(upbeat music) >> Hello, everyone. Welcome to theCUBE's special presentation of International Women's Day. I'm John Furrier, host of theCUBE. Jenni Troutman is here, Director of Products and Services, and Training and Certification at AWS, and Heather Ruden, Director of Education Programs, Training and Certification. Thanks for coming on theCUBE and for the International Women's Day special program. >> Thanks so much for having us. >> So, I'll just get it out of the way. I'm a big fan of what you guys do. I've been shouting at the top of my lungs, "It's free. Get cloud training and you'll have a six figure job." Pretty much. I'm over amplifying. But this is really a big opportunity in the industry, education and the skills gap, and the skill velocities that's changing. New roles are coming on around cloud native, cloud native operators, cybersecurity. There's so much excitement going on around the industry, and all these open positions, and they need new talent. So you can't get a degree for some of these things. So, nope, it doesn't matter what school you went to, everyone's kind of level. This is a really big deal. So, Heather, share with us your thoughts as well on this topic. Jenni, you too. Like, where are you guys at? 'Cause this is a big opportunity for women and anyone to level up in the industry. >> Absolutely. So I'll jump in and then I'll hand it over to Jenni. We're your dream team here. We can talk about both sides of this. So I run a set of programs here at AWS that are really intended to help build the next generation of cloud builders. And we do that with a variety of programs, whether it is targeting young learners from kind of 12 and up. We have AWS GetIT that is designed to get women ambassadors or women mentors in front of girls 12 to 14 and get them curious about a career in STEM. We also have a program that is all digital online. It's available in 11 languages. It's got hundreds of courses. That's called AWS Educate that is designed to do exactly what you just talked about, expose the opportunities and start building cloud skills for learners at age 13 and up. They can go online and register with an email and start learning. We want them to understand not only what the opportunity is for them, but the ways that they can help influence and bring more diversity and more inclusion and into the cloud technology space, and just keep building all those amazing builders that we need here for our customers and partners. And those are the programs that I manage, but Jenni also has an amazing program, a set of programs. And so I'll hand it over to her as you get into the professional side of this things. >> So Jenni, you're on the product side. You've got the keys to the kingdom on all the materials and shaping it. What's your view on this? 'Cause this is a huge opportunity and it's always changing. What's the latest and greatest? >> It is a massive opportunity and to give you a sense, there was a study in '21 where IT executives said that talent availability is the biggest challenge to emerging tech adoption. 64% of IT executives said that up from only 4% the year before. So the challenge is growing really fast, which for everyone that's ready to go out there and learn and try something new is a massive opportunity. And that's really why I'm here. We provide all kinds of learning experiences for people across different cloud technologies to be able to not only gain the knowledge around cloud, but also the confidence to be able to build in the cloud. And so we look across different learner levels, different roles, different opportunities, and we provide those experiences where people can actually get hands-on in a totally risk-free environment and practice building in the cloud so they can go and be ready to get their certifications, their AWS certifications, give them the credentials to be able to show an employer they can do it, and then go out and get these jobs. It's really exciting. And we go kind of end to end from the very beginning. What is cloud? I want to know what it is all the way through to I can prove that I can build in the cloud and I'm ready for a job. >> So Jenni, you nailed that confidence word. I think I want to double click on that. And Heather, you talked about you're the dream team. You guys, you're the go to market, you bring this to the marketplace. Jenni, you get the products. This is the key, but to me the the international women days angle is, is that what I hear over and over again is that, "It's too technical. I'm not qualified." It can be scary. We had a guest on who has two double E degrees in robotics and aerospace and she's hard charging. She almost lost her confidence twice she said in her career. But she was hard charging. It can get scary, but also the ability to level up fast is just as good. So if you can break through that confidence and keep the curiosity and be a builder, talk about that dynamic 'cause you guys are in the middle of it, you're in the industry, how do you handle that? 'Cause I think that's a big thing that comes up over and over again. And confidence is not just women, it's men too. But women can always, that comes up as a theme. >> It is. It is a big challenge. I mean, I've struggled with it personally and I mentor a lot of women and that is the number one challenge that is holding women back from really being able to advance is the confidence to step out there and show what they can do. And what I love about some of the products we've put out recently is we have AWS Skill Builder. You can go online, you can get all kinds of free core training and if you want to go deeper, you can go deeper. And there's a lot of different options on there. But what it does is not only gives you that based knowledge, but you can actually go in. We have something called AWS Labs. You can go in and you can actually practice on the AWS console with the services that people are using in their jobs every day without any risk of doing something that is going to blow up in your face. You're not going to suddenly get this big AWS bill. You're not going to break something that's out there running. You just go in. It's your own little environment that gets wiped when you're done and you can practice. And there's lots of different ways to learn as well. So if you go in there and you're watching a video and to your point you're like, "Oh my gosh, this is too technical. I can't understand it. I don't know what I'm going to go do." You can go another route. There's something called AWS Cloud Quest. It's a game. You go in and it's like you're gaming and it walks you through. You're actually in a virtual world. You're walking through and it's telling you, "Hey, go build this and if you need help, here's hints and here's tips." And it continues to build on itself. So you're learning and you're applying practical skills and it's at your own pace. You don't have to watch somebody else talking that is going at a pace that maybe accelerates beyond what you're ready. You can do it at your own pace, you can redo it, you can try it again until you feel confident that you know it and you're really ready to move on to the next thing. Personally, I find that hugely valuable. I go in and do these myself and I sit there and I have a lot of engineers on my team, very smart people. And I have my own imposter syndrome. I get nervous to go talk to them. Like, are they going to think I'm totally lost? And so I go in and I learn some of this myself by experiment. And then I feel like, okay, now I can go ask them some intelligent questions and they're not going to be like, "Oh gosh, my leader is totally unaware of what we're doing." And so I think that we all struggle with confidence. I think everybody does, but I see it especially in women as I mentor them. And that's what I encourage them to do is go and on your own time, practice a bit, get a little bit of experience and once you feel like you can throw a couple words out there that you know what they mean and suddenly other people look at you like, "Oh, she knows what she's talking about." And you can kind of get past that feeling. >> Well Jenni, you nailed it. Heather, she just mentioned she's in the job and she's going and she's still leveling up. That's the end when you're in, but it's also the barriers to entry are lowering. You guys are doing a good job of getting people in, but also growing fast too. So there's two dynamics at play here. How do people do this? What's the playbook? Because I think that's really key, easy to get in. And then once you're in, you can level up fast at your own pace to ride the wave. And then there's new stuff coming. I mean, every re:Invent there's 5,000 announcements. So it's like zillion new things and AI taught now. >> re:Invent is a perfect example of that ongoing imposter syndrome or confidence check for all of us. I think something that that Jenni said too is we really try and meet learners where they are and make sure that we have the support, whether it's accessibility requirements or we have the content that is built for the age that we're talking to, or we have a workforce development program called re/Start that is for people that have very little tech experience and really want to talk about a career in cloud, but they need a little bit more handholding. They need a combination of instructor-led and digital. But then we have AWS educators, I mentioned. If you want to be more self-directed, all of these tools are intended to work well together and to be complimentary and to take you on a journey as a learner. And the more skills you have, the more you increase your knowledge, the more you can take on more. But meeting folks where they are with a variety of programs, tools, languages, and accessibility really helps ensure that we can do that for learners throughout the world. >> That's awesome. Let's get into it. Let's get into the roadmaps of people and their personas. And you guys can share the programs that you have and where people could fit in. 'Cause this comes up a lot when I talk to folks. There's the young person who's I'm a gamer or whatever, I want to get a job. I'm in high school or an elementary or I want to tinker around or I'm in college or I'm learning, I'm an entry level kind of entry. Then you have the re-skilling. I'm going to change my careers, I'm kind of bored, I want to do something compelling. How do I get into the cloud game? And then the advanced re-skill is I want to get into cyber and AI and then there's other. Could you break down? Did I get that right or did I miss anything? And then what's available for those kind of lanes? So those persona lanes? >> Well, let's see, I could start with maybe the high schooler stuff and then we can bring Jenni in as well. I would say a great place to start for anyone is aws.amazon.com/training. That's going to give them the full suite of options that they could take on. If you're in high school, you can go onto AWS Educate. All you need is an email. And if you're 13 years and older, you can start exploring the types of jobs that are available in the cloud and you could start taking some introductory classes. You can do some of those labs in a safe environment that Jenni mentioned. That's a great place to start. If you are in an environment where you have an educator that is willing to go on this with you, this journey with you, we have this AWS GetIT program that is, again, educator-led. So it's an afterschool or it's an a program where we match mentors and students up with cloud professionals and they do some real-time experimentation. They build an app, they work on things together, and do a presentation at the end. The other thing I would say too is that if you are in a university, I would double check and see if the AWS Academy curriculum is already in your university. And if so, explore some of those classes there. We have instructor-led, educator-ready. course curriculum that we've designed that help people get to those certifications and get closer to those jobs and as well as hopefully then lead people right into skill builder and all the things that Jenni talked about to help them as they start out in a professional environment. >> So is the GetIT, is that an instructor-led that the person has to find someone for? Or is this available for them? >> It is through teachers. It's through educators. We are in, we've reached over 19,000 students. We're available in eight countries. There are ways for educators to lead this, but we want to make sure that we are helping the kids be successful and giving them an educator environment to do that. If they want to do it on their own, then they can absolutely go through AWS Educate or even and to explore where they want to get started. >> So what about someone who's educated in their middle of their career, might want to switch from being a biologist to a cloud cybersecurity guru or a cloud native operator? >> Yeah, so in that case, AWS re/Start is one of the great program for them to explore. We run that program with collaborating organizations in 160 cities in 80 countries throughout the world. That is a multi-week cohort-based program where we do take folks through a very clear path towards certification and job skilling that will help them get into those opportunities. Over 98% of the cohorts, the graduates of those cohorts get an interview and are hopefully on their path to getting a job. So that really has global reach. The partnership with collaborating organizations helps us ensure that we find communities that are often unreached by cloud skills training and we really work to keep a diverse focus on those cohorts and bring those folks into the cloud. >> Okay. Jenni, you've got the Skill Builder action here. What's going on on your side? Because you must have to manage all the change. I mean, AI is hot right now. I'm sure you're cranking away on curriculum and content for SageMaker, large language models, computer vision, cybersecurity. >> We do. There are a lot of options. >> How is your world? Tell us about what people can take out of way from your side. >> Yeah. So a great way to think about it is if they're already out in the workforce or they're entering the workforce, but they are technical, have technical skills is what are the roles that are interesting in the technologies that are interesting. Because the way we put out our training and our certifications is aligned to paths. So if you're look interested in a specific role. If you're interested in architecting a cloud environment or in security as you mentioned, and you want to go deep in security, there are AWS certifications that give you that. If you achieve them, they're very difficult. But if you work to them and achieve them, they give you the credential that you can take to an employer and say, "Look, I can do this job." And they are in very high demand. In fact that's where if you look at some of the publications that have come out, they talk about, what are people making if they have different certifications? What are the most in-demand certifications that are out there? And those are what help people get jobs. And so you identify what is that role or that technology area I want to learn. And then you have multiple options for how you build those skills depending on how you want to learn. And again, that's really our focus, is on providing experiences based on how people learn and making it accessible to them. 'Cause not everybody wants to learn in the same way. And so there is AWS Skill Builder where people can go learn on their own that is really great particularly for people who maybe are already working and have to learn in the evenings, on the weekends. People who like to learn at their own pace, who just want to be hands-on, but are self-starters. And they can get those whole learning plans through there all the way aligned to the certification and then they can go get their certification. There's also classroom training. So a lot of people maybe want to do continuous learning through an online, but want to go really deep with an expert in the room and maybe have a more focused period of time if they can go for a couple days. And so they can do classroom training. We provide a lot of classroom training. We have partners all over the globe who provide classroom training. And so there's that and what we find to be the most powerful is when you couple the two. If you can really get deep, you have an expert, you can ask questions, but first before you go do that, you get some of that foundational that you've kind of learned on your own. And then after you go back and reinforce, you go back online, you try out things that maybe you learned in the classroom, but you didn't quite, you hadn't used it enough yet to quite know how to do it. Now you can go back and actually use it, experiment and play around. And so we really encourage that kind of, figure out what are some areas you're interested in, go learn it and then go get a job and continue to learn because then once you learn that first area, you start to build confidence in it. Suddenly other areas become interesting. 'Cause as you said, cloud is changing fast. And once you learn a space, first of all you have to keep going back to stay up on it as it changes. But you quickly find that there are other areas that are really interesting too. >> I've observed that the training side, it's just like cloud itself, it's very agile. You can get hands-on quickly, you don't need to take a class, and then get in weeks later. You're in it like it's real time. So you're immersed in gamification and all kinds of ways to funnel into the either advanced tracks and certification. So you guys do a great job and I want to give you props for that and a shout out. The question I have for you guys is can you scope the opportunity for these certifications and opportunities for women in particular? What are some of the top jobs pulling down? Scope out the opportunity because I think when people hear that they really fall out of their chair, they go, "Wow, I didn't know I could make $200,000 doing cybersecurity." Well, yeah or maybe more. I just made the number, I don't actually know, but like I know people do make that much in cyber, but there are huge financial opportunities with certifications and education. Can you scope that order of magnitude? Can you share any data? >> Yeah, so in the US they certainly are. Certifications on average aligned to six digit type jobs. And if you go out and do a search, there are research studies out there that are refreshed every year that say what are the top IT industry certifications and how much money do they make? And the reason I don't put a number out there is because it's constantly changing and in fact it keeps going up, >> It's going up, not going down. >> But I would encourage people to do that quick search. What are the top IT industry certifications. Again, based on the country you're in, it makes a difference. But if you're US, there's a lot of data out there for the US and then there is some for other countries as well around how much on average people make. >> Do you list like the higher level certifications, stack rank them in terms of order? Like say, I'm a type A personnel, I want to climb Mount Everest, I want to get the highest level certification. How do I know that? Is it like laddered up or is like how do you guys present that? >> Yeah, so we have different types of certifications. There is a foundational, which we call the cloud practitioner. That one is more about just showing that you know something about cloud. It's not aligned to a specific job role. But then we have what we call associate level certifications, which are aligned to roles. So there's the solutions architect, cloud developer, so developer operations. And so you can tell by the role and associate is kind of that next level. And then the roles often have a professional level, which is even more advanced. And basically that's saying you're kind of an Uber expert at that point. And then there are technology specialties, which are less about a specific role, although some would argue a security technology specialty might align very well to a security role, but they're more about showing the technology. And so typically, it goes foundational, advanced, professional, and then the specialties are more on the side. They're not aligned, but they're deep. They're deep within that area. >> So you can go dig and pick your deep dive and jump into where you're comfortable. Heather, talk about the commitment in terms of dollars. I know Amazon's flaunted some numbers like 30 million or something, people they want to have trained, hundreds of millions of dollars in investment. This is key, obviously, more people trained on cloud, more operators, more cloud usage, obviously. I see the business connection. What's the women relationship to the numbers? Or what the experience is? How do you guys see that? Obviously International Women's Day, get the confidence, got the curiosity. You're a builder, you're in. It's that easy. >> It doesn't always feel that way, I'm sure to everybody, but we'd like to think that it is. Amazon and AWS do invest hundreds of millions of dollars in free training every year that is accessible to everyone out there. I think that sometimes the hardest obstacles to get overcome are getting started and we try and make it as easy as possible to get started with the tools that we've talked about already today. We run into plenty of cohorts of women as part of our re/Start program that are really grateful for the opportunity to see something, see a new way of thinking, see a new opportunity for them. We don't necessarily break out our funding by women versus men. We want to make sure that we are open and diverse for everybody to come in and get the training that they need to. But we definitely want to make sure that we are accessible and available to women and all genders outside of the US and inside the US. >> Well, I know the number's a lot lower than they should be and that's obviously why we're promoting this heavily. There's a lot more interest I see in tech. So digital transformation is gender neutral. I mean, it's like the world eats software and uses software, uses the cloud. So it has to get 50/50 in my opinion. So you guys do a great job. Now that we're done kind of promoting Amazon, which I wanted to do 'cause I think it's super important. Let's talk about you guys. What got you guys involved in tech? What was the inspiration and share some stories about your experiences and advice for folks watching? >> So I've always been in traditionally male dominated roles. I actually started in aviation and then moved to tech. And what I found was I got a mentor early on, a woman who was senior to me and who was kind of who I saw as the smartest person out there. She was incredibly smart, she was incredibly kind, and she was always lifting women up. And I kind of latched onto her and followed her around and she was such an amazing mentor. She brought me from throughout tech, from company to company, job to job, was always positioning me in front of other people as the go-to person. And I realized, "Wow, I want to be like her." And so that's been my focus as well in tech is you can be deeply technical in tech or you can be not deeply technical and be in tech and you can be successful both ways, but the way you're going to be most successful is if you find other people, build them up and help put them out in front. And so I personally love to mentor women and to put them in places where they can feel comfortable being out in front of people. And that's really been my career. I have tried to model her approach as much as I can. >> That's a really interesting observation. It's the pattern we've been seeing in all these interviews for the past two years of doing the International Women's Day is that networking, mentoring and sponsorship are one thing. So it's all one thing. It's not just mentoring. It's like people think, "Oh, just mentoring. What does that mean? Advice?" No, it's sponsorship, it's lifting people up, creating a keiretsu, creating networks. Really important. Heather, what's your experience? >> Yeah, I'm sort of the example of somebody who never thought they'd be in tech, but I happened to graduate from college in the Silicon Valley in the early nineties and next thing you know, it's more than a couple years later and I'm deeply in tech and I think it when we were having the conversation about confidence and willingness to learn and try that really spoke to me as well. I think I had to get out of my own way sometimes and just be willing to not be the smartest person in the room and just be willing to ask a lot of questions. And with every opportunity to ask questions, I think somebody, I ended up with good mentors, male and female, that saw the willingness to ask questions and the willingness to be humble in my approach to learning. And that really helped. I'm also very aware that nobody's journey is the same and I need to create an environment on my team and I need to be a role model within AWS and Amazon for allowing people to show up in the way that they're going to be most successful. And sometimes that will mean giving them learning opportunities. Sometimes that will be hooking them up with a mentor. Sometimes that will be giving them the freedom to do what they need for their family or their personal life. And modeling that behavior regardless of gender has always been how I choose to show up and what I ask my leaders to do. And the more we can do that, I've seen the team been able to grow and flourish in that way and support our entire team. >> I love that story. You also have a great leader, Maureen Lonergan, who I've met many conversations with, but also it starts at the top. Andy Jassy who can come across, he's kind of technical, he's dirty, he's a builder mentality. He has first principles and you're bringing up this first principles concept and whether that's passing it forward, what you've learned, having first principles helps in an organization. Can you guys talk about what that's like at your company? 'Cause everyone's different. And sometimes whether, and I sometimes I worry about what I say, but I also have my first principles. So talk about how principles matter in how you guys interface with others and letting people be their authentic self. >> Yeah, I'll jump in Jenni and then you can. The Amazon leadership principles are super important to how we interact with each other and it really does provide a set of guidelines for how we work with each other and how we work for our customers and with our partners. But most of all it gives us a common language and a common set of expectations. And I will be honest, they're not always easy. When you come from an environment that tends to be less open to feedback and less open to direct conversations than you find at Amazon, it could take a while to get used to that, but for me at least, it was extremely empowering to have those tools and those principles as guidance for how to operate and to gain the confidence in using them. I've also been able to participate in hundreds and hundreds of interviews in the time that I've been here as part of an interview team of bar raisers. I think that really helps us understand whether or not folks are going to be successful at AWS and at Amazon and helps them understand if they're going to be able to be successful. >> Bar raising is an Amazon term and it's gender neutral, right Jenni? >> It is gender neutral. >> Bar is a bar, it raises. >> That's right. And it's funny, we say that our culture here is peculiar. And when I started, I had been in consulting for several years, so I worked with a lot of different companies in tech and so I thought I'd seen everything and I came here and I went, "Hmm." I see what they mean by peculiar. It is very different environment. >> In the fullness of time, it'll all work out. >> That's right, that's right. Well and it's funny because when you first started, it's a lot to figure out to how to operate in an environment where people do use a 16 leadership principles. I've worked at a lot of companies with three or four core values and nobody can state those. We could state all 16 leadership principles and we use them in our regular everyday dialogue. That is an awkward thing when you first come to have people saying, "Oh, I'm going to use bias for action in this situation and I'm going to go move fast. And they're actually used in everyday conversations. But after a couple years suddenly you realize, "Oh, I'm doing that." And maybe even sometimes at the dinner table I'm doing that, which can get to be a bit much. But it creates an environment where we can all be different. We can all think differently. We can all have different ways of doing things, but we have a common overall approach to what we're trying to achieve. And that's really, it gives us a good framework for that. >> Jenni, it's great insight. Heather, thank you so much for sharing your stories. We're going to do this not once a year. We're going to continue this Women in Tech program every quarter. We'll check in with you guys and find out what's new. And thank you for what you do. We appreciate that getting the word out and really is an opportunity for everyone with education and cloud and it's only going to get more opportunities at the edge in AI and so much more tech. Thank you for coming on the program. >> Thank you for having us. >> Thanks, John. >> Thank you. That's the International Women's Day segment here with leaders from AWS. I'm John Furrier. Thanks for watching. (upbeat musiC)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (bright upbeat music plays) >> Welcome back to Barcelona, everybody. You're watching theCUBE's coverage of MWC '23, my name is Dave Vellante. Just left a meeting with the CEO of Cisco, Chuck Robbins, to meet with Jeetu Patel, who's our Executive Vice President and General Manager of security and collaboration at Cisco. Good to see you. >> You never leave a meeting with Chuck Robbins to meet with Jeetu Patel. >> Well, I did. >> That's a bad idea. >> Walked right out. I said, hey, I got an interview to do, right? So, and I'm excited about this. Thanks so much for coming on. >> Thank you for having me. It's a pleasure. >> So, I mean you run such an important part of the business. I mean, obviously the collaboration business but also security. So many changes going on in the security market. Maybe we could start there. I mean, there hasn't been a ton of security talk here Jeetu, because I think it's almost assumed. It was 45 minutes into the keynote yesterday before anybody even mentioned security. >> Huh. >> Right? And so, but it's the most important topic in the enterprise IT world. And obviously is important here. So why is it you think that it's not the first topic that people mention. >> You know, it's a complicated subject area and it's intimidating. And actually that's one of the things that the industry screwed up on. Where we need to simplify security so it actually gets to be relatable for every person on the planet. But, if you think about what's happening in security, it's not just important for business it's critical infrastructure that if you had a breach, you know lives are cost now. Because hospitals could go down, your water supply could go down, your electricity could go down. And so it's one of these things that we have to take pretty seriously. And, it's 51% of all breaches happen because of negligence, not because of malicious intent. >> It's that low. Interesting. I always- >> Someone else told me the same thing, that they though it'd be higher, yeah. >> I always say bad user behavior is going to trump good security every time. >> Every single time. >> You can't beat it. But, you know, it's funny- >> Jeetu: Every single time. >> Back, the earlier part of last decade, you could see that security was becoming a board level issue. It became, it was on the agenda every quarter. And, I remember doing some research at the time, and I asked, I was interviewing Robert Gates, former Defense Secretary, and I asked him, yeah, but we're getting attacked but don't we have the best offense? Can't we have the best technology? He said, yeah but we have so much critical infrastructure the risks to United States are higher. So we have to be careful about how we use security as an offensive weapon, you know? And now you're seeing the future of war involves security and what's going on in Ukraine. It's a whole different ballgame. >> It is, and the scales always tip towards the adversary, not towards the defender, because you have to be right every single time. They have to be right once. >> Yeah. And, to the other point, about bad user behavior. It's going now beyond the board level, to it's everybody's responsibility. >> That's right. >> And everybody's sort of aware of it, everybody's been hacked. And, that's where it being such a complicated topic is problematic. >> It is, and it's actually, what got us this far will not get us to where we need to get to if we don't simplify security radically. You know? The experience has to be almost invisible. And what used to be the case was sophistication had to get to a certain level, for efficacy to go up. But now, that sophistication has turned to complexity. And there's an inverse relationship between complexity and efficacy. So the simpler you make security, the more effective it gets. And so I'll give you an example. We have this great kind of innovation we've done around passwordless, right? Everyone hates passwords. You shouldn't have passwords in 2023. But, when you get to passwordless security, not only do you reduce a whole lot of friction for the user, you actually make the system safer. And that's what you need to do, is you have to make it simpler while making it more effective. And, I think that's what the future is going to hold. >> Yeah, and CISOs tell me that they're, you know zero trust before the pandemic was like, yeah, yeah zero trust. And now it's like a mandate. >> Yeah. >> Every CISO you talk to says, yes we're implementing a zero trust architecture. And a big part of that is that, if they can confirm zero trust, they can get to market a lot faster with revenue generating or critical projects. And many projects as we know are being pushed back, >> Yeah. >> you know? 