(upbeat music) >> Hi, everyone. Welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. As part of International Women's Day, we're featuring some of the leading women in business technology from developer to all types of titles and to the executive level. And one topic that's really important is called Getting a Seat at the Table, board makeup, having representation at corporate boards, private and public companies. It's been a big push. And former technology operating executive and corporate board member, she's a board machine Sue Barsamian, formerly with HPE, Hewlett Packard. Sue, great to see you. CUBE alumni, distinguished CUBE alumni. Thank you for coming on. >> Yes, I'm very proud of my CUBE alumni title. >> I'm sure it opens a lot of doors for you. (Sue laughing) We're psyched to have you on. This is a really important topic, and I want to get into the whole, as women advance up, and they're sitting on the boards, they can implement policy and there's governance. Obviously public companies have very strict oversight, and not strict, but like formal. Private boards have to operate, be nimble. They don't have to share all their results. But still, boards play an important role in the success of scaled up companies. So super important, that representation there is key. >> Yes. >> I want to get into that, but first, before we get started, how did you get into tech? How did it all start for you? >> Yeah, long time ago, I was an electrical engineering major. Came out in 1981 when, you know, opportunities for engineering, if you were kind, I went to Kansas State as an undergrad, and basically in those days you went to Texas and did semiconductors. You went to Atlanta and did communication satellites. You went to Boston or you went to Silicon Valley. And for me, that wasn't too hard a choice. I ended up going west and really, I guess what, embarked on a 40 year career in Silicon Valley and absolutely loved it. Largely software, but some time on the hardware side. Started out in networking, but largely software. And then, you know, four years ago transitioned to my next chapter, which is the corporate board director. And again, focused on technology software and cybersecurity boards. >> For the folks watching, we'll cut through another segment we can probably do about your operating career, but you rose through the ranks and became a senior operating executive at the biggest companies in the world. Hewlett Packard Enterprise, Hewlett Packard Enterprise and others. Very great career, okay. And so now you're kind of like, put that on pause, and you're moving on to the next chapter, which is being a board director. What inspired you to be a board director for multiple public companies and multiple private companies? Well, how many companies are you on? But what's the inspiration? What's the inspiration? First tell me how many board ships you're on, board seats you're on, and then what inspired you to become a board director? >> Yeah, so I'm on three public, and you are limited in terms of the number of publics that you can do to four. So I'm on three public, and I'm on four private from a tech perspective. And those range from, you know, a $4 billion in revenue public company down to a 35 person private company. So I've got the whole range. >> So you're like freelancing, I mean, what is it like? It's a full-time job, obviously. It's a lot of work involved. >> Yeah, yeah, it's. >> John: Why are you doing it? >> Well, you know, so I retired from being an operating executive after 37 years. And, but I loved, I mean, it's tough, right? It's tough these days, particularly with all the pressures out there in the market, not to mention the pandemic, et cetera. But I loved it. I loved working. I loved having a career, and I was ready to back off on, I would say the stresses of quarterly results and the stresses of international travel. You have so much of it. But I wasn't ready to back off from being involved and engaged and continuing to learn new things. I think this is why you come to tech, and for me, why I went to the valley to begin with was really that energy and that excitement, and it's like it's constantly reinventing itself. And I felt like that wasn't over for me. And I thought because I hadn't done boards before I retired from operating roles, I thought, you know, that would fill the bill. And it's honestly, it has exceeded expectations. >> In a good way. You feel good about where you're at and. >> Yeah. >> What you went in, what was the expectation going in and what surprised you? And were there people along the way that kind of gave you some pointers or don't do this, stay away from this. Take us through your experiences. >> Yeah, honestly, there is an amazing network of technology board directors, you know, in the US and specifically in the Valley. And we are all incredibly supportive. We have groups where we get together as board directors, and we talk about topics, and we share best practices and stories, and so I underestimated that, right? I thought I was going to, I thought I was going to enter this chapter where I would be largely giving back after 37 years. You've learned a little bit, right? What I underestimated was just the power of continuing to learn and being surrounded by so many amazing people. When, you know, when you do, you