 Good morning, everyone. Welcome back to theCUBE's continuing coverage of SuperCloud 5, the battle for AI supremacy. Lisa Martin here with Savannah Peterson, live in Palo Alto, but as you know, cause you've been watching us over the last couple of days, we've got crews on the ground in Las Vegas at AWS Reinvent, John Furrier, Dave Vellante there, having some amazing conversations. You're going to get more of that today. We also have Rob and Rebecca at HPE Discover in Barcelona. We are giving you a canon of CUBE content, but we've been having great time the last couple of days talking with loads of guests, different vendors, partners, Savannah, we've been talking about that the battle for AI supremacy isn't really a battle, it's all about collaboration. Yeah, I would say that it's a collective, you know, instead of, I mean, it feels like a sprint right now, but everyone's got to get across the finish line. It seems like a bit of a rally race, you know, a four by four people are handing off different patterns of the process. Just came up with that one. On the fly here, you heard our first folks, but I do think that that's what it's going to take. It's going to take different players. It's not just going to be that one star sprinter that comes out. There's going to be a lot of parts and components of this. Many of those components and pieces we've discussed here and had as lovely guests on the show. Yes, and we're very excited to welcome back a more than 10 timer to the CUBE, Dave Donatell, CEO of Riverbed. Dave, it's great to have you back, welcome. Great to be here, good to see you guys. So we've been talking a lot about customer experiences, employee experiences, digital experiences, so incredibly important for businesses across any organization. But it's not easy for organizations to deliver that truly seamless digital experience that we demand. Why is that? Well, it's getting harder every day, right? And it's part of what we're discussing here. We're going to discuss AI. It's yet another change to the IT environment. Over the last several years, we've seen everybody, you know, work in the office to work from home, to work from the beach and Starbucks and everything else. So the more complexity you add, the more difficult it is to deliver seamlessly for IT departments, and that's what they face. And with that complexity, you know, I believe you're going to need more automation to make it work for everybody. One note I'd add on that is, you know, we recently did a survey, 10 different countries, and 68% of millennials said they would leave their company based on a bad digital experience. 68%. 68%, that's over two thirds. 63% believe that their company really would suffer, you know, if they offer a bad digital experience to customers. Think about it, right? In your own life? Yeah, absolutely. If you're online and you're buying something, you know, get a good experience, you go somewhere else. Absolutely. Let's step back just for a second. It's obviously fluent in our lexicon, but the digital employee experience, DEX, what does that actually mean? Can you define that end to end? Everybody defines it very differently. I had a hunch that that might be the case, so... I mean, what I'd say in general, it is, do you have a seamless experience? And I can give you all kinds of different examples of this from every... I mean, I have a food delivery app, a seamless experience. Well, let me give you one you might not think about, doctors. Ooh. Okay, so just a very non-traditional one. We work with a bunch of hospitals, a hospital who I know very well. We talked about, talked with the riverbed. They were losing in one hospital 900 doctor hours a month due to their inability for their end points, like your laptop there, to work properly. Oh my gosh, this is insane. And if you think about it, doctors are not... My gosh, that feels so preventable. Yes. Exactly, and that's kind of, we help them solve that problem. Amazing. But think about the ramifications for that problem. There is definitely a medical shortage post COVID. People can't get appointments, they're stretching out. And so 900 doctor hours a month, if you think about appointment-wise, let's say an appointment's 30 minutes, that's 1800 appointments in a hospital that can't get done. Second issue around that that they had is that they want to go to digital medical records, right? For all the benefits of those. Well, guess what? If your end point's not working, you can't do your digital medical record design. Doesn't matter where it's stored. You're back to paper. Exactly. So in our case, we're... Physical on-prem at that point. Able to use automation to reduce that down to 200 hours a month. Okay, so that's 1400 doctor visits a month. You get back by offering a good digital experience. Okay, so that's a medical example. I can give you that across every different engine. Exactly, but I love the healthcare examples because it affects everybody. We were talking about that yesterday. Absolutely. And it's life and death. Absolutely. Bottom line, life and death. Yeah, it is. So that's a really beautiful and compelling example. We