'Cause of the macro. But, projects that drive revenue and value they want to accelerate, and a zero trust confirmation allows people to rubber stamp it and go faster. >> And the whole concept of zero trust is least privileged access, right? But what we want to make sure that we get to is continuous assessment of least privileged access, not just a one time at login. >> Dave: 'Cause things change so frequently. >> So, for example, if you happen to be someone that's logged into the system and now you start doing some anomalous behavior that doesn't sound like Dave, we want to be able to intercept, not just do it at the time that you're authenticating Dave to come in. >> So you guys got a good business. I mentioned the macro before. >> Yeah. >> The big theme is consolidating redundant vendors. So a company with a portfolio like Cisco's obviously has an advantage there. You know, you guys had great earnings. Palo Alto is another company that can consolidate. Tom Gillis, great pickup. Guy's amazing, you know? >> Love Tom. >> Great respect. Just had a little webinar session with him, where he was geeking out with the analyst and so- >> Yeah, yeah. >> Learned a lot there. Now you guys have some news, at the event event with Mercedes? >> We do. >> Take us through that, and I want to get your take on hybrid work and what's happening there. But what's going on with Mercedes? >> Yeah so look, it all actually stems from the hybrid work story, which is the future is going to be hybrid, people are going to work in mixed mode. Sometimes you'll be in the office, sometimes at home, sometimes somewhere in the middle. One of the places that people are working more and more from is their cars. And connected cars are getting to be a reality. And in fact, cars sometimes become an extension of your home office. And many a times I have found myself in a parking lot, because I didn't have enough time to get home and I was in a parking lot taking a conference call. And so we've made that section easier, because we have now partnered with Mercedes. And they aren't the first partner, but they're a very important partner where we are going to have Webex available, through the connected car, natively in Mercedes. >> Ah, okay. So I could take a call, I can do it all the time. I find good service, pull over, got to take the meeting. >> Yeah. >> I don't want to be driving. I got to concentrate. >> That's right. >> You know, or sometimes, I'll have the picture on and it's not good. >> That's right. >> Okay, so it'll be through the console, and all through the internet? >> It'll be through the console. And many people ask me like, how's safety going to work over that? Because you don't want to do video calls while you're driving. Exactly right. So when you're driving, the video automatically turns off. And you'll have audio going on, just like a conference call. But the moment you stop and put it in park, you can have video turned on. >> Now, of course the whole hybrid work trend, we, seems like a long time ago but it doesn't, you know? And it's really changed the security dynamic as well, didn't it? >> It has, it has. >> I mean, immediately you had to go protect new endpoints. And those changes, I felt at the time, were permanent. And I think it's still the case, but there's an equilibrium now happening. People as they come back to the office, you see a number of companies are mandating back to work. Maybe the central offices, or the headquarters, were underfunded. So what's going on out there in terms of that balance? >> Well firstly, there's no unanimous consensus on the way that the future is going to be, except that it's going to be hybrid. And the reason I say that is some companies mandate two days a week, some companies mandate five days a week, some companies don't mandate at all. Some companies are completely remote. But whatever way you go, you want to make sure that regardless of where you're working from, people can have an inclusive experience. You know? And, when they have that experience, you want to be able to work from a managed device or an unmanaged device, from a corporate network or from a Starbucks, from on the road or stationary. And whenever you do any of those things, we want to make sure that security is always handled, and you don't have to worry about that. And so the way that we say it is the company that created the VPN, which is Cisco, is the one that's going to kill it. Because what we'll do is we'll make it simple enough so that you don't, you as a user, never have to worry about what connection you're going to use to dial in to what app. You will have one, seamless way to dial into any application, public application, private application, or directly to the internet. >> Yeah, I got a love, hate with my VPN. I mean, it's protecting me, but it's in the way a lot. >> It's going to be simple as ever. >> Do you have kids? >> I do, I have a 12 year old daughter. >> Okay, so not quite high school age yet. She will be shortly. >> No, but she's already, I'm not looking forward to high school days, because she has a very, very strong sense of debate and she wins 90% of the arguments. >> So when my kids were that age, I've got four kids, but the local high school banned Wikipedia, they can't use Wikipedia for research. Many colleges, I presume high schools as well, they're banning Chat GPT, can't use it. Now at the same time, I saw recently on Medium a Wharton school professor said he's mandating Chat GPT to teach his students how to prompt in progressively more sophisticated prompts, because the future is interacting with machines. You know, they say in five years we're all going to be interacting in some way, shape, or form with AI. Maybe we already are. What's the intersection between AI and security? >> So a couple very, very consequential things. So firstly on Chat GPT, the next generation skill is going to be to learn how to go out and have the right questions to ask, which is the prompt revolution that we see going on right now. But if you think about what's happening in security, and there's a few areas which are, firstly 3,500 hundred vendors in this space. On average, most companies have 50 to 70 vendors in security. Not a single vendor owns more than 10% of the market. You take out a couple vendors, no one owns more than 5%. Highly fractured market. That's a problem. Because it's untenable for companies to go out and manage 70 policy engines. And going out and making sure that there's no contention. So as you move forward, one of the things that Chat GPT will be really good for is it's fundamentally going to change user experiences, for how software gets built. Because rather than it being point and click, it's going to be I'm going to provide an instruction and it's going to tell me what to do in natural language. Imagine Dave, when you joined a company if someone said, hey give Dave all the permissions that he needs as a direct report to Chuck. And instantly you would get all of the permissions. And it would actually show up in a screen that says, do you approve? And if you hit approve, you're done. The interfaces of the future will get more natural language kind of dominated. The other area that you'll see is the sophistication of attacks and the surface area of attacks is increasing quite exponentially. And we no longer can handle this with human scale. You have to handle it in machine scale. So detecting breaches, making sure that you can effectively and quickly respond in real time to the breaches, and remediate those breaches, is all going to happen through AI and machine learning. >> So, I agree. I mean, just like Amazon turned the data center into an API, I think we're now going to be interfacing with technology through human language. >> That's right. >> I mean I think it's a really interesting point you're making. Now, from a security standpoint as well, I mean, the state of the art today in my email is be careful, this person's outside your organization. I'm like, yeah I know. So it's a good warning sign, but it's really not automated in any way. So two part question. One is, can AI help? You know, with the phishing, obviously it can, but the bad guys have AI too. >> Yeah. >> And they're probably going to be smarter than I am about using it. >> Yeah, and by the way, Talos is our kind of threat detection and response >> Yes. >> kind of engine. And, they had a great kind of piece that came out recently where they talked about this, where Chat GPT, there is going to be more sophistication of the folks that are the bad actors, the adversaries in using Chat GPT to have more sophisticated phishing attacks. But today it's not something that is fundamentally something that we can't handle just yet. But you still need to do the basic hygiene. That's more important. Over time, what you will see is attacks will get more bespoke. And in order, they'll get more sophisticated. And, you will need to have better mechanisms to know that this was actually not a human being writing that to you, but it was actually a machine pretending to be a human being writing something to you. And that you'll have to be more clever about it. >> Oh interesting. >> And so, you will see attacks get more bespoke and we'll have to get smarter and smarter about it. >> The other thing I wanted to ask you before we close is you're right on. I mean you take the top security vendors and they got a single digit market share. And it's like it's untenable for organizations, just far too many tools. We have a partner at ETR, they do quarterly survey research and one of the things they do is survey emerging technology companies. And when we look at in the security sector just the number of emerging technology companies that are focused on cybersecurity is as many as there are out there already. And so, there's got to be consolidation. Maybe that's through M & A. I mean, what do you think happens? Are company's going to go out of business? There's going to be a lot of M & A? You've seen a lot of companies go private. You know, the big PE companies are sucking up all these security companies and may be ready to spit 'em out and go back public. How do you see the landscape? You guys are obviously an inquisitive company. What are your thoughts on that? >> I think there will be a little bit of everything. But the biggest change that you'll see is a shift that's going to happen with an integrated platform, rather than point solution vendors. So what's going to happen is the market's going to consolidate towards very few, less than a half a dozen, integrated platforms. We believe Cisco is going to be one. Microsoft will be one. There'll be others over there. But these, this platform will essentially be able to provide a unified kind of policy engine across a multitude of different services to protect multiple different entities within the organization. And, what we found is that platform will also be something that'll provide, through APIs, the ability for third parties to be able to get their technology incorporated in, and their telemetry ingested. So we certainly intend to do that. We don't believe, we are not arrogant enough to think that every single new innovation will be built by us. When there's someone else who has built that, we want to make sure that we can ingest that telemetry as well, because the real enemy is not the competitor. The real enemy is the adversary. And we all have to get together, so that we can keep humanity safe. >> Do you think there's been enough collaboration in the industry? I mean- >> Jeetu: Not nearly enough. >> We've seen companies, security companies try to monetize private data before, instead of maybe sharing it with competitors. And so I think the industry can do better there. >> Well I think the industry can do better. And we have this concept called the security poverty line. And the security poverty line is the companies that fall below the security poverty line don't have either the influence or the resources or the know how to keep themselves safe. And when they go unsafe, everyone else that communicates with them also gets that exposure. So it is in our collective interest for all of us to make sure that we come together. And, even if Palo Alto might be a competitor of ours, we want to make sure that we invite them to say, let's make sure that we can actually exchange telemetry between our companies. And we'll continue to do that with as many companies that are out there, because actually that's better for the market, that's better for the world. >> The enemy of the enemy is my friend, kind of thing. >> That's right. >> Now, as it relates to, because you're right. I mean I, I see companies coming up, oh, we do IOT security. I'm like, okay, but what about cloud security? Do you that too? Oh no, that's somebody else. But, so that's another stove pipe. >> That's a huge, huge advantage of coming with someone like Cisco. Because we actually have the entire spectrum, and the broadest portfolio in the industry of anyone else. From the user, to the device, to the network, to the applications, we provide the entire end-to-end story for security, which then has the least amount of cracks that you can actually go out and penetrate through. The biggest challenges that happen in security is you've got way too many policy engines with way too much contention between the policies from these different systems. And eventually there's a collision course. Whereas with us, you've actually got a broad portfolio that operates as one platform. >> We were talking about the cloud guys earlier. You mentioned Microsoft. They're obviously a big competitor in the security space. >> Jeetu: But also a great partner. >> So that's right. To my opinion, the cloud has been awesome as a first line of defense if you will. But the shared responsibility model it's different for each cloud, right? So, do you feel that those guys are working together or will work together to actually improve? 'Cause I don't see that yet. >> Yeah so if you think about, this is where we feel like we have a structural advantage in this, because what does a company like Cisco become in the future? I think as the world goes multicloud and hybrid cloud, what'll end up happening is there needs to be a way, today all the CSPs provide everything from storage to computer network, to security, in their own stack. If we can abstract networking and security above them, so that we can acquire and steer any and all traffic with our service providers and steer it to any of those CSPs, and make sure that the security policy transcends those clouds, you would actually be able to have the public cloud economics without the public cloud lock-in. >> That's what we call super cloud Jeetu. It's securing the super cloud. >> Yeah. >> Hey, thanks so much for coming to theCUBE. >> Thank you for having me. >> Really appreciate you coming on our editorial program. >> Such a pleasure. >> All right, great to see you again. >> Cheers. >> All right, keep it right there. Dave Vellante with David Nicholson and Lisa Martin. We'll be back, right after this short break from MWC '23 live, in the Fira, in Barcelona. (bright music resumes) (music fades out)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> A decade of big data investments combined with cloud scale, the rise of much more cost effective processing power. And the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may actually even be doing your job. Artificial intelligence is being infused into applications, infrastructure, equipment, and virtually every aspect of our lives. AI is proving to be extremely helpful at things like controlling vehicles, speeding up medical diagnoses, processing language, advancing science, and generally raising the stakes on what it means to apply technology for business advantage. But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable upfront investments, ethical concerns, and lack of business alignment. Mastering AI technology will not be a requirement for success in our view. However, figuring out how and where to apply AI to your business will be crucial. That means understanding the business case, picking the right technology partner, experimenting in bite-sized chunks, and quickly identifying winners to double down on from an investment standpoint. Hello and welcome to this week's Wiki-bond CUBE Insights powered by ETR. In this breaking analysis, we update you on the state of AI and what it means for the competition. And to do so, we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply. He knows the players, he knows the pitfalls of AI investment, and he's a collaborator. Andy, great to have you on the program. Thanks for coming into our CUBE studios. >> Thanks for having me on. >> You're very welcome. Okay, let's set the table with a premise and a series of assertions we want to test with Andy. I'm going to lay 'em out. And then Andy, I'd love for you to comment. So, first of all, according to McKinsey, AI adoption has more than doubled since 2017, but only 10% of organizations report seeing significant ROI. That's a BCG and MIT study. And part of that challenge of AI is it requires data, is requires good data, data proficiency, which is not trivial, as you know. Firms that can master both data and AI, we believe are going to have a competitive advantage this decade. Hyperscalers, as we show you dominate AI and ML. We'll show you some data on that. And having said that, there's plenty of room for specialists. They need to partner with the cloud vendors for go to market productivity. And finally, organizations increasingly have to put data and AI at the center of their enterprises. And to do that, most are going to rely on vendor R&D to leverage AI and ML. In other words, Andy, they're going to buy it and apply it as opposed to build it. What are your thoughts on that setup and that premise? >> Yeah, I see that a lot happening in the field, right? So first of all, the only 10% of realizing a return on investment. That's so true because we talked about this earlier, the most companies are still in the innovation cycle. So they're trying to innovate and see what they can do to apply. A lot of these times when you look at the solutions, what they come up with or the models they create, the experimentation they do, most times they don't even have a good business case to solve, right? So they just experiment and then they figure it out, "Oh my God, this model is working. Can we do something to solve it?" So it's like you found a hammer and then you're trying to find the needle kind of thing, right? That never works. >> 'Cause it's cool or whatever it is. >> It is, right? So that's why, I always advise, when they come to me and ask me things like, "Hey, what's the right way to do it? What is the secret sauce?" And, we talked about this. The first thing I tell them is, "Find out what is the business case that's having the most amount of problems, that that can be solved using some of the AI use cases," right? Not all of them can be solved. Even after you experiment, do the whole nine yards, spend millions of dollars on that, right? And later on you make it efficient only by saving maybe $50,000 for the company or a $100,000 for the company, is it really even worth the experiment, right? So you got to start with the saying that, you know, where's the base for this happening? Where's the need? What's a business use case? It doesn't have to be about cost efficient and saving money in the existing processes. It could be a new thing. You want to bring in a new revenue stream, but figure out what is a business use case, how much money potentially I can make off of that. The same way that start-ups go after. Right? >> Yeah. Pretty straightforward. All right, let's take a look at where ML and AI fit relative to the other hot sectors of the ETR dataset. This XY graph shows net score spending velocity in the vertical axis and presence in the survey, they call it sector perversion for the October survey, the January survey's in the field. Then that squiggly line on ML/AI represents the progression. Since the January 21 survey, you can see the downward trajectory. And we position ML and AI relative to the other big four hot sectors or big three, including, ML/AI is four. Containers, cloud and RPA. These have consistently performed above that magic 40% red dotted line for most of the past two years. Anything above 40%, we think is highly elevated. And we've just included analytics and big data for context and relevant adjacentness, if you will. Now note that green arrow moving toward, you know, the 40% mark on ML/AI. I got a glimpse of the January survey, which is in the field. It's got more than a thousand responses already, and it's trending up for the current survey. So Andy, what do you make of this downward trajectory over the past seven quarters and the presumed uptick in the coming months? >> So one of the things you have to keep in mind is when the pandemic happened, it's about survival mode, right? So when somebody's in a survival mode, what happens, the luxury and the innovations get cut. That's what happens. And this is exactly what happened in the situation. So as you can see in the last seven quarters, which is almost dating back close to pandemic, everybody was trying to keep their operations alive, especially digital operations. How do I keep the lights on? That's the most important thing for them. So while the numbers spent on AI, ML is less overall, I still think the AI ML to spend to sort of like a employee experience or the IT ops, AI ops, ML ops, as we talked about, some of those areas actually went up. There are companies, we talked about it, Atlassian had a lot of platform issues till the amount of money people are spending on that is exorbitant and simply because they are offering the solution that was not available other way. So there are companies out there, you can take AoPS or incident management for that matter, right? A lot of companies have a digital insurance, they don't know how to properly manage it. How do you find an intern solve it immediately? That's all using AI ML and some of those areas actually growing unbelievable, the companies in that area. >> So this is a really good point. If you can you bring up that chart again, what Andy's saying is a lot of the companies in the ETR taxonomy that are doing things with AI might not necessarily show up in a granular fashion. And I think the other point I would make is, these are still highly elevated numbers. If you put on like storage and servers, they would read way, way down the list. And, look in the pandemic, we had to deal with work from home, we had to re-architect the network, we had to worry about security. So those are really good points that you made there. Let's, unpack this a little bit and look at the ML AI sector and the ETR data and specifically at the players and get Andy to comment on this. This chart here shows the same x y dimensions, and it just notes some of the players that are specifically have services and products that people spend money on, that CIOs and IT buyers can comment on. So the table insert shows how the companies are plotted, it's net score, and then the ends in the survey. And Andy, the hyperscalers are dominant, as you can see. You see Databricks there showing strong as a specialist, and then you got to pack a six or seven in there. And then Oracle and IBM, kind of the big whales of yester year are in the mix. And to your point, companies like Salesforce that you mentioned to me offline aren't in that mix, but they do a lot in AI. But what are your takeaways from that data? >> If you could put the slide back on please. I want to make quick comments on a couple of those. So the first one is, it's surprising other hyperscalers, right? As you and I talked about this earlier, AWS is more about logo blocks. We discussed that, right? >> Like what? Like a SageMaker as an example. >> We'll give you all the components what do you need. Whether it's MLOps component or whether it's, CodeWhisperer that we talked about, or a oral platform or data or data, whatever you want. They'll give you the blocks and then you'll build things on top of it, right? But Google took a different way. Matter of fact, if we did those numbers a few years ago, Google would've been number one because they did a lot of work with their acquisition of DeepMind and other things. They're way ahead of the pack when it comes to AI for longest time. Now, I think Microsoft's move of partnering and taking a huge competitor out would open the eyes is unbelievable. You saw that everybody is talking about chat GPI, right? And the open AI tool and ChatGPT rather. Remember as Warren Buffet is saying that, when my laundry lady comes and talk to me about stock market, it's heated up. So that's how it's heated up. Everybody's using ChatGPT. What that means is at the end of the day is they're creating, it's still in beta, keep in mind. It's not fully... >> Can you play with it a little bit? >> I have a little bit. >> I have, but it's good and it's not good. You know what I mean? >> Look, so at the end of the day, you take the massive text of all the available text in the world today, mass them all together. And then you ask a question, it's going to basically search through that and figure it out and answer that back. Yes, it's good. But again, as we discussed, if there's no business use case of what problem you're going to solve. This is building hype. But then eventually they'll figure out, for example, all your chats, online chats, could be aided by your AI chat bots, which is already there, which is not there at that level. This could build help that, right? Or the other thing we talked about is one of the areas where I'm more concerned about is that it is able to produce equal enough original text at the level that humans can produce, for example, ChatGPT or the equal enough, the large language transformer can help you write stories as of Shakespeare wrote it. Pretty close to it. It'll learn from that. So when it comes down to it, talk about creating messages, articles, blogs, especially during political seasons, not necessarily just in US, but anywhere for that matter. If people are able to produce at the emission speed and throw it at the consumers and confuse them, the elections can be won, the governments can be toppled. >> Because to your point about chatbots is chatbots have obviously, reduced the number of bodies that you need to support chat. But they haven't solved the problem of serving consumers. Most of the chat bots are conditioned response, which of the following best describes your problem? >> The current chatbot. >> Yeah. Hey, did we solve your problem? No. Is the answer. So that has some real potential. But if you could bring up that slide again, Ken, I mean you've got the hyperscalers that are dominant. You talked about Google and Microsoft is ubiquitous, they seem to be dominant in every ETR category. But then you have these other specialists. How do those guys compete? And maybe you could even, cite some of the guys that you know, how do they compete with the hyperscalers? What's the key there for like a C3 ai or some of the others that are on there? >> So I've spoken with at least two of the CEOs of the smaller companies that you have on the list. One of the things they're worried about is that if they continue to operate independently without being part of hyperscaler, either the hyperscalers will develop something to compete against them full scale, or they'll become irrelevant. Because at the end of the day, look, cloud is dominant. Not many companies are going to do like AI modeling and training and deployment the whole nine yards by independent by themselves. They're going to depend on one of the clouds, right? So if they're already going to be in the cloud, by taking them out to come to you, it's going to be extremely difficult issue to solve. So all these companies are going and saying, "You know what? We need to be in hyperscalers." For example, you could have looked at DataRobot recently, they made announcements, Google and AWS, and they are all over the place. So you need to go where the customers are. Right? >> All right, before we go on, I want to share some other data from ETR and why people adopt AI and get your feedback. So the data historically shows that feature breadth and technical capabilities were the main decision points for AI adoption, historically. What says to me that it's too much focus on technology. In your view, is that changing? Does it have to change? Will it change? >> Yes. Simple answer is yes. So here's the thing. The data you're speaking from is from previous years. >> Yes >> I can guarantee you, if you look at the latest data that's coming in now, those two will be a secondary and tertiary points. The number one would be about ROI. And how do I achieve? I've spent ton of money on all of my experiments. This is the same thing theme I'm seeing across when talking to everybody who's spending money on AI. I've spent so much money on it. When can I get it live in production? How much, how can I quickly get it? Because you know, the board is breathing down their neck. You already spend this much money. Show me something that's valuable. So the ROI is going to become, take it from me, I'm predicting this for 2023, that's going to become number one. >> Yeah, and if people focus on it, they'll figure it out. Okay. Let's take a look at some of the top players that won, some of the names we just looked at and double click on that and break down their spending profile. So the chart here shows the net score, how net score is calculated. So pay attention to the second set of bars that Databricks, who was pretty prominent on the previous chart. And we've annotated the colors. The lime green is, we're bringing the platform in new. The forest green is, we're going to spend 6% or more relative to last year. And the gray is flat spending. The pinkish is our spending's going to be down on AI and ML, 6% or worse. And the red is churn. So you don't want big red. You subtract the reds from the greens and you get net score, which is shown by those blue dots that you see there. So AWS has the highest net score and very little churn. I mean, single low single digit churn. But notably, you see Databricks and DataRobot are next in line within Microsoft and Google also, they've got very low churn. Andy, what are your thoughts on this data? >> So a couple of things that stands out to me. Most of them are in line with my conversation with customers. Couple of them stood out to me on how bad IBM Watson is doing. >> Yeah, bring that back up if you would. Let's take a look at that. IBM Watson is the far right and the red, that bright red is churning and again, you want low red here. Why do you think that is? >> Well, so look, IBM has been in the forefront of innovating things for many, many years now, right? And over the course of years we talked about this, they moved from a product innovation centric company into more of a services company. And over the years they were making, as at one point, you know that they were making about majority of that money from services. Now things have changed Arvind has taken over, he came from research. So he's doing a great job of trying to reinvent themselves as a company. But it's going to have a long way to catch up. IBM Watson, if you think about it, that played what, jeopardy and chess years ago, like 15 years ago? >> It was jaw dropping when you first saw it. And then they weren't able to commercialize that. >> Yeah. >> And you're making a good point. When Gerstner took over IBM at the time, John Akers wanted to split the company up. He wanted to have a database company, he wanted to have a storage company. Because that's where the industry trend was, Gerstner said no, he came from AMEX, right? He came from American Express. He said, "No, we're going to have a single throat to choke for the customer." They bought PWC for relatively short money. I think it was $15 billion, completely transformed and I would argue saved IBM. But the trade off was, it sort of took them out of product leadership. And so from Gerstner to Palmisano to Remedi, it was really a services led company. And I think Arvind is really bringing it back to a product company with strong consulting. I mean, that's one of the pillars. And so I think that's, they've got a strong story in data and AI. They just got to sort of bring it together and better. Bring that chart up one more time. I want to, the other point is Oracle, Oracle sort of has the dominant lock-in for mission critical database and they're sort of applying AI there. But to your point, they're really not an AI company in the sense that they're taking unstructured data and doing sort of new things. It's really about how to make Oracle better, right? >> Well, you got to remember, Oracle is about database for the structure data. So in yesterday's world, they were dominant database. But you know, if you are to start storing like videos and texts and audio and other things, and then start doing search of vector search and all that, Oracle is not necessarily the database company of choice. And they're strongest thing being apps and building AI into the apps? They are kind of surviving in that area. But again, I wouldn't name them as an AI company, right? But the other thing that that surprised me in that list, what you showed me is yes, AWS is number one. >> Bring that back up if you would, Ken. >> AWS is number one as you, it should be. But what what actually caught me by surprise is how DataRobot is holding, you know? I mean, look at that. The either net new addition and or expansion, DataRobot seem to be doing equally well, even better than Microsoft and Google. That surprises me. >> DataRobot's, and again, this is a function of spending momentum. So remember from the previous chart that Microsoft and Google, much, much larger than DataRobot. DataRobot more niche. But with spending velocity and has always had strong spending velocity, despite some of the recent challenges, organizational challenges. And then you see these other specialists, H2O.ai, Anaconda, dataiku, little bit of red showing there C3.ai. But these again, to stress are the sort of specialists other than obviously the hyperscalers. These are the specialists in AI. All right, so we hit the bigger names in the sector. Now let's take a look at the emerging technology companies. And one of the gems of the ETR dataset is the emerging technology survey. It's called ETS. They used to just do it like twice a year. It's now run four times a year. I just discovered it kind of mid-2022. And it's exclusively focused on private companies that are potential disruptors, they might be M&A candidates and if they've raised enough money, they could be acquirers of companies as well. So Databricks would be an example. They've made a number of investments in companies. SNEAK would be another good example. Companies that are private, but they're buyers, they hope to go IPO at some point in time. So this chart here, shows the emerging companies in the ML AI sector of the ETR dataset. So the dimensions of this are similar, they're net sentiment on the Y axis and mind share on the X axis. Basically, the ETS study measures awareness on the x axis and intent to do something with, evaluate or implement or not, on that vertical axis. So it's like net score on the vertical where negatives are subtracted from the positives. And again, mind share is vendor awareness. That's the horizontal axis. Now that inserted table shows net sentiment and the ends in the survey, which informs the position of the dots. And you'll notice we're plotting TensorFlow as well. We know that's not a company, but it's there for reference as open source tooling is an option for customers. And ETR sometimes like to show that as a reference point. Now we've also drawn a line for Databricks to show how relatively dominant they've become in the past 10 ETS surveys and sort of mind share going back to late 2018. And you can see a dozen or so other emerging tech vendors. So Andy, I want you to share your thoughts on these players, who were the ones to watch, name some names. We'll bring that data back up as you as you comment. >> So Databricks, as you said, remember we talked about how Oracle is not necessarily the database of the choice, you know? So Databricks is kind of trying to solve some of the issue for AI/ML workloads, right? And the problem is also there is no one company that could solve all of the problems. For example, if you look at the names in here, some of them are database names, some of them are platform names, some of them are like MLOps companies like, DataRobot (indistinct) and others. And some of them are like future based companies like, you know, the Techton and stuff. >> So it's a mix of those sub sectors? >> It's a mix of those companies. >> We'll talk to ETR about that. They'd be interested in your input on how to make this more granular and these sub-sectors. You got Hugging Face in here, >> Which is NLP, yeah. >> Okay. So your take, are these companies going to get acquired? Are they going to go IPO? Are they going to merge? >> Well, most of them going to get acquired. My prediction would be most of them will get acquired because look, at the end of the day, hyperscalers need these capabilities, right? So they're going to either create their own, AWS is very good at doing that. They have done a lot of those things. But the other ones, like for particularly Azure, they're going to look at it and saying that, "You know what, it's going to take time for me to build this. Why don't I just go and buy you?" Right? Or or even the smaller players like Oracle or IBM Cloud, this will exist. They might even take a look at them, right? So at the end of the day, a lot of these companies are going to get acquired or merged with others. >> Yeah. All right, let's wrap with some final thoughts. I'm going to make some comments Andy, and then ask you to dig in here. Look, despite the challenge of leveraging AI, you know, Ken, if you could bring up the next chart. We're not repeating, we're not predicting the AI winter of the 1990s. Machine intelligence. It's a superpower that's going to permeate every aspect of the technology industry. AI and data strategies have to be connected. Leveraging first party data is going to increase AI competitiveness and shorten time to value. Andy, I'd love your thoughts on that. I know you've got some thoughts on governance and AI ethics. You know, we talked about ChatGBT, Deepfakes, help us unpack all these trends. >> So there's so much information packed up there, right? The AI and data strategy, that's very, very, very important. If you don't have a proper data, people don't realize that AI is, your AI is the morals that you built on, it's predominantly based on the data what you have. It's not, AI cannot predict something that's going to happen without knowing what it is. It need to be trained, it need to understand what is it you're talking about. So 99% of the time you got to have a good data for you to train. So this where I mentioned to you, the problem is a lot of these companies can't afford to collect the real world data because it takes too long, it's too expensive. So a lot of these companies are trying to do the synthetic data way. It has its own set of issues because you can't use all... >> What's that synthetic data? Explain that. >> Synthetic data is basically not a real world data, but it's a created or simulated data equal and based on real data. It looks, feels, smells, taste like a real data, but it's not exactly real data, right? This is particularly useful in the financial and healthcare industry for world. So you don't have to, at the end of the day, if you have real data about your and my medical history data, if you redact it, you can still reverse this. It's fairly easy, right? >> Yeah, yeah. >> So by creating a synthetic data, there is no correlation between the real data and the synthetic data. >> So that's part of AI ethics and privacy and, okay. >> So the synthetic data, the issue with that is that when you're trying to commingle that with that, you can't create models based on just on synthetic data because synthetic data, as I said is artificial data. So basically you're creating artificial models, so you got to blend in properly that that blend is the problem. And you know how much of real data, how much of synthetic data you could use. You got to use judgment between efficiency cost and the time duration stuff. So that's one-- >> And risk >> And the risk involved with that. And the secondary issues which we talked about is that when you're creating, okay, you take a business use case, okay, you think about investing things, you build the whole thing out and you're trying to put it out into the market. Most companies that I talk to don't have a proper governance in place. They don't have ethics standards in place. They don't worry about the biases in data, they just go on trying to solve a business case >> It's wild west. >> 'Cause that's what they start. It's a wild west! And then at the end of the day when they are close to some legal litigation action or something or something else happens and that's when the Oh Shit! moments happens, right? And then they come in and say, "You know what, how do I fix this?" The governance, security and all of those things, ethics bias, data bias, de-biasing, none of them can be an afterthought. It got to start with the, from the get-go. So you got to start at the beginning saying that, "You know what, I'm going to do all of those AI programs, but before we get into this, we got to set some framework for doing all these things properly." Right? And then the-- >> Yeah. So let's go back to the key points. I want to bring up the cloud again. Because you got to get cloud right. Getting that right matters in AI to the points that you were making earlier. You can't just be out on an island and hyperscalers, they're going to obviously continue to do well. They get more and more data's going into the cloud and they have the native tools. To your point, in the case of AWS, Microsoft's obviously ubiquitous. Google's got great capabilities here. They've got integrated ecosystems partners that are going to continue to strengthen through the decade. What are your thoughts here? >> So a couple of things. One is the last mile ML or last mile AI that nobody's talking about. So that need to be attended to. There are lot of players in the market that coming up, when I talk about last mile, I'm talking about after you're done with the experimentation of the model, how fast and quickly and efficiently can you get it to production? So that's production being-- >> Compressing that time is going to put dollars in your pocket. >> Exactly. Right. >> So once, >> If you got it right. >> If you get it right, of course. So there are, there are a couple of issues with that. Once you figure out that model is working, that's perfect. People don't realize, the moment you decide that moment when the decision is made, it's like a new car. After you purchase the value decreases on a minute basis. Same thing with the models. Once the model is created, you need to be in production right away because it starts losing it value on a seconds minute basis. So issue number one, how fast can I get it over there? So your deployment, you are inferencing efficiently at the edge locations, your optimization, your security, all of this is at issue. But you know what is more important than that in the last mile? You keep the model up, you continue to work on, again, going back to the car analogy, at one point you got to figure out your car is costing more than to operate. So you got to get a new car, right? And that's the same thing with the models as well. If your model has reached a stage, it is actually a potential risk for your operation. To give you an idea, if Uber has a model, the first time when you get a car from going from point A to B cost you $60. If the model decayed the next time I might give you a $40 rate, I would take it definitely. But it's lost for the company. The business risk associated with operating on a bad model, you should realize it immediately, pull the model out, retrain it, redeploy it. That's is key. >> And that's got to be huge in security model recency and security to the extent that you can get real time is big. I mean you, you see Palo Alto, CrowdStrike, a lot of other security companies are injecting AI. Again, they won't show up in the ETR ML/AI taxonomy per se as a pure play. But ServiceNow is another company that you have have mentioned to me, offline. AI is just getting embedded everywhere. >> Yep. >> And then I'm glad you brought up, kind of real-time inferencing 'cause a lot of the modeling, if we can go back to the last point that we're going to make, a lot of the AI today is modeling done in the cloud. The last point we wanted to make here, I'd love to get your thoughts on this, is real-time AI inferencing for instance at the edge is going to become increasingly important for us. It's going to usher in new economics, new types of silicon, particularly arm-based. We've covered that a lot on "Breaking Analysis", new tooling, new companies and that could disrupt the sort of cloud model if new economics emerge. 'Cause cloud obviously very centralized, they're trying to decentralize it. But over the course of this decade we could see some real disruption there. Andy, give us your final thoughts on that. >> Yes and no. I mean at the end of the day, cloud is kind of centralized now, but a lot of this companies including, AWS is kind of trying to decentralize that by putting their own sub-centers and edge locations. >> Local zones, outposts. >> Yeah, exactly. Particularly the outpost concept. And if it can even become like a micro center and stuff, it won't go to the localized level of, I go to a single IOT level. But again, the cloud extends itself to that level. So if there is an opportunity need for it, the hyperscalers will figure out a way to fit that model. So I wouldn't too much worry about that, about deployment and where to have it and what to do with that. But you know, figure out the right business use case, get the right data, get the ethics and governance place and make sure they get it to production and make sure you pull the model out when it's not operating well. >> Excellent advice. Andy, I got to thank you for coming into the studio today, helping us with this "Breaking Analysis" segment. Outstanding collaboration and insights and input in today's episode. Hope we can do more. >> Thank you. Thanks for having me. I appreciate it. >> You're very welcome. All right. I want to thank Alex Marson who's on production and manages the podcast. Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and our newsletters. And Rob Hoof is our editor-in-chief over at Silicon Angle. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, all you got to do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and silicon angle.com or you can email me at david.vellante@siliconangle.com to get in touch, or DM me at dvellante or comment on our LinkedIn posts. Please check out ETR.AI for the best survey data and the enterprise tech business, Constellation Research. Andy publishes there some awesome information on AI and data. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on "Breaking Analysis". (gentle closing tune plays)