know, multiple boards, your learnings are just multiplied, right? Because you see not just one model, but you see many models. You see not just one problem, but many problems. Not just one opportunity, but many opportunities. And I underestimated how great that would be for me from a learning perspective and then your ability to share from one board to the other board because all of my boards are companies who are also quite close to each other, the executives collaborate. So that has turned out to be really exciting for me. >> So you had the stressful job. You rose to the top of the ranks, quarterly shot clock earnings, and it's hard charging. It's like, it's like, you know, being an athlete, as we say tech athlete. You're a tech athlete. Now you're taking that to the next level, which is now you're juggling multiple operational kind of things, but not with super pressure. But there's still a lot of responsibility. I know there's one board, you got compensation committee, I mean there's work involved. It's not like you're clipping coupons and having pizza. >> Yeah, no, it's real work. Believe me, it's real work. But I don't know how long it took me to not, to stop waking up and looking at my phone and thinking somebody was going to be dropping their forecast, right? Just that pressure of the number, and as a board member, obviously you are there to support and help guide the company and you feel, you know, you feel the pressure and the responsibility of what that role entails, but it's not the same as the frontline pressure every quarter. It's different. And so I did the first type. I loved it, you know. I'm loving this second type. >> You know, the retirement, it's always a cliche these days, but it's not really like what people think it is. It's not like getting a boat, going fishing or whatever. It's doing whatever you want to do, that's what retirement is. And you've chose to stay active. Your brain's being tested, and you're working it, having fun without all the stress. But it's enough, it's like going the gym. You're not hardcore workout, but you're working out with the brain. >> Yeah, no, for sure. It's just a different, it's just a different model. But the, you know, the level of conversations, the level of decisions, all of that is quite high. Which again, I like, yeah. >> Again, you really can't talk about some of the fun questions I want to ask, like what's the valuations like? How's the market, your headwinds? Is there tailwinds? >> Yes, yes, yes. It's an amazing, it's an amazing market right now with, as you know, counter indicators everywhere, right? Something's up, something's down, you know. Consumer spending's up, therefore interest rates go up and, you know, employment's down. And so or unemployment's down. And so it's hard. Actually, I really empathize with, you know, the, and have a great deal of respect for the CEOs and leadership teams of my board companies because, you know, I kind of retired from operating role, and then everybody else had to deal with running a company during a pandemic and then running a company through the great resignation, and then running a company through a downturn. You know, those are all tough things, and I have a ton of respect for any operating executive who's navigating through this and leading a company right now. >> I'd love to get your take on the board conversations at the end if we have more time, what the mood is, but I want to ask you about one more thing real quick before we go to the next topic is you're a retired operating executive. You have multiple boards, so you've got your hands full. I noticed there's a lot of amazing leaders, other female tech athletes joining boards, but they also have full-time jobs. >> Yeah. >> And so what's your advice? Cause I know there's a lot of networking, a lot of sharing going on. There's kind of a balance between how much you can contribute on the board versus doing the day job, but there's a real need for more women on boards, so yet there's a lot going on boards. What's the current state of the union if you will, state of the market relative to people in their careers and the stresses? >> Yeah. >> Cause you left one and jumped in all in there. >> Yeah. >> Some can't do that. They can't be on five boards, but they're on a few. What's the? >> Well, and you know, and if you're an operating executive, you wouldn't be on five boards, right? You would be on one or two. And so I spend a lot of time now bringing along the next wave of women and helping them both in their career but also to get a seat at the table on a board. And I'm very vocal about telling people not to do it the way I do it. There's no reason for it to be sequential. You can, you know, I thought I was so busy and was traveling all the time, and yes, all of that was true, but, and maybe I should say, you know, you can still fit in a board. And so, and what I see now is that your learnings are so exponential with outside perspective that I believe I would've been an even better operating executive had I done it earlier. I know I would've been an even better operating executive had I done it earlier. And so my advice is don't do it the way I did it. You know, it's worked out fine for me, but hindsight's 2020, I would. >> If you can go back and do a mulligan or a redo, what would you