talked a bit as you were getting settled today about the customer service experience. Like you said, nobody wants to call a customer service center. I feel like, I mean, I'm actually procrastinating probably three of these phone calls myself right now. And so how does automation... I think when people think about AI, one of the big fears and anxiety comes around it taking jobs away. How does AI change this experience as we know it when it comes to customer service? I think dramatically. Yeah. I can give you a couple of examples. First at the highest level, right? The best customer call center is no customer call center. Yes. And that really gets to automation, resolving problems so you don't have to call anybody. You know, we were joking before, right? Again, if you look at your endpoint here, who wants to call the help desk? My answer is nobody. Right. No. Right? Because we know delayed, you're waiting, you just want to do your job. So in the idea of AI, we have products today at Riverbed as an example that can understand either while something's happening or in many cases before, what your issue is, use data and actually real data, not synthetic data to understand what that problem is, use something we call a run book to actually automate it in an automated way, fix that for you. So no call, everything's resolved, and it's also tracked so the people who do kind of look at these things holistically can understand, hey, something happened there, it was resolved, this is exactly what it was. So we understand that Riverbed has shifted the business towards the observability market. I want to understand, Dave, from your perspective, what, why observability plays such a key role in the success of AI? Very simple. And it's interesting, I've heard a lot from your other guests, right, over this course. And the best way to think about, in my opinion, to have good AI and good machine learning, because both are sort of coupled, depending on how you want to define things, it's all about data, right? You have to train your machine to actually do what you want it to do. And you've heard a lot, I think, over your last few days here, and certainly they're talking about it out at a lot of the various shows, is synthetic data can lead to a lot of issues. And what we do, and what helps with around digital experiences, we collect data from all different points. Okay, we collect network data, we collect application data, we collect data how you interact with your cloud, we collect data how your endpoints are working. Are you collecting data on us right now? We could be if you're on our products, yeah. But the idea behind that is real data, not synthetic data. So when you're dealing with real data, you actually can train machines to actually have great accuracy in terms of what they do. I'll give you an example of how we can fix things in an automated way today. And so to me, data is the center of all this. And in my career, which has spanned a bunch of different technologies in our industry, it always comes back to data. And having accurate data, and more importantly for companies, having the ability to actually understand what their data is, and then how to action it. And so again, to get the business benefit that people are really looking for AI, this is gonna be the key. We're gonna be talking about this a lot. You mentioned your career, which is quite impressive. One of the other dialogues that we had to start off the day was that it has spanned the pre-Internet business world and now the obviously post-Internet, mid-Internet business world. Do you think we're going through one of those transitions again? Absolutely. And I would say, I think for, I have kids, so I always use my kids as my internal focus group. If you talk to them and say things like pre-Internet, they look at me like, what? Yeah. But I worked in the technology industry before the internet was here. You mean that industry existed? It was an industry. We actually, in the Dark Ages, had computers. I've read stories. Exactly. So, but if you look at it again, from a big business perspective, what happened was a whole bunch of new winners emerged and we know who they are, right? Everybody from Google to Facebook to Airbnb, whoever you want to talk about, Uber, these are all companies that were enabled by the internet age. A whole bunch of companies went away because they couldn't adapt, famously Blockbuster, many regular retailers who were only brick and mortar, world change, and then a lot of big companies who were around were able to adapt successfully and become even more successful than they ever before. Simply put, if you look at companies like UPS, FedEx, Walmart, they are bigger than they ever were and they successfully adapted to the internet world. AI is at discussion now. Okay, so if you're on a board and I'm on a board, first thing that happens with the CEO, you ask him a couple of questions. One, how are we not going to be put out of business by AI? And again, regardless of industry, regardless of anything you do, that CEO, I guarantee you, is getting that question asked. Second question I'm going to ask the