>>Hello, brilliant humans and welcome back to Las Vegas, Nevada, where we are live from the AWS Reinvent Show floor here with the cube. My name is Savannah Peterson, joined with Dave Valante, and we have a very exciting conversation with you. Two, two companies you may have heard of. We've got AWS and Red Hat in the house. Manu and Joel, thank you so much for being here. Love this little fist bump. Started off, that's right. Before we even got rolling, Manu, you said that you wanted this to be the best segment of, of the cubes airing. We we're doing over a hundred segments, so you're gonna have to bring the heat. >>We're ready. We're did go. Are we ready? Yeah, go. We're ready. Let's bring it on. >>We're ready. All right. I'm, I'm ready. Dave's ready. Let's do it. How's the show going for you guys real quick before we dig in? >>Yeah, I think after Covid, it's really nice to see that we're back into the 2019 level and, you know, people just want to get out, meet people, have that human touch with each other, and I think a lot of trust gets built as a functional that, so it's super amazing to see our partners and customers here at Reedman. Yeah, >>And you've got a few in the house. That's true. Just a few maybe, maybe a couple >>Very few shows can say that, by the way. Yeah, it's maybe a handful. >>I think one of the things we were saying, it's almost like the entire Silicon Valley descended in the expo hall area, so >>Yeah, it's >>For a few different reasons. There's a few different silicon defined. Yeah, yeah, yeah. Don't have strong on for you. So far >>It's, it's, it is amazing. It's the 10th year, right? It's decade, I think I've been to five and it's, it grows every single year. It's the, you have to be here. It's as simple as that. And customers from every single industry are here too. You don't get, a lot of shows have every single industry and almost every single location around the globe. So it's, it's a must, must be >>Here. Well, and the personas evolved, right? I was at reinvent number two. That was my first, and it was all developers, not all, but a lot of developers. And today it's a business mix, really is >>Totally, is a business mix. And I just, I've talked about it a little bit down the show, but the diversity on the show floor, it's the first time I've had to wait in line for the ladies' room at a tech conference. Almost a two decade career. It is, yeah. And it was really refreshing. I'm so impressed. So clearly there's a commitment to community, but also a commitment to diversity. Yeah. And, and it's brilliant to see on the show floor. This is a partnership that is robust and has been around for a little while. Money. Why don't you tell us a little bit about the partnership here? >>Yes. So Red Hand and AWS are best friends, you know, forever together. >>Aw, no wonder we got the fist bumps and all the good vibes coming out. I know, it's great. I love that >>We have a decade of working together. I think the relationship in the first phase was around running rail bundled with E two. Sure. We have about 70,000 customers that are running rail, which are running mission critical workloads such as sap, Oracle databases, bespoke applications across the state of verticals. Now, as more and more enterprise customers are finally, you know, endorsing and adopting public cloud, I think that business is just gonna continue to grow. So a, a lot of progress there. The second titration has been around, you know, developers tearing Red Hat and aws, Hey, listen, we wanna, it's getting competitive. We wanna deliver new features faster, quicker, we want scale and we want resilience. So just entire push towards devs containers. So that's the second chapter with, you know, red Hat OpenShift on aws, which launched as a, a joint manage service in 2021 last year. And I think the third phase, which you're super excited about, is just bringing the ease of consumption, one click deployment, and then having our customers, you know, benefit from the joint committed spend programs together. So, you know, making sure that re and Ansible and JBoss, the entire portfolio of Red Hat products are available on AWS marketplace. So that's the 1, 2, 3, it of our relationship. It's a decade of working together and, you know, best friends are super committed to making sure our customers and partners continue successful. >>Yeah, that he said it, he said it perfectly. 2008, I know you don't like that, but we started with Rel on demand just in 2008 before E two even had a console. So the partnership has been there, like Manu says, for a long time, we got the partnership, we got the products up there now, and we just gotta finalize that, go to market and get that gas on the fire. >>Yeah. So Graviton Outpost, local zones, you lead it into all the new stuff. So that portends, I mean, 2008, we're talking two years after the launch of s3. >>That's right. >>Right. So, and now look, so is this a harbinger of things to come with these new innovations? >>Yeah, I, I would say, you know, the innovation is a key tenant of our partnership, our relationship. So if you look at from a product standpoint, red Hat or Rel was one of the first platforms that made a support for graviton, which is basically 40% better price performance than any other distribution. Then that translated into making sure that Rel is available on all of our regions globally. So this year we launched Switzerland, Spain, India, and Red Hat was available on launch there, support for Nitro support for Outpost Rosa support on Outpost as well. So I think that relationship, that innovation on the product side, that's pretty visible. I think that innovation again then translates into what we are doing on marketplace with one click deployments we spoke about. I think the third aspect of the know innovation is around making sure that we are making our partners and our customers successful. So one of the things that we've done so far is Joe leads a, you know, a black belt team that really goes into each customer opportunity, making sure how can we help you be successful. We launched and you know, we should be able to share that on a link. After this, we launched like a big playlist, which talks about every single use case on how do you get successful and running OpenShift on aws. So that innovation on behalf of our customers partners to make them successful, that's been a key tenant for us together as >>Well. That's right. And that team that Manu is talking about, we're gonna, gonna 10 x that team this year going into January. Our fiscal yield starts in January. Love that. So yeah, we're gonna have a lot of no hiring freeze over here. Nope. No ma'am. No. Yeah, that's right. Yeah. And you know what I love about working with aws and, and, and Manu just said it very, all of that's customer driven. Every single event that we, that he just talked about in that timeline, it's customer driven, right? Customers wanted rail on demand, customers want JBoss up in the cloud, Ansible this week, you know, everything's up there now. So it's just getting that go to market tight and we're gonna, we're gonna get that done. >>So what's the algorithm for customer driven in terms of taking the input? Because if every customers saying, Hey, I this a >>Really similar >>Question right up, right? I, that's what I want. And if you know, 95% of the customers say it, Jay, maybe that's a good idea. >>Yeah, that's right. Trends. But >>Yeah. You know, 30% you might be like, mm, you know, 20%, you know, how do you guys decide when to put gas on the fire? >>No, that, I think, as I mentioned, there are about 70,000 large customers that are running rail on Easy Two, many of these customers are informing our product strategy. So we have, you know, close to about couple of thousand power users. We have customer advisory booths, and these are the, you know, customers are informing us, Hey, let's get all of the Red Hat portfolio and marketplace support for graviton, support for Outpost. Why don't we, why are we not able to dip into the consumption committed spend programs for both Red Hat and aws? That's right. So it's these power users both at the developer level as well as the guys who are actually doing large commercial consumption. They are the ones who are informing the roadmap for both Red Hat and aws. >>But do, do you codify the the feedback? >>Yeah, I'm like, I wanna see the database, >>The, I think it was, I don't know, it was maybe Chasy, maybe it was Besos, that that data beats intuition. So do you take that information and somehow, I mean, it's global, 70,000 customers, right? And they have different weights, different spending patterns, different levels of maturity. Yeah. Do you, how do you codify that and then ultimately make the decision? Yeah, I >>If, I mean, well you, you've got the strategic advisory boards, which are made up of customers and partners and you know, you get, you get a good, you gotta get a good slice of your customer base to get, and you gotta take their feedback and you gotta do something with it, right? That's the, that's the way we do it and codify it at the product level, I'm sure open source. That's, that's basically how we work at the product level, right? The most elegant solution in open source wins. And that's, that's pretty much how we do that at the, >>I would just add, I think it's also just the implicit trust that the two companies had built with each other, working in the trenches, making our customers and partners successful over the last decade. And Alex, give an example. So that manifests itself in context of like, you know, Amazon and Red Hat just published the entire roadmap for OpenShift. What are the new features that are becoming over the next six to nine to 12 months? It's open source available on GitHub. Customers can see, and then they can basically come back and give feedback like, Hey, you know, we want hip compliance. We just launched. That was a big request that was coming from our >>Customers. That is not any process >>Also for Graviton or Nvidia instances. So I I I think it's a, >>Here's the thing, the reason I'm pounding on this is because you guys have a pretty high hit rate, and I think as a >>Customer, mildly successful company >>As, as a customer advocate, the better, you know, if, if you guys make bets that pay off, it's gonna pay off for customers. Right. And because there's a lot of failures in it. Yeah. I mean, let's face it. That's >>Right. And I think, I think you said the key word bets. You place a lot of small bets. Do you have the, the innovation engine to do that? AWS is the perfect place to place those small bets. And then you, you know, pour gas on the fire when, when they take off. >>Yeah, it's a good point. I mean, it's not expensive to experiment. Yeah. >>Especially in the managed service world. Right? >>And I know you love taking things to market and you're a go to market guy. Let's talk gtm, what's got your snow pumped about GTM for 2023? >>We, we are gonna, you know, 10 x the teams that's gonna be focused on these products, right? So we're gonna also come out with a hybrid committed spend program for our customers that meet them where they want to go. So they're coming outta the data center going into a cloud. We're gonna have a nice financial model for them to do that. And that's gonna take a lot of the friction out. >>Yeah. I mean, you've nailed it. I, I think the, the fact that now entire Red Hat portfolio is available on marketplace, you can do it on one click deployment. It's deeply integrated with Amazon services and the most important part that Joel was making now customers can double dip. They can drive benefit from the consumption committed spend programs, both from Red Hat and from aws, which is amazing. Which is a game changer That's right. For many of our large >>Customers. That's right. And that, so we're gonna, we're gonna really go to town on that next year. That's, and all the, all the resources that I have, which are the technology sellers and the sas, you know, the engineers we're growing this team the most out that team. So it's, >>When you say 10 x, how many are you at now? I'm >>Curious to see where you're headed. Tell you, okay. There's not right? Oh no, there's not one. It's triple digit. Yeah, yeah. >>Today. Oh, sweet. Awesome. >>So, and it's a very sizable team. They're actually making sure that each of our customers are successful and then really making sure that, you know, no customer left behind policy. >>And it's a great point that customers love when Amazonians and Red Hats show up, they love it and it's, they want to get more of it, and we're gonna, we're gonna give it to 'em. >>Must feel great to be loved like that. >>Yeah, that's right. Yeah. Yeah. I would say yes. >>Seems like it's safe to say that there's another decade of partnership between your two companies. >>Hope so. That's right. That's the plan. >>Yeah. And I would say also, you know, just the IBM coming into the mix here. Yeah. I, you know, red Hat has informed the way we have turned around our partnership with ibm, essentially we, we signed the strategic collaboration agreement with the company. All of IBM software now runs on Rosa. So that is now also providing a lot of tailwinds both to our rail customers and as well as Rosa customers. And I think it's a very net creative, very positive for our partnership. >>That's right. It's been very positive. Yep. Yeah. >>You see the >>Billboards positive. Yeah, right. Also that, that's great. Great point, Dave. Yep. We have a, we have a new challenge, a new tradition on the cube here at Reinvent where we're, well, it's actually kind of a glamor moment for you, depending on how you leverage it. We're looking for your 32nd hot take your Instagram reel, your sizzle thought leadership, biggest takeaway, most important theme from this year's show. I know you want, right, Joel? I mean, you TM boy, I feel like you can spit the time. >>Yeah. It is all about Rosa for us. It is all in on that, that's the native OpenShift offering on aws and that's, that's the soundbite we're going go to town with. Now, I don't wanna forget all the other products that are in there, but Rosa is a, is a very key push for us this year. >>Fantastic. All right. Manu. >>I think our customers, it's getting super competitive. Our customers want to innovate just a >>Little bit. >>The enterprise customers see the cloud native companies. I wanna do what these guys are doing. I wanna develop features at a fast clip. I wanna scale, I wanna be resilient. And I think that's really the spirit that's coming out. So to Joel's point, you know, move to worlds containers, serverless, DevOps, which was like, you know, aha, something that's happening on the side of an enterprise is not becoming mainstream. The business is demanding it. The, it is becoming the centerpiece in the business strategy. So that's been really like the aha. Big thing that's happening here. >>Yeah. And those architectures are coming together, aren't they? That's correct. Right. You know, VMs and containers, it used to be one architecture and then at the other end of the spectrum is serverless. People thought of those as different things and now it's a single architecture and, and it's kind of right approach for the right job. >>And, and a compliments say to Red Hat, they do an incredible job of hiding that complexity. Yeah. Yes. And making sure that, you know, for example, just like, make it easier for the developers to create value and then, and you know, >>Yeah, that's right. Those, they were previously siloed architectures and >>That's right. OpenShift wanna be place where you wanna run containers or virtual machines. We want that to be this Yeah. Single place. Not, not go bolt on another piece of architecture to just do one or the other. Yeah. >>And hey, the hybrid cloud vision is working for ibm. No question. You know, and it's achievable. Yeah. I mean, I just, I've said unlike, you know, some of the previous, you know, visions on fixing the world with ai, hybrid cloud is actually a real problem that you're attacking and it's showing the results. Agreed. Oh yeah. >>Great. Alright. Last question for you guys. Cause it might be kind of fun, 10 years from now, oh, we're at another, we're sitting here, we all look the same. Time has passed, but we are not aging, which is a part of the new technology that's come out in skincare. That's my, I'm just throwing that out there. Why not? What do you guys hope that you can say about the partnership and, and your continued commitment to community? >>Oh, that's a good question. You go first this time. Yeah. >>I think, you know, the, you know, for looking into the future, you need to look into the past. And Amazon has always been driven by working back from our customers. That's like our key tenant, principle number 1 0 1. >>Couple people have said that on this stage this week. Yeah. >>Yeah. And I think our partnership, I hope over the next decade continues to keep that tenant as a centerpiece. And then whatever comes out of that, I think we, we are gonna be, you know, working through that. >>Yeah. I, I would say this, I think you said that, well, the customer innovation is gonna lead us to wherever that is. And it's, it's, it's gonna be in the cloud for sure. I think we can say that in 10 years. But yeah, anything from, from AI to the quant quantum computing that IBM's really pushing behind that, you know, those are, those are gonna be things that hopefully we show up on a, on a partnership with Manu in 10 years, maybe sooner. >>Well, whatever happens next, we'll certainly be covering it here on the cube. That's right. Thank you both for being here. Joel Manu, fantastic interview. Thanks to see you guys. Yeah, good to see you brought the energy. I think you're definitely ranking high on the top interviews. We >>Love that for >>The day. >>Thank >>My pleasure >>Job, guys. Now that you're competitive at all, and thank you all for tuning in to our live coverage here from AWS Reinvent in Las Vegas, Nevada, with Dave Valante. I'm Savannah Peterson. You're watching The Cube, the leading source for high tech coverage.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Cube's coverage. We're wrapping up day two, John furrier and Dave ante. We got some friends and colleagues, longtime friends, Crawford Del Pret is the president of IDC. Matt Eastwood is the senior vice president of infrastructure and cloud guys. Thanks for coming on spending time. Great to you guys. >>That's fun to do it. Awesome. >>Cravin I want to ask you, I, I think this correct me if I'm wrong, but this was your first physical directions as, as president. Is that true or did you do one in 2019? >>Uh, no, we did one in 20. We did, we did one in 20. I was president at the time and then, and then everything started, >>Well, how was directions this year? You must have been stoked to get back together. Yeah, >>It was great. I mean, it was actually pretty emotional, you know, it's, it's a community, right? I mean, we have a lot of customers that have been coming to that event for a long, long time and to stand up on the stage and look out and see people, you know, getting a little bit emotional and a lot of hugs and a lot of bringing people together. And this year in Boston, we were the first event really of any size that kind of came back. And when I kind of didn't see that coming in terms of how people, how ready people were to be together. Cause >>When did you did it April >>In Boston? Yeah, we did it March in March. Yeah, it was, it was, it was, it was a game day decision. I mean, we were, we had negotiated it, we were going back and forth and then I kind of made the call at the last minute, say, let's go and do it. And in Santa Clara, I felt like we were kind of opening up the crypt at the convention center. I mean, all the production people said, you know what? You guys were really the first event to be back. And attendance was really strong. You know, we, we, we got over a thousand. It was, it was really good. >>Good. It's always a fun when I was there. It was, it's a big deal. You guys prepare for it. Yeah. Some new faces up on the stage. Yeah. So, so Matt, um, you've been doing the circuit. I take it like, like all top analysts, super busy. Right. This is kind of end of the spring. I mean, I know it's summer, right. That's right. But, um, how do you look at, at discover relative some, some of the other events you've been at? >>So I think if you go back to what Crawford was just talking about our event in March, I mean, March was sort of the, the reopening and there was, I think people just felt so happy to be, to be back out there. You still get a little bit at, at these events. I mean, cuz for each, each company it's their first time back at it, but I think we're starting to get down what these events are gonna feel like going forward. Um, and it, I mean, there's good energy here. There's been a good attendance. I think the, the interest in getting back live and having face to face meetings is clearly strong. >>Yeah. I mean, this definitely shows that hybrids, the steady state, both events cloud. Yeah. Virtualization remotes. So what are you guys seeing with that hybrid mode? Just from a workforce, certainly people excited to get back together, but it's gonna continue. You're starting to see that digital piece. How is that impacting some of the, some of the customers you're tracking, who's winning and who's losing, coming out of the pandemic. What's the big picture look like? >>Yeah. I mean, if you, if you take a look at hybrid work, um, people are testing many, many, many different models. And I think as we move from a pandemic to an em, we're gonna have just waves and waves and waves of people needing that flexibility for a lot of different reasons, whether they have, uh, you know, preexisting conditions, whether they're just not comfortable, whether they have people who can't be vaccinated at home. So I think we're gonna be in this hybrid work for a long, long time. I do think though that we are gonna transition back into some kind of a normal, um, and I, and I think the big difference is that I think leaders back in the day, a long time ago, when people weren't coming into work, it was kind of like, oh, I know nothing's going on there. People aren't getting worked. And I think we're over that stage. Yeah. I think we're now into a stage where we know people can be productive. We know people can effectively work from home and now we're into the reason to be in the office. And the reason to be in the office is that collaboration, it's that mentoring it's that, you know, think about your 25 year old self. Do you wanna be staring at a windshield all day long and not kind of building those relationships? People want face to face, it's difficult. They want face >>To face and I would, and you guys had a great culture and it's a young culture. How are you handling it as an executive in terms of, is there a policy for hybrid or >>Yeah, so, so, so at IDC, what we did is we're in a pilot period and we've kind of said that the summertime is gonna be a pilot period and we've asked people, we're actually serving shocker, we're >>Serving, >>But we're, but we're, but, but we're actually asking people to work with their manager on what works for them. And then we'll come up with, you know, whether you are in, out of the office worker, which will be less than two days a hybrid worker, which will be three days or, uh, in, in the office, which is more than three days a week. And you know, we all know there's, there's, there's limitation, there's, there's, there's variability in that, but that's kind of what we're shooting for. And we'd like to be able to have that in place in the fall. >>Are you pretty much there? >>Yeah, I am. I, I am there three days a week. I I, Mondays and Fridays, unless, >>Because you got the CEO radius, right? Yeah. >><laugh>, <laugh> >>The same way I'm in the office, the smaller, smaller office. But so, uh, let's talk a little bit about the, the numbers we were chatting earlier, trying to squint through you guys are, you know, obviously the gold standard for what the market does, what happened in, you know, during the pandemic, what happened in 2021 and what do you expect to happen in, in 2022 in terms of it spending growth? >>Yeah. So this is, this is a crazy time, right? We've never seen this. You and I have a long history of, uh, of tracking this. So we saw in, in, in, in 2020, the market decelerated dramatically, um, the GDP went down to a negative like it always does in these cases, it was, you know, probably negative six in that, in that, in that kind of range for the first time, since I've been tracking it, which goes back over 30 years, tech didn't go negative tech went to about just under 3%. And then as we went to 2021, we saw, you know, everything kind of snap back, we saw tech go up to about 11% growth. And then of course we saw, you know, GDP come back to about a 4%, you know, ki kind of range growth. Now what's I think the story there is that companies and you saw this anecdotally everywhere companies leaned into tech, uh, company. >>You know, I think, you know, Matt, you have a great statistic that, you know, 80% of companies used COVID as their point to pivot into digital transformation, right. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers now. So this year what's fascinating is we're looking at two Fastly different markets. We've got gasoline at $7 a gallon. We've got that affecting food prices. Uh, interesting fun fact recently it now costs over $1,000 to fill an 18 Wheeler. All right. Based on, I mean this just kind of can't continue. So you think about it, don't put the boat >>In the wall. Yeah. Yeah. >>Good, good, good, good luck. It's good. Yeah, exactly. <laugh> so a family has kind of this bag of money, right? And that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more gadgets and consumer tech are not, you know, you're gonna use that iPhone a little longer. You're gonna use that Android phone a little longer. You're gonna use that TV a little longer. So consumer tech is getting crushed, you know, really it's very, very, and you saw it immediately and ad spending, you've seen it in meta. You've seen it in Facebook. Consumer tech is doing very, very it's tough enterprise tech. We haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be, uh, servers, whether that be, uh, commercial PCs, as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. Um, we have combined that with a component shortage and you're seeing some enterprise companies with a quarter of backlog. I mean, that's, you know, really unheard at higher >>Prices, which >>Also, and therefore that drives that >>Drives. It shouldn't be that way. If there's a shortage of chips, it shouldn't be that way, >>But it is, but it is, but it is. And then you look at software and we saw this, you know, we've seen this in previous cycles, but we really saw it in the COVID downturn where, uh, in software, the stickiness of SaaS means that you just, you're not gonna take that stuff out. So the, the second half of last year we saw double digit rates in software surprise. We're seeing high single digit revenue growth in software now, so that we think is gonna sustain, which means that overall it demand. We expect to be between five and 6% this year. Okay, fine. We have a war going on. We have, you know, potentially, uh, a recession. We think if we do, it'll be with a lower case, R maybe you see a banded down to maybe 4% growth, but it's gonna grow this. >>Is it, is it both the structural change of the disruption of COVID plus the digital transformation yeah. Together? Or is it, >>I, I think you make a great point. Um, I, I, I think that we are entering a new era for tech. I think that, you know, Andrew's famous wall street journal oped 10 years ago, software is even world was absolutely correct. And now we're finding that software is, is eing into every nook and cranny people have to invest. They, they know disruptors are coming around every single corner. And if I'm not leaning into digital transformation, I'm dead. So >>The number of players in tech is, is growing, >>Cuz there's well, the number of players in tech number >>Industry's coming >>In. Yeah. The industry's coming in. So I think the interesting dynamic you're gonna see there is now we have high interest rates. Yeah. Which means that the price of funding these companies and buying them and putting data on is gonna get higher and higher, which means that I think you could, you could see another wave of consolidation. Mm-hmm <affirmative> because tech large install based tech companies are saying, oh, you know what? I like that now >>4 0 9 S are being reset too. That's another point. >>Yeah. I mean, so if you think about this, this transformation, right. So it's all about apps, absent data and differentiating and absent data. What the, the big winner the last couple years was cloud. And I would just say that if this is the first potential recession that we're talking about, where the cloud service providers. So I think a cloud as an operating model, not necessarily a destination, but for these cloud service providers, they've actually never experienced a slowdown. So how, and, and if you think about the numbers, 30% of, of the typical it budget is now quote, unquote cloud and 30% of all expenditures are it related. So there's a lot of exposure there. And I think you're gonna see a lot of, a lot of focus on how we can rationalize some of those investments. >>Well, that's a great point. I want to just double click on that. So yeah, the cloud did well during the pandemic. We saw that with SAS, have you guys tracked like the Tams of what got pulled forward? So the bit, a big discussion about something that pulled forward because of the pandemic, um, like zoom, for instance, obviously everyone's using zoom. Yeah, yeah, yeah. Was there fake Tams? There was one, uh, couple analysts who were pointing out that some companies were hot during the pandemic will go away that that Tam doesn't really exist, but there's some that got pulled forward early. That's where the growth is. So is there a, is there a line between the, I call fake Tam or pulled forward TA that was only for the pandemic situationally, um, devices might be like virtual event, virtual event. Software was one, I know Hoppin got laid a lot of layoffs. And so that was kind of gone coming, coming and going. And you got SAS which got pulled forward. Yep. And it's not going away, but it's >>Sustaining. Yeah. Yeah. But it's, but, but it's sustaining, um, you know, I definitely think there was a, there was a lot of spending that absolutely got pulled forward. And I think it's really about CEO's ability to control expectations and to kind of message what it, what it looks like. Um, you know, I think I look, I, I, I think virtual event platforms probably have a role. I think you can, you can definitely, you know, raise your margins in the event, business, significantly using those platforms. There's a role for them. But if you were out there thinking that this thing was gonna continue, then you know, that that was unrealistic, you know, Dave, to, to your point on devices, I'm not necessarily, you know. Sure. I think, I think we definitely got ahead of our expectations and things like consumer PCs, those things will go back to historical growth >>Rates. Yeah. I mean, you got the install base is pretty young right now, but I think the one way to look at it too, is there was some technical debt brought in because people didn't necessarily expect that we'd be moving to a permanent hybrid state two years ago. So now we have to actually invest on both. We have to make, create a little bit more permanency around the hybrid world. And then also like Crawford's talking about the permanency of, of having an office and having people work in, in multiple modes. Yeah. It actually requires investment in both the office. And >>Also, so you're saying operationally, you gotta run the company and do the digital transformation to level up the hybrid. >>Yeah. Yeah. Just the way people work. Right. So, so, you know, you basically have to, I mean, even for like us internally, Crawford was saying, we're experimenting with what works for us. My team before the pandemic was like one third virtual. Now it's two third virtual, which means that all of our internal meetings are gonna be on, on teams or zoom. Right. Yeah. They're not gonna necessarily be, Hey, just coming to the office today, cuz two thirds of people aren't in the Boston area. >>Right. Matt, you said if you see cloud as an operating model, not necessarily a place. I remember when you were out, I was in the, on the, on the, on the zoom when, when first met Adam Celski yeah. Um, he said, you were asking him about, you know, the, the on-prem guys and he's like, nah, it's not cloud. And he kind of was very dismissive of it. Yeah. Yeah. I wanna get your take on, you know, what we're seeing with as Azure service GreenLake, apex, Cisco's got their version. IBM. Fewer is doing it. Is that cloud. >>I think if it's, I, I don't think all of it is by default. I think it is. If I actually think what HPE is doing is cloud, because it's really about how you present the services and how you allow customers to engage with the platform. So they're actually creating a cloud model. I think a lot of people get lost in the transition from, you know, CapEx to OPEX and the financing element of this. But the reality is what HPE is doing and they're sort of setting the standard. I think for the industry here is actually setting up what I would consider a cloud model. >>Well, in the early days of, of GreenLake, for sure it was more of a financial, you >>Know, it was kind of bespoke, right. But now you've got 70 services. And so you can, you can build that out. But >>You know, we were talking to Keith Townsend right after the keynote and we were sort of UN unpacking it a little bit. And I, I asked the question, you know, if you, if you had to pin this in terms of AWS's maturity, where are we? And the consensus was 2014 console filling, is that fair or unfair? >>Oh, that's a good question. I mean, um, I think it's, well, clouds come a long way, right? So it'd be, I, I, I think 20, fourteen's probably a little bit too far back because >>You have more modern tools I Kubernetes is. Yeah. >>And, but you also have, I would say the market still getting to a point of, of, of readiness and in terms of buying this way. So if you think about the HP's kind of strategy around edge, the core platform as a, as a service, you know, we're all big believers in edge and the apps follow the data and the data's being created in new locations and you gotta put the infrastructure there. And for an end user, there's a lot of risk there because they don't know how to actually plan for capacity at the edge. So they're gonna look to offload that, but this is a long term play to actually, uh, build out and deploy at the edge. It's not gonna happen tomorrow. It's a five, 10 year play. >>Yeah. I mean, I like the operating model. I'd agree with you, Matt, that if it's, if it's cloud operations, DevSecOps and all that, all that jazz it's cloud it's cloud operating and, and, and public cloud is a public cloud hyperscaler on premise. And the storage folks were presented. That's a single pane of glass. That's old school concepts, but cloud based. Yep. Shipping hardwares, auto figures. Yeah. That's the kind of consumption they're going for now. I like it. Then I, then they got the partner led thing is the partner piece. How do you guys see that? Because if I'm a partner, there's two things, wait a minute, am I at bottleneck to the direct self-service? Or is that an enabler to get more cash, to make more money? If I'm a partner. Cause you see what Essentia's doing with what they do with Amazon and Deloitte and et C. Yeah. You know, it's interesting, right? Like they've a channel partner, I'm making more cash. >>Yeah. I mean, well, and those channel partners are all in transition too. They're trying to yeah. Right. Figure out. Right, right. Are they, you know, what are their managed services gonna look like? You know, what kind of applications are they gonna stand up? They're they're not gonna just be >>Reselling, bought a big house in a boat. The box is not selling. I wanna ask you guys about growth because you know, the big three cloud, big four growing pick a number, I dunno, 30, 35% revenue big. And like you said, it's 30% of the business now. I think Dell's growing double digits. I don't know how much of that is sustainable. A lot of that is PCs, but still strong growth. Yep. I think Cisco has promised 9% >>In, in that. Right, right. >>About that. Something like that. I think IBM Arvin is at 6%. Yep. And I think HPE has said, Hey, we're gonna do three to 