do? >> Yeah, I would get on a board earlier, full stop, yeah. >> Board, singular, plural? >> Well, I really, I don't think as an operating executive you can do, you could do one, maybe two. I wouldn't go beyond that, and I think that's fine. >> Yeah, totally makes sense. Okay, I got to ask you about your career. I know technical, you came in at that time in the market, I remember when I broke into the business, very male dominated, and then now it's much better. When you went through the ranks as a technical person, I know you had some blockers and definitely some, probably some people like, well, you know. We've seen that. How did you handle that? What were some of the key pivot points in your journey? And we've had a lot of women tell their stories here on theCUBE, candidly, like, hey, I was going to tell that professor, I'm going to sit in the front row. I'm going to, I'm getting two degrees, you know, robotics and aerospace. So, but they were challenged, even with the aspiration to do tech. I'm not saying that was something that you had, but like have you had experience like that, that you overcome? What were those key points and how did you handle them and how does that help people today? >> Yeah, you know, I have to say, you know, and not discounting that obviously this has been a journey for women, and there are a lot of things to overcome both in the workforce and also just balancing life honestly. And they're all real. There's also a story of incredible support, and you know, I'm the type of person where if somebody blocked me or didn't like me, I tended to just, you know, think it was me and like work harder and get around them, and I'm sure that some of that was potentially gender related. I didn't interpret it that way at the time. And I was lucky to have amazing mentors, many, many, many of whom were men, you know, because they were in the positions of power, and they made a huge difference on my career, huge. And I also had amazing female mentors, Meg Whitman, Ann Livermore at HPE, who you know well. So I had both, but you know, when I look back on the people who made a difference, there are as many men on the list as there are women. >> Yeah, and that's a learning there. Create those coalitions, not just one or the other. >> Yeah, yeah, yeah, absolutely. >> Well, I got to ask you about the, well, you brought up the pandemic. This has come up on some interviews this year, a little bit last year on the International Women's Day, but this year it's resonating, and I would never ask in an interview. I saw an interview once where a host asked a woman, how do you balance it all? And I was just like, no one asked men that. And so it's like, but with remote work, it's come up now the word empathy around people knowing each other's personal situation. In other words, when remote work happened, everybody went home. So we all got a glimpse of the backdrop. You got, you can see what their personal life was on Facebook. We were just commenting before we came on camera about that. So remote work really kind of opened up this personal side of everybody, men and women. >> Yeah. >> So I think this brings this new empathy kind of vibe or authentic self people call it. Is remote work an opportunity or a threat for advancement of women in tech? >> It's a much debated topic. I look at it as an opportunity for many of the reasons that you just said. First of all, let me say that when I was an operating executive and would try to create an environment on my team that was family supportive, I would do that equally for young or, you know, early to mid-career women as I did for early to mid-career men. And the reason is I needed those men, you know, chances are they had a working spouse at home, right? I needed them to be able to share the load. It's just as important to the women that companies give, you know, the partner, male or female, the partner support and the ability to share the love, right? So to me it's not just a woman thing. It's women and men, and I always tried to create the environment where it was okay to go to your soccer game. I knew you would be online later in the evening when the kids were in bed, and that was fine. And I think the pandemic has democratized that and made that, you know, made that kind of an everyday occurrence. >> Yeah the baby walks in. They're in the zoom call. The dog comes in. The leaf blower going on the outside the window. I've seen it all on theCUBE. >> Yeah, and people don't try to pretend anymore that like, you know, the house is clean, the dog's behaved, you know, I mean it's just, it's just real, and it's authentic, and I think that's healthy. >> Yeah. >> I do, you know, I also love, I also love the office, and you know, I've got a 31 year old and a soon to be 27 year old daughter, two daughters. And you know, they love going into the office, and I think about when I was their age, how just charged up I would get from being in the office. I also see how great it is for them to have a couple of days a week at home because you can get a few things done in between Zoom calls that you don't have to end up piling onto the weekend, and, you know, so I think it's a really healthy, I think it's a really healthy mix now. Most tech companies are not mandating five days in. Most tech companies are at two to three days in. I