microsoft Ignite 2024 spotlighted innovative approaches to simplifying AI deployment and enhancing productivity.Simplifying connectivity has become a critical focus due to the growing need for consistent access to data and applications in multicloud environments, according to theCUBE Research’s Rob Strechay and Bob Laliberte

Nutanix partners with Microsoft Azure to offer hybrid AI infrastructure

Artificial intelligence applications are the future of cloud computing, and Nutanix Inc. looks to capitalize on that with its Nutanix Enterprise AI offering.Nutanix has partnered with Microsoft Azure to offer platform engineering and AI services across a hybrid environment. Its Enterprise AI solution will support customers’ AI workloads across private and public clouds.“We brought a cloud operating model to an on-premises environment,” said Lee Caswell (pictured), senior vice president of product and solutions marketing at Nutanix

play_circle_outline Nutanix cloud clusters enabling seamless IT ops across on-premise and Azure environments

play_circle_outline Portable licensing model for applications and data movement across environments

play_circle_outline Enterprise AI applications driving productivity and customer relationships

play_circle_outline Data services for protection and restoration of data across different environments

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Lee Caswell, Nutanix

Lee Caswell

SVP, Product & Solutions Marketing Nutanix

Lee Caswell, SVP of product and solutions marketing for Nutanix, discusses their partnership with Microsoft to bring their cloud operating model to Azure. Nutanix offers a portable licensing model for managing environments across on-premise and Azure. Nutanix AI on Azure Kubernetes Service enhances enterprise AI capabilities. Nutanix also helps secure endpoints and APIs for AI applications, scale workloads in Azure, and offer data services for consistent protection. The partnership aims to support running business-critical applications effectively.

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What benefits does partnering with Microsoft bring to Nutanix in terms of extending their operating model into Azure? add

What is the importance of Nutanix's customer-managed environment and integrated security features in the hybrid cloud? add

What are some key factors that organizations consider when deciding to utilize Azure or other platforms for their applications and services? add

What are the key aspects of the data services piece in Nutanix and how does it provide consistency in protecting and restoring data across different platforms and environments? add

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Lee Caswell, Nutanix

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>> Hello, and welcome to Microsoft Ignite 2024 Unpacked. I'm Rob Stretchay, a managing director with theCUBE Research. One of the things we are unpacking is the technology ecosystem and how organizations are looking to span on-premises in Azure and how they're really trying to leverage this to get more out of applications, not just Microsoft SQL, but things like AI. To help me unpack this, I have Lee Caswell who's the SVP of product and solutions marketing for Nutanix. Welcome on board. Lee.

Lee Caswell

>> Rob, always great to be with you. Thank you for having me.

>> I mean, we've known each other through, it seems like multiple life cycles here, but I think one of the things that's always stayed really true to what we've both worked on is really hybrid and hybrid cloud and Microsoft's been part of this ecosystem with Nutanix for quite some time. For those who really don't know or really don't get or haven't been exposed to what Nutanix is doing, or maybe they know you from the on-premise components, help organizations understand how Nutanix cloud clusters enable seamless IT ops across on-premise and Azure environments, and what specific challenges you guys are looking to help those organizations with.

Lee Caswell

>> Yeah, terrific. I mean, it's so exciting to be partnered with Microsoft here because many customers got familiar with Nutanix because we brought a cloud operating model to an on-premises environment that meant basically seamless scaling, for example, the resiliency you could expect, and also the idea that you'd have this flexibility of running applications of all types. And now what we've done with Microsoft and Azure is we were now extended that operating model into Azure natively so that you can go and run this same common operating model. And we're starting to call this, Rob, a platform, if you will, and the idea is instead of thinking about infrastructure as being a specific server that you own or a network switch or something like that, you've abstracted all of that. And so now what you can think of is it's the same operating model you run on-prem and all of that enterprise resilience, the day two operations and security and privacy you can now extend into Azure and as we'll talk about extends now into AI.

>> Yeah, I think again, before we get there, I think everybody wants to know because I think companies that we know very well have kind of thrown licensing into the purview, and one of the things that I was wondering about, and I'm sure organizations are wondering about how does this impact licensing across on premise and cloud and what's the story behind your portable licensing model to really help enable applications and data movement across environments?

Lee Caswell

>> Yeah, I think it's super important that Nutanix wasn't the first actually to try this, but we did it the right way. And let me describe what that means. What that means is that the Nutanix environment is customer-managed wherever it exists, and so running it in an on-premise environment or even at the edge or then into Azure for example, it's customer-managed and actually the licenses, in this case are, fully yours also, and the customer has the full opportunity to go and deploy those licenses where they are optimally needed and change it at will over time. So that flexibility of having that integrated operating model first and then secondly, having things like integrated security in through ExpressRoute for example, is a way to go and bring your own security policies across this new, what we call the hybrid cloud. And that hybrid cloud environment is super important I think for customers looking to future-proof.