4%. Right. Which is so really sort of lagging and which I think a lot of people in wall street is like, okay, well that's not necessarily so compelling. Right. What does HPE have to do to double that growth? Or even triple that growth. >>Yeah. So they're gonna need, so, so obviously you're right. I mean, being able to show growth is Tanem out to this company getting, you know, more attention, more heat from, from investors. I think that they're rightly pointing to the triple digit growth that they've seen on green lake. I think if you look at the trailing, you know, 12 month bookings, you got over, you know, 7 billion, which means that in a year, you're gonna have a significant portion of the company is as a service. And you're gonna see that revenue that's rat being, you know, recognized over a series of months. So I think that this is sort of the classic SAS trough that we've seen applied to an infrastructure company where you're basically have to kind of be in the desert for a long time. But if they can, I think the most important number for HPE right now is that GreenLake booking snow. >>And if you look at that number and you see that number, you know, rapidly come down, which it hasn't, I mean off a very large number, you're still in triple digits. They will ultimately start to show revenue growth, um, in the business. And I think the one thing people are missing about HPE is there aren't, there are a lot of companies that want to build a platform, but they're small and nobody cares. And nobody let's say they throw a party and nobody comes. HP has such a significant installed base that if they do build a platform, they can attract partners to that platform. What I mean by that is partners that deliver services on GreenLake that they're not delivering. They have the girth to really start to change an industry and change the way stuff is being built. And that's the be they're making. And frankly, they are showing progress in that direction. >>So I buy that. But the one thing that concerns me is they kind of hide the ball on services. Right. And I, and I worry about that is like, is this a services kind of just, you know, same wine, new bottle or, >>Or, yeah. So, so I, I, I would argue that it's not about hiding the ball. It's about eliminating confusion of the marketplace. This is the company that bought EDS only to spin it off <laugh>. Okay. And so you don't wanna have a situation where you're getting back into services. >>Yeah. They're the only one >>They're product, not the only ones who does, I mean, look at the way IBM used to count and still >>I get it. I get it. But I think it's, it's really about clarity of mission. Well, I point next they are in the Ts business, absolutely. Point of it. It's important prop >>Drive for them at the top. Right. The global 50 say there's still a lot of uniqueness in what they want to buy. So there's definitely a lot of bespoke kind of delivery. That's still happening there. The real promise here is when you get into the global 2000 and yeah. And can start them to getting them to consume very standardized offers. And then the margins are, are healthy >>And they got they're what? Below 30, 33, 30 3%. I think 34% last quarter gross margin. Yeah. That that's solid. Just compare that with Dell is, I don't know. They're happy with 20, 21% of correct. You get that, which is, you know, I I'll come back. Go ahead. I want, I wanna ask >>Guys. No, I wanna, I wanna just, he said one thing I like, which was, I think he nailed it. They have such, um, big install base. They have a great channel. They know how to use it. Right. That's a real asset. Yeah. And Microsoft, I remember when their stock was trading at 26 when Baltimore was CEO. Yep. What they did with no, they had office and windows, so a little bit different. Yep. But similar strategy, leverage our install base, bring something up to them. That's what you're kind of connecting the >>Absolutely. You have this velocity, uh, machine with a significant girth that you can now move to a new model. They move that to a new model. To Matt's point. They lead the industry, they change the way large swath the customers buy and you will see it in steady revenue growth over time. Okay. So I just in that, well, >>So your point is the focus and there the right it's the right focus. And I would agree what's >>What's the other move. What's their other move, >>The problem. Triple digit booking growth off a number that gets bigger >>Inspired. Okay. >>Whats what's the scoreboard. Okay. Now they're go at the growth. That's the scoreboard. What are the signals? Are you looking at on the scoreboard Crawford and Matt in terms of success? What are the benchmarks? Is it ecosystem growth, number of services, triple growth. Yeah. What's the, what are some of the metrics that you guys are gonna be watching and we should be watching? >>Yeah. I mean, I dunno if >>You wanna jump in, I mean, I think ecosystem's really critical. Yeah. You want to, you want to have well and, and you need to sell both ways like HPE needs to be selling their technology on other cloud providers and vice versa. You need to have the VMs of the world on, you know, offering services on your platform and, and kind of capturing some, some motion off that. I think that's pretty critical. The channel definitely. I mean, you have to help and what you're gonna see happen there is there will be channel partners that succeed in transforming and succeeding and there'll be a lot that go away and that some, some of that's, uh, generational there'll be people that just kind of age outta the system and, and just go home. >>Yeah. Yeah. So I would argue it's, it's, it's, it's gonna be, uh, bookings growth rate. It's gonna be retention rate of the, of, of, of the customers, uh, that they have. And then it's gonna be that, that, um, you know, ultimately you're gonna see revenue, um, growth, and which is that revenue growth is gonna have to be correlated to the booking's growth for green lake cross. >>What's the Achilles heel on, on HPE. If you had to do the SWAT, what's the, what's the w for HPE that they really need to pay >>Attention to. I mean, they, they need to continue their relentless focus on cost, particularly in the, in the core compute, you know, segment they need to be, they need to be able to be as cost effective as possible while the higher profit dollars associated with GreenLake and other services come in and then increase the overall operating margin and gross margin >>Picture for the, I mean, I think the biggest thing is they just have, they have to continue the motion that they've been on. Right. And they've been consistent about that. Mm-hmm, <affirmative> what you see where others have, have kind of slipped up is when you go to, to customers and you present the, the OPEX as a service and the traditional CapEx side by side, and the customers put in this position of trying to detangle what's in that OPEX service, you don't wanna do that obviously. And, and HP has not done that, but we've seen others kind of slip up. And, but >>A lot of companies still wanna buy CapEx. Right. Absolutely liquid. And, and I think, >>But you shouldn't do a, you shouldn't do that bake off by putting those two offers out. You should basically ascertain what they want to do. >>What's kind of what Dell does. Right. Hey, how, what do you want? We got this, we got >>This on one hand, we got this, the, we got that, right. Uh, the two hand sales rep, no, this CapEx. Thing's interesting. And if you're Amazon and Azure and, and GCP, what are they thinking right now? Cause remember what, four years ago outpost was launched, which essentially hardware. Yeah. This is cloud operating model. Yep. Yeah. They're essentially bringing outpost. This is what they got basically is Amazon and Azure, like, is this ABL on the radar for them? How would you, what, what are they thinking in your mind if we're on, if we're in their office, in their brain trust, are they laughing? Are they like saying, oh, they're scared. Is this real threat >>Opportunity? I, I, I mean, I wouldn't say they're laughing at all. I, I would say they're probably discounting a little bit and saying, okay, fine. You know, that's a strategy that a traditional hardware company is moving to. But I think if you look underneath the covers, you know, two years ago it was, you know, pretty basic stuff they were offering. But now when you start getting into some, you know, HPC is a service, you start getting into data fabric, you start getting into some of the more, um, sophisticated services that they're offering. And, and I think what's interesting about HP. What my, my take is that they're not gonna go after the 250 services the Amazon's offering, they're gonna basically have a portfolio of services that really focus on the core use cases of their infrastructure set. And, and I think one of the danger things, one, one of the, one of the red flags would be, if they start going way up the stack and wanting to offer the entire application stack, that would be like a big flashing warning sign, cuz it's not their sweet spot. It's not, not what they have. >>So machine learning, machine learning and quantum, okay. One you can argue might be up the stack machine learning quantum should be in their wheelhouse. >>I would argue machine learning is not up the stack because what they would focus on is inference. They'd focus on learning. If they came out and said, machine learning all the way up to the, you know, what a, what, what a drug discovery company needs to do. >>So they're bringing it down. >>Yeah. Yeah. Well, no, I think they're focusing on that middle layer, right? That, that, that data layer. And I think that helping companies manage their data make more sense outta their data structure, their data that's core to what they wanna do. >>I, I feel as though what they're doing now is table stakes. Honestly, I do. I do feel like, okay, Hey finally, you know, I say the same thing about apex, you >>Know, we finally got, >>It's like, okay guys, the >>Party. Great. Welcome to the, >>But the one thing I would just say about, about AWS and the other big clouds is whether they might be a little dismissive of what's truly gonna happen at the edge. I think the traditional OEMs that are transforming are really betting on that edge, being a huge play and a huge differentiator for them where the public cloud obviously have their own bets there. But I think they were pretty dismissive initially about how big that went. >>I don't, and I don't think anybody's really figured out the edge yet. >>Well, that's an, it's a battleground. That's what he's saying. I think you're >>Saying, but on the ecosystem, I wanna say up the stack, I think it's the ecosystem. That's gotta fill that out. You gotta see more governance tools and catalogs and AI tools and, and >>It immediately goes more, it goes more vertical when you go edge, you're gonna have different conversations and >>They're >>Lacking. Yeah. And they, but they're in there though. They're in the verticals. HP's in the, yeah, >>For sure. But they gotta build out an ego. Like you walk around here, the data, the number of data companies here. I mean, Starburst is here. I'm actually impressed that Starburst is here. Cause I think they're a forward thinking company. I wanna see that times a hundred. Right. I mean, that's >>You see HP's in all the verticals. That's I think the point here, >>So they should be able to attract that ecosystem and build that, that flywheel that's the, that's the hallmark of a cloud that marketplace. >>Yeah, it is. But I think there's a, again, I go back to, they really gotta stay focused on that infrastructure and data management. Yeah. >>But they'll be focused on that, but, but their ecosystem, >>Their ecosystem will then take it up from there. And I think that's the next stage >>And that ecosystem's gotta include OT players and communications technologies players as well. Right. Because that stuff gets kind of sucked up in that, in that edge play. Do >>You feel like HPE has a, has a leg up on that or like a little, a little bit of a lead or is it pretty much, you know, even raced right now? >>I think they've, I think the big infrastructure companies have all had OEM businesses and they've all played there. It's it's, it's also helping those OT players actually convert their own needs into more of a software play and, and not so much of >>Physical. You've been, you've been following and you guys both have been following HP and HPE for years. They've been on the edge for a long time. I've been focused on this edge. Yeah. Now they might not have the product traction that's right. Or they might not develop as fast, but industrial OT and IOT they've been talking about it, focused on it. I think Amazon was mostly like, okay, we gotta get to the edge and like the enterprise. And, and I think HP's got a leg up in my opinion on that. Well, I question is can they execute? >>Yeah. I mean, PTC was here years ago on stage talking >>About, but I mean, you think about, if you think about the edge, right. I mean, I would argue one of the best acquisitions this company ever did was Aruba. Right. I mean, it basically changed the whole conversation of the edge changed the whole conversation. >>If >>Became GreenLake, it was GreenLake. >>Well, it became a big department. They gave a big, but, but, but I mean, you know, I mean they, they, they went after going selling edge line servers and frankly it's very difficult to gain traction there. Yeah. Aruba, huge area. And I think the March announcement was when they brought Aruba management into. Yeah. Yeah. >>Totally. >>Last question. Love >>That. >>What are you guys saying about the, the Broadcom VMware acquisition? What's the, what are the implications for the ecosystem for companies like HPE and just generally for the it business? >>Yeah. So >>You start. Yeah, sure. I'll start, I'll start there. So look, you know, we've, you know, spent some time, uh, going through it spent some time, you know, speaking, uh, to the, to the, to the folks involved and, and, and I gotta tell you, I think this is a really interesting moment for Broadcom. This is Broadcom's opportunity to basically build a different kind of a conversation with developers to, uh, try to invest in. I mean, just for perspective, right? These numbers may not be exact. And I know a dollar is not a dollar, but in 2001, anybody, remember what HP paid for? Compact >>8,000,000,020, >>So 25 billion, 25 billion. Wow. VMware just got sold for 61 billion. Wow. Okay. Unbill dollars. Okay. That gives you a perspective. No, again, I know a dollar is not a dollar 2000. >>It's still big numbers, >>2022. So having said that, if you just did it to, to, to basically build your DCF model and say, okay, over this amount of time, I'll pay you this. And I'll take the money out of this period of time, which is what people have criticized them for. I think that's a little shortsighted. I, yeah, I think this is Broadcom's opportunity to invest in that product and really try to figure out how to get a seat at the table in software and pivot their company to enterprise software in a different way. They have to prove that they're willing to do that. And then frankly, that they can develop the skills to do that over time. But I do believe this is a, a different, this is a pivot point. This is not >>CA this is not CA >>It's not CA >>In my, in my mind, it can't be CA they would, they would destroy too much. Now you and I, Dave had some, had some conversations on Twitter. I, I don't think it's the step up to them sort of thinking differently about semiconductor, dying, doing some custom semi I, I don't think that's. Yeah. I agree with that. Yeah. I think I, I think this is really about, I got two aspiration for them pivoting the company. They could >>Justify the >>Price to the, getting a seat at the adults table in software is, >>Well, if, if Broadcom has been squeezing their supplies, we all hear the scutle butt. Yeah. If they're squeezing, they can use VMware to justify the prices. Yeah. Maybe use that hostage. And that installed base. That's kind of Mike conspiracy. >>I think they've told us what they're gonna do. >><laugh> I do. >>Maybe it's not like C what's your conspiracy theory like Symantec, but what >>Do you think? Well, I mean, there's still, I mean, so VMware there's really nobody that can do all the things that VMware does say. So really impossible for an enterprise to just rip 'em out. But obviously you can, you can sour people's taste and you can very much influence the direction they head in with the collection of, of providers. One thing, interesting thing here is, was the 37% of VMware's revenues sold through Dell. So there's, there's lots of dependencies. It's not, it's not as simple as I think John, you you're right. You can't just pull the CA playbook out and rerun it here. This is a lot more complex. Yeah. It's a lot more volume of, of, of distribution, but a fair amount of VMware's install >>Base Dell's influence is still there basically >>Is in the mid-market. It's not, it's not something that they're gonna touch directly. >>You think about what VMware did. I mean, they kept adding new businesses, buying new businesses. I mean, is security business gonna stay >>Networking security, I think are interesting. >>Same >>Customers >>Over and over. Haven't done anything. VMware has the same customers. What new >>Customers. So imagine simplifying VMware. Right, right. Becomes a different equation. It's really interesting. And to your point, yeah. I mean, I think Broadcom is, I mean, Tom Crouse knows how to run a business. >>Yeah. He knows how to run a business. He's gonna, I, I think it's gonna be, you know, it's gonna be an efficient business. It's gonna be a well run business, but I think it's a pivot point for >>Broadcom. It's amazing to me, Broadcom sells to HPE. They sell it to Dell and they've got a market cap. That's 10 X, you know? Yes. Yeah. All we gotta go guys. Awesome. Great conversation guys. >>A lot. Thanks for having us on. >>Okay. Listen, uh, day two is a, is a wrap. We'll be here tomorrow, all day. Dave ante, John furrier, Lisa Martin, Lisa. Hope you're feeling okay. We'll see you tomorrow. Thanks for watching the cube, your leader in enterprise tech, live coverage.

>>From the cube studios in Palo Alto, in Boston, bringing you data driven insights from the cube and ETR. This is breaking analysis with Dave ante. >>When Frank sluman took service, now public many people undervalued the company, positioning it as just a better help desk tool. You know, it turns out that the firm actually had a massive Tam expansion opportunity in it. SM customer service, HR, logistics, security marketing, and service management. Generally now stock price followed over the years, the stellar execution under Slootman and CFO, Mike scar Kelly's leadership. Now, when they took the reins at snowflake expectations were already set that they'd repeat the feet, but this time, if anything, the company was overvalued out of the gate, the thing is people didn't really better understand the market opportunity this time around, other than that, it was a bet on Salman's track record of execution and on data, pretty good bets, but folks really didn't appreciate that snowflake. Wasn't just a better data warehouse that it was building what they call a data cloud, and we've turned a data super cloud. >>Hello and welcome to this. Week's Wikibon cube insights powered by ETR in this breaking analysis, we'll do four things. First. We're gonna review the recent narrative and concerns about snowflake and its value. Second, we're gonna share survey data from ETR that will confirm precisely what the company's CFO has been telling anyone who will listen. And third, we're gonna share our view of what snowflake is building IE, trying to become the defacto standard data platform, and four convey our expectations for the upcoming snowflake summit. Next week at Caesar's palace in Las Vegas, Snowflake's most recent quarterly results they've been well covered and well documented. It basically hit its targets, which for snowflake investors was bad news wall street piled on expressing concerns about Snowflake's consumption, pricing model, slowing growth rates, lack of profitability and valuation. Given the, given the current macro market conditions, the stock dropped below its IPO offering price, which you couldn't touch on day one, by the way, as the stock opened well above that and, and certainly closed well above that price of one 20 and folks express concerns about some pretty massive insider selling throughout 2021 and early 2022, all this caused the stock price to drop quite substantially. >>And today it's down around 63% or more year to date, but the only real substantive change in the company's business is that some of its largest consumer facing companies, while still growing dialed back, their consumption this past quarter, the tone of the call was I wouldn't say contentious the earnings call, but Scarelli, I think was getting somewhat annoyed with the implication from some analyst questions that something is fundamentally wrong with Snowflake's business. So let's unpack this a bit first. I wanna talk about the consumption pricing on the earnings call. One of the analysts asked if snowflake would consider more of a subscription based model so that they could better weather such fluctuations and demand before the analyst could even finish the question, CFO Scarelli emphatically interrupted and said, no, <laugh> the analyst might as well have asked, Hey Mike, have you ever considered changing your pricing model and screwing your customers the same way most legacy SaaS companies lock their customers in? >>So you could squeeze more revenue out of them and make my forecasting life a little bit easier. <laugh> consumption pricing is one of the things that makes a company like snowflake so attractive because customers is especially large customers facing fluctuating demand can dial and their end demand can dial down usage for certain workloads that are maybe not yet revenue producing or critical. Now let's jump to insider trading. There were a lot of insider selling going on last year and into 2022 now, I mean a lot sloop and Scarelli Christine Kleinman. Mike SP several board members. They sold stock worth, you know, many, many hundreds of millions of dollars or, or more at prices in the two hundreds and three hundreds and even four hundreds. You remember the company at one point was valued at a hundred billion dollars, surpassing the value of service now, which is this stupid at this point in the company's tenure and the insider's cost basis was very often in the single digit. >>So on the one hand, I can't blame them. You know what a gift the market gave them last year. Now also famed investor, Peter Linsey famously said, insiders sell for many reasons, but they only buy for one. But I have to say there wasn't a lot of insider buying of the stock when it was in the three hundreds and above. And so yeah, this pattern is something to watch our insiders buying. Now, I'm not sure we'll keep watching snowflake. It's pretty generous with stock based compensation and insiders still own plenty of stock. So, you know, maybe not, but we'll see in future disclosures, but the bottom line is Snowflake's business. Hasn't dramatically changed with the exception of these large consumer facing companies. Now, another analyst pointed out that companies like snap, he pointed to company snap, Peloton, Netflix, and face Facebook have been cutting back. >>And Scarelli said, and what was a bit of a surprise to me? Well, I'm not gonna name the customers, but it's not the ones you mentioned. So I, I thought I would've, you know, if I were the analyst I would've follow up with, how about Walmart target visa, Amex, Expedia price line, or Uber? Any of those Mike? I, I doubt he would've answered me anything. Anyway, the one thing that Scarelli did do is update Snowflake's fiscal year 2029 outlook to emphasize the long term opportunity that the company sees. This chart shows a financial snapshot of Snowflake's current business using a combination of quarterly and full year numbers in a model of what the business will look like. According to Scarelli in Dave ante with a little bit of judgment in 2029. So this is essentially based on the company's framework. Snowflake this year will surpass 2 billion in revenues and targeting 10 billion by 2029. >>Its current growth rate is 84% and its target is 30% in the out years, which is pretty impressive. Gross margins are gonna tick up a bit, but remember Snowflake's cost a good sold they're dominated by its cloud cost. So it's got a governor. There has to pay AWS Azure and Google for its infrastructure. But high seventies is a, is a good target. It's not like the historical Microsoft, you know, 80, 90% gross margin. Not that Microsoft is there anymore, but, but snowflake, you know, was gonna be limited by how far it can, how much it can push gross margin because of that factor. It's got a tiny operating margin today and it's targeting 20% in 2029. So that would be 2 billion. And you would certainly expect it's operating leverage in the out years to enable much, much, much lower SGNA than the current 54%. I'm guessing R and D's gonna stay healthy, you know, coming in at 15% or so. >>But the real interesting number to watch is free cash flow, 16% this year for the full fiscal year growing to 25% by 2029. So 2.5 billion in free cash flow in the out years, which I believe is up from previous Scarelli forecast in that 10, you know, out year view 2029 view and expect the net revenue retention, the NRR, it's gonna moderate. It's gonna come down, but it's still gonna be well over a hundred percent. We pegged it at 130% based on some of Mike's guidance. Now today, snowflake and every other stock is well off this morning. The company had a 40 billion value would drop well below that midday, but let's stick with the 40 billion on this, this sad Friday on the stock market, we'll go to 40 billion and who knows what the stock is gonna be valued in 2029? No idea, but let's say between 40 and 200 billion and look, it could get even ugly in the market as interest rates rise. >>And if inflation stays high, you know, until we get a Paul Voker like action, which is gonna be painful from the fed share, you know, let's hope we don't have a repeat of the long drawn out 1970s stagflation, but that is a concern among investors. We're gonna try to keep it positive here and we'll do a little sensitivity analysis of snowflake based on Scarelli and Ante's 2029 projections. What we've done here is we've calculated in this chart. Today's current valuation at about 40 billion and run a CAGR through 2029 with our estimates of valuation at that time. So if it stays at 40 billion valuation, can you imagine snowflake grow into a 10 billion company with no increase in valuation by the end, by by 2029 fiscal 2029, that would be a major bummer and investors would get a, a 0% return at 50 billion, 4% Kager 60 billion, 7%. >>Kegar now 7% market return is historically not bad relative to say the S and P 500, but with that kind of revenue and profitability growth projected by snowflake combined with inflation, that would again be a, a kind of a buzzkill for investors. The picture at 75 billion valuation, isn't much brighter, but it picks up at, at a hundred billion, even with inflation that should outperform the market. And as you get to 200 billion, which would track by the way, revenue growth, you get a 30% plus return, which would be pretty good. Could snowflake beat these projections. Absolutely. Could the market perform at the optimistic end of the spectrum? Sure. It could. It could outperform these levels. Could it not perform at these levels? You bet, but hopefully this gives a little context and framework to what Scarelli was talking about and his framework, not with notwithstanding the market's unpredictability you're you're on your own. >>There. I can't help snowflake looks like it's going to continue either way in amazing run compared to other software companies historically, and whether that's reflected in the stock price. Again, I, I, I can't predict, okay. Let's look at some ETR survey data, which aligns really well with what snowflake is telling the street. This chart shows the breakdown of Snowflake's net score and net score. Remember is ETS proprietary methodology that measures the percent of customers in their survey that are adding the platform new. That's the lime green at 19% existing snowflake customers that are ex spending 6% or more on the platform relative to last year. That's the forest green that's 55%. That's a big number flat spend. That's the gray at 21% decreasing spending. That's the pinkish at 5% and churning that's the red only 1% or, or moving off the platform, tiny, tiny churn, subtract the red from the greens and you get a net score that, that, that nets out to 68%. >>That's an, a very impressive net score by ETR standards. But it's down from the highs of the seventies and mid eighties, where high seventies and mid eighties, where snowflake has been since January of 2019 note that this survey of 1500 or so organizations includes 155 snowflake customers. What was really interesting is when we cut the data by industry sector, two of Snowflake's most important verticals, our finance and healthcare, both of those sectors are holding a net score in the ETR survey at its historic range. 83%. Hasn't really moved off that, you know, 80% plus number really encouraging, but retail consumer showed a dramatic decline. This past survey from 73% in the previous quarter down to 54%, 54% in just three months time. So this data aligns almost perfectly with what CFO Scarelli has been telling the street. So I give a lot of credibility to that narrative. >>Now here's a time series chart for the net score and the provision in the data set, meaning how penetrated snowflake is in the survey. Again, net score measures, spending velocity and a specific platform and provision measures the presence in the data set. You can see the steep downward trend in net score this past quarter. Now for context note, the red dotted line on the vertical axis at 40%, that's a bit of a magic number. Anything above that is best in class in our view, snowflake still a well, well above that line, but the April survey as we reported on May 7th in quite a bit of detail shows a meaningful break in the snowflake trend as shown by ETRS call out on the bottom line. You can see a steady rise in the survey, which is a proxy for Snowflake's overall market penetration. So steadily moving up and up. >>Here's a bit of a different view on that data bringing in some of Snowflake's peers and other data platforms. This XY graph shows net score on the vertical axis and provision on the horizontal with the red dotted line. At 40%, you can see from the ETR callouts again, that snowflake while declining in net score still holds the highest net score in the survey. So of course the highest data platforms while the spending velocity on AWS and Microsoft, uh, data platforms, outperforms that have, uh, sorry, while they're spending velocity on snowflake outperforms, that of AWS and, and Microsoft data platforms, those two are still well above the 40% line with a stronger market presence in the category. That's impressive because of their size. And you can see Google cloud and Mongo DB right around the 40% line. Now we reported on Mongo last week and discussed the commentary on consumption models. >>And we referenced Ray Lenchos what we thought was, was quite thoughtful research, uh, that rewarded Mongo DB for its forecasting transparency and, and accuracy and, and less likelihood of facing consumption headwinds. And, and I'll reiterate what I said last week, that snowflake, while seeing demand fluctuations this past quarter from those large customers is, is not like a data lake where you're just gonna shove data in and figure it out later, no schema on, right. Just throw it into the pond. That's gonna be more discretionary and you can turn that stuff off. More likely. Now you, you bring data into the snowflake data cloud with the intent of driving insights, which leads to actions, which leads to value creation. And as snowflake adds capabilities and expands its platform features and innovations and its ecosystem more and more data products are gonna be developed in the snowflake data cloud and by data products. >>We mean products and services that are conceived by business users. And that can be directly monetized, not just via analytics, but through governed data sharing and direct monetization. Here's a picture of that opportunity as we see it, this is our spin on our snowflake total available market chart that we've published many, many times. The key point here goes back to our opening statements. The snowflake data cloud is evolving well beyond just being a simpler and easier to use and more elastic cloud database snowflake is building what we often refer to as a super cloud. That is an abstraction layer that companies that, that comprises rich features and leverages the underlying primitives and APIs of the cloud providers, but hides all that complexity and adds new value beyond that infrastructure that value is seen in the left example in terms of compressed cycle time, snowflake often uses the example of pharmaceutical companies compressing time to discover a drug by years. >>Great example, there are many others this, and, and then through organic development and ecosystem expansion, snowflake will accelerate feature delivery. Snowflake's data cloud vision is not about vertically integrating all the functionality into its platform. Rather it's about creating a platform and delivering secure governed and facile and powerful analytics and data sharing capabilities to its customers, partners in a broad ecosystem so they can create additional value. On top of that ecosystem is how snowflake fills the gaps in its platform by building the best cloud data platform in the world, in terms of collaboration, security, governance, developer, friendliness, machine intelligence, etcetera, snowflake believes and plans to create a defacto standard. In our view in data platforms, get your data into the data cloud and all these native capabilities will be available to you. Now, is that a walled garden? Some might say it is. It's an interesting question and <laugh>, it's a moving target. >>It's definitely proprietary in the sense that snowflake is building something that is highly differentiatable and is building a moat around it. But the more open snowflake can make its platform. The more open source it uses, the more developer friendly and the great greater likelihood people will gravitate toward snowflake. Now, my new friend Tani, she's the creator of the data mesh concept. She might bristle at this narrative in favor, a more open source version of what snowflake is trying to build, but practically speaking, I think she'd recognize that we're a long ways off from that. And I also think that the benefits of a platform that despite requiring data to be inside of the data cloud can distribute data globally, enable facile governed, and computational data sharing, and to a large degree be a self-service platform for data, product builders. So this is how we see snow, the snowflake data cloud vision evolving question is edge part of that vision on the right hand side. >>Well, again, we think that is going to be a future challenge where the ecosystem is gonna have to come to play to fill those gaps. If snowflake can tap the edge, it'll bring even more clarity as to how it can expand into what we believe is a massive 200 billion Tam. Okay, let's close on next. Week's snowflake summit in Las Vegas. The cube is very excited to be there. I'll be hosting with Lisa Martin and we'll have Frank son as well as Christian Kleinman and several other snowflake experts. Analysts are gonna be there, uh, customers. And we're gonna have a number of ecosystem partners on as well. Here's what we'll be looking for. At least some of the things, evidence that our view of Snowflake's data cloud is actually taking shape and evolving in the way that we showed on the previous chart, where we also wanna figure out where snowflake is with it. >>Streamlet acquisition. Remember streamlet is a data science play and an expansion into data, bricks, territory, data, bricks, and snowflake have been going at it for a while. Streamlet brings an open source Python library and machine learning and kind of developer friendly data science environment. We also expect to hear some discussion, hopefully a lot of discussion about developers. Snowflake has a dedicated developer conference in November. So we expect to hear more about that and how it's gonna be leveraging further leveraging snow park, which it has previously announced, including a public preview of programming for unstructured data and data monetization along the lines of what we suggested earlier that is building data products that have the bells and whistles of native snowflake and can be directly monetized by Snowflake's customers. Snowflake's already announced a new workload this past week in security, and we'll be watching for others. >>And finally, what's happening in the all important ecosystem. One of the things we noted when we covered service now, cause we use service now as, as an example because Frank Lupin and Mike Scarelli and others, you know, DNA were there and they're improving on that service. Now in his post IPO, early adult years had a very slow pace. In our view was often one of our criticism of ecosystem development, you know, ServiceNow. They had some niche SI uh, like cloud Sherpa, and eventually the big guys came in and, and, and began to really lean in. And you had some other innovators kind of circling the mothership, some smaller companies, but generally we see sluman emphasizing the ecosystem growth much, much more than with this previous company. And that is a fundamental requirement in our view of any cloud or modern cloud company now to paraphrase the crazy man, Steve bomber developers, developers, developers, cause he screamed it and ranted and ran around the stage and was sweating <laugh> ecosystem ecosystem ecosystem equals optionality for developers and that's what they want. >>And that's how we see the current and future state of snowflake. Thanks today. If you're in Vegas next week, please stop by and say hello with the cube. Thanks to my colleagues, Stephanie Chan, who sometimes helps research breaking analysis topics. Alex, my is, and OS Myerson is on production. And today Andrew Frick, Sarah hiney, Steven Conti Anderson hill Chuck all and the entire team in Palo Alto, including Christian. Sorry, didn't mean to forget you Christian writer, of course, Kristin Martin and Cheryl Knight, they helped get the word out. And Rob ho is our E IIC over at Silicon angle. Remember, all these episodes are available as podcast, wherever you listen to search breaking analysis podcast, I publish each week on wikibon.com and Silicon angle.com. You can email me directly anytime David dot Valante Silicon angle.com. If you got something interesting, I'll respond. If not, I won't or DM me@deteorcommentonmylinkedinpostsandpleasedocheckoutetr.ai for the best survey data in the enterprise tech business. This is Dave Valante for the insights powered by ETR. Thanks for watching. And we'll see you next week. I hope if not, we'll see you next time on breaking analysis.