think that's a, I think that's a really good combination. >> It's interesting how people are changing their culture to get together more as groups and even events. I mean, while I got you, I might as well ask you, what's the board conversations around, you know, the old conferences? You know, before the pandemic, every company had like a user conference. Right, now it's like, well, do we really need to have that? Maybe we do smaller, and we do digital. Have you seen how companies are handling the in-person? Because there's where the relationships are really formed face-to-face, but not everyone's going to be going. But now certain it's clearly back to face-to-face. We're seeing that with theCUBE as you know. >> Yeah, yeah. >> But the numbers aren't coming back, and the numbers aren't that high, but the stakeholders. >> Yeah. >> And the numbers are actually higher if you count digital. >> Yeah, absolutely. But you know, also on digital there's fatigue from 100% digital, right? It's a hybrid. People don't want to be 100% digital anymore, but they also don't want to go back to the days when everybody got on a plane for every meeting, every call, every sales call. You know, I'm seeing a mix on user conferences. I would say two-thirds of my companies are back, but not at the expense level that they were on user conferences. We spend a lot of time getting updates on, cause nobody has put, interestingly enough, nobody has put T&E, travel and expense back to pre-pandemic levels. Nobody, so everybody's pulled back on number of trips. You know, marketing events are being very scrutinized, but I think very effective. We're doing a lot of, and, you know, these were part of the old model as well, like some things, some things just recycle, but you know, there's a lot of CIO and customer round tables in regional cities. You know, those are quite effective right now because people want some face-to-face, but they don't necessarily want to get on a plane and go to Las Vegas in order to do it. I mean, some of them are, you know, there are a lot of things back in Las Vegas. >> And think about the meetings that when you were an operating executive. You got to go to the sales kickoff, you got to go to this, go to that. There were mandatory face-to-faces that you had to go to, but there was a lot of travel that you probably could have done on Zoom. >> Oh, a lot, I mean. >> And then the productivity to the family impact too. Again, think about again, we're talking about the family and people's personal lives, right? So, you know, got to meet a customer. All right. Salesperson wants you to get in front of a customer, got to fly to New York, take a red eye, come on back. Like, I mean, that's gone. >> Yeah, and oh, by the way, the customer doesn't necessarily want to be in the office that day, so, you know, they may or may not be happy about that. So again, it's and not or, right? It's a mix. And I think it's great to see people back to some face-to-face. It's great to see marketing and events back to some face-to-face. It's also great to see that it hasn't gone back to the level it was. I think that's a really healthy dynamic. >> Well, I'll tell you that from our experience while we're on the topic, we'll move back to the International Women's Day is that the productivity of digital, this program we're doing is going to be streamed. We couldn't do this face-to-face because we had to have everyone fly to an event. We're going to do hundreds of stories that we couldn't have done. We're doing it remote. Because it's better to get the content than not have it. I mean it's offline, so, but it's not about getting people to the event and watch the screen for seven hours. It's pick your interview, and then engage. >> Yeah. >> So it's self-service. So we're seeing a lot, the new user experience kind of direct to consumer, and so I think there will be an, I think there's going to be a digital first class citizen with events, so that that matches up with the kind of experience, but the offline version. Face-to-face optimized for relationships, and that's where the recruiting gets done. That's where, you know, people can build these relationships with each other. >> Yeah, and it can be asynchronous. I think that's a real value proposition. It's a great point. >> Okay, I want to get, I want to get into the technology side of the education and re-skilling and those things. I remember in the 80s, computer science was software engineering. You learned like nine languages. You took some double E courses, one or two, and all the other kind of gut classes in school. Engineering, you had the four class disciplines and some offshoots of specialization. Now it's incredible the diversity of tracks in all engineering programs and computer science and outside of those departments. >> Yeah. >> Can you speak to the importance of STEM and the diversity in the technology industry and how this brings opportunity to lower the bar to get in and how people can stay in and grow and keep leveling up? >> Yeah, well look, we're constantly working on how to, how to help the incoming funnel. But then, you know, at a university level, I'm on the foundation board of Kansas State where I got my engineering degree. I was also Chairman of the National Action Council for Minorities in Engineering, which was all about