Episode Transcript
[00:00:15] Speaker A: Welcome to K beyond the go. This week on on the ground at NetApp Insight 2024 conference at the MGM grand in the heart of Las Vegas. For this bonus series, we've been lucky enough to have lined up conversations with the selection of NetApp executives and other guests exploring the future of data and Aihdenhe. Stay tuned for the Insight track from some of the world's leading authorities, presenting at Insight 2024 as KBI Media brings you all of the highlights.
Joining me now in person is hey, Ann Sol, executive vice president, intelligent services at Netapp. And today we're discussing cloud Ops and the role and trends and the way forward. So, hey, Ann, thanks for joining.
[00:00:56] Speaker B: Malcolm, thank you for having me.
[00:00:58] Speaker A: Now, I know you had a bit of a job title change, so I really want to perhaps let's explore a little bit more about what is that role of intelligent services, and then how does that play in intelligent data infrastructure, then?
[00:01:14] Speaker B: The title is really just a reflection of the evolution of NatApp's intelligent data infrastructure vision coming to life.
I was super excited to be able to come in front of this audience this week and talked about the evolution and when we had cloud ops, and that was part of our evolution as a company going from hardware to expanding to cloud. And in order to get to really build a cloud business, you've got to understand how cloud operates, and you got to talk to the right Personas and build things so you can understand how that operates. And now I think we're at the phase that we understand customers look at their enterprise and their cloud as their intelligence data infrastructure that to really serve what they need to do, whether they're in the AI journey, whether they're in a digitization journey, is the fluid data infrastructure that would help them, would modernize their processes and things. So we evolved to be the intelligence data infrastructure company, and what constitute that is the unified data storage, which is the very foundation. But you can operationalize that infrastructure without all those intelligent services who manage data to get the best value of infrastructure. So the title change, I think, is really just an indication of the company's evolution.
[00:02:39] Speaker A: So what I've seen as an undertone throughout this conference is how the customers and sort of the outside market views NetApp in terms of evolved.
[00:02:49] Speaker B: Yep.
[00:02:49] Speaker A: Would you say as well that people's version of Maud is changing around from you're just a storage company to so much more? We're cybersecurity podcasts, as you know, and there's been a very big narrative around cybersecurity. So was there anything you'd like to share in terms of that evolution and where sort of NetApp's headed from your perspective?
[00:03:09] Speaker B: Yeah, I think this is the conference. I met many customers, and in the feedback I'm hearing is, wow, this is the time that we see how all the different pieces come together. And we love the fact that you're using intelligence data infrastructure to articulate how each part of your technology is helping us in a holistic way. And cybersecurity was one certainly top of mind for many people, and it's a passion of mine, given, you know, my background in that area. And I think we are exemplifying to the field and to the customers that security doesn't have to be an afterthought. And we have protections for ransomware built into our secure storage. Right. People may have heard my conversation with the CTO from DreamWorks, and one of the things is we built ransomware protection, and customer can benefit from built in security. So it's peace of mind, and that's an evolution as we're not just storage, we're actually bringing intelligence to data. We're bringing intelligence to operations.
[00:04:11] Speaker A: Talk to me a little bit more about intelligence to data.
What does that sort of mean? And I asked that because people had different versions of what that means. So we're sort of starting off from this like we're walking and singing from the same hymnbook, as they say.
[00:04:25] Speaker B: Yeah, I think there's several aspects I can talk about. The intelligence for data, right. One of the conversations that people are having is, well, we live in the world that data is exploding, and we live in the era of data and AI and intelligence. So use AI as an example. Intelligence of data means you got to understand what data you have, right. Because there's a lot of conversations on data are the field for AI. Data is going to help you with training whatever models you want. But if you don't understand what data you're using to train the models, then you would not have a good sense. And the result, the outcome of your models and how useful, how biased and how probably partial it can be. So one thing, that's why we announced the data Explorer, to give people a view of, hey, get a full view of all the data you have in your enterprise, and you can make better decisions on how you apply those data for your AI 20 as a use case. And the other part of the intelligence for data is the classification part, right. Do we know if we have certain PiI's in the system? We got to provide different type of protection for the customers. So that's the other value of bringing that intelligence data to help with privacy, to help with AI training. Two examples.