>>Hi, everyone. Welcome to the cubes presentation of the AWS startup showcase the theme. This episode is data as code, and this is season two, episode two of the ongoing series covering exciting startups from the ecosystem in cloud and the future of data analytics. I'm your host, John furry. You're getting great featured panel here with AWS heroes, Lynn blankets, the CEO of Lindbergh Lega consulting, Peter Hanson's, founder of cloud Cedar and Alex debris, principal of debris advisory. Great to see all of you here and, uh, remotely and look forward to see you in person at the next re-invent or other event. >>Thanks for having us. >>So Lynn, you're doing a lot of work in healthcare, Peter you're in the middle of all the action as data as code Alex. You're in deep on the databases. We've got a good round up of, of topics here ranging from healthcare to getting under the hood on databases. So as we'll start with you, what are you working on right now? What trends do you see in the database space? >>Yeah, sure. So I do, uh, I do a lot of consulting work working with different people and, you know, often with, with dynamo DB or, or just general serverless technology type stuff. Um, if you want to talk about trends that I'm seeing right now, I would say trends you're seeing as a lot, just more serverless native databases or cloud native databases where you're seeing these cool databases come out that really take advantage of, uh, this new cloud environment, right? Where you have scalability, you have plasticity of the clouds. So you're not having, you know, instant space environments anymore. You're paying for capacity, you're paying for throughput. You're able to scale up and down. You're not managing individual instances. So a lot of cool stuff that we're seeing, you know, um, with this new generation of, of infrastructure and in particular database is taking advantage of this, this new cloud world >>And really lot deep into the database side in terms of like cloud native impact, diversity of database types, when to use certain databases that also a big deal. >>Yeah, absolutely. I like, I totally agree. I love seeing the different types of databases and, you know, AWS has this whole, uh, purpose-built database strategy. And I think that, that makes a lot of sense. Um, you know, I want to go too far with it. I would, I would more think about purpose-built categories and things like that, you know, specialize in an OLTB database within your, within your organization, whether that's dynamo DB or document DB or relational database Aurora or something like that. But then also choose some sort of analytics database, you know, if it's drew it or Redshift or Athena, and then, you know, if you have some specialized needs, you want to show some real time stuff to your users, check out rock site. If you want to, uh, you know, do some graph analytics, fraud detection, checkout tiger graph, a lot of cool stuff that we're seeing from the startup showcase here. >>Looking forward to unpacking that Lynn you've been in love now, a healthcare action with cloud ops, the pandemic pushes hard core on everybody. What are you working on? >>Yeah, it's all COVID data all the time. Uh, before the pandemic, I was supporting research groups for cancer genomics, which I still do, but, um, what's, uh, impactful is the explosive data volumes. You know, when you there's big data and there's genomic data, you know, I've worked with clients that have broken data centers, broken public cloud provider data centers because of the daily volume they're putting in. So there's this volume aspect. And then there's a collaboration, particularly around COVID research because of pandemic. And so you have this explosive volume, you have this, um, need for, uh, computational complexity. And that means cloud the challenge is it, you know, put the pedal to the metal. So you've got all these bioinformatics researchers that are used to single machine. Suddenly they have to deal with distributed compute. So it's a wild time to be in this space. >>What was the big change that you've seen with the, uh, the pandemic and in genomic cloud genomic specifically what's the big change has happened. >>The amount of data that is being put into the public cloud, um, previously people would have their data on their local, uh, capacity, and then they would publish their paper and the data may or may not become available for, uh, reproducing the research, uh, to accelerate for drug discovery and even variant identification. The data sets are being pushed to public cloud repositories, which is a whole new set of concerns. You have not only dealing with the volume and cost, but security, you know, there's federated security is non-trivial and not well understood by this domain. So there's so much work available here. >>Awesome. Peter, you're doing a lot with the data as a platform kind of view and platform engineering data as code is, is something that's being kicked around. What are you working on and how does platform engineering change as data becomes so much more prevalent in its value proposition? >>Yeah. So I'm the founder of cloud Cedar and, um, we sort of built this company out, this consultancy all around the challenges that a lot of companies have got with getting their data sorted, getting it organized, getting it ready for other use cases, such as analytics and machine learning, um, AI workloads and the like. So typically a platform engineering team will look after the organization of a company infrastructure, making sure that it's coherent across the company and a data platform, engineering teams doing something similar in that sense where they're, they're looking at making sure that, uh, data teams have a solid foundation to build upon, uh, that everything's quite predictable and what that enables is a faster velocity and the ability to use data as code as a way of specifying and onboarding data, building that, translating it, transforming it out into its specific domains and then on to data products. >>I have to ask you while you're here. Um, there's a big trend around data meshes right now. You're hearing, we've had a lot of stuff on the cube. Um, what are practical that people are using data mesh, first of all, is it relevant and how are people looking at this data mesh conversation? >>I think it becomes more and more relevant, uh, the bigger the organization that you're dealing with. So, you know, often times in the enterprise, you've got, uh, projects with timelines of five to 10 years often outlasting technology life cycles. The technology that you're building on is probably irrelevant by the time that you complete it. And what we're seeing is that data engineering teams and data teams more broadly, this organizational bottleneck and data mesh is all about, uh, breaking down that, um, bottleneck and decentralizing the work, shifting that work back onto, uh, development teams who oftentimes have got more of the context and a centralized data engineering team. And we're seeing a lot of, uh, Philocity increases as a result of that. >>It's interesting. There's so many different aspects of how data is changing the world. Lynn talks about the volume with the cloud and genomics. We're hearing data engineering at a platform level. You're talking about slicing and dicing and real-time information. You mentioned rock set, Alex. So I'd like to ask each of you to answer this next question, which is how has the team dynamics changed with data engineering because every single company's impacted. So if you're researchers, Lynn, you're pumping more data into the cloud, that's got a little bit of data engineering to it. Do they even understand that is that impacting them? So how has data changed the responsibilities or roles in this new emerging area of data engineering or whatever you want to call it? Lynn, we'll start with you. What do you, what do you see this impact? >>Well, you know, I mean, dev ops becomes data ops and ML ops and, uh, you know, this is a whole emergent area of work and it starts with an understanding of container technologies, which, you know, in different verticals like FinTech, that's a given, right, but in bioinformatics building an appropriately optimized Docker container is something I'm still working with customers now on because they have the concept of a Docker container is just a virtual machine, which obviously it isn't, or shouldn't be. So, um, you have, again, as I mentioned previously, this humongous skill gap, um, concepts like D, which are prevalent in ad tech FinTech, that's not available yet for most of my customers. So those are the things that I'm building. So the whole ops space is, um, this a wide open area. And really it's a question of practicality. Um, you know, I have, uh, a lot of experience with data lakes and, you know, containerizing and using the data lake platform. But a lot of my customers are going to move to like an interim pass based solutions. If they're using spark, for example, they might use to use a managed spark solution as an interim, um, step up to the cloud before they build their own containers. Because the amount of knowledge to do that effectively is non-trivial >>Peter, you mentioned data, you mentioned data lakes, onboarding data into lake house architectures, for instance, something that you're familiar with. Um, this is not obvious to some verticals obvious to others. What do you see this data engineering impact from a personnel standpoint? And then ultimately how things get built, >>You know, are you directing that to me, >>Peter? >>Yeah. So I think, um, first and foremost, you know, the workload that data engineering teams are dealing with is ever increasing. Usually there's a 10 X ratio of, um, software engineers to data engineers within a business and usually double the amount of analysts to data engineers again. And so they're, they're fighting it ever increasing backload. And, uh, so they're fighting an ever increasing backlog of, of, uh, tasks to do and tickets to, to, to churn through. And so what we're seeing is that data engineering teams are becoming data platform engineering teams where they're building capability instead of constantly hamster wheels spinning if you will. And so with that in mind, with onboarding data into, uh, a Lakehouse architecture or a data lake where data engineering teams, uh, uh, getting wins is developing a very good baseline of structure where they're getting the categorization, the data tagging, whether this data is of a particular domain, does it contain some, um, PII data, for instance, uh, and, and, and, and then the security aspects, and also, you know, the mechanisms on which to do the data transformations, >>Alex, on the database side, those are known personas in an enterprise, a them, the database team, but now the scale is so big. Um, and there's so much going on in databases. How does the data engineering impact organizations from your standpoint? >>Yeah, absolutely. I think definitely, you know, gone are the days where you have a single relational database that is serving operational queries for your users, and you can also serve analytics queries, you know, for your internal teams. It's, it's now split up into those purpose-built databases, like we've said. Uh, but now you've got two different teams managing it and they're, they're designing their data model for different things. You know? So L LLTP might have a more de-normalized model, something that works for very fast operations and it's optimized for that, but now you need to suck that data out and get it elsewhere so that your, your PM or your business analyst, or whoever can crunch through some of that. And, you know, now it needs to be in a more normalized format. How do you sort of bridge that gap? That's a tough one. I think you need to, you know, build empathy on each side of, of what each side is doing and, and build the tools to say, Hey, this is going to help you, uh, you know, LLTP team, if we know what, what users are actually doing, and, and if you can get us into the right format there, so that then I can, you know, we can analyze it, um, on the backend. >>So I think, I think building empathy across those teams is helpful. >>When I left to come back to, you mentioned a health and informatics is coming back. Um, but it's interesting, you know, I look at a database world and you look at the solutions that are out there. A lot of companies that build data solutions don't have a data problem. They've never, they're not swimming in a lot of data, but then you look at like the field that you're working in right now with the genomics and health and, and quantum, they're always, they're dealing with data all the time. So you have people who deal with a lot of data all the time are breaking through New Zealand. People who are don't have that experience are now becoming data full, right? So people are now either it's a first time problem, or they've always been swimming in a ton of data. So it's more of what's the new playbook. And then, wow, I've never had to deal with a lot of data before. What's your take? >>It's interesting. Cause they know, uh, bioinformatics hires, um, uh, grad students. So grad students, you know, use their, our scripts with their file on their laptop. And so, um, to get those folks to understand distributed container-based computing is like I said, a not non-trivial problem. What's been really interesting with the money pouring in to COVID research is when I first started, some of the workflows would take, you know, literally 500 hours and that was just okay. And coming out of FinTech, I was, uh, I could, I was blown away like FinTech is like, could that please take a millisecond rather than a second? Right. And so what has now happened, which makes it, you know, like I said, even more fun to work in this domain is, uh, the research dollars have really gone up because of the pandemic. And so there are, there are, there's this blending of people like me with more of a big data background coming into bioinformatics and working side by side. >>So it's this interesting sort of translation because you have the whole taxonomy of bioinformatics with genomics and sequencers and all the weird file types that you get. And then you have the whole taxonomy of dev ops data ops, you know, containers and Kubernetes and all that. And trying to get that into pipelines that can actually, you know, be efficient, given the constraints. Of course, we, on the tech side, we always want to make it super optimized. I had a customer that we got it down from 500 hours to minutes, but they wanted to stay with the past solution because it was easier for them to go from 500 hours to five hours was good enough, but you know, the techies want to get it down to five minutes. >>This is, this is, we've seen this movie before dev ops, um, edge and op operations, you know, IOT, world scenes, the convergence of cultures. Now you have data and then old, old school operations kind of coming up. So this kind of supports the thesis. That data as code is the next infrastructure as code. What do you guys, what's the reaction there for you guys? What do you think about that? What does data's code mean? If infrastructure's code was cloud and dev ops, what is data as code? What does that mean? >>I could take it if you like. I think, um, data teams, organizations, um, have been long been this bottleneck within the organization and there's like this dark matter of untapped energy and potential waiting to be unleashed a data with the advent of open source projects like DBT, um, have been slowly sort of embracing software development, lifecycle practices. And this is really sort of seeing a, a big steep increase in, um, in their velocity. And, and this is only going to increase and improve as we're seeing data teams, um, embrace starter as code. I think it's, uh, the future is bright for data. So I'm very excited. >>Lynn Peter reaction. I mean, agility data is code is developer concept CICB pipeline. You mentioned it new operational workflows coming into traditional operations reaction. >>Yeah. I mean, I think Peter's right on there. I'd say, you know, some of those tools we're seeing come in from, from software, like, like DBT, basically giving you that infrastructure as code, but applied to that data realm. Also there have been a few, like get for data type things, pack a derm, I believe is one and a few other ones where you bring that in and you also see a lot of immutability concepts flowing into the data realm. So I think just seeing some of those software engineering concepts come over to the data world has, has been pretty interesting >>What we'll literally just versioning datasets and the identification of what's in a data set. What's not in a data set. Some of this is around ethical AI as well, um, is a whole, uh, area that has come out of research groups. Um, mostly AI research groups, but is being applied to medical data and needs to be obviously, um, so this, this, this, um, metadata and versioning around data sets is really, I think, a very of the moment area. >>Yeah, I think we, we, you guys are bringing up a really good kind of direction that's happening in data. And that is something that you're seeing on the software side, open source and now dev ops. And now going to data is that the supply chain challenges of we've been talking about it here on the cube and this, this, um, this episode is, you know, we've seen Ukraine war, but some open source, you know, malware hitting datasets is data secure. What is that going to look like? So you starting to get into this what's the supply chain, is it verified data sets if data sets have to be managed a whole nother level of data supply chain comes up, what do you guys think about that? >>I'll jump in. Oh, sorry. I'll jump in again. I think that, you know, there's, there's, um, some, some of the compliance requirements, um, around financial data are going to be applied to other types of data, probably health data. So immutability reproducibility, um, that is, uh, legally required. Um, also some of the privacy requirements that originated in Europe with GDPR are going to be replicated as more and more, um, types of data. And again, I'm always going to speak for health, but there's other types as well coming out of personal devices and that kind of stuff. So I think, you know, this idea of data as code is it's, it goes down to versioning and controlling and, um, that's, uh, that's sort of a real succinct way to say it that we didn't used to think about that. We just put it in our, you know, relational database and we were good to go, but, um, versioning and controlling in the global ecosystem is kind of, uh, where I'm focusing my efforts. >>It brings up a good question. If databases, if data is going to be part of the development process has to be addressable, which means horizontally scalable. That means it has to be accessible and open. How do you make that work and not foreclose it with a lot of restrictions? >>I think the use of data catalogs and appropriate tagging and categorization, you know, I think, you know, everyone's heard of the term data swamp, and I think that just came about because that everyone saw like, oh, wow, S3, you know, infinite storage. We just, you know, throw whatever in there for as long as we want. And I think at times, you know, the proliferation of S3 buckets, um, and the like, you know, we've just seen, uh, perhaps security, not maintained as well as it could have been. And I think that's kind of where data platform engineering teams have really sort of, uh, come into the, for, you know, creating a governance set of buckets like formation on top. But I think that's kind of where we need to see a lot more work with appropriate tags and also the automatic publishing of metadata into data catalogs so that, um, folks can easily search and address particular data sets and also control the access. You know, for instance, you've got some PII data, perhaps really only your marketing folks should be looking at email addresses and the like not perhaps your finance folks. So I think, you know, there's, there's a lot to be leveraged there in formation and other solutions, >>Alex, let's back up and talk about what's in it for the customer, right. Let's zoom back and saying reality is I just got to get my data to make sure it's secure always on and not going to be hackable. And I just got to get my data available on river performance. So then, then I got to start thinking about, okay, how do I intersect it? So what should teams be thinking about right now as I look up all their data options or databases across their enterprise? >>Yeah, it's, it's a, it's a good question. I just, you know, I think Peter made some good points there and you can think of history as sort of ebbing and flowing between centralization and decentralization a lot of times. And you know, when storage was expensive, data was going to be sort of centralized and Maine maintained, sort of a, you know, by the, uh, the people that are in charge of it. But then when, when S3 comes along, it really decreases storage. Now we can do a lot more experiments on it. We can store a lot more of our data, keep it around and do different things on it. You know, now we've got regulations again, we were, we gotta, we gotta be more realistic about, about keeping that data secure and make sure we're, we're doing the right things with it. So it's, we're gonna probably go through a period of, of centralization as we work out some of this tooling around, you know, tagging and, and ethical AI that, that both Peter. And when we're talking about here and maybe get us into that, that next wearable world of de-centralization again. But I, I think that ebb and flow is going to be natural in response to, you know, the problems of the, the other extreme, >>Where are we in the market right now from progress standpoint, because data lakes don't want to be data swamps. You seeing lake formation as a data architecture, as an example, where are we with customers? What are they doing right now? Where would you put them in the progress bar of, of evolution towards the Nirvana of having this data sovereignty? And this data is code environment. Are they just now in the data lake store, everything real-time and historical? >>Well, I can jump in there. Um, SQL on files is the, is the driver. And so we know when Amazon got Athena, um, that really drove a lot of the customers to really realistically look at data lake technologies, but data warehouses are not going away. And the integration between the two is not seamless. No, we, we are partners with AWS, but we don't work for them. So we can tell you the truth here. Um, there's, there's work to it, but it really, for my customers, it really upped the ante around data lake, uh, because Athena and technologies like that, the serverless, um, SQL queries or the familiar quarry, um, uh, libraries really drove a movement away from either OLTB or OLAP, more expensive, more cumbersome structures, >>But they still need that. Oh, LTP, like if they have high latency issues, they want to be low latency. Can they have the best of both worlds? That's the question. >>I mean, I w I would say we're getting, you know, we're getting closer. We're always going to be, uh, you know, that technology is going to be moving forward, and then we'll just move the goalpost again, in terms of, of what we're asking from it. But I think, you know, the technology that's getting out there, you can get, get really well. And then, you know, just what I work in the dynamo DB world. So you can get really great low latency. So, you know, single digit millisecond LLTP response times on that. I think some of the analytics stuff has been a problem with that. And there, there are different solutions out there to where you can export dynamo to S3, and then you can be doing SQL on your FA your files with Athena Lakeland's talking about, or now you see, you know, rock set of partner here that that'll just ingest your dynamo, DB data, you know, make all those changes. So if you're doing a lot of, uh, changes to your data and dynamo is going to reflect in Roxanna, and then you can do analytics queries, you can do complex filters, different things like that. So, you know, I, I think we continue to push the envelope and then we moved the goalpost again. But, um, you know, I think we're in a, a lot better place than we were a few years ago, for sure. >>Where do you guys see this going relative to the next level? If data as code becomes that next agile, um, software defined environment with open source? Well, all of these new tools with serverless things happening with data lakes are built in with nice architectures with data warehouses, where does it go next? What happens next? If this becomes an agile environment, what's the impact? >>Well, I don't want to be so dominant, but I have, I feel strongly, so I'm going to jump in here. So, so I, um, I feel like, you know, now for my, my, my most computationally intensive workloads, I'm using GPS, I'm bursting to GPU for TensorFlow neural networks. So I've been doing quite a bit of exploration around Amazon bracket for QPS and it's early. Um, and it's specialty. It's not, you know, for everybody. And the learning curve again is pretty daunting, but, um, there are some use cases out there. I mean, I got ahold of a paper where some people did some, um, it was a Q CNN, um, quantum convolutional neural network for lung cancer images, um, from COVID patients and the, the, uh, the QP Hugh, um, algorithm pipeline performed more accurately and faster. So I think, um, bursting to quantum is something to pay attention to. >>Awesome. Peter, what's your take on what's next? >>Well, I think there's still, um, that, that was absolutely fascinating from Lynn, but I think also there's, there's, uh, you know, some more sort of low-level, uh, low-hanging fruit available in, in the data stack. I think there's a lot of, there's still a lot of challenges around the transformation there, getting our data from sort of raw landed data into business domains, and that sort of talks to a lot of what data mesh is all about. I think if we can somehow make that a little more frictionless, because that that's really where the like labor intensive work is. That's, that's kinda dominating, uh, data engineering teams and where we're sort of trying to push that, that workload back onto, um, you know, software engineering teams. >>Alice will give you the final word. What's the impact. What's the next step? What's it look like in the future? >>Yeah, for sure. I mean, I've never had the, uh, breaking a data center problem that wind's had, or the bursting the quantum problem, for sure. But, you know, if you're in that, you know, the pool I swim and of terabytes of data and below and things like that, I think it's a good time. It just like we saw, you know, like we were talking about dev ops and, and pushing, uh, you know, allowing software engineers to handle more of, of the operation stuff. I think the same thing with data can happen where, you know, software engineering teams can handle not just their code, not just, you know, deploying and operating it, but also thinking about their data around the code. And that doesn't mean you won't have people assist you within your organization. You won't have some specialists in there, but I think pushing more stuff, even onto the individual development teams where they have ownership of that. And they're thinking about it through all this different life cycle. I mean, I'm pretty bullish on that. And I think that's an exciting development >>Was that shift, what left with left is security. What does that mean to >>Shipped so much stuff left, but now, you know, the things that were at the end are back at the end again, but, uh, you know, at least we think we can think about that stuff early in the process, which is good, >>Great conversation, very provocative, very realistic and great impact on the future data as code is real, the developers I do believe will have a great operational role and the data stack concept and impacting things like quantum, it's all kind of lining up nicely. Um, and it's a great opportunity to be in this field from a science and policy standpoint. Um, data engineering is legit. It's going to continue to grow and thanks for unpacking that here on the queue. Appreciate it. Okay. Great panel D AWS heroes. They work with AWS and the ecosystem independently out there. They're in the trenches doing the front lines, cracking the code here with data as code season two, episode two of the ongoing series of the 80, but startups I'm John for your host. Thanks for watching.