diversity in STEM and how do you keep that pipeline going because honestly the US needs more tech resources than we have. And if you don't tap into the diversity of our entire workforce, we won't be able to fill that need. And so we focused a lot on both the funnel, right, that starts at the middle school level, particularly for girls, getting them in, you know, the situation of hands-on comfort level with coding, with robot building, you know, whatever gives them that confidence. And then keeping that going all the way into, you know, university program, and making sure that they don't attrit out, right? And so there's a number of initiatives, whether it's mentoring and support groups and financial aid to make sure that underrepresented minorities, women and other minorities, you know, get through the funnel and stay, you know, stay in. >> Got it. Now let me ask you, you said, I have two daughters. You have a family of girls too. Is there a vibe difference between the new generation and what's the trends that you're seeing in this next early wave? I mean, not maybe, I don't know how this is in middle school, but like as people start getting into their adult lives, college and beyond what's the current point of view, posture, makeup of the talent coming in? >> Yeah, yeah. >> Certain orientations, do you see any patterns? What's your observation? >> Yeah, it's interesting. So if I look at electrical engineering, my major, it's, and if I look at Kansas State, which spends a lot of time on this, and I think does a great job, but the diversity of that as a major has not changed dramatically since I was there in the early 80s. Where it has changed very significantly is computer science. There are many, many university and college programs around the country where, you know, it's 50/50 in computer science from a gender mix perspective, which is huge progress. Huge progress. And so, and to me that's, you know, I think CS is a fantastic degree for tech, regardless of what function you actually end up doing in these companies. I mean, I was an electrical engineer. I never did core electrical engineering work. I went right into sales and marketing and general management roles. So I think, I think a bunch of, you know, diverse CS graduates is a really, really good sign. And you know, we need to continue to push on that, but progress has been made. I think the, you know, it kind of goes back to the thing we were just talking about, which is the attrition of those, let's just talk about women, right? The attrition of those women once they got past early career and into mid-career then was a concern, right? And that goes back to, you know, just the inability to, you know, get it all done. And that I am hopeful is going to be better served now. >> Well, Sue, it's great to have you on. I know you're super busy. I appreciate you taking the time and contributing to our program on corporate board membership and some of your story and observations and opinions and analysis. Always great to have you and call you a contributor for theCUBE. You can jump on on one more board, be one of our board contributors for our analysts. (Sue laughing) >> I'm at capacity. (both laughing) >> Final, final word. What's the big seat at the table issue that's going well and areas that need to be improved? >> So I'll speak for my boards because they have made great progress in efficiency. You know, obviously with interest rates going up and the mix between growth and profitability changing in terms of what investors are looking for. Many, many companies have had to do a hard pivot from grow at all costs to healthy balance of growth and profit. And I'm very pleased with how my companies have made that pivot. And I think that is going to make much better companies as a result. I think diversity is something that has not been solved at the corporate level, and we need to keep working it. >> Awesome. Thank you for coming on theCUBE. CUBE alumni now contributor, on multiple boards, full-time job. Love the new challenge and chapter you're on, Sue. We'll be following, and we'll check in for more updates. And thank you for being a contributor on this program this year and this episode. We're going to be doing more of these quarterly, so we're going to move beyond once a year. >> That's great. (cross talking) It's always good to see you, John. >> Thank you. >> Thanks very much. >> Okay. >> Sue: Talk to you later. >> This is theCUBE coverage of IWD, International Women's Day 2023. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hi everybody. Welcome back to Barcelona. We're here at the Fira Live, theCUBE's ongoing coverage of day two of MWC 23. Back in 2021 was my first Mobile World Congress. And you know what? It was actually quite an experience because there was nobody there. I talked to my friend, who's now my co-host, Chris Lewis about what to expect. He said, Dave, I don't think a lot of people are going to be there, but Danielle Royston is here and she's the CEO of Totoge. And that year when Erickson tapped out of its space she took out 60,000 square feet and built out Cloud City. If it weren't for Cloud City, there would've been no Mobile World Congress in June and July of 2021. DR is back. Great to see you. Thanks for coming on. >> It's great to see you. >> Chris. Awesome to see