CEO is, how are we going to use AI within our company to become more competitive, more efficient, to be one of the winners in this space? And then I think the third thing, aside from that CEO, is there's a whole bunch of startups, as you know, because you talk to them all the time saying, hey, we're going to be one of these new players who emerges out of this and become part of the new economy going forward. It's one of those moments. Again, the internet, it was really exciting to live through and see all the innovation that happened and everything that went on with that. And I believe this is every bit as powerful a change in our industry. When you're talking with CIOs, CEOs, what are some of the, how do you talk to them about making the right investments in cloud, in AI, and other emerging technologies as we enter almost 2024? What are some of those recommendations that you have? Yeah, I'd say, I think there's different ways to look at it, right? On the technology side, because I proudly work on new products and everything else, in our industry in general, everybody wants to talk about leading edge, leading edge, leading edge, which is great, because that's what we do. When you get to the business side of things, what they really want to talk about is, what can I practically do? So meaning in, and it's a big lesson, I think for all companies, whatever your shipping has to work, and it has to provide a business value that people can measure and say, look, I can make my, when we talk about digital experience here, I can make either my customers or the folks who work here experience measurably better by implementing this, right? This makes sense. And so as you know, our whole industry, I love the whole idea of the hype cycle and the trough of disillusionment. Gartner gave us a gift with that one. Yeah, yeah. Because it's true. Mm-hmm, it is. And so clearly we've gone through a huge AI hype cycle, and now it's down to who can deliver practical solutions that work. And the good news is products are out there today, right? Yeah. You see a lot of co-pilot type products that provide real value. They definitely work. People see, okay, this makes sense. We have a product called Aluvio IQ that does some of the things we were talking about. It's real. You can implement it today. And that's what people want to see is, how do I make things better in don't just sell me hype? Yeah. You mentioned Aluvio recently went to market with that. What's the strategy behind that approach and how is it going to enable those organizations that have been struggling to deliver that seamless digital experience actually achieve it? Yeah, I think one of the big things that isn't talked about, and you see this, again, every time we get to one of these new trends in IT is, you can't find enough people understand these things. Yes. Okay, so. A lot of people want to pretend though. Certainly, but in our industry, right? What are we seeing? Shortage, can't hire enough AI engineers. Yeah. Build fast enough because people don't have enough skills. Yes. The same thing happens. We're talking about, hey, it's difficult to deliver these experiences. Why? Because they can't hire enough smart people who understand each of the intricacies of these things. So that's where automation comes in. And the whole idea I mentioned data collection. So how do you collect the data that normally a human would be looking at? Yeah. Get it into a way that a machine can handle that and understand that. And that's kind of what our products do today. It's that easy button we've been talking about on the show. Yeah. What's developer productivity? What can you bounce off of from now? Well, it's the whole idea of using automation to augment. Yeah. And I think the other thing. Like a trampoline. Yeah, well, you hear other people say they're worried about well job replacement, all this other stuff. In the tech world, there's plenty of jobs. Absolutely. And there's plenty to do. Yes. What people are bogged down with it is a lot of noise. And if you look. That's my point. So when we talk about copiloting and we talk about augmentation, the idea is, okay, look, we'll take away a lot of this drudgery that you've kind of had to spend your time on it. And that'll go focus on the real problems where you want to use your brain on. The cool stuff. Exactly. The 20% of the things that you wanted to be spending your day on. That you can't. Anyway, or at least, you know, to some degree a bit more. You mentioned the hype curve. Where do you think we are off at on that little baby right now? Well, I think it depends what we're talking about. That's why I mentioned practical solutions. You know, for businesses is what can I do now that makes sense? Right. And then architecturally, what do I need to start to plan for? Yeah. And so I'd say most businesses are kind of, in that phase now, architecturally are more dramatic type changes that will play out over years. They don't happen as fast as everybody says they do, in many cases. And then the practical solutions, like co-piloting as we spoke about, they're doing that stuff now. Yeah. So we're in an