>>And welcome to this special cube conversation. I'm John for a, your host of the cube. We're here in Palo Alto, California, and I'm here with a very special guest coming down from Seattle remotely into the cube studios is the leader at AWS Amazon web services, the vice president of database analytics and machine learning Swami. Great to see you cube alumni recently taking over the database business at AWS as a leader. Congratulations. And thanks for coming on the cube. >>Hey, my pleasure to be here, John, very excited to talk to you. >>Yeah. We've had many conversations on the cube and also in person and also online around all the major mega trends. You've had your hand in all the action, going back to your days when you were in school learning and, and writing papers. And 10 years ago, Amazon web services launched AWS dynamo, DB, fast, flexible, no SQL database that everyone loves today, which has inspired a generation of what I would call database distributing cloud scale, single digit millisecond performance at scale. And again, the key scale. And again, this is 10 years ago, so it seems like yesterday, but you guys are celebrating and your name was on the original paper with CTO Verner. Vogel's your celebrity. Congratulations. >>Thank you. Not sure about the celebrating part, but I'm very excited. At least I played a hand in building such an amazing technology that has enabled so many amazing customers along the way as well. So >>Trivia on the, on the paper as you were an intern at AWS, so you're getting your PhD. And then since, since rising through the ranks and involved in a lot of products over the years, and then leading the machine learning and AI, which is now changing the game at the industry level, but I got to ask you getting back to the story here. A lot of customers have built amazing things on top of dynamo DB, not to mention lots of other AWS and Amazon tech riding on it. Can you share some of the highlights that came out of the original paper? And so with some examples, because I think this is a point in time, 10 years ago, where you start to, so the KickUp of cloud scale, not just, just for developers and building startups, you're really starting to see the scale rise. >>Yeah, I actually, I mean, as you probably know, based on what he read to explain the Genesis of dynamo DB itself had to explain the Genesis of how Amazon got into building the original dynamo, right? And this was during the time when miner, I joined Ron esteem as an intern and, and Amazon was one of the pioneers in pushing the boundary of scale. And a year over year, our Q4 holiday season tends to be really, really bad for all the right reasons. We all want our holiday shopping done during that time. And you want to be able to scale your website, arters fulfillment centers, all of them at that time. And those are the times around 2005. And the answer is when people think our database, they think of a single database server that actually runs on a box and has a certain characteristics and does a scale and availability and whatnot. >>And it's usually relational. And then when we had a major disruption during Q4 that's when yeah, ask ourselves the question, why are we actually using a relational database for some of these things when they really didn't need the data model complexity of relational database. And normally I would say most companies where to actually ask an intern or a few engineers who are early in the career saying like, what the hell are you suggesting? Just go away. But Amazon being enabling Buddhists to build what they want. And they actually let us start reimagining what a database or our scale could look like. And that led to dynamo. And since she unstained mine, then we migrated from an traditional relational database stair this one for some of the amazon.com services. And then I moved on to actually start building some butts off our storage service and then our managed relational database service, I explicitly remember. >>And one of our customer advisory board, we're just the set off some of our leading customers who actually give us feedback on roadmap. Another son, Don, who's the CEO and chief geek of spunk bargain faker. And him actually looking at the Trinity me, I was starting in the corner and saying like you all, both tomorrow and why do I need to keep shotting my, my sequel database and reshooting assigned scaling. And this is the time when the state of the art in most databases were around. Like, you start sharding your relational database and constantly reshaping. And this is when most websites are starting to experience the kind of scale which we consider a normal month. During those times it was mostly, most companies used to have a single relational database backend and start scaling that way. And that conversation led entirely under duress, unaided read, lot of AWS leaders and myself saying like, Hey, what is a cloud database reimagined without the hampering SQL look like? And that led us to start building dynamo DB, but just a key value database at that time. Now we support document might've too, but that single digit millisecond latency at any scale imagine. So >>I think about that time at that time, 10 years ago, when you were having this conversation and I know the smug mug and I, he said, he's in totally geek and he's, he's good to point that out. You also have Netflix as customers too. I'd like to hear how that's evolved, but, but I think back at the time, if you look back then I got to ask you most people we've talked about this before. No one database rules, a world that's now standard people now don't see one database back then it was a one database kind of mindset back then. Yeah. And then you had that big data movement happening with Hadoop. You had the object store developing. So you're in you're you're circling around that area. What was it like then? I mean, take, take us through that because there was obvious visibility that, Hey, let's just store this. Now you see data lakes and that's all happening. But back then object store was kind of new. Yeah. >>Ah, it's a great question. Now, one of the things I realized early on, especially when I was working with binary, when you're saying amazon.com itself as an example, that the access patterns for various applications and Amazon, but let alone AWS customers tend to be very, very, very, some of them really just needed an object store. Some of them needed a relational database. Some of them really wanted a key value store within a fast latency. Some of them really needed a durable cash. And, but it so happens when you have a giant hammer. You use that for everything looks like a map, which is essentially the story at that time. And so everyone kept using the same database, irrespective of what the problem was because nobody else, I mean, thought about like, what else can we build that is better? So this let us do, literally I remember writing a paper with Bernard internally that is widely used in Amazon explaining what are all the menu of booklets that access. >>And then how do we go about actually solving for each of these things so that they can actually grow and innovate faster. And, and this was led to actually the Genesis of not only building IDs and so forth, but also dynamo and various other non-relational data. There's a still let alone not so storage access patterns and what not. So, and this was one of the big revelations he had just that there is not a single database that is going to meet the customer, needs us. The diversity of workloads in the internet is growing. And this was a key pivotal moment because with cloud now applications can scale very more instantly than before now. Building an application for Superbowl is very easier than before. That means that on, I mean, everybody is pushing the boundaries of what scale means, and they are expecting more from their obligations. That's when you need technologies like dynamo, DB, and that's exactly what dynamo already be set out to do. And since then, we are continuing to innovate on behalf of our customers and the purpose of the database story as well. And this concept has resonated well across the board. If you see that the database industry has also embraced this method, >>It's natural that you obviously evolved into the machine learning side of it because that's data is big part of that. And you see back then you, you bringing up kind of like flashes for me where it's like those, the data conversations back then and the data movement was just beginning. So the idea that you can have diversity in access methods of the kind of databases was a use case driven by the application, not so much database saying, this is how you have to work, that the script was flipped. It it's changed from infrastructure dictating to the applications, what to do. Now, the applications are going to the infrastructure and saying, give me what I want. I want to access something here in an office store, something here in no SQL that became the Genesis of infrastructure as code at a, at a global level. And so your paper kind of set the, the, the wave, the influence for this, no SQL did big data movement. It's created tons of value, maybe a third Mongo might've been influenced by this other people have been influenced. Can you share some stories of how people adopted the concept of dynamo DB and how that's changed in the industry and how has that helped the industry evolve? >>I mean, plus file data. Most share our experience of building and dynamo style data store. Very, it is a non-relational API and showing what are some of the experiences that the Venter in building such an paper and these set out early on itself, that it is should not be just a design paper, but it should be something that we shared our experiences. So even now, when I talked to my friends and colleagues and various other companies, one thing they always tell me is they appreciated the openness with which we were sharing. Some of the examples and learnings that we learned to not optimizing for percentile latencies, and what are some of the scalability challenges, how we solved and some of the techniques around things like sloppy Cora or various other stuff. We invented a lot of towns along the way too, but people really appreciated several of some of our findings and as talking about it. >>And since then I met so many other innovations are happening in the industry and the AWS, but also across the entire academia and industry in this space, the databases I've been going through what I call as a period of Renaissance, where one of the things, if you see our own arc, when Roger and I started on the database, front Disney started over the promo saying like, if you were to build a database where cloud is the new normal, this is again in 2008, we asked ourselves that question and what the belt that led us to start building things like dynamo, DB, RDS star. I know that alone, we reimagined data viruses with Redshift and several, and then several other databases like time stream for time series workloads started running Neptune for graph and whatnot. But at the moment we started actually asking that question and working backwards from customers. Then you will start being able to innovate accordingly. And this has worked really well. Then more than a hundred thousand AWS customers have chosen dynamo DB for mobile gaming tech IOT. Many of these are fast growing businesses, such as ledge, Darryl BNB, red fan, as soon as enterprises like Samsung Toyota, capital one and so far. So these are like really some meaningful clouds, let alone amazon.com. I run this. >>We have an internal customer is always good to have that entire inside customer. You know, I really find this a really profound use case because you're just talking, you know, in Amazonian terms, I'll just translate for the audience working backwards from the customer, which is the customer obsession you guys have. So here's, what's going on off the way I see it. You got dynamo, DB, paper, you and Verner, and the team Paul was a great as a great video on your blog posts that goes into the, to the talk he gave at around that time, which is fun to watch if you look back, but you have a radical enabler here, that's disrupting and changing S3 RDS, Aurora. These are game-changing concepts inside the, the landscape of AWS at the same time, you're working backwards from the customer. So the question I have for you as a leader and as a builder, how did you balance the working backwards from the customer while bringing something brand new and radical at that time to the market? >>Yeah, this is one of the S I mean hardest things to be, as leaders need to balance on. If you see many times, then we actually worked backwards from customers. The literal later translated this, literally do what customers are asking for, which is true nine out of 10 times, but there is one or a 10 times, you got to read between the lines on what they are asking. Because many times customers when are articulate that they need to go fast. If in the right way, they might say, Hey, I wish my heart storage goes faster, but they're not going to tell you they need a car, but you need to know and be able to translate and read between the lines we call it under the bucket of innovate on behalf of customers. And that is exactly the kind of a mantra we had when we were thinking about concepts like dynamo DB, because essentially at that time, almost everybody would, if I asked, they would just say, I wish a relational database could actually be able to scale from not just like a hundred gigabyte to one terabyte are, it can take up to like 2 million transactions, a second and so forth and still be cheap and made in reality as relational databases, the way they were engineered at that time, those are not going to meet the scale needs. >>So this is fair. We hunted read between the lines on what are some of the key Mustang needs from customers and then work backwards and then innovate on behalf of these workloads, be enabled by the sun oh four, which are some of the reasons that led to us launching some of the initial sets on dynamo on a single digit millisecond latency and seamless scale. At that time, databases didn't have the elasticity to go from like 10 requests, a second to like a hundred thousand or 1 million requests a second, and then scaled right back in an hour. So that was not possible. And we kind of enabled that. And that was an, a pretty big game changer that showed the elasticity of the cloud to a database. Well, >>Yeah, I think also just to, not to nerd out on this, but it enables a lot of other kind of cool scaled concepts, like queuing storage. It's all kind of together. This database piece of that you guys are solving. And again, props to you guys on the team. Congratulations. I have to ask, you know, more generally, how has your thinking changed since the paper? I'll see, you've got more experience under your belt. You don't yet have the gray hairs yet, but we'll see those soon come in, but you know, you're, you got a lot more experience. You're running teams, you're launching a lot of products. How has your thinking changed in the industry since the paper what's happening now? What's the big evolution. What are those new things now that are in the innovate on behalf of the customer? What's between the lines now, how do you see this happening? >>I mean, now since wanting dynamo via a victim, I had the opportunity to work on various problems in the big data space. There we've worked on some are fire things that you might be aware of in the analytics all the way from Redshift to quick side, too. Then I moved on to start some of our efforts, having built systems that enabled customer to store process and credit, and then analyze them. One of the realizations, I had this, the in around 2015 or 2016, I kinda had that machine learning was hitting a critical point where now it is ready for being scaled at option. Their cloud has basically enabled limitless compute and limitless storage, which are the factors that are holding back machine learning technology. Then I realized that now we have a unique opportunity to bring machine learning BI to everybody, not just folks with PhD in machine learning. >>And that's when I moved on from database and analytics areas, they started machine learning. We're just a descent area because machine learning is powered by data and then started building capabilities like SageMaker, which is our end to end ML platform to build, train and deploy them on models. And this, what does the leading enterprise platform by several gaggled users and then also a bunch of our AI services since then, I view the reason I'm giving all this historical context is one of the biggest realization I had early on itself. And 2016 as first machine learning is one of the most disruptive technologies. She will then country in our generation. This is right after cloud. I think these still are the most amazing combination that is going to revolutionize how we build applications and how we actually reason about that. Now, the second thing is that at the end of the day, when you look at the ANC and journey, it is not just about one database or one data Varroa. >>So one data lake product, or even 1:00 AM out platform. It is about the end to end journey where a customer is storing their order database. And then they are actually building a data lake that test customer history and order history. And they want to be able to personalize. And for their viewer experience are actually forecast what products to staff in their fulfillment center, but then all these things need to work and to handle. And that view is one of the big things that struck me for the past five years. And I've been on this journey in addition to building this Emma building blocks to connect the dots so that customers can go on this modern end to end data strategy as I call it, right. It goes beyond a single database technology or data technology, but putting now all of these end to end together so that customers don't end up spending six months connecting the dots, which has been the state of the down for the last couple of years. And we are bringing it down to matter of the Sundays. Now >>He's incredible Swami. Thank you so much for spending the time with us here in the, >>Yeah, my pleasure. Thanks again, Sean. Thanks for having me.

(bright upbeat music) >> Welcome back to theCube's coverage of AWS re:Invent 2021. This is "theCube". We go out to the events. We extract the signal from the noise. We're here at a live event, hybrid event, two sets. We had two remote studios prior to the event, over 100 interviews. Really excited to have George Elissaios here. He's the director of product management for EC2 Edge, really interesting topic at AWS. George, great to see you. Thanks for coming on. >> Yeah, great to be here. Thanks for having me. >> So, everybody's talking about Edge, IoT, EC2. What's the scope of your portfolio, your responsibility? >> Yeah, well, our vision here at AWS is to really bring the power of the AWS platform wherever customers need it. AWS wherever our customers want it is our long-term vision. And we have a bunch of products in this space that help us do that and help us enable our customers whatever their use case is. So we have things like Wavelength. I know we talked about Wavelength before here in "theCube", where we bring full AWS service at the edge of the 5G network, so with 5G edge computing in partnership with telcos worldwide, our partnership with Verizon in the US has been flourishing. We're up to, I think, 15 or more Wavelength zones right now in many of the major cities in the US, but also in Japan and Korea, and in Europe with Vodafone. So that's one of the portfolio kind of offerings. And that helps you as a customer of AWS if you want to have the best latency to mobile devices, whether they are sensors, or mobile phones, or what have you. But we're also feeling out that Edge portfolio with local zones. Earlier today in Werner's keynote, we announced that we're going to launch another 30 local zones in 20 new countries, everywhere from South America, Africa, Asia, Australia, and Europe, obviously. So a lot of expansion there. Very excited about that. And that is kind of a similar offering, but it basically brings you closer to customers in metropolitan areas over the internet. >> So, Wavelength's a big feature. George, I want to get just to touch on it because I think latency comes up a lot in Edge conversations, low latency issues, whether it's cars, factories. You guys gave a demo yesterday to the press corps in the press room, I was there, where you had someone in San Francisco from the Opera and someone in person here in Vegas, and you had 13 milliseconds going back and forth demoing, real time- >> Collaboration. >> The benefit of low latency in remote. It wasn't next door. It was San Francisco. This is kind of the purpose of what Edge is about. Can you explain what that means, that demo, why it was important, and what you were trying to show, and how does it mean for the Edge? >> So there is multiple use cases. One of them is human collaboration, right? Like, we spent the last two years of our lives over conferences and kind of like the teleconferences, and trying to talk over each other and unmute ourselves desperately. But existing solutions kind of work, generally, for most of the things that we do, but when it comes to music collaboration where milliseconds matter, it's a lot harder with existing solutions to get artists to collaborate when they're hundreds of miles away. Last night, we saw a really inspiring demo, I think, of how two top tier musicians, one located in San Francisco and one located in Vegas, can collaborate in opera, which is one of the most precise art forms in the music world. There are no beats in opera to kind of synchronize, so you really need to play off each other, right? So we provided a latency between them of less than 30 milliseconds, which translates, if you're thinking about audio or if you're thinking about the speed of sound, that's like being in the same stage. And that was very inspiring. But there's also a lot of use cases that are machine to machine communications, where even lower latencies matter, and we can think of latencies down to one millisecond, like single digit milliseconds when it comes to, for example, vehicles or robots, and things like that. So we're, with our products, we're enabling customers to drive down that latency, but also the jitter, which is the variation of latency. Especially in human communications, that is almost more important than latency itself. Your mind can adapt to latency, and you can start predicting what's going to happen, but if I'm keep changing that for you, that becomes even harder. >> Well, this is what I want to get to because you got outcomes and applications like this opera example. That's an application, I guess. So working backwards from the application, that's one thing, but now people are really starting to trying to figure out, "What is the Edge?" So I have to ask you, what is AWS's Edge? Is it Outpost, Wavelength? What do people buy to make the Edge work? >> Well, for us, is providing a breadth of services that our customers can either use holistically or combine multiple of those. So a really good example, for example, is DISH Wireless. I'm sure you know we're building with DISH the first in the world mobile network, 5G mobile network fully on cloud, right? So these combines Outposts and combines local zones in order to distribute the 5G network across nationwide. And different parts of their applications live in different edges, right? The local zone, the Outputs, and the region itself. So we have our customers... You know, I talked about how local zones is going to be, you know, in total, 45 cities in the world, right? We're already in 15 in the U.S. We're going to do another 30. But customers might still come, and say, "Oh, why are you not," you know, "in "in Costa Rica?" Well, we'll have Outposts in Costa Rica. So you could build your own offering there, or you could build on top of Outputs while you distribute the rest of your workload in existing AWS offering. So to answer your question, John, there is no single answer. I think that it is per use case and per workload that customers are going to combine or choose which one of- >> Okay, so let's go through local zones. Explain what a local zone is real quick. I know we covered it a bit last year with the virtual event, but local zones are now part of the nomenclature of the AWS language. >> Yes. >> And we know what a region is, right? So regions are regions. What's a local zone? >> When your region's saying new availability zones, and then we're just (chuckles)- >> You got availability zones. Now you got local zones. Take us through the topology, if you will, of how to think about this. >> Right, so a local zone is a fully-managed AWS infrastructure deployment. So it's owned and managed and operated by AWS. And because of that, it offers you the same elasticity, and security, and all of the goodies of the cloud, but it's positioned closer to your end customers or to your own deployment. So it's positioned in the local urban, metropolitan or industrial center closer to you. So if you think about the U.S., for example, we have a few regions, like, in the East Coast and in the West Coast, but now, we're basically extending these regions, and we're bringing more and more services to 15 cities. So if you are in Miami, there is a local zone there. If you are in LA, there is two locals zones actually in LA. That enables customers to run two different types of workloads. One is these distributed clouds or distributed Edge kind of workload that we've been hearing more and more about. Think of gaming, for example, right? Like, we have customers that are, like Supercell, that need to be closer to the gamers, wherever they are. So they're going to be using a bunch of local zones to deploy. And also, we have these hyper-local use cases, where we're talking, for example, about Netflix that are enabling in LA their creative artists to connect locally and get like as low as single millisecond latencies. So local zone is like an availability zone, but it's closer to you. It offers the same scalability, the same elasticity, the same security and the same services as the AWS cloud. And it connects back to the regions to offer you the full breadth of the platform. >> So just to clarify, so the Edge strategy essentially is to bring the cloud, AWS, the primitives, the APIs, to where the customers are in instances where they either can't move or won't move their resources into the cloud, or there's no connectivity? >> Right, we have a bunch of use cases where customers either need to be there because of regulation or because of some data gravity, so data is being generated in a specific place and you need to locally process it, or we'll have customers in this distributed use case. But I think that you're pointing out a very important thing, which is a common factor across all of these offerings. It's it is the cloud. It's not like a copycat of the cloud. It's the same API. It's the same services that you already know and use, et cetera. So extending the cloud rather than copying it around is our vision, and getting those customers who, well, connectivity obviously needs to be there. We were offering AWS Private 5G. We talked about it yesterday. >> Now, a premise that we've had is that a lot of Edge use cases will be driven by AI inferencing. And so... First of all, is that a reasonable premise, that's growing, we think, very quickly, and it has huge potential. What does the compute, if that's the correct premise, what does the compute look like for that type of workload? >> That is a great premise, and that's why we think that the model that we're offering is so powerful, because you have the Edge and the cloud fully cooperating and being connected together. You know, the Edge is a resource that's more limited than the full cloud in the AWS region. So when you're doing inferencing, what you really want to do is you want to train your models back up in the region where you get more scalability and the best prices. You know, you have the full scale of AWS. But for the latency-sensitive parts of your applications, you want to push those to the Edge. So when you're doing the actual inferencing, not the training of the models- >> Real time. Yeah. >> Real time, you push that to the Edge, whether that's if your connectivity is 5G, you can push that into a Wavelength zone. If your connectivity is wired, you can push it into a local zone. If you really need it to be in your data center, you can push it in your Outposts. So you see how our kind of like building out for all of those use cases. >> But in those instances, I'm interested in what the compute looks like, 'cause I presume it's got to be low power, low cost, super high performance. I mean, all of those things that are good for data-driven workloads. >> Right, the power, if we think here, is the same compute that you know and love in the cloud. So the same EC2 instance types, the EBS volumes, the S3 for storage, or RDS for your databases and EMR clusters. You can use the same service. And the compute is the same powerful all the way down from the hardware up to the service. >> And is the promise to customers that eventually those... It's not all of those services, right? I mean, you go to Outposts today, it continues to grow. >> Continuing to grow, yeah. Right, so but conceptually, as many services you could possibly push to the Edge, you intend to do so? >> We are pushing services according to customer requests, but also there is a nuance here. The nuance is that you push down the services that are truly latency-sensitive. You don't need to push everything down to the Edge when you're talking about latency- >> Like, what's an example of what you wouldn't push down? >> So management tools, right? So when you're doing monitoring and management, yeah, you don't need these to be at the Edge. You can do that, and you can scale that. Or, you know, batch processing, it doesn't have to be at the Edge because it's, by definition, not online, not like a latency service. So we're keeping those, like AWS Batch, for example, that's in the region because, you know, that's where customers really use it. But things like EC2, EBS, EMR, we're pushing those to the Edge because those are more- >> We got two minutes left. I want to get the Outposts kind of update. I remember when Outposts launched. It was really a seminal moment for re:Invent. Hybrid. "Oh, Andy Jassy said hybrid." Yeah. "I'll never say hybrid." But now hybrid's kind of translated into all cloud operations. Now you got local zones. A lot's changed from Amazon Web Services standpoint since Outposts launched. Local zones, things are happening. 5G, DISH. Now what's the status of Outposts? Are you guys happy with it? What has it morphed into? Is it still the same game? What is Outposts today, vis-a-vis what people may think it is or isn't? >> Yeah, we've been focusing in what we're talking about, building out a number of services that customers request, but also being in more and more places. So I think we're in more than 60, now, countries with Outposts. We've seen very good adoption. We've seen very good feedback. You know, half of my EBCs have been on Outposts, but this year, I think that one of the most exciting announcements were the Outposts servers. So the smaller form factors that enable an additional use cases, like for example, retail or even building your 5G networks. You know, one of our partners, Mavenir, is moving their 5G core, so the smarts of the network that does all the routing, on Outposts servers, and we can distribute those all over the place. So, we're keeping on the innovation. We're keeping on the expansion. And we've been getting very good customer feedback- >> So all steam ahead, full steam ahead? >> Full steam ahead plus 10%. (John laughs) >> All right, guys. Thank you so much, George. Really appreciate it. We're seeing the cloud expand. The definition is growing, kind of like the universe, John. Dave Vellante for John John Furrier. You're watching "theCube" at AWS re:Invent, the leader in high tech coverage globally. We'll be right back.

>>Welcome back to the cubes. Continuous live coverage of AWS reinvent 2021 live from Las Vegas. It's I'm Lisa Martin. And it's so great to say that we are doing with AWS and its massive ecosystem of partners. One of the most important hybrid tech events of the year. We've two sets over a hundred guests to remote studios, lots going on. I've got an alumni back with me and a new guest. Please. Welcome back. Sabina. Jo said the GM of technology partners at AWS and Neil Fowler joins her is the GM of micro-focus AMC. And you're going to tell me what AMC stands for >>Application modernization and >>Connectivity. I love it. Awesome guys. It's great. It's great to see you again in person. Thank you for having us. It's great to have the buzz. I know it's gonna be a little bit hard to hear, but great to have. AWS has done a phenomenal job of getting everyone in here safely. I want to give them kudos to that. So being to talk to me with, it's been a while since I've seen you in person, but talk to me about your current role at AWS. What's going on? >>Yeah, so I'm the general manager for technology partnerships globally out of the Americas. We also help partners out of EMEA and APAC grow in the Americas. And one of the great examples of a successful partnership is micro-focus with their solutions across application modernization security, database services, mainframes. >>And so from your perspective, through your lens, how do you think they're performing as a partner? Yes. >>So, um, first of all, kudos to Neil and the entire micro-focus team. They have done a great job leaning in with a cloud first strategy with SAS solutions on AWS and these solutions help customers across application modernization, application, delivery, security, cyber resiliency, database services, and also it performance management. And we've been working with them now for a few years. And in fact, today we have actually 400 customer wins together regulations and then also eight digit annual recurring revenue. They have six active listings in marketplace and all of this is really helping customers move their workloads and modernize their workloads into AWS. >>We've seen that such an acceleration nail in the digital transformation cloud adoption. The pandemic has really been a forcing function for that. There are some silver linings, but talk to me about some of the things that you've seen at micro-focus the last 20 months or so. And how have you helped those 400 customers, you know, getting to that big ARR, how are you helping them with that acceleration? >>Well, I think as you're saying that there's lots of changes in the last 12 to 18 months, some of it brought on by the pandemic and the change in business in business to having to respond, deliver solutions more quickly to the market, as well as remote working. So optimizing and the economic environment of costs, but being there to be more dynamic, it really has caused businesses to have to do something different than just to be able to survive and serve their customers better. That was a >>Big thing that we saw in the very beginning. It was not survival mode. And then of course it wasn't too long when we started seeing those survivors really start to thrive. And you started seeing who were going to be the winners of tomorrow. Cause the thing is every company, these days is a data company. If it's not, it's going to be passed up by competitor, that's right there in the rear view mirror. >>For sure. And so we've got, you know, organizations, so running mainframes, you know, older applications, legacy applications, modernization, where are most industries in terms of adopting that, the mindset, first of all, that they need to change? Well, I think across the whole industry, I mean, it doesn't matter whether it's retail. I mean, if you think about airlines with when the, when the pandemic hit business went down to, unless they've got that elastic nature of flashy to respond to it, but everyone had to bring in new services, new offerings very quickly. So the ability to be able to innovate in their environments and bring more solutions to their customers in a really fast way, you know, they couldn't just sit there and work with what they had. They had to move forward just to be able to stay in the business, but also be able to reduce the costs out of what they're trying to do. So running and transforming at the same time. >>Absolutely. And so how can organizations integrate existing core applications with new technologies to really be able to thrive in today's dynamic market? >>We look at modernization overall. We think of it in sort of three different ways with application process and infrastructure. So with a move to cloud, that's the infrastructure modernization they've immediately got far more access to more scalable dynamic elastic, compute resources, as well as all the technology platforms they have around. And then if you look at the application size and that's where the Microfocus platform comes in, we can help customers actually move those applications forward in terms of making them available through API APIs, maybe as a journey to microservices and cloud native. But once that core business logic and that data is available, it can be integrated into artificial intelligence machine learning and actually rained out the whole solution. So the final part of that from the process modernization, if you, as they're developing these applications with new tools, new ranges, in terms of where they can deploy on the AWS platform, they can automate the build deployment and operations so that all those existing applications and they were running on to contemporary platform with full access to the technologies that were available. >>That's fantastic and so necessary for businesses in any industry. So can you talk about some of the different business units of micro-focus? Are there any ones in particular that you want to call out? >>Yeah, so we work with them across all of their business units, but some of them that come to my mind is of course, Neil and team are doing a great job with application modernization and connectivity, really helping customers modernize the applications. And as customers are modernizing the applications, their cyber resiliency business unit is helping customers secure those applications. And then they also have their it operations management bridge product listed in marketplace. And then just since September are verdict a business unit launch Vertica accelerator on AWS. So I think they have a very holistic story to help customers >>On AWS. Talk to me a little bit, Neil, about cyber resiliency. We have seen such a dramatic change in cybersecurity in the threat landscape the last 20 months. I think I saw a stat recently that ransomware was up almost 11 X in the first half of 2021. Every, every day that companies had had a company, that data is gotta be secure. It's no longer a nice to have. That is a core requirement. How are you helping customers achieve that cyber? >>Well, the thing is, I mean, as you say, across the whole spectrum from cyber, from, from the identity access management through data encryption, through data protection, it's not, it's not a nice to actually say it's not a nice to have Kate take capability. You really have to have an integrated solution to be able to manage access control it, and also generating the events in terms of being able to, if anyone tries to get into the systems and log it because, you know, before, by the time you've discovered something it's too late, so you really need a combined solution for multi-factor authentication to really take it to that next level. >>Absolutely. Right. Once you've detected it, it's too late. And I mean, with ransomware as a service, cyber criminals are getting so much more sophisticated and also more brazen. There's so much money in it that the security front is, is I think even more interesting now than it's ever been. Talk to me about some joint customers and how you've helped them together with AWS with micro-focus achieve some of those key outcomes that you were talking about earlier. Well, I think >>Obviously with AWS as a platform has quite over a technology solutions going in, what we often find with our customers is a lots of, um, they're coming from an existing on-prem solution. So they need that hybrid model. So as part of taking that forward, been able to have that integrated solution that allows them to work both on-prem and as part of the cloud, most of it all being hooked up now, even that from even down to the, uh, as they're developing the applications now to do static code analysis, to help those applications be more secure with things like 40 pound demand, as well as integrating internet security platform for multifactor. So I think as you know, it's a combination of Brunel to bridge between all the different technologies, but have one single view of mail to protect the whole real estate, multiple layers for both external and internal threat. So that's, that's the other thing you also need to take into and can be able to protect all, all layers multi-layered approach. >>Absolutely. But you're right. The internal threats is something that we don't talk about as much, but that is obviously a substantial problem for organizations and most, if not any industries to be, to talk to me a little bit about, let's kind of get into the, the responsibilities that you have a little bit more in there. You've got responsibility for multiple solutions segments at AWS. You told me before we went live, you have 50 meetings this week. My goodness. And since day one, it taught all good. It's fun, fun. It is. Talk to me about AWS approach to partnering. What does it look like? What are some of the things that you think are really critical components? Yeah. >>So as you may have heard, we always start with the, at Amazon and AWS, we start with the customer. We work backwards when we are relaunching our products, our programs or services, you really go and ask the customers, what do you want us to develop? Where do you want us to focus the resources? It takes a lot of discipline to do that, but it's something that where we really want to walk the talk and we use the same approach with our partners when we started to work with micro-focus, we really kind of want to make sure that what we are working on together is what customers want, because we firmly believe that once you lay that foundation of that solution, you can scale your business a lot more quicker. Your story is a lot more simple and the customers are going to find a lot of value in what you are doing together. So it's really all about the customer for us. It is >>Absolutely critical, right? That's the whole point that the whole reason that we're here now, talk to me a little bit about maybe some cultural alignment with AWS, that customer first customer obsession. It sounds like at Microfocus, very similar. >>Absolutely. I mean, the way that we always think about how we're building our products, it's all around customer centric innovation. So that aspect of trying to make sure that we can solve what the business, understanding what the customers are trying to do to then help develop, to deliver solutions that meet that and that combination of a, the way that we look at it from that infrastructure modernization and the range of technologies that are available and that relentless focus on making customer successful is so key. But we have to make sure that that collaboration works together to make sure that the solutions align and we're helping customers get there together >>In your customer conversations. I imagine they've changed quite a bit during the pandemic with so many things being escalated to the C-suite to the board. How have your, how important is that cultural alignment between AWS and Microfocus from your customer's perspective? Is it something that comes up fairly often? Well, >>It's, it's a, I think it, when you actually get a mismatching culture, it's more obvious. So don't think that necessarily people are looking for it to say, I need organizations, but if you're not thinking the same way, you're not behaving the same way and actually partnering. I think that partnering part of it is really important because you're both working together to come up with that desired outcome. So I think it's more, more obvious when it isn't a good match as opposed to what it looking for that particular site. But I think that's a really key aspect in the sense of working together to help that customer be successful. >>Right? That's a great point that you bring up, but it's probably more obvious when it isn't working than when it's beautifully aligned, falling into place and really focused on that customer. So what are some of the things that attendees can, can feel and see and learn at the micro-focus booth at this year's reinvent nail, >>As well as obviously the key Roundup application modernization, where we're looking at the mainframe modernization on the site, we've got the full range of the Microsoft booth in terms of cyber resilience, as well as our, uh, item, my top, uh, it operations management or ADM portfolios. So we've got a lot of technologies which we can learn about in the booth interactive as well as all by experts to understand how we can do all these things and work together as part of the AWS platform to be able to deliver those solutions. >>Excellent. I'm sure there will be plethora of, of knowledge shared at the booth there. Last question, Neil, for you, talk to me about the vision going forward with the partnership. What are some of the things that you're looking forward to as we end 2021 and go into hopefully what is a better year, 2022? >>You know, one of the key things, you know, especially range, no one might, my passionate areas is helping our customers really look in terms of building the platform of the future. We can help solve their customer the problems today, but we're really trying to create that innovation platform to going through. So again, that combination of the technologies that we can bring to help our customers and the breadth and the investment that AWS continue making in the platform, those two combinations really helps us help our customers, not just solve today's problems, who really move into the forward to be the platform for innovation for the next decade. >>And that's really critical that that future ready state that is so undefined most of the time, I mean, none of us saw the pandemic coming, all right. That was a complete shock, but to be able to partner together, to help your customers really set up the foundation to be innovative as things happen that we can't even predict is really critical. So congratulations on your 400 customer wins your eight digit ARR. That's fantastic. Yes, we thank you so much for joining us on the queue, talking about the Microfocus AWS partnership and all of the successes that you guys have had. Great job. And I hope that you have cough drops and a lot of water this week. Sabina. I hope you do too guys. Thanks for joining me. Pleasure for my is I'm Lisa Martin. You're watching the cube, the global leader in live tech coverage.