you. >> Yeah, Chris. Yep. >> Good to be back. Yep. >> You guys remember the narrative back then. There was this lady running around this crazy lady that I met at at Google Cloud next saying >> Yeah. Yeah. >> the cloud's going to take over Telco. And everybody's like, well, this lady's nuts. The cloud's been leaning in, you know? >> Yeah. >> So what do you think, I mean, what's changed since since you first caused all those ripples? >> I mean, I have to say that I think that I caused a lot of change in the industry. I was talking to leaders over at AWS yesterday and they were like, we've never seen someone push like you have and change so much in a short period of time. And Telco moves slow. It's known for that. And they're like, you are pushing buttons and you're getting people to change and thank you and keep going. And so it's been great. It's awesome. >> Yeah. I mean, it was interesting, Chris, we heard on the keynotes we had Microsoft, Satya came in, Thomas Curian came in. There was no AWS. And now I asked CMO of GSMA about that. She goes, hey, we got a great relationship with it, AWS. >> Danielle: Yeah. >> But why do you think they weren't here? >> Well, they, I mean, they are here. >> Mean, not here. Why do you think they weren't profiled? >> They weren't on the keynote stage. >> But, you know, at AWS, a lot of the times they want to be the main thing. They want to be the main part of the show. They don't like sharing the limelight. I think they just didn't want be on the stage with the Google CLoud guys and the these other guys, what they're doing they're building out, they're doing so much stuff. As Danielle said, with Telcos change in the ecosystem which is what's happening with cloud. Cloud's making the Telcos think about what the next move is, how they fit in with the way other people do business. Right? So Telcos never used to have to listen to anybody. They only listened to themselves and they dictated the way things were done. They're very successful and made a lot of money but they're now having to open up they're having to leverage the cloud they're having to leverage the services that (indistinct words) and people out provide and they're changing the way they work. >> So, okay in 2021, we talked a lot about the cloud as a potential disruptor, and your whole premise was, look you got to lean into the cloud, or you're screwed. >> Danielle: Yeah. >> But the flip side of that is, if they lean into the cloud too much, they might be screwed. >> Danielle: Yeah. >> So what's that equilibrium? Have they been able to find it? Are you working with just the disruptors or how's that? >> No I think they're finding it right. So my talk at MWC 21 was all about the cloud is a double-edged sword, right? There's two sides to it, and you definitely need to proceed through it with caution, but also I don't know that you have a choice, right? I mean, the multicloud, you know is there another industry that spends more on CapEx than Telco? >> No. >> Right. The hyperscalers are doing it right. They spend, you know, easily approaching over a $100 billion in CapEx that rivals this industry. And so when you have a player like that an industry driving, you know and investing so much Telco, you're always complaining how everyone's riding your coattails. This is the opportunity to write someone else's coattails. So jump on, right? I think you don't have a choice especially if other Telco competitors are using hyperscalers and you don't, they're going to be left behind. >> So you advise these companies all the time, but >> I mean, the issue is they're all they're all using all the hyperscalers, right? So they're the multi, the multiple relationships. And as Danielle said, the multi-layer of relationship they're using the hyperscalers to change their own internal operational environments to become more IT-centric to move to that software centric Telco. And they're also then with the hyperscalers going to market in different ways sometimes with them, sometimes competing with them. What what it means from an analyst point of view is you're suddenly changing the dynamic of a market where we used to have nicely well defined markets previously. Now they're, everyone's in it together, you know, it's great. And, and it's making people change the way they think about services. What I, what I really hope it changes more than anything else is the way the customers at the end of the, at the end of the supply, the value chain think this is what we can get hold of this stuff. Now we can go into the network through the cloud and we can get those APIs. We can draw on the mechanisms we need to to run our personal lives, to run our business lives. And frankly, society as a whole. It's really exciting. >> Then your premise is basically you were saying they should ride on the top over the top of the cloud vendor. >> Yeah. Right? >> No. Okay. But don't they lose the, all the data if they do that? >> I don't know. I mean, I think the hyperscalers are not going to take their data, right? I mean, that would be a really really bad business move if Google Cloud and Azure and and AWS start to take over that, that data. >> But they can't take it. >> They can't. >> From regulate, from sovereignty and regulation. >> They can't because of regulation, but also just like business, right? If they started