>> I agree. And I think again, that having that ability that you get to determine where your licenses live, like you said on the platform and the being the same platform is totally key because especially with things like AI, and you guys had a pretty big announcement last week around Nutanix AI, help people who may not have heard the announcement understand what the key advantages of deploying Nutanix AI on Azure Kubernetes Service or AKS for validating and managing LLMs and large language models.

Lee Caswell

>> Well, I think it's important to start off with thinking ... when we talk about enterprise AI, what does the enterprise part of that mean by the way? As you're seeing the evolution of platform engineering, which really means developers don't want to understand and know all of the underlying infrastructure elements. And so platform engineering as a way to go bring the enterprise value, that's basically resiliency and day two operation. And finally, security and privacy. You're taking all of those and bringing those together. So that's the enterprise value first off. Then when we do enterprise AI, you're getting a next level of abstraction which says you want to make sure that you have flexibility over time to take advantage of the pieces of enterprise AI that are moving the fastest, and that would be new LLMs, for example, all of the software that's coming on board as well as new GPUs, right? You could see my dog's excited about it even.

>> Yeah, you always love when the animals get involved. I didn't bring mine in today, but it's always good. I think when you look at it, especially because I think what was exciting about your announcement last week was that it is across all of these different platforms, and I think one of the things that ... I think we talked about this on a different call, but bringing AI to the data in particular, and you guys have been around for quite some time, your hypervisor has matured over the last 10 years, really getting in there and being able to bring this, that has to be what some of the excitement's been over the last week.

Lee Caswell

>> A lot of excitement for taking that enterprise value as you mentioned from a hypervisor standpoint, having that be able to run across the hybrid cloud and in the Azure environment. And also now with our Kubernetes platform, through our D2iQ acquisition, we have the opportunity now to go and run Kubernetes environments and you get a choice here, by the way. So you're going to have choices of environments, whether it's Kubernetes or LLMs or even down to the underlying GPUs that you have access to. One of the interesting things here we're offering though is to think about having GPUs access in the public cloud into Azure that you rent. So the idea is for customers who are trying to get started, and this is what we find with a lot of customers now, they're trying to figure out how do I get started and don't get locked into pieces that I might want to change over time. So that's where we offer choices of LLMs choices of GPUs, choices for running on-prem or in the public cloud, and then you can run where you're most confident around security performance and even costs.

>> Well, that brings up a great segue because I think when you start to look at LLMs and the data and things of that nature, people really want to understand what measures are in place to secure endpoints and APIs for Gen AI applications, and how does that scale when you get out to Azure to support high-demand AI workloads? I mean, I think people are really worried about that.

Lee Caswell

>> And you start thinking, let's say you want to be running an AKS and you want to think, Hey, how do I do that from an inferencing standpoint, but do it with the same private data, for example, run inferencing there. Many of these workflows, by the way, are going to be ... we call them inherently hybrid, right? LLMs that are developed in the public cloud, then applied to your data, for example, and thinking about how you optimally run these over time and by location. When you start thinking about what vertical markets might be most excited about this, things like healthcare, financial services, and even public sector. These are environments where you and I have long data histories. So the idea you think about the data first, that data, you want to be very privately protected and secured, but you want to have the opportunity to move the applications to where the data is. That's really the way this works. Moving all the data all the time is a really expensive proposition, takes a long time. So the idea that you could now have data in the public cloud in Azure or on-prem or even at the edge and you have one team that can manage that consistently, that's a very powerful concept.

>> No, I think it is, and I don't want to bury the lead because you hit on something a little bit back there, which was that Nutanix enterprise AI on Kubernetes, the Azure Kubernetes service or AKS, you've packaged it up so we can actually run off-platform ... Basically, it is a platform, so you're taking that with you, so if you go and build on it, you take it where you want to go and run it such as AKS.

Lee Caswell

>> And that's really important for customers who decide, Hey, where do I want to spend my critical staffing resources? Ideally, what you'd like to do is kind of train once or train once, run many is the idea. So I could go and train one time and get familiar with the tools that I have. So within the Azure environment, getting familiar with AKS, being familiar with how we have from a Nutanix standpoint, this consistent operating model, being able to have integrated security policies across this hybrid environment that are the same. And finally, I'll bring up one interesting thing is the data services that we have are super important for customers thinking about snapshots, replication, DR. These have always been the hallmarks of enterprise value for infrastructure providers, super important for a database, equally important for an AI application where these new applications, because of their speed, their productivity enhancements and the sticky relationships they promise for customers and mates, it means that these applications are going to be as business-critical as anything we've ever built.

>> And I think we were even talking about this a little bit before we went live here is the fact that AI isn't the answer, it's part of the answer. These net new applications that are being built out are really pieces of AI, which again, to what you were just saying there, having a platform where other parts of the application live in harmony is a piece of it. Are you seeing a lot of that where organizations, this is why they want you to come to Azure and go to other places, is marry up with some of the other things that they're running there?

Lee Caswell

>> And I think what happens is the first wave of thinking on AI is, well, what is the application? In fact, we think this is actually critical. Find an application area where you've got a concrete business financial return. Once you've got that, now you can start thinking what are the services that I might want to go and access. They could be services within Azure, they could be services that you have in an on-prem environment. You've got that full flexibility to go and have your application running and particularly on inferencing, doing inferencing at the location that makes the most sense, tap into the services that you have from whatever platform you're running on. That gives you a lot of flexibility moving forward for customers.

>> And I think again, it's that optionability that organizations are really looking for. You touched on it a little bit before, but let's kind of go back to it and break out some of the main use cases or industries that you guys are going to be able to benefit from Nutanix cloud clusters with Azure because I think this does help people bring that cloud operating model to a new level as well.

Lee Caswell

>> Yeah, we're seeing some really interesting use cases around things like support co-pilots as a way to go and bring new value. And particularly it could be like internal productivity. I mean, we're seeing data that suggests that even CEOs think they're going to gain over 15% in productivity across an entire organization by working with AI applications. Another one would be in retail. For example, fraud detection determination or in healthcare environments, intelligent claim processing. All of these can actually drive new synergies internally and also then drive a more concrete customer relationship. And that's one of the things we're seeing, Rob, overall is apps are now the competitive currency. When you think about your relationship with a financial provider for example, it's probably not based on the brick-and-mortar bank that you used to have, right? It is based on the applications, how quickly can you engage there, what sort of new insights do you get around your particular situation, and then how can you go and make decisions faster. It's a really exciting time I think for industries of all types, but particularly for those ones with private data, all of a sudden a model that spans the hybrid cloud becomes really important with Azure at the basis.

>> Yeah, I mean we're seeing that about 1% of corporate data is actually in the large language models that have been trained already, whose 1% is that. That's the scary part when you think about the security aspect of it. But I would assume that you're also seeing that because Nutanix has been so prevalent in these organizations and you have such great storage, you kind of started in the storage area and really moved to the hypervisor and the rest of these services and built that platform out from what I would say is the most important part. I'm a little biased, but when you start from the data, that feeds the AI engine, and that's got to be why a lot of organizations been looking for you guys to kind of do the cloud clusters, Nutanix cloud clusters with Azure and with the enterprise AI on Azure as well because they know they have their data in you guys.

Lee Caswell

>> Yeah, I think the data services piece is really important because what we're able to offer now is consistent ways to both protect and then restore your data. And that goes across a wide range of things in Nutanix all the way from blocks, files, and objects, but also to VMs and now containers. And from an on-prem to a public cloud environment. So that flexibility means, again, you can train once, run many. It's that ideal situation where you want to go and build one thing one time, be able to run it anywhere. But then importantly from an enterprise standpoint, it's how do I make sure that I can go and run it responsibly over time as these become production apps with mission-critical responsibilities.

>> No, I think that's the key. And we went in deep on this around the D2iQ stuff and how containers has really been a piece of what you've been doing for six to seven years and how it's really advanced with the D2iQ acquisition back in January and how really you're looking to push this forward. So great stuff. And this is really exciting news for those who are using Azure and Nutanix and now being able to really get even higher ROI out of the two product sets.

Lee Caswell

>> Yeah. One thing I suggest also is as you start thinking about the LLMs, and this is where everybody sees that right at the tip of the iceberg, but underneath the iceberg is pretty big around how do you make sure that the infrastructure is going to keep up. What we found is almost all customers believe they're going to have to upgrade their infrastructure and the team's expertise in order to go run AI applications. So our advice is get started now. We can help you get the choice of your LLMs with our API integrations. That's part of the Nutanix enterprise AI solution. And with that, you get your choice of LLMs fully certified down to GPU-enabled servers from all of our top partners, and now you can go and run that right across the full hybrid experience from the edge into the virtual private data center, and then now connect it into Microsoft Azure. It's a great story for how you optimally locate applications and their associated data in an AI-driven world.

>> And it gives them a perfect way to understand how that platform works. Well, hey, I really want to thank you, Lee, for joining us today. I mean, this has been great. I think, again, unpacking what's going on at Ignite all day long today, you've really been pushing forward on the innovations front, and I really appreciate you coming on board again.

Lee Caswell

>> Well, I love to see partnerships where they're customer-driven and that's what we're seeing. Customers want us to work together. We've got great intersection today on all business-critical applications, and SQL servers are our number one application today. But you watch tomorrow as we move forward into a AI applications, this is going to be a critical part of how we help our joint customers be successful. Couldn't be more exciting.

>> Yeah, I can imagine that. And there's still a ton of SQL server out in the world to put it mildly.

Lee Caswell

>> Yes, there is.

>> Funny enough, there's a lot of data in SQL servers still, and it's an important part. Well, thanks again, Lee.

Lee Caswell

>> Rob, always a pleasure. Thanks so much.

>> And thank you for watching Microsoft Ignite 2024 Unpacked. Stay tuned for more on theCUBE, the leader in tech news and analysis.