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante full stack observability is the new buzz phrase as businesses go digital customer experience becomes ever more important why because fickle consumers can switch brands in the blink of an eye or the click of a mouse every vendor wants a piece of the action in this market including companies that have provided traditional monitoring log analytics application performance management etc and they're joined by a slew of new entrants claiming end invisibility across the so-called modern tech stack recent survey research from etr however confirms our thesis that no one company has it all new entrants they've got a vision and and they're not encumbered with legacy technical debt however their offerings are immature on the other hand established players with deep feature sets in one segment are pivoting through m a and some organic development to fill gaps meanwhile the cloud players are well positioned and participating through a combination of their own native tooling combined with strong ecosystems in their respective marketplaces to address this opportunity hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we dive into a recent etr drill down study on full stack observability and to do so we once again welcome in our colleague eric bradley chief engagement strategist and director of research at etr eric good to see you my friend thanks for coming on uh always good to be here dave thank you so much for having us we appreciate it all right before we get into the survey eric i i want to talk a little bit about full stack observability define what it is and so let me start and then you can chime in so when people talk about full stack observability they're referring to the need to understand the behavior of all the technology components that support an application i.e the stack right throughout the entire system meaning the full piece of the equation right the entire system so the compute we're talking about the storage the network and of course that's all software defined today the containers that are running the software the database other middleware components the pipeline of data and then of course the client-side code everything the html the css everything down to the mobile device and the idea is to give people who can fix problems full visibility into the system with a dashboard of metrics that can be visualized at a high level and then drilled into to see logs or traces or events all the metrics that could help remediate an issue so a simple way to think about this eric is i like to think of it as the ability to see everything in the tech stack that could impact the customer experience right how do you see it if only we're that simple right it's it's a huge thing that we're trying to encompass there with full stack observability and uh even though the vendors might tell you on the first sales call that they can do it it's really not that simple based on everything you just said um in this particular survey we tried our best to look at it and we'll go into it later but you know we had to survey on the application side infrastructure side database side blog management security network it's a very difficult thing to encompass um the holy grail would be able to do it with one vendor and do it with one dashboard i don't think we're there anytime soon all right so let's get into this drill down survey results and talk about what you've learned first what is explain what a drill down study is how often does etr conduct these types of things you know who responds what can you tell us yeah sure so the drill downs are actually basically think of it as a custom type of survey work and that could be customized from two different ways either our clients will come to us with a particular topic and we will hold their hands and make sure that they get the the responses that they need uh and more often than not it's actually us as a research department uh wanting to dig into trends that our larger data encompasses and then we'll say hey we really need to look into that and we've done it with everything from rpa to identity access to you know hearing observability and also vendor specific and and macro trends as you know david this particular one the genesis was really a large amount of interest not only from our community the end users but clients i i can't tell you how much interest there is in observability right now we're constantly getting questions and demands for more research and deeper research in this space yeah so our audience will be familiar with the concept of net score that's the periodic survey every quarter like clockwork etr does that then in addition as eric was saying hot topics like in this case full stack observability so we're talking about respondents in the etr community in this case who have a deep understanding of observability and related topics and and they had varying degrees of knowledge about each vendor's offering so you asked the respondents to concentrate on the ones that they knew well correct yes that is correct so this was a smaller survey that we did the end was a little under 188 i believe um and essentially what we did was we took people that responded in the bigger study on these observability vendors and then sent this drill down out so they were specifically people that have purview over their spend with observability now some of it might be more database infrastructure application or security but everyone here is already qualified as an expert to answer these questions that's correct dave yeah so the first data point is the one we're showing you right here the respondents were asked who uses observability tools and eric i've highlighted app ops in in the site reliability engineers because given the emphasis on customer centricity that we hear all the time from the vendor community you would think these roles would be more highly represented but it's the folks in the boiler room that are using these tools highly technical and specialized roles what are your thoughts on this data you know i was a little surprised as well i i kind of thought the sres would be a little bit higher on this but it really just comes down to you know it's the infrastructure um devops and secops that seem to be using it the most i thought maybe the application operations teams would be a little bit more involved as well so i agree with you i was a little bit surprised on this but you know they're the experts so we have to take the data at their word for it but i think what's really happening here is you're recognizing that the work is being done across the entire enterprise as you mentioned before about full stack this isn't just one aspect it's touching every aspect of the enterprise and that's including the internal i.t teams well and i think too eric that this what i took away from this drill down and we'll get more into it is that the vendor marketing is not aligned with what's actually happening in the field and so there's these early days we'll talk about that some more okay next question i thought this was very interesting etr asked on the scale of one to three three being most preferred which pricing model host-based user-based or amount of data ingested based pricing that the responders preferred and eric so what are your what are your thoughts on this because just doing a quick scan scan pricing is all over the map yeah it really is all over the map from a vendor perspective right and also from an end user perspective and all the interviews and panels that i host pricing's a real concern but it is always but in this particular field it's a real concern and i actually just did a panel yesterday of four of these 88 survey takers to get a little bit deeper so i'm going to kind of remark on what they taught me a little bit yesterday one of them said ingestion pricing might be preferable but because it's so unpredictable that's why we're seeing the results skew away from it another one went so far that said uh ingestion based pricing is a nightmare that keeps him up at night because he's just so afraid he's gonna wake up the next day and see what the bill is so um really what they're looking for here and the reason the pricing is skewing that way in this survey is because they need predictability it's about their budget and it's about their planning even though they would prefer an ingestion-based model the fact that they have to plan for their budgets and they have to concern themselves with spending it's moving more to host based yeah so i mean it is complicated and because so for example i just took a quick snapshot of some of the pricing models like dynatrace appd datadog aws and others they tout their host-based pricing new relic they have a splash page up around its user-based pricing and the tiers datadog talks about its ingestion-based pricing for security monitoring aws prices by ingestion for cloud watch logs splunk prices on index data and calculates a per gigabyte per day metric so metrics dashboards alarms alerts events it's they could all be priced differently yeah that's true a few that got called out on us and i'm sure we're going to get into them later so i don't want to you know kill all of our fodder right now but when we were talking about this slide one person particularly decided to call out new relic and specif specifically for their flexibility around pricing he said that they have the ability to rapidly scale up but also contract as needed and he actually even though he's a user of splunk he's a user of dyna trees user of elastic um he also just really wanted to call out the flexibility of new relic in this area so to your point there's a lot of different ways to price this it's a complex problem but i think the key takeaway for vendors is flexibility is the key you really need to give people the ability to be flexible in what they want all right let's drill into the functionality and explore the usage and adoption of the different features by the respondents so this next chart shows module adoption for application performance monitoring apm database and digital experience down to the user and eric i underlined apm which is the blue bar because it seems it stands out especially for aws and you can see dynast dyna trace but also azure new relic and splunk and then digital experience which is the gray bar because despite all the chatter in the market and the marketing around digital transformation and customer experience other than a slightly higher response percentage for aws not a lot of adoption on that front so the vendor marketing again doesn't match the user behavior does it eric no it doesn't there's a couple of things to point out here but let's stick with that digital experience i i was surprised that it was so low on this slide and overall in our survey i did expect it to be more and not just from the vendor marketing perspective but you and i both know at the end of the day the whole point of this is to actually get into that 360 view of what your customer's doing so i i was a little bit surprised to see it that low when we spoke to the panel yesterday a couple of people said no listen it's not that we aren't doing that it's just that it's not the vendors that you put on this survey and they called out two particular names one is called catchpoint and the other one is thousand dies and i think you're aware a thousand dice i'm going to transition that off to you there yeah so a thousand eyes is now part of cisco and we're gonna talk about that a little bit later but but essentially like as i was saying up front they've got gaps in their in their product line so they've got to do m a and then package that up so you know we'll we'll get into that a little bit down the road but i want to bring up the next graphic because that looks at incident management infrastructure monitoring and log management and and what i did here is i called out infrastructure monitoring which is the gray bar and log management that light blue because aws and azure they stand out in these categories and splunk of course eric for for log management what what do you take away from this data yeah the previous slide and this slide you really have to call out aws cloudwatch and microsoft is your monitor um they are very pervasive in this survey and we could probably do an entire show on just that on the cloud versus independent but a couple of things i do want to point out even though these numbers are so high for these cloud tools the the panelists and the people i spoke to in more detail all said listen i'm going to look at my cloud tools first i'm on their infrastructure they're handing it to me i'm going to look at it and i'll use it for what it's good for however we're in a multi-cloud world and they're not good at things that aren't in their ecosystem so these are not even though these numbers are high i do not believe that you know aws or azure is going to go and take over all the independents in a multi-cloud world they want an independent vendor whether it's a data dog new relic we could talk about all of those later but um you know really i was surprised that the aws particularly was so high and so pervasive in here across the way a splunk what can you say i mean they are the most pervasive vendor you know they they're everywhere uh we had people in the panel call them a swiss army knife and you know that's a good and a bad that they have a lot of breadth of coverage which is great but because there's a breadth of coverage not all of it is great log management without a doubt is what they are great at they're specialized at it but the panelists were saying listen if you go away from their core and you try to use some of the other things they claim that they can do it requires a lot of heavy lifting and then we can get into a little bit later about their cloud cloud sas integration we had some issues with that in the survey as well and great points about the multi-cloud you're probably not going to trust that to your your cloud your public cloud vendor and so a lot of white space available for the traditional on-prem guys okay next the etr survey drilled into network monitoring and security monitoring and then other security functions and eric there are a couple of things that stood out to me in this chart i highlighted security monitoring which is the blue bar because you can again see the adoption from aws and azure and of course splunk and also we called out solar winds because of the large adoption in network monitoring so let me ask you what are you seeing in the data since the solarwinds breach and is there anything else in this chart that you want to call out i could go on for a while about solarwinds but you know the data since i guess it broke around 12 months ago even though the breach was even prior to that uh the headlines were big i think you remember you and i last year did a quick drill down survey just on solarwinds uh and the impact that we thought we would have it uh there's a very real impact happening uh with that said they're not easy to move away from um we asked about is there any one vendor that could take this entire space and the answer was solar winds was best positioned to do that but it's too late now and then i drilled down a little bit and i asked the panel well what can they do to reinvent themselves what can they do to change the reputational damage from this breach and the panelists all said nothing the reputational damage is done the best way for them to reinvent themselves would be to do an m a consolidate with somebody else change their name they truly believe that right now the only reason that people are still using solarwinds is it's not that easy to lift and shift away from but there will be no new net workloads going to these people at least according to the the ones who took our survey um that's on solar winds and we could get you know in more if you want but i think that's kind of you know giving the the the crux of the matter on splunk again what can you say on the security side on the sim side people don't want to use multiple vendors on the other side we were talking about with full stack some might be better at apm some might be better at infrastructure monitoring when you're talking about security you truly do want one vendor to rule them all and splunk does seem to be the one that's most well entrenched on the security side and as long as the policy is consistent across security you really can't say much about them so what they do well their core their the data shows that you know people still trust them great thank you for that okay now the last set of data we want to show we kind of consolidated some things you want the the detail and the drill down you had several drill down questions and what we try to do is consolidate them into a single chart which we had to stare at for a while so for each of the 11 companies etr asked respondents if the features across the top that you see here were strengths weaknesses or neutral and what we've done is we tried to consolidate the chart showing the strengths in the green which we just subjectively said okay that means more than 40 percent of the respondents identified the feature as a strength the weaknesses in yellow meant that more than 20 percent of the respondents cited the feature as a weakness and the neutrals in the gray where neither of those conditions were met but the gray was you know the neutral was high and what we did is we added four stars for standout features where 60 or more of the respondents cited the feature as a strength and we threw in two stars if they were close to 60 you know high 50s even mid 50s but but not single digit weakness for that feature that was got two stars so it was able to sort of visualize a lot of data so eric just a quick scan of this chart chart shows that the two big cloud players aws in particular but also azure they have a relatively strong showing and i say relatively because as you know eric there wasn't a single category of feature for any vendor where more than 70 percent of the respondents cited the strength for that single feature not one and there was a lot of gray and you can see pricing is a sore point for many customers including those evaluating solarwinds new relic elastic datadog dynatrace appd and splunk only aws and grafana were hit not hit hard on pricing and i guess the other thing that stands out to me here is that new relic eric showed some relative strength so the last thing i'll mention before you dive in look at what cisco is doing we talked about this before a little bit the drill down focused on appd but as i mentioned earlier companies that have mature stacks are filling the gaps so if you look at what cisco's doing this space they've put an interface layer over appd inner site and thousand eyes even though they're separate products they're historically priced separately i think they're still trying to figure out the pricing but they are definitely going to market with a strategy that bolts together these three separate products and that's not necessarily a bad strategy because combined they can claim even more depth and breadth eric what do you make of this data yeah just like this chart there is a lot there right so uh on a macro level let's just the obvious situation here is this is a crowded crowded marketplace and consolidation is needed i had one panelist say to me yesterday i can't wait for this to consolidate like this is just crazy that there needs to be consolidation uh now to your point about cisco cisco's taking the same playbook they did with security right they're going out and they're buying great tools and then now we have to make sure that they figure out a way to integrate these better uh the security side took them a little while to do that but they're getting there hopefully they can do this a little bit quicker here what we did here is that um appd is actually very strong on the application monitoring side for the core apm uh maybe not so much on these others and then that's why they go out and do what you're doing what you're saying about now so hopefully they will get there um kind of talking across the board pricing was a problem for all of them right so it just seems to me that you know the end users the buyers just feel like hey i shouldn't be paying this much for this we've got a lot of choices maybe there's some collusion on the pricing side but we have to figure it out because they do not want to pay this much for it it was the number one concern across almost every single vendor another aspect that i really want to call out on this and is something that our research team found really interesting and it's really about the digital transformation as digital transformation continues the workloads are moving towards the cloud and we're clearly seeing in this data that that's benefiting the newer players the data dogs and the new relics versus some of the others like a dynatrace and a splunk and when you go and actually look at the cloud sas integration answer option specifically it becomes very very obvious um you know splunk had a 38 on that number whereas datadog had 61 new relic at 58. so it's just very clear as a digital transformation increases workloads on observability it is lifting all boats but it's lifting some faster than others great points um all right as we said at the top you've got a set of incumbents they're jockeying for position you've got companies like datadog it's got as eric just mentioned strong cloud model elastic's got got the open source mojo and they're going after splunk's install base as is datadog and then you see startups like chaos search they're out now talking about how to do log analytics they do more than that but that's their sort of starter use case and they're going after the elastic and the elk stack which got dinged a bit in the survey on simplicity uh you know ease of standing it up and and so forth not a weakness if you're comfortable with full open source model but maybe not well understood as some of the other solution oriented plays and then you got other new entrants which are not covered in the drill down they're not as pervasive in the marketplace but guys like honeycomb and observe eric you mentioned some others that came out in the panel vmware even is getting into the act they're positioning tanzu around observability with really a strong kubernetes emphasis and there's dozens of other players in the space which we haven't talked about so eric this is jump ball and i'll give you the final word give us your last thoughts yeah there's a again a lot there it's such an interesting space like even ibm right they go out and buy turbonomics right everyone seems to be playing and not only that the ones that are already playing are expanding data dog comes out and says hey we do security now so i don't really know where this is going to end but there's too much happening there needs to be some sort of you know order out of the chaos uh to your point about some of the emerging names we just launched our emerging technology survey this week david those are the ones where we're going to see data on those names so stay tuned for that we don't track them in the core tsis which are more mature public vendors but we will be getting some data on those uh but to your point i really do believe that this space is rapidly expanding and i just kind of want to leave everyone with this there's a lot of growth still left in the panel yesterday i basically said to people how much of your infrastructure are you monitoring today versus how much you want to and the answer was around 65 to 70 percent being monitored now and without a doubt they all want to get to 100 so there is still a lot of room to grow in this space but i just don't know if there's enough room for all of these people that are basically going after the same percentage points so what we're seeing from a vendor strategy now is bundling they're trying to bundle because that's the way they're gonna actually gain that market share right and uh just one last point to you for elastic a lot of people still view elastic as a search functionality so even though they have use cases and observability i still think there's a lot of people that the elastic got into the elk stack in general got into their enterprise for search so that is still kind of where they are and maybe they're not moving as fast as a data dog or a new relic in pure full stack observability eric so great to have you on you guys cover so much space so we're gonna leave it there for now we really appreciate our friends at etr for the the work that they do and thank you eric for joining us today and sharing your insights great stuff welcome dave i always enjoy talking to you you know that and uh everyone else we'll be back in a couple of months with our predictions as well so yeah that's right yeah look for those all right remember these episodes are all available as podcasts wherever you listen all you gotta do is search breaking analysis podcast check out etr's website etr dot plus they've got a whole new packaging and and pricing models so check that out we also publish a full report every week on wikibon.com and siliconangle.com and you can get in touch with me david.velante at siliconangle.com or at divalante on twitter i'm on linkedin all the time this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well and we'll see you next time you

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante recent earnings reports from key enterprise software and infrastructure players underscore that tech spending remains robust in the post isolation economy especially for those companies that have figured out a cloud strategy now despite covert variant uncertainties and component shortages and hardware most leading tech names outperformed expectations this past week that said investors were not in the mood to reward all names and any variability in product mix or earnings outlook or other nuances were met with a tepid response from the street hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll provide you with commentary and data points on key tech companies that announced this past week including snowflake salesforce workday splunk elastic palo alto networks vmware dell pure storage hp inc and netapp let's start by rolling back a week or so and look at how stocks that are priced to perfection get impacted by any negative news back on august 20th we saw this headline hit snowflake stock falls as analyst says signings growth has slowed the analyst report was put out by a boutique firm cleveland research the stock took a double-digit hit as you can see here i immediately got several texts from investors who know i follow the company asking me what i thought now as a disclaimer i don't give stock picking advice please do your own research but between the cube wikibon and etr we do see a lot of data and i'm happy to share that which i did with this tweet it said lots of talk ahead of snowflake's earnings some analysts have said their data suggests a slowdown etr data looks pretty encouraging and i tagged merv adrian he's a sharp analyst over at gartner who follows data and database he responded i don't speculate about revenues but there's no discernible shift in our client conversations though interest still seems high okay cool but let's let's dig into the etr data a bit and see why we remained positive this is a larger and more detailed version of the chart in the tweet it's a candlestick that shows a time series of the spending data on snowflake using etr's net score methodology the stacked bars represent the percent of customers in the survey that are newly adding the snowflake platform the forest green indicates the number of customers reporting that their spending is increasing by six percent or more the gray is flat spend that's plus or minus five percent the pinkish stack that's decreasing spend by six percent or more and the bright red is where chucking the platform we're leaving now you subtract the reds from the greens and that yields a net score which for snowflake last survey was a very elevated 81.3 percent we've highlighted the spending velocity line that's net score at the top put a picture of that blue line for snowflake in your mind because we're going to come back to it the yellow line down below is market share which is a measure of the pervasiveness in the survey i.e mention share if you will so looking at this chart one might conclude that the lime green i.e new account acquisition is compressing however in further analyzing the data back in january 2019 snowflake's presence in the survey was much lower only 35 accounts in subsequent quarters that number has jumped to over between 120 and 140 snowflake accounts so big much bigger n so while the percentage of respondents may be shrinking the absolute number of new accounts is growing on the snowflake earnings call snowflake said that new customers increased this past quarter to 458 up from 397 in the same period last year what's also telling is the forest green on its very first earnings call as a public company snowflake cfo mike scarpelli said very clearly the company's revenue growth in the near term will come from existing customers and the forest green i.e existing customers spending more is expanding in the etr survey so very strong confirmation of that trend and note the red is virtually non-existent for snowflake so it's no surprise that snowflake handily beat its earnings on the 25th of august which prompted a flurry of texts to me saying you were right thanks don't thank me do your own research we're just one data source okay so here's a snapshot of some of the major players that announced earnings this past week this chart is our popular xy view with net score or spending momentum on the vertical axis and market share or pervasiveness in the survey in the horizontal plane we talked about snowflake already but i'll emphasize they've held that roughly eighty percent net score for ten plus quarterly surveys now and they've continued to move steadily to the right on the horizontal axis let's make some comments on these other names and then dig in a bit more salesforce of course they're the big player amongst these names that we're showing and as we've said in previous breaking analysis segments they have become the next great software company showing 20 plus growth for five consecutive quarters which is quite impressive splunk as we've reported has struggled in the survey but you can see splunk has a great presence in the data set they have an awesome customer base and the acquisition of signal fx plotted on the left with an elevated next net score represents a really good opportunity to enter new markets like observability and pull signalfx to the right to the rest of splunk's customers and that can help accelerate splunk's move toward a subscription model then there's workday we're plotting the company's core hcm business as well as its emerging financial software suite the latter represents workday's tam expansion opportunity and the company appears to be back on track to show sustained growth now let's dig a little deeper into these names and we'll start with salesforce here's the etr spending profile for salesforce salesforce as we showed earlier has a huge and growing presence in the market and a consistently elevated net score in the etr data and while the chart shows much more green than red and a strong uptick in spending momentum from last october survey this doesn't really tell the whole story salesforce's stock price rocketed out of the march 2020 crash and ran up to a peak last august and is on its way back salesforce has made a number of strategic acquisitions including tableau slack mulesoft and several other billion dollar plus buys as well as a number of smaller acquisitions this past quarter saw 23 revenue growth relative to last year with 20 percent plus operating margins that's huge salesforce's acquisition strategy is beginning to demonstrate the company's promised operating leverage and slack in our view will only add to that benefit including continuous improvement and free cash flow sales force revenue will blow through 25 billion dollars this fiscal year it's a company with a 250 billion dollar market cap and appears to be one a name that has meaningful upside opportunity okay let's take a quick look at splunk we're finally seeing an uptick in splunk's spending momentum with within the etr data set eric bradley and i have discussed this in previous breaking analysis segments the key point as we've reported is we see splunk as a company that has been in transition from a traditional license to an arr subscription model and finally the company is showing clarity that there's light at the end of that tunnel investors don't like companies in transition and like salesforce splunk's stock price ran up to an all-time high last august but then came down hard and never fully recovered but it has come off its may lows and there were some real positives this past quarter cloud annual recurring revenue for splunk this past quarter grew 72 percent and its bookings grew 20 29 year on year the company was conservative in its guidance and there still seems to be some uncertainty around cash flow but more clear guidance by splunk on the top line is a welcome sign and now another name that we've been following that announced earnings this week is elastic and as you can see by the etr data that company has an elevated net score with very little red in the bars now note that blue line while it's slowly decelerating it remains very strong and elevated remember the comment earlier i made about freezing that snowflake blue line in your head the reason we said that is because for snowflake to hold its roughly 80 net score position firmly over the past 10 plus quarters is quite astounding and for the most part it's unprecedented in the etr data set in recent memory back to elastic the company grew its top line by 45 which is a healthy beat and that helped operating margins come in above expectations elastic has become the open source poster child for observability but customers often cite challenges related to complexity and scaling with the need often to seek professional services help which sometimes impacts adoption and cost obviously but overall very strong report especially in its cloud business which grew 89 relative to last year all right let's pivot to infrastructure we're going to do that with palo alto networks and then look at a broader more traditional hardware and software players in february of 2020 we reported the valuation of divergence between palo alto networks and fortinet and we cited the challenges that palo alto was having around its shift to cloud that was a clear headwind at the time especially with regard to some of its go to market challenges at the same time we said that we were confident that palo alto would work through these issues and the csos from the etr panels along with other anecdotal information from the cube community suggested that the company would power through these problems well it has palo alto has a huge presence in the market and consistently elevated net scores as you can see here palo alto stock is trading near all-time highs and it reacted very well to its uh to the earnings report this past week where revenue grew nicely at 20 28 year on year the company has consistently impressed despite some hiccups of the past and appears to be well positioned for the emerging hybrid work economy okay now let's take a look at some of the key infrastructure players that announced this past week this chart shows our popular xy view with netscore spending momentum on the vertical axis and market share and or pervasiveness on the horizontal axis we'll start with vmware it has the biggest presence in the market amongst these names vmware's revenue grew nine percent in the quarter which was in line with estimates the company had a solid quarter but only marginally beat expectations and the stock got hit hard it was down 8 percent midday on friday vmware cited stronger than expected perpetual license sales and somewhat softer sas subscription revenue now it's not surprising that we're going to see some lumpiness in those two lines as the company transitions to a subscription model but investors clearly want to see more growth in sas and subscriptions than they do in the traditional perpetual license model vmware cloud on aws grew 80 and that's confirmed in the data here compute was also strong one concern in the etr data is the vmware cloud which is the the core the vm vmr cloud foundation vcf which you can see here is well off its january net score highs now it's possible the etr is picking up some of the conservative clients that don't want to move to an ar or subscription model it's unclear but we'll continue to watch that trend overall vmware's business model is solid in our view and very very strong now let's talk about dell next dell in our view had a great quarter it grew top-line revenues by 15 year-on-year its client business grew 27 percent and you can see the elevated dell laptop net net scores in this chart the isg business was up three percent that comprises service and networking which was up six percent and storage which was off one percent the storage business contin continues to struggle but management reported that its mid-range storage revenue was up 17 now the challenge here is that high-end storage it's cyclical it's exposed sometimes you know somewhat to mainframe cycles but but but but the other thing is that a lot of the mid-range capability is eating away at the high end not the least which by the way is is pure storage competing at the higher end but also dell's own mid-range business so that continues to be a drag on revenue the the size of the traditional high-end business that that v-max power max business still is is is quite large and the the new is not growing fast enough to offset the decline in in the old but i mean i saw these numbers from dell i was surprised to see the stock down nearly five percent at midday on friday and i think what's happening is a couple things one is that hpq hp inc which we show here at a lower net score than dell's laptop business cited supply chain issues and component shortages now dell cited the same but maybe it's off on sympathy it's clear to us that dell is doing a much better job than hp with regard to managing component shortages the frustrating thing for these companies is it might be a 50 part holding up a server or in dell's case or a laptop in dell and hpq's case but demand is good which is a positive but the biggest factor in dell stock price we think is it's getting dragged down with vmware in a way if you think about it with vmware's value comprising so much of dell's market cap being down only four percent while vmware is down eight percent implies that the core dell business is viewed positively by the street but i thought with the vmware spin coming later this year investors might gravitate more aggressively toward dell but that didn't happen maybe over time now you see netapp on the chart netapp beat on top line revenue and earnings this past quarter however the company has not performed well in the etr surveys for several quarters and has a negative net score this is due when you tear apart the the math this is due to a low number of new adoptions and a fat middle very big fat middle of flat spending and a pretty high churn in the data set now the company claims they've picked up 1500 new customers in its cloud business so maybe maybe the etr survey is not picking that up or perhaps it's existing customers that are moving to netapp's cloud service that they're counting as new that's unclear but netapp claims that its public cloud business grew 155 in the quarter regardless the street likes netapp's story the stock has been acting very well this year out passing outpacing the s p 500. now you also see pure on the chart with a nicely elevated net score the company beat top and bottom lines this quarter and its ceo charlie giancarlo promised roughly 20 percent revenue growth going forward the street sure liked that that story and the stock shot up nearly 20 percent on that news and you can see here a little drill down the etr spending data trends in the right direction for pure to support this momentum pure's messaging is all around a modern data platform and it's clear from customer conversations that its storage products are easier to use than traditional storage offerings and it has a leg up on the as a service trend which we've been reporting on which pure has been pursuing for a number of years but it's still a much smaller player a couple billion dollars than the dells and the netapps of the storage world but if it can continue on a strong growth trajectory it will of course become a larger custom company the question will be how to continue to expand its total available market now the obvious path has been share gains which over the years it has accomplished and has served them well but that won't be as easy as it was last decade when pure caught emc and netapp flat-footed without strong flash array strategies pure's port works acquisition is something to watch as well as it tries to transition the market to a true cloud-like program programmable infrastructure model infrastructure as code and we'll leave you with this thought about the infrastructure space generally in storage specifically while cloud storage has exploded over the past several years on-prem storage has been extremely soft this in our view has been due to the double whammy that we've reported the combination of cloud stealing share from on-prem and the big flash injection in other words the latter suppressed the need to buy more spinning spindles and controllers for better performance and it hurt demand you don't need to do that when you have all this flash headroom but as we predicted last year we believe that there's pent up demand as people go back to work and headquarters need refresh there's only so much blood that it managers can squeeze from the stone moving storage around optimizing servers and and improving things like utilization while at the same time maintaining adequate performance and doing so within some kind of reasonable window of a day storage is no longer monolithic there are emerging use cases especially ones that are data intensive different storage types are emerging as satya nadella said recently we've reached peak centralization and as such that will create tailwinds for storage offerings that can accommodate cloud and on-prem because it pros understand that moving data is expensive and risky it's best to keep data where it belongs for reasons of performance and of course compliance so it looks like there's a decent chance that the long storage winter is over and the market could return to solid growth even the face of a continued cloud explosion now to circle back quickly to the enterprise software business there seems to be no end in sight to the shift to cloud-based offerings both sas and snowflake-like consumption models of which we're big believers digital transformation initiatives are real they're meaningful and software spending we believe is going to be robust and power these transformations for quite some time okay that's it for today remember these episodes are all available as podcasts all you got to do is search breaking analysis podcast we publish each week on wikibon.com and siliconangle.com you can reach me at divalante on twitter or my linkedin posts or email me at david.vellante siliconangle.com please do check check out the etr website at etr.plus and see their new data packages and offerings for all the survey data this is dave vellante for the cube insights powered by etr thanks for watching everybody be well and we'll see you next time [Music] you