implementation phase, but we're in the early, as I like to say always, the early endings of this dramatic change. What a diplomatic answer when it comes to the curve. I love it. We got introduced to a very fun term on theCUBE with one of our guests on Tuesday. Vaughn told us about fofu, fear of effing up, which is a bit of a conversation that he's having in the C-suite right now to, as folks map out their strategy for AI, is that an experience that you're having? Do you, in some of your conversations, are people anxious? Are they excited? Equal parts both? Well, I think equal parts both is the best way to say it. I think anytime we've had these big changes, the human reaction in many cases is fear. Right. Right. And typically, what they don't really say is they'll talk about fear of all these things, but it's ultimately fear for themselves. Right. And what I mean by fear for themselves is, how do I fit into this new world? Are my skillset, is my skillset still relevant? That type of thing. And I think that's just human nature that we see. And then the leaders kind of get past that and get into, hey, it's safe over here, and we can go implement and look at the great changes that happen with that. And so that's kind of one of the fears I see. I don't, and the other fear I see is the, the overused word of disruption. Is am I missing something here that's gonna come back and really bite my business? And fear of missing out or fear of I'm late to the game or big fears? Yeah, yeah, FOMO is real. It is real. The FOMO, the FOMO, the Fofu. When you think about the future of the observability market and its potential for growth, what does that look like? And as we are today, the one-year birthday, as you brought up, chat GPT, how has this injection of Gen AI in the last 12 months, how is it going to influence or impact the observability market? Yeah, here's what I'd say is right now, as I mentioned, complexity is a real problem. I was speaking with a customer the other day, they're using 58 products and observability today, 58. Whoa, okay, now think about that for a second, right? How many different suppliers you have to go deal with? How you have the burdens on the customer to try and knit all this stuff together in order to really understand what's happening? So the mega trend we see there, I mean, we see lots of mega trends. One I mentioned, real data, right? Big trend has to happen. Second big trend that you really see customers desiring is fewer suppliers to cover more of the space. I need fewer, speaking of the voice of the customer, I need fewer tools to help me deal with this because I can't stitch 58 things together. It's just way too complex for me. So that really is a trend and I think you're going to see that continue to play out in our space, which is more consolidation and people wanting to cover more of their environment is very, very important to our customers. I think the other thing I'd say is agent proliferation. So, you know, go ask a customer, hey, show of hands, how many people want to load another agent? This gets kind of wonky, I know it's a little technical, but it's important. And if you talk to, most of these products run on agents is the idea. And if you talk to some big customers on a device like you have right here, they're loading 18. That's a lot. Okay, so now I got to keep this updated. I got to make sure there's no security issues and go on and on and on. Right. So it's consolidation of product, consolidation of agents, give me more data. And that's why, you know, in our case, a riverbed, we're doing everything based on platforms now. Okay, single agent, single place to keep all your data, make it simple and cover everything from networks to endpoints to applications. Theme, oh, go for it. I was going to say, getting rid of that complexity is so key because as emerging technologies become more widely adopted, the complexity, the potential for complexity, the sprawl is real and organizations cannot survive. We talked about, you know, the call center, the best call center is no call center. We don't want a call, but if we have a bad digital experience, we turn. We go somewhere else. So really. What would be fair to call centers if I can add? If you do have to have one, you know, most of these are going virtual now, which is right call center from your house. And, you know, the technology itself now, we can understand, do you have load time issues? You know, meaning so your customer data is either coming up slow so that person can't respond. Or the agent, the call agent, isn't following things in the order they should. All kinds of different measurements you can do, even though the person's at their house, to understand what's the efficiency of that call center, how do you get to the answer that people want faster? And we found that to be incredibly popular because most companies have some form of call center one way or another. I was saying, employee experience, customer experience like this. They're totally linked. They have to be absolutely linked, inextricably so. For that digital experience to be successful and deliver what the end user is looking