taking their data and like no enterprises would use them. So I think, I think the data is safe. I think you, obviously every country is different. You got to understand the different rules and regulations for data privacy and, and how you keep it. But I think as we look at the long term, right and we always talk about 10 and 20 years there's going to be a hyperscaler region in every country right? And there will be a way for every Telco to use it. I think their data will be safe. And I think it just, you're going to be able to stand on on the shoulders of someone else for once and use the building blocks of software that these guys provide to make better experiences for subscribers. >> You guys got to explain this to me because when I say data I'm not talking about, you know, personal information. I'm talking about all the telemetry, you know, all the all the, you know the plumbing. >> Danielle: Yeah. >> Data, which is- >> It will increasingly be shared because you need to share it in order to deliver the services in the streamline efficient way that needs to be deliver. >> Did I hear the CEO of Ericsson Wright where basically he said, we're going to charge developers for access to that data through APIs. >> What the Ericsson have done, obviously with the Vage acquisition is they want to get into APIs. So the idea is you're exposing features, quality policy on demand type features for example, or even pulling we still use that a lot of SMS, right? So pulling those out using those APIs. So it will be charged in some way. Whether- >> Man: Like Twitter's charging me for APIs, now I API calls, you >> Know what it is? I think it's Twilio. >> Man: Oh, okay. >> Right. >> Man: No, no, that's sure. >> There's no reason why telcos couldn't provide a Twilio like service itself. >> It's a horizontal play though right? >> Danielle: Correct because developers need to be charged by the API. >> But doesn't there need to be an industry standard to do that as- >> Well. I think that's what they just announced. >> Industry standard. >> Danielle: I think they just announced that. Yeah. Right now I haven't looked at that API set, right? >> There's like eight of them. >> There's eight of them. Twilio has, it's a start you got to start somewhere Dave. (crosstalk) >> And there's all, the TM forum is all the other standard >> Right? Eight is better than zero- >> Right? >> Haven't got plenty. >> I mean for an industry that didn't really understand APIs as a feature, as a product as a service, right? For Mats Granryd, the deputy general of GSMA to stand on the keynote stage and say we partnered and we're unveiling, right. Pay by the use APIs. I was for it. I was like, that is insane. >> I liked his keynote actually, because I thought he was going to talk about how many attendees and how much economic benefiting >> Danielle: We're super diverse. >> He said, I would usually talk about that and you know greening in the network by what you did talk about a little bit. But, but that's, that surprised me. >> Yeah. >> But I've seen in the enterprise this is not my space as, you know, you guys don't live this but I've seen Oracle try to get developers. IBM had to pay $35 billion trying to get for Red Hat to get developers, right? EMC used to have a thing called EMC code, failed. >> I mean they got to do something, right? So 4G they didn't really make the business case the ROI on the investment in the network. Here we are with 5G, same discussion is having where's the use case? How are we going to monetize and make the ROI on this massive investment? And now they're starting to talk about 6G. Same fricking problem is going to happen again. And so I think they need to start experimenting with new ideas. I don't know if it's going to work. I don't know if this new a API network gateway theme that Mats talked about yesterday will work. But they need to start unbundling that unlimited plan. They need to start charging people who are using the network more, more money. Those who are using it less, less. They need to figure this out. This is a crisis for them. >> Yeah our own CEO, I mean she basically said, Hey, I'm for net neutrality, but I want to be able to charge the people that are using it more and more >> To make a return on, on a capital. >> I mean it costs billions of dollars to build these networks, right? And they're valuable. We use them and we talked about this in Cloud City 21, right? The ability to start building better metaverses. And I know that's a buzzword and everyone hates it, but it's true. Like we're working from home. We need- there's got to be a better experience in Zoom in 2D, right? And you need a great network for that metaverse to be awesome. >> You do. But Danielle, you don't need cellular for doing that, do you? So the fixed network is as important. >> Sure. >> And we're at mobile worlds. But actually what we beginning to hear and Crystal Bren did say this exactly, it's about the comp the access is sort of irrelevant. Fixed is better because it's more the cost the return on investment is better from fiber. Mobile we're going to change every so many years because we're a new generation. But we need to get the mechanism in place to deliver that. I actually don't agree that we should everyone should pay differently for what they use. It's a universal service. We