[00:05:48] Speaker A: Okay, so going back to what data you are using to train the model. Now, I've spoken a lot in the past, but also over the last few days around, like, hallucinations.
[00:05:57] Speaker B: Yeah.
[00:05:57] Speaker A: What concerns you about data in terms of, you know, the hallucinations and people sort of deriving perhaps wrong insights or incorrect insights on perhaps not the right data?
[00:06:09] Speaker B: Yeah, I think this has been some good conversations I'm having with customers, others on the quality of data. Do we have an understanding of the quality of the data, that how they contribute to trainings? I think that's probably going to be the frontier of, you know, what people are thinking, what more intelligent data you can bring into your training versus, well, this one really helps, and that one is really noise. The other angle, I think, on the hallucination part, I don't claim I'm an expert in that area, but AI is still in this stage, the development of AI in this stage, the human need to get sort of involved and validating and providing the corrective. So, hey, this is hallucination and what's causing it? How do we reduce the, the amount of sort of noise that's causing this? I think there's still that whole process. That's why we talk about rag and other things. The more you can make it more specific to a particular use case, a domain, the better you can spot those hallucinations and fix them.
[00:07:11] Speaker A: So I made you a comment before Hayen, around quality of the data, or data, as you say. Sorry.
[00:07:17] Speaker B: Yeah.
[00:07:19] Speaker A: How does someone understand if it's high quality or nothing? What would that look like?
[00:07:23] Speaker B: I think that is going to be a new frontier that we in the data industry have to really work on is you got to trace the lineage of this data was used to train this model, and this model is used in those cases. And there is some hallucination happens and you go back and say, hey, this is causing some of the problems. And with us fixing some of the, or augmenting the data now, we got much better accuracy. And how do we really evaluate that process and give, say, scores or metrics to start thinking about? How do we measure the quality of the data in the context of AI? I think that's a frontier that we need to go explore. I'm not aware of any particular solutions to say, I can give you the readings of the data, but you can see the need that because you don't have the luxury to say I just gonna put every data, every bit of data into the system is super expensive and could create a lot of noise. So I think that's a frontier that I'm excited that we can continue to help Menelau.
[00:08:27] Speaker A: So obviously we're still early days, as we've discussed, in terms of identifying the quality of the data.
[00:08:32] Speaker B: Yes.
[00:08:33] Speaker A: What about sort of the next twelve months perhaps when I come back and I sit down with you again, for now, I've inside 2025, you think that sort of would have evolved in terms of the approach and methodology to that?
[00:08:43] Speaker B: I think so. I think our data explore is just the very beginning. We're starting with all the metadata and all the other things I'm sure was working with design partners and customers. And especially one of the other dimensions could be how do we help with the data mobility between enterprise and the cloud? I think you'll hear us talk about the progression in multiple dimensions and maybe.
[00:09:09] Speaker A: Let'S touch on a little bit more about Nanette's approach to cloud operations or cloud ops and intelligent services.
What are we going to start to see now moving forward?
[00:09:17] Speaker B: Yeah, one of the things I announced is how we're releasing capabilities of intelligence services in tandem with our storage products. That's the new beginning, because we do believe that in order for you to operate your data infrastructure, you need more and more of the solutions and services to make it simpler, make it faster, make it more automated. And so I think you'll see us doing more of that releases in tandem, and you'll see us to take more solution. Hey, we go into the cloud and customers are migrating their workloads to the cloud. How can we build an end to end? I talked about, we're there for every step of the way. How do we connect that? So people who are thinking of going into the cloud don't think of that as a major, major undertaking. And they can have tools and partners along the way to make it simpler, easier, and also, sometimes people want to repatriate, we want to get that flexibility. So you'll see us really bringing more automation, bringing better solutioning, sort of tandem releases. Those probably are the two things I'll call out.
[00:10:29] Speaker A: So in terms of automation, is that what you mean by how to connect things, make it easier and simple? Is that what you mean by that?