>>President. >>Hello everyone and welcome to wien on 2021. My name is Dave Volonte and you're watching the cubes continuous coverage of the event. You know, VM is a company that made its mark riding the virtualization wave, but quite amazingly has continued to extend its product portfolio and catch the other major waves of the industry. Of course, we're talking about cloud backup. SaS data protection was one of the early players there making moves and containers. And this is the VM on power panel with me or Danny Allen, who is the Ceo and Senior vice president of product strategy at VM. Dave Russell is the vice President of enterprise Strategy, of course, said Vin and Rick Vanover, senior director of product strategy at VM. It's great to see you again. Welcome back to the cube. >>Good to be here. >>Well, it had to be here. >>Yeah, let's do it. >>Let's do this. So Danny, you know, we heard you kind of your keynotes and we saw the general sessions and uh sort of diving into the breakouts. But the thing that jumps out to me is this growth rate that you're on. Uh you know, many companies and we've seen this throughout the industry have really struggled, you know, moving from the traditional on prem model to an an A. R. R. Model. Uh they've had challenges doing so the, I mean, you're not a public company, but you're quite transparent and a lot of your numbers 25% a our our growth year of a year in the last quarter, You know, 400,000 plus customers. You're talking about huge numbers of downloads of backup and replication Danny. So what are your big takeaways from the last, You know, 6-12 months? I know it was a strange year obviously, but you guys just keep cranking. >>Yeah, so we're obviously hugely excited by this and it really is a confluence of various things. It's our, it's our partners, it's the channel. Um, it's our customers frankly that that guide us and give us direction on what to do. But I always focus in on the product because I, you know, we run product strategy here, this group and we're very focused on building good products and I would say there's three product areas that are on maximum thrust right now. One is in the data center. So we built a billion dollar business on being the very best in the data center for V sphere, hyper V, um, for Nutanix, HV and as we announced also with red hat virtualization. So data center obviously a huge thrust for us going forward. The second assess Office 3 65 is exploding. We already announced we're protecting 5.8 million users right now with being back up for Office 3 65 and there's a lot of room to grow there. There's 145 million daily users of Microsoft teams. So a lot of room to grow. And then the third areas cloud, we moved over 100 petabytes of data into the public cloud in Q one and there's a lot of opportunity there as well. So those three things are driving the growth, the data center SaAS and cloud >>Davis. I want to get your kind of former analyst perspective on this. Uh you know, I know, you know, it's kind of become cliche but you still got that D. N. A. And I'm gonna tap it. So when you think about and you were following beam, of course very closely during its ascendancy with virtualization. And back then you wouldn't just take your existing, you know, approaches to back up in your processes and just slap them on to virtualization. That that wouldn't have worked. You had to rethink your backup. And it seems like I want to ask you about cloud because people talk about lift and shift and what I hear from customers is, you know, if I just lift and shift to cloud, it's okay, but if I don't have a plan to change my operating model, you know, I don't get the real benefit out of it. And so I would think back up data protection, data management etcetera is a key part of that. So how are you thinking about cloud and the opportunity there? >>Yeah, that's a good point, David. You know, I think the key area right there is it's important to protect the workload of the environment. The way that that environment is naturally is best suited to be protected and also to interact in a way that the administrator doesn't have to rethink, doesn't have to change their process so early on. Um I think it was very successful because the interface is the work experience looked like what an active directory administrator was used to, seeing if they went to go and protect something with me where to go recover an item. Same is true in the cloud, You don't want to just take what's working well in one area and just force it, you know, around round peg into a square hole. This doesn't work well. So you've got to think about the environment and you've got to think about what's gonna be the real use case for getting access to this data. So you want to really tune things and there's obviously commonality involved, but from a workflow perspective, from an application perspective and then a delivery model perspective, Now, when it comes to hybrid cloud multi cloud, it's important to look like that you belong there, not a fish out of water. >>Well, so of course, Danny you were talking to talking about you guys have product first, Right? And so rick your your key product guy here. What's interesting to me is when you look at the history of the technology industry and disruption, it's it's so often that the the incumbent, which you knew now an incumbent, you know, you're not the startup anymore, but the incumbent has challenges riding these these new waves because you've got to serve the existing customer base, but you gotta ride the new momentum as well. So how rick do you approach that from a product standpoint? Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business and the new business. So how do you adapt from a product standpoint? >>Well, Dave, that's a good question. And Danny set it up? Well, it's really the birth of the Wien platform and its relevance in the market. In my 11th year here at Wien, I've had all kinds of conversations. Right. You know, the perception was that, you know, this smb toy for one hyper Advisor those days are long gone. We can check the boxes across the data center and cloud and even cloud native apps. You know, one of the things that my team has done is invest heavily in both people and staff on kubernetes, which aligns to our casting acquisition, which was featured heavily here at V Mon. So I think that being able to have that complete platform conversation Dave has really given us incredible momentum but also credibility with the customers because more than ever, this fundamental promise of having data backed up and being able to drive a recovery for whatever may happen to data nowadays. You know, that's a real emotional, important thing for people and to be able to bring that kind of outcome across the data center, across the cloud, across changes in what they do kubernetes that's really aligned well to our success and you know, I love talking to customers now. It's a heck of a lot easier when you can say yes to so many things and get the technical win. So that kind of drives a lot of the momentum Dave, but it's really the platform. >>So let's talk about the future of it and I want all you guys to chime in here and Danny, you start up, How do you see it? I mean, I always say the last 10 years, the next 10 years ain't gonna be like the last 10 years whether it's in cloud or hybrid et cetera. But so how Danny do you see I. T. In the future of I. T. Where do you see VM fitting in, how does that inform your roadmap, your product strategy? Maybe you could kick that segment off? >>Yeah. I think of the kind of the two past decades that we've gone through starting back in 2000 we had a lot of digital services built for end users and it was built on physical infrastructure and that was fantastic. Obviously we could buy things online, we could order close we could order food, we we could do things interact with end users. The second era about a decade later was based on virtualization. Now that wasn't a benefit so much to the end user is a benefit to the business. The Y because you could put 10 servers on a single physical server and you could be a lot more flexible in terms of delivery. I really think this next era that we're going into is actually based on containers. That's why the cost of acquisition is so strategic to us. Because the unique thing about containers is they're designed for to be consumption friendly. You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. You can move it >>from on >>premises if you're running open shift to e k s a k s G k E. And so I think the next big era that we're going to go through is this movement towards containerized infrastructure. Now, if you ask me who's running that, I still think there's going to be a data center operations team, platform ups is the way that I think about them who run that because who's going to take the call in the middle of the night. But it is interesting that we're going through this transformation and I think we're in the very early stages of this radical transformation to a more consumption based model. Dave. I don't know what you think about that. >>Yeah, I would say something pretty similar Danny. It sounds cliche day valenti, but I take everything back to digital transformation. And the reason I say that is to me, digital transformation is about improving customer intimacy and so that you can deliver goods and services that better resonate and you can deliver them in better time frame. So exactly what Danny said, you know, I think that the siloed approaches of the past where we built very hard in environments and we were willing to take a long time to stand those up and then we have very tight change control. I feel like 2020 sort of a metaphor for where the data center is going to throw all that out the window we're compiling today. We're shipping today and we're going to get experience today and we're going to refine it and do it again tomorrow. But that's the environment we live in. And to Danny's point why containers are so important. That notion of shift left meaning experience things earlier in the cycle. That is going to be the reality of the data center regardless of whether the data center is on prem hybrid cloud, multi cloud or for some of us potentially completely in the cloud. >>So rick when you think about some of your peeps like the backup admit right and how that role is changing in a big discussion in the economy now about the sort of skills gap we got all these jobs and and yet there's still all this unemployment now, you know the debate about the reasons why, but there's a there's a transition enrolls in terms of how people are using products and obviously containers brings that, what what are you seeing when you talk to like a guy called him your peeps? Yeah, it's >>an evolving conversation. Dave the audience, right. It has to be relevant. Uh you know, we were afforded good luxury in that data center wheelhouse that Danny mentioned. So virtualization platform storage, physical servers, that's a pretty good start. But in the software as a service wheelhouse, it's a different persona now, they used to talk to those types of people, there's a little bit of connection, but as we go farther to the cloud, native apps, kubernetes and some of the other SAAS platforms, it is absolutely an audience journey. So I've actually worked really hard on that in my team, right? Everything from what I would say, parachuting into a community, right? And you have to speak their language. Number one reason is just number one outcomes just be present. And if you're in these communities you can find these individuals, you can talk their language, you can resonate with their needs, right? So that's something uh you know, everything from Levin marketing strategy to the community strategy to even just seating products in the market, That's a recipe that beam does really well. So yeah, it's a moving target for sure. >>Dave you were talking about the cliche of digital transformation and I'll say this may be pre Covid, I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, but then the force marks the digital change that uh and now we kind of understand if you're not a digital business, you're in trouble. Uh And so my question is how it relates to some of the trends that we've been talking about in terms of cloud containers, We've seen the SAs ification for the better part of a decade now, but specifically as it relates to migration, it's hard for customers to just migrate their application portfolio to the cloud. Uh It's hard to fund it. It takes a long time. It's complex. Um how do you see that cloud migration evolving? Maybe that's where hybrid comes in And again, I'm interested in how you guys think about it and how it affects your strategy. >>Yeah. Well it's a complex answer as you might imagine because 400,000 customers, we take the exact same code. The exact same ice so that I run on my laptop is the exact same being backup and replication image that a major bank protects almost 20,000 machines and a petabytes of data. And so what that means is that you have to look at things on a case by case basis for some of us continuing to operate proprietary systems on prem might be the best choice for a certain workload. But for many of us the Genie is kind of out of the bottle with 2020 we have to move faster. It's less about safety and a lot more about speed and favorable outcome. We'll fix it if it's broken but let's get going. So for organizations struggling with how to move to the cloud, believe it or not, backup and recovery is an excellent way to start to venture into that because you can start to move data backup ISm data movement engine. So we can start to see data there where it makes sense. But rick would be quick to point out we want to offer a safe return. We have instances of where people want to repatriate data back and having a portable data format is key to that Rick. >>Uh yeah, I had a conversation recently with an organization managing cloud sprawl. They decided to consolidate, we're going to use this cloud, so it was removing a presence from one cloud that starts with an A and migrating it to the other cloud that starts with an A. You know, So yeah, we've seen that need for portability repatriation on prem classic example going from on prem apps to software as a service models for critical apps. So data mobility is at the heart of VM and with all the different platforms, kubernetes comes into play as well. It's definitely aligning to the needs that we're seeing in the market for sure. >>So repatriation, I want to stay on that for a second because you're, you're an arms dealer, you don't care if they're in the cloud or on prem and I don't know, maybe you make more money in one or the other, but you're gonna ride whatever waves the market gives you so repatriation to me implies. Or maybe I'm just inferring that somebody's moved to the cloud and they feel like, wow, we've made a mistake, it was too fast, too expensive. It didn't work for us. So now we're gonna bring it back on prem. Is that what you're saying? Are you saying they actually want their data in both both places. As another layer of data protection Danny. I wonder if you could address that. What are you seeing? >>Well, one of the interesting things that we saw recently, Dave Russell actually did the survey on this is that customers will actually build their work laid loads in the cloud with the intent to bring it back on premises. And so that repatriation is real customers actually don't just accidentally fall into it, but they intend to do it. And the thing about being everyone says, hey, we're disrupting the market, we're helping you go through this transformation, we're helping you go forward. Actually take a slightly different view of this. The team gives them the confidence that they can move forward if they want to, but if they don't like it, then they can move back and so we give them the stability through this incredible pace, change of innovation. We're moving forward so so quickly, but we give them the ability to move forward if they want then to recover to repatriate if that's what they need to do in a very effective way. And Dave maybe you can touch on that study because I know that you talked to a lot of customers who do repatriate workloads after moving them to the cloud. >>Yeah, it's kind of funny Dave not in the analyst business right now, but thanks to Danny and our chief marketing Officer, we've got now half a dozen different research surveys that have either just completed or in flight, including the largest in the data protection industry's history. And so the survey that Danny alluded to, what we're finding is people are learning as they're going and in some cases what they thought would happen when they went to the cloud they did not experience. So the net kind of funny slide that we discovered when we asked people, what did you like most about going to the cloud and then what did you like least about going to the cloud? The two lists look very similar. So in some cases people said, oh, it was more stable. In other cases people said no, it was actually unstable. So rick I would suggest that that really depends on the practice that you bring to it. It's like moving from a smaller house to a larger house and hoping that it won't be messy again. Well if you don't change your habits, it's eventually going to end up in the same situation. >>Well, there's still door number three and that's data reuse and analytics. And I found a lot of organizations love the idea of at least manipulating data, running test f scenarios on yesterday's production, cloud workload completely removed from the cloud or even just analytics. I need this file. You know, those types of scenarios are very easy to do today with them. And you know, sometimes those repatriations, those portable recoveries, Sometimes people do that intentionally, but sometimes they have to do it. You know, whether it's fire, flood and blood and you know, oh, I was looks like today we're moving to the cloud because I've lost my data center. Right. Those are scenarios that, that portable data format really allows organizations to do that pretty easily with being >>it's a good discussion because to me it's not repatriation, it has this negative connotation, the zero sum game and it's not Danny what you describe and rick as well. It was kind of an experimentation, a purposeful. We're going to do it in the cloud because we can and it's cheap and low risk to spin it up and then we're gonna move it because we've always thought we're going to have it on prem. So, so you know, there is some zero sum game between the cloud and on prem. Clearly no question about it. But there's also this rising tide lifts all ship. I want to, I want to change the subject to something that's super important and and top of mind it's in the press and it ain't going away and that is cyber and specifically ransomware. I mean, since the solar winds hack and it seems to me that was a new milestone in the capabilities and aggressiveness of the adversary who is very well funded and quite capable. And what we're seeing is this idea of tucking into the supply chain of islands, so called island hopping. You're seeing malware that's self forming and takes different signatures very stealthy. And the big trend that we've seen in the last six months or so is that the bad guys will will lurk and they'll steal all kinds of sensitive data. And then when you have an incident response, they will punish you for responding. And they will say, okay, fine, you want to do that. We're going to hold you ransom. We're gonna encrypt your data. And oh, by the way, we stole this list of positive covid test results with names from your website and we're gonna release it if you don't pay their. I mean, it's like, so you have to be stealthy in your incident response. And this is a huge problem. We're talking about trillions of dollars lost each year in, in in cybercrime. And so, uh, you know, it's again, it's this uh the bad news is good news for companies like you. But how do you help customers deal with this problem? What are you seeing Danny? Maybe you can chime in and others who have thoughts? >>Well we're certainly seeing the rise of cyber like crazy right now and we've had a focus on this for a while because if you think about the last line of defense for customers, especially with ransomware, it is having secure backups. So whether it be, you know, hardened Linux repositories, but making sure that you can store the data, have it offline, have it, have it encrypted immutable. Those are things that we've been focused on for a long while. It's more than that. Um it's detection and monitoring of the environment, which is um certainly that we do with our monitoring tools and then also the secure recovery. The last thing that you want to do of course is bring your backups or bring your data back online only to be hit again. And so we've had a number of capabilities across our portfolio to help in all of these. But I think what's interesting is where it's going, if you think about unleashing a world where we're continuously delivering, I look at things like containers where you have continues delivery and I think every time you run that helm commander, every time you run that terra form command, wouldn't that be a great time to do a backup to capture your data so that you don't have an issue once it goes into production. So I think we're going towards a world where security and the protection against these cyber threats is built into the supply chain rather than doing it on just a time based uh, schedule. And I know rick you're pretty involved on the cyber side as well. Would you agree with that? I >>would. And you know, for organizations that are concerned about ransomware, you know, this is something that is taken very seriously and what Danny explained for those who are familiar with security, he kind of jumped around this, this universally acceptable framework in this cybersecurity framework there, our five functions that are a really good recipe on how you can go about this. And and my advice to IT professionals and decision makers across the board is to really align everything you do to that framework. Backup is a part of it. The security monitoring and user training. All those other things are are areas that that need to really follow that wheel of functions. And my little tip here and this is where I think we can introduce some differentiation is around detection and response. A lot of people think of backup product would shine in both protection and recovery, which it does being does, but especially on response and detection, you know, we have a lot of capabilities that become impact opportunities for organizations to be able to really provide successful outcomes through the other functions. So it's something we've worked on a lot. In fact we've covered here at the event. I'm pretty sure it will be on replay the updated white paper. All those other resources for different levels can definitely guide them through. >>So we follow up to the detection is what analytics that help you identify whatever lateral movement or people go in places they shouldn't go. I mean the hard part is is you know, the bad guys are living off the land, meaning they're using your own tooling to to hack you. So they're not it's not like they're introducing something new that shouldn't be there. They're they're just using making judo moves against you. So so specifically talk a little bit more about your your detection because that's critical. >>Sure. So I'll give you one example imagine we capture some data in the form of a backup. Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. Use explicit minimal permissions. And those three things right there and keep it up to date. Those four things right there will really hedge off a lot of the different threat vectors to the back of data, couple that with some of the mutability offline or air gapped capabilities that Danny mentioned and you have an additional level of resiliency that can really ensure that you can drive recovery from an analytic standpoint. We have an api that allows organizations to look into the backup data. Do more aggressive scanning without any exclusions with different tools on a flat file system. You know, the threats can't jump around in memory couple that with secure restore. When you reintroduce things into the environment From a recovery standpoint, you don't want to reintroduce threats. So there's protections, there's there's confidence building steps along the way with them and these are all generally available technologies. So again, I got this white paper, I think we're up to 50 pages now, but it's a very thorough that goes through a couple of those scenarios. But you know, it gets the uh, it gets quickly into things that you wouldn't expect from a backup product. >>Please send me a copy if you, if you don't mind. I this is a huge problem and you guys are global company. I admittedly have a bit of a US bias, but I was interviewing robert Gates one time the former defense secretary and we're talking about cyber war and I said, don't we have the best cyber, can't we let go on the offense? He goes, yeah, we can, but we got the most to lose. So this is really a huge problem for organizations. All right, guys, last question I gotta ask you. So what's life like under, under inside capital of the private equity? What's changed? What's, what's the same? Uh, do you hear from our good friend ratner at all? Give us the update there. >>Yes. Oh, absolutely fantastic. You know, it's interesting. So obviously acquired by insight partners in February of 2020, right, when the pandemic was hitting, but they essentially said light the fuse, keep the engine's going. And we've certainly been doing that. They haven't held us back. We've been hiring like crazy. We're up to, I don't know what the count is now, I think 4600 employees, but um, you know, people think of private equity and they think of cost optimizations and, and optimizing the business, That's not the case here. This is a growth opportunity and it's a growth opportunity simply because of the technology opportunity in front of us to keep, keep the engine's going. So we hear from right near, you know, on and off. But the new executive team at VM is very passionate about driving the success in the industry, keeping abreast of all the technology changes. It's been fantastic. Nothing but good things to say. >>Yes, insight inside partners, their players, we watched them watch their moves and so it's, you know, I heard Bill McDermott, the ceo of service now the other day talking about he called himself the rule of 60 where, you know, I always thought it was even plus growth, you know, add that up. And that's what he was talking about free cash flow. He's sort of changing the definition a little bit but but so what are you guys optimizing for you optimizing for growth? Are you optimising for Alberta? You optimizing for free cash flow? I mean you can't do All three. Right. What how do you think about that? >>Well, we're definitely optimizing for growth. No question. And one of the things that we've actually done in the past 12 months, 18 months is beginning to focus on annual recurring revenue. You see this in our statements, I know we're not public but we talk about the growth in A. R. R. So we're certainly focused on that growth in the annual recovering revenue and that that's really what we tracked too. And it aligns well with the cloud. If you look at the areas where we're investing in cloud native and the cloud and SAAS applications, it's very clear that that recurring revenue model is beneficial. Now We've been lucky, I think we're 13 straight quarters of double-digit growth. And and obviously they don't want to see that dip. They want to see that that growth continue. But we are optimizing on the growth trajectory. >>Okay. And you see you clearly have a 25% growth last quarter in A. R. R. Uh If I recall correctly, the number was evaluation was $5 billion last january. So obviously then, given that strategy, Dave Russell, that says that your tam is a lot bigger than just the traditional backup world. So how do you think about tam? I'll we'll close there >>and uh yeah, I think you look at a couple of different ways. So just in the backup recovery space or backup in replication to paying which one you want to use? You've got a large market there in excess of $8 billion $1 billion dollar ongoing enterprise. Now, if you look at recent i. D. C. Numbers, we grew and I got my handy HP calculator. I like to make sure I got this right. We grew 44.88 times faster than the market average year over year. So let's call that 45 times faster and backup. There's billions more to be made in traditional backup and recovery. However, go back to what we've been talking around digital transformation Danny talking about containers in the environment, deployment models, changing at the heart of backup and recovery where a data capture data management, data movement engine. We envision being able to do that not only for availability but to be able to drive the business board to be able to drive economies of scale faster for our organizations that we serve. I think the trick is continuing to do more of the same Danny mentioned, he knows the view's got lit. We haven't stopped doing anything. In fact, Danny, I think we're doing like 10 times more of everything that we used to be doing prior to the pandemic. >>All right, Danny will give you the last word, bring it home. >>So our goal has always been to be the most trusted provider of backup solutions that deliver modern data protection. And I think folks have seen at demon this year that we're very focused on that modern data protection. Yes, we want to be the best in the data center but we also want to be the best in the next generation, the next generation of I. T. So whether it be sas whether it be cloud VM is very committed to making sure that our customers have the confidence that they need to move forward through this digital transformation era. >>Guys, I miss flying. I mean, I don't miss flying, but I miss hanging with you all. We'll see you. Uh, for sure. Vim on 2022 will be belly to belly, but thanks so much for coming on the the virtual edition and thanks for having us. >>Thank you. >>All right. And thank you for watching everybody. This keeps continuous coverage of the mon 21. The virtual edition. Keep it right there for more great coverage. >>Mm

>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody and welcome again to theCUBE. We continue our initiative here at IBM Think and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Khee-Hong Song, who is the CEO and President of IBM Korea and Mr. Jung Sik Suh, who is the CEO of Hyundai AutoEver, which is an IT service company affiliated with the Hyundai Motor Group. And gentlemen (greeting in Korean) Thank you for joining this. We appreciate it. >> Thank you. >> Thank you for inviting us. >> Hi. >> Yes, hi, very good to see you there. And I hope I didn't do the greeting injustice there. First off, Khee, I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course is global. And certainly, with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post-COVID world and how it is going to look like. What changes this pandemic will bring. The Korean government is really focusing on growing the digital sector. Taking this advantage, and taking this opportunity as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by -1% and industry players also faced difficulties. For example, discount stores are -20% Y2Y. department stores are lost 30% of their revenue. But the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID, and obviously that's had a global impact. Not only in your operations here in the United States certainly, but Africa in Europe, and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been and maybe a little more specificity on coming out of that. You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government. Maybe a little more specifics about the impact of COVID. And then Mr. Sung, I'll turn to you for that as well. First off, Khee, if you will. >> Okay, in an effort to recover from COVID-19 economic recession, Korean government announced Digital New Deal, which is to lay a foundation for digital economy that will spur economic growth and innovation. Now the policy aims to create a new digital economy, which is underpinned by new technologies such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward the growth in next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37% in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next, even in the face of a crisis. >> Jung, We've been hearing from Khee talking about the digital and certainly the impacts of COVID. And I assume that at Hyundai, you have had to deal with this certainly, this impact and are now coming out the other end, some very positive news from numbers we're hearing from Khee. If you could talk about though, maybe from your perspective in terms of that impact. And then, what kind of a rebound do you see or kind of positive uptick do you see in terms of digital in your business, say, in the next 12 to 18 months? >> I think the 12 to 18 months, we are reinforcing the digitalization, not just the working environment, but also others, especially for in terms of sales. Until now most of the B2C sales changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies are not too ready for the e-commerce environment. But Hyundai is very actively, and proactively, and preemptively starting the e-commerce. So I think, next to 12 to 18 month, two-digit percent of our sales are will be fulfilled by internet-based. I mean, we'll have to face the most biggest and most challenging but possible change after COVID. >> Yeah, what's driving that then, is it just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce, whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world as I'm hearing you describe it. Is that accurate? >> Yes. So we are the digital world, from just communicate with customer, but also our internal operation. Like the manufacturing environment and also the sales environment, et cetera. >> And Khee, if you would talk about maybe how this is impacting your business and just in terms of IBM in general. Not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other e-commerce initiatives and what have you, What's kind of the bottom line impact there for you right now in terms of this massive shift over to digital? >> Well, in IBM, our goal is to work with industry clients and technology partners to accelerate this transformation through automation, transition to hybrid cloud, and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, amid the economic downturn, and for hygiene purposes as well. So Seoul Asan Hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a bed allocation automation system based on design thinking, workshop and garage method. The automation system considers a patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minutes with a 0% error rate. And currently, more than a hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to a managed private cloud using cloud technology from IBM and Red Hat. >> Khee, you talked about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies and all these very fundamental. But very important factors to consider, when you're talking to your clients right now, what are their, I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what, where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> Well, I think the barrier to any decision, like quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean, last year, two years ago, versus now, when all technology companies, should we say something different. And that is not because it changed the position itself. The technology itself changed, and technology companies are responding to the trend. So that's why some clients get confused, and that confusion slows down the adaption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're, like Mr. Sung can talk about some changes in Hyundai motors. Many companies realized that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jung, if you would then follow up on that, I would like to hear from you about Hyundai and the factors that you've considered in your digital decision making in terms of workloads, and capacities, and just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward, how much more are you going to do? What are you considering right now in terms of future transformations? >> I think the other, our competitor, the other OEMs also think like that the car itself should be changed to digital. It means that, currently, the software portion of the car is just a seven to 10% of total our, the procurement. But it'll be changed to 20 to 30% in five years. It means that some portion will be to increased by three times There is a one our research changed. The other one is that kind of a software mostly located and not just in the car, which means that car is just a software edge activity. It means that just that the input and output, or some real-time transaction, or other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main party of the car software. And also the car is it's just to edge. We have edge cloud and main cloud. It will be occurred just to within just several years. First, really, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around the four million car in the word. It will be changed to 10 million car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information and also- >> Yes, collecting information. And we are ready for the OTA, which means over-the-air software update for the 10 million car within one years. And also, it will double up year by year. >> Okay. >> Which means that all of the car, all the operated by cloud. >> Okay. >> And cars, it says to input and output an edge activities, therefore car is on cloud. >> Okay. >> John: Right? Khee: Interesting. >> Jung: That is the major driver for our digital transformation. >> And if you would, just what role is IBM having that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing are will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So that at the real time, the 10 million cars get the information timely. And also, like all those cars are communicating with each other that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors. Not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, lately, IBM helped us our all IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that dozens of billion of revenue operation is located in US and Europe. All over the US, Europe IT operation conducted by the IBM India and orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned, IBM Korea is leading the project. All the service delivery is done in India leveraging IBM India. And we are serving Hyundai motors in the United States and Europe. So it's a truly a global IT operation environment. And that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say it any better, Khee. Thank you for that. Jung, thank you as well. Talking about this impressive global impact and really partnership that Hyundai is taking with IBM in the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Khee: Thank you very much, John. >> Jung: Thank you. >> All right, we've been talking about Korea as an IT power country for the IBM perspective. And certainly, using Hyundai is a beautiful example of just how this partnership is working and growing, and providing great service for consumers at the end of the day. You've been watching "theCube" and IBM Think. (upbeat theme music) (upbeat theme music) (humming)