need it as individuals. We need to make it sustainable for every user. Let's just not go for the biggest user. It's not, it's not the way to build it. It won't work if you do that you'll crash the system if you do that. And, and the other thing which I disagree on it's not about standing on the shoulders and benefiting from what- It's about cooperating across all levels. The hyperscalers want to work with the telcos as much as the telcos want to work with the hyperscalers. There's a lot of synergy there. There's a lot of ways they can work together. It's not one or the other. >> But I think you're saying let the cloud guys do the heavy lifting and I'm - >> Yeah. >> Not at all. >> And so you don't think so because I feel like the telcos are really good at pipes. They've always been good at pipes. They're engineers. >> Danielle: Yeah. >> Are they hanging on to the to the connectivity or should they let that go and well and go toward the developer. >> I mean AWS had two announcements on the 21st a week before MWC. And one was that telco network builder. This is literally being able to deploy a network capability at AWS with keystrokes. >> As a managed service. >> Danielle: Correct. >> Yeah. >> And so I don't know how the telco world I felt the shock waves, right? I was like, whoa, that seems really big. Because they're taking something that previously was like bread and butter. This is what differentiates each telco and now they've standardized it and made it super easy so anyone can do it. Now do I think the five nines of super crazy hardcore network criteria will be built on AWS this way? Probably not, but no >> It's not, it's not end twin. So you can't, no. >> Right. But private networks could be built with this pretty easily, right? And so telcos that don't have as much funding, right. Smaller, more experiments. I think it's going to change the way we think about building networks in telcos >> And those smaller telcos I think are going to be more developer friendly. >> Danielle: Yeah. >> They're going to have business models that invite those developers in. And that's, it's the disruption's going to come from the ISVs and the workloads that are on top of that. >> Well certainly what Dish is trying to do, right? Dish is trying to build a- they launched it reinvent a developer experience. >> Dave: Yeah. >> Right. Built around their network and you know, again I don't know, they were not part of this group that designed these eight APIs but I'm sure they're looking with great intent on what does this mean for them. They'll probably adopt them because they want people to consume the network as APIs. That's their whole thing that Mark Roanne is trying to do. >> Okay, and then they're doing open ran. But is it- they're not really cons- They're not as concerned as Rakuten with the reliability and is that the right play? >> In this discussion? Open RAN is not an issue. It really is irrelevant. It's relevant for the longer term future of the industry by dis aggregating and being able to share, especially ran sharing, for example, in the short term in rural environments. But we'll see some of that happening and it will change, but it will also influence the way the other, the existing ran providers build their services and offer their value. Look you got to remember in the relationship between the equipment providers and the telcos are very dramatically. Whether it's Ericson, NOKIA, Samsung, Huawei, whoever. So those relations really, and the managed services element to that depends on what skills people have in-house within the telco and what service they're trying to deliver. So there's never one size fits all in this industry. >> You're very balanced in your analysis and I appreciate that. >> I try to be. >> But I am not. (chuckles) >> So when Dr went off, this is my question. When Dr went off a couple years ago on the cloud's going to take over the world, you were skeptical. You gave a approach. Have you? >> I still am. >> Have you moderated your thoughts on that or- >> I believe the telecom industry is is a very strong industry. It's my industry of course I love it. But the relationship it is developing much different relationships with the ecosystem players around it. You mentioned developers, you mentioned the cloud players the equipment guys are changing there's so many moving parts to build the telco of the future that every country needs a very strong telco environment to be able to support the site as a whole. People individuals so- >> Well I think two years ago we were talking about should they or shouldn't they, and now it's an inevitability. >> I don't think we were Danielle. >> All using the hyperscalers. >> We were always going to need to transform the telcos from the conservative environments in which they developed. And they've had control of everything in order to reduce if they get no extra revenue at all, reducing the cost they've got to go on a cloud migration path to do that. >> Amenable. >> Has it been harder than you thought? >> It's been easier than I thought. >> You think it's gone faster than >> It's gone way faster than I thought. I mean pushing on this flywheel I thought for sure it would take five to 10 years it is moving. I mean the maths comp thing the AWS announcements last week they're putting in hyperscalers in Saudi Arabia