for, the employee experience has to be dialed in and seamless. Yeah, and I'll give you a fun fact from our survey because we're all out here in Silicon Valley. So, you know, the trifecta in Silicon Valley is give me merch, give me free food and give me happy hour, right? Those are like three big employee benefit, right? That's the trifecta. The thrills of the Silicon Valley. Exactly, if you live here. In the Valley, actually above all those, internal digital experience was ranked higher. Wow. It could be shocking to the people who live out here, right? They'll give up the triple in order just to get that. They'll give up a manufactured social life to have a really high quality meal. Free food, I mean, that's a big give up. Hey, it is. Yeah, yeah. But it just shows that the impact, I mean, is profound. Yeah. And I think generationally, you know, that the tolerance level goes way down. Oh, 100%. Yeah. Well, you know, that's been another one of our themes on the show is once you have a different experience, you don't want to go back to the poor experience. Once you've used Grock, you don't want to use a slower AI. It's just a reality. It's like driving a Porsche and then going back to your old Toyota. It's just not the same. No, that's not an experience I want to have. No. I want to go the other way. We were talking about cars last night after the show. So question for you, because you obviously see a lot of different applications, a lot of different tools, like you said, different, and you're talking about platforms, agents, the whole shebang. Theme of the show is battle for AI supremacy. Are you seeing a lot of, do you have some clear front runners? Do you think it's still a bit of a grab bag in terms of where the chips are gonna fall, say, in a year from now? So my personal view is this, is because this is so data dependent as we discussed. It's been very, very difficult in the history of our industry, and I've worked my whole career around data to have one mega data player. Think about data lakes and all this stuff. Everybody talked about that. Most of those projects failed. Yes. Okay, why? Because it's really challenging. It's not that, this is very difficult stuff to do. So if you think about that in that context, what I believe is gonna play out is, to my earlier theme of practical solutions, people can actually see business impact from, is you're gonna have multiple winners who specialize in an area of data that they can actually manage and get real results out of, versus saying we're gonna have some Uber data container that will solve all things for all people. I think in the short term, that's just not practical. In the short term, you have to go for things that actually work, and things that work are gonna be, although very large, in this context of what I'm explaining, smaller data sets that are more focused on specific areas. And then over time, like I said, if we figure that out as we do, and I'm confident that we will, yeah, then there's a chance to have more data consolidation and solve more problems, which to your answer would be more of a singular winner who can cover more of the marketplace. Interesting. And then the other thing I'd say is, look, if you see the market already today, just like we talked about on the internet, we're gonna have some of our tech companies who have always flourished, who are gonna adopt to this and do well. And then we're gonna have new entrants who no one had ever heard of, even today, who also become household names. Yeah, definitely. As you look into the future, the near future is 2024. What are some of the top priorities that you're gonna advise CIOs really start paying attention to? Well, I mean, I think you have some of the same old and then you have things that are changing fairly rapidly. In our case on the same old, same old, we just talked a lot about digital experience, right? That this is a problem that is not solved and it is getting more and more attention to it every day for that reason, security forever. Oh yeah. Yeah, right? That gets more challenging every single day out there. And we talked about board level discussions, that is certainly a board level discussion. And the problems are getting so severe now, you see really significant company damage on some of these breaches now, which is really a shame, right? No one wants to see that, but it's just a reality where we live. And then offensively, as we talked about, people wanna invest in AI. People want to be more competitive and people wanna grow. And that's a pretty good, I think priority list these days for people. That's great advice. Dave, thank you so much for coming on SuperCloud 5, the battle for AI supremacy, sharing with us what Riverbed is doing to help organizations on the dex front. Why that's so challenging, but also how Riverbed is helping them tackle those challenges, give some great examples in healthcare, but I know this goes across every industry. We so appreciate your time, thank you. Great to be here, great to be with you. All right. In a moment, John Ferrier and Dave Vellante talk with CEO of Aviatrix, Doug Merritt. Stick around.