[00:10:34] Speaker B: Automation, like for example, right now, when people go into the cloud, they discover a lot of new things, they deploy their workloads, they realize, oh my God, this is like really expensive because we're not able to utilize the best resources that's there. And they have the data, but they don't have the automation. So automation means if we'll give you observability, we can give you corrective actions or auto scaling. So some of those things will be interesting to just continue to improve.
[00:11:04] Speaker A: So, in terms of trends in intelligence services and cloud operations, well, some of the things that are impacting customers, obviously, you just said you've spent the last three days side by side with customers. You've interviewed one of them on the main stage. So what, no, what is impacting some of your passwords you can share with us today?
[00:11:21] Speaker B: Yeah, on a very high level. Right. You know, data gonna continue to grow, data gonna just have more ways of impacting our day to day life through AI or through different ways of being leveraged. So I think the trend is how do we really turning data and into opportunities and turning the challenges that customers are having to manage and harness the value of data in a way that is working positively for them versus becoming something that keep them up at night. I think the data explosion, the data quality thing we touched upon a little bit. I think the other thing is really around intelligent services is two aspects, the data and AI services, and then the infrastructure and workload services. I think the trend on infrastructure and workload is there will be more workload coming into the cloud, there'll be more demanding workload coming to the cloud versus the initial simpler ones. Lift and shift. When you have more demanding workload, is the entire data infrastructure that supports workloads needs to be managed, operated in the best possible ways. So I think those are the demands that we want to step up to and continue to help customers.
[00:12:40] Speaker A: So in terms of more demanding workload, what are sort of what's doing to support customers with that? Sorry.
[00:12:49] Speaker B: For example, yeah, we talked about some of the most demanding workloads. Think of SAP.
We have already cast SAP applications running, or Azure, in the cloud for Ans, as we call it, Azure NetApp files.
And we had customers talk about how, because the Japan Coca Cola example, how because we're natively integrated with the hyperscalers, that they were able to do this in a few months. So that's an example. Another example around ebas, you can imagine those are gigantic files and they requires a lot of compute. So you really get to work the system that your infrastructure for compute, your infrastructure is for storage and all the things, and also they're under a lot of pressure. You got to do real time. So those are two examples I can give you. And of course, AI is probably training rag. And I think that's the most topical workloads.
[00:13:51] Speaker A: I want to sort of close our interview now Hayen and asking one question around, what's your definition of cloud ops or cloud operations? Do you think that perhaps people use these terms interchangeably a little bit? What does that mean to you?
[00:14:07] Speaker B: 100%. So cloud operations rooted from when people started moving a lot of things to cloud, they say, hey, what is the cloud operating model? Because that's different than what you do in on Prem. And it's more agile. It's blending the lines between developer and Srehenheathere, and it's the rules and the tools for CICD, the continuous integration, continuous delivery. So cloud operations, and sometimes people accept that to say, hey, security is an important part of it. It's not as afterthought. So some people say hey is devsecops. So cloud ops, I think is a general term to really think about operating your cloud infrastructure, cloud workload, cloud processes in the most agile, most integrated and most secure way. That's how I think about it.
[00:15:06] Speaker A: Joining me now in person is Sandeep Singh, senior vice president, general manager enterprisestories NetApp. And today we're discussing enterprise storage being front of mind. So, Sandeep, thanks for joining in. Welcome.
[00:15:15] Speaker C: Thank you for having me. KB. It's great to be here.
[00:15:18] Speaker A: Well, I want to start with storage. Now, it's one of those things that perhaps gets relegated. What are your thoughts then on that?
[00:15:28] Speaker C: Well, look, in terms of storage, it's one of those things that can be behind the scenes, but fundamentally and crucially important to customers, especially in today's day and age, where data has become the crown jewel. It used to be about where storage was all about just storing it and serving data to your applications. But now, when you think about the role of storage, it is expanded dramatically, shifting from not only storing your data and serving it to the applications, but how do you protect that data from ransomware and cybersecurity attacks? How do you protect the privacy and make sure your data is compliant to governance practices? And how do you enable customers to be able to benefit from the agility of having your data on Prem as well as in the cloud? And finally, which everyone is realizing right now, how can you truly unleash the power of Gen AI and AI, which can only be done with your enterprise data? So fundamentally, even though it's behind the scenes, it's become absolutely crucial to every organization.
But there's the other side of it, which is in terms of relegating behind the scenes, from an operational standpoint, that's what you want. You want it to be simple and just behind the scenes and just, you know, it just works. It can be simply managed and protected and upgraded where you don't have to pay attention to it and don't have to worry about it.
[00:16:56] Speaker A: The reason why I wanted to start there is because it's one of those things that perhaps out of sight, out of mind. And what I mean by that is it's sort of like electricity. You go home, you turn on the light, and it works. Although when it doesn't work, you really notice it and it's going back to data and storage and things like that. It's something that's important, but perhaps, again, can't really see it, and it gets sort of pushed to the back. Maybe not as such a sexy conversation as some of the other things in technology. So are you seeing that a lot as well in terms of we can't see it when you forget about it.
[00:17:27] Speaker C: Actually, storage has become the front and center conversation for many, many customers now because the focus goes back to data.
Data is the most fundamental, important asset for every organization now, and it begins with having to store that data. But the whole security aspect of data is bringing storage at the forefront again, because storage often becomes that last line of defense for customers from ransomware, cybersecurity attacks. And if you can protect and detect right there in real time and do that with high degree of accuracy, you can enable a rapid recovery for customers. Again, coming back to the AI conversation, that conversation is fundamentally tied to AI is really a data problem that customers need to be able to bridge the gap between AI and data. So storage is absolutely becoming front and center for customers now.
[00:18:24] Speaker A: Makes sense. So then let's go, perhaps on your role and your background experience. What's your view then, on enterprise storage?
[00:18:33] Speaker C: Yeah. Enterprise storage has become the foundation for customers.
[00:18:39] Speaker A: Okay.
[00:18:40] Speaker C: Right. Enterprise storage needs to always have the high performance for customers. I mean, high in consistent performance. It has to have that mission critical reliability. These are the high end capabilities that customers look for. It absolutely needs to ensure that it has this advanced data management capabilities to be able to manage your data that are stored there. So that's the foundation of it. But customers tell us continuously that they don't want to have to sacrifice getting the high end capabilities.
One of their other bigger challenges is complexity, and they need to be able to solve that complexity challenge, both within the system and at scale. So what that means is they need simple FyDe operations and they need those simplified operations, that they can bring the consistency of those operations across their different application workloads end to end. Those are some of the basic elements of enterprise storage there. And increasingly, where customers need it is it's got to have the built in security and design for security from the beginning. It has to be designed to enable their hybrid cloud for their data.
[00:19:58] Speaker A: Okay, so you said before, simplified operations. Now if I look at a bank, I worked in a bank before, you've gone very legacy systems, technical debt. How do you simplify operations then? That's not an easy thing to do.
[00:20:10] Speaker C: Is said than done, easier said than done.
Customers are struggling with complexity. When you double click on what is leading to that complexity, very quickly it becomes complexity that's compounded through bespoke infrastructure silos. What I mean by that is customers will have file environments, their vmware environments, their database application workloads, their AI analytics workloads, their secondary or tertiary workloads, and then they'll also have cloud storage environments. And if every one of those is a bespoke infrastructure silo run. What it means for those banking customers, or any large customer, is they have inconsistent management while they're facing talent and skills gaps. They have inconsistent automation, they have inconsistent data security model that they can't trust in. They have inconsistent operational recovery workloads in the event of a disaster, and they have an inconsistent vendor experience. When you change that equation and say, what if I can bring a consistent management, consistent automation, consistent data security model, consistent disaster recovery workflows, all of a sudden that's a game changer for customers. And only NetApp is enabling and empowering customers to do that with the power of ONTAP.
[00:21:35] Speaker A: So you said before around we talked about enter by storage. Would you say that's your definition of high performance?
[00:21:42] Speaker C: High performance will vary.
Enterprise storage absolutely needs to deliver high performance capability to customers, of course. And at the end of the day, that high performance ends up becoming, from the application perspective, is the application able to go at the pace that the application is consuming and then enabling customers to consolidate multiple workloads on shared infrastructure and still being able to get consistency? This is where our ability of where NetApp is helping customers is to be able to get high levels of performance in a single system. And through our technology, customers have the flexibility to scale out across a cluster, and they're able to continue to scale the performance levels and dynamically load balance their workloads.
[00:22:33] Speaker A: So everything we sort of just discussed, we've looked at, you know, the value of enterprise storage, spoken about how things are forgotten.
But more importantly, what are things that probably missed or what are some of the myths that people have around enterprise storage from your experience?
[00:22:50] Speaker C: Yeah, well, where I would take that is enterprise storage.
I would say that the changes that are taking place when you look at the security and ransomware, this is where I get the vast majority of questions from customers.
[00:23:07] Speaker A: You're on a cybersecurity podcast, by the way.
[00:23:11] Speaker C: What's happening is essentially that there's a game changing proposition taking place where essentially the detection in terms of ransomware is typically happening today in post process through backups. And that can be hours to days later, versus where we're leading that change is to real time detection of ransomware attacks. Now, if you can change that to detect in real time, in seconds to minutes, and do that with high degree of accuracy, where we designed it for 99% plus accuracy, all of a sudden you're minimizing the impact and you're minimizing the false positives and it becomes the enabler then for a rapid recovery for customers. That's a game changer for customers. And that's where we're seeing just a fantastic adoption right now across the board.
[00:24:07] Speaker A: So I want to follow us a little bit more. So obviously you're saying now customers are very focused on Renzo, which makes sense happening probably why Fiat NetApp to discuss it from a cyber security perspective. But maybe like your lanes on, okay, the ransomware itself. But then the other thing that's coming up a lot from a media perspective and in some of the interviews that I'm conducting is business continuity as well as downtime. So if you're running a manufacturing company, you've got an issue, can't deploy things, that's one thing. But then in terms of your downtime, how much of an impact that has in terms of long term, long term impacts, do you think it's something that customers are really starting to understand more, or do you think it's something they're considering?
[00:24:45] Speaker C: Perhaps 100%. Business continuity and high availability is incredibly important for customers. If you think about it in terms of the mission critical workloads that typically run on block storage systems. What we just announced, for example, the new ASA, a series, one of the core pillars of it, in addition to simple, powerful, affordable, the powerful pillar is all about giving you the scale as well as the six nine availability guarantees, alongside with all of the business continuity capabilities, to be able to simultaneously have active, active business continuity across two sides to be able to protect your application. So incredibly important and absolute must have for customers.
[00:25:34] Speaker A: And in terms of moving forward, I know you've released a lot of new product announcements. They're all over our site, but do you have any sort of high level thoughts you can share with us today?
[00:25:43] Speaker C: Yeah. First of all, one of the core areas is we are bringing intelligent data infrastructure for customers to empower them to solve the challenges both across their mission critical environments, both across their security and protection mechanisms, as well as for AI Gen AI's. In terms of the specific areas of the announcements, the way I would recap it, in enterprise and unified data storage, we have rapidly expanded our portfolio. And what we have introduced is the new ASA, a series. This is for helping customers with their vmware database application workloads and giving them this fundamental proposition. They no longer have to choose between simple and powerful. They can get all of the simplicity that they need, including simplicity at scale, alongside with all of the high end capabilities, and giving them what is affordable, making it available for them to modernize to all flash and be able to do that within their budget. That's one core part of the announcement. Second core part, talking about security ransomware with our next version of ONTAP, this real time detection with six nines or, sorry, 99% plus accuracy that becomes generally available. And in addition to that, we're orchestrating the entire workflow for customers to protect, not only detect and then recover from an application workload perspective. And then thirdly, the big one, in terms of helping customers truly unleash the power of AI and Gen AI and be able to do that with their enterprise data, by helping customers get their data AI ready, as well as bring AI to their data to fundamentally help them solve this chasm between AI and data chasm. And that's the promise that George made on the day one keynote for customers. We're doing that both for our on prem customers through just a series of announcements that we laid out, as well as from a cloud storage perspective, working with each of our hyperscaler partners to ensure that all of the billions of dollars that the hyperscalers are putting into AI and Gen AI tools, customers can take advantage of that with their enterprise data.
[00:28:11] Speaker A: And there you have it. This is KB on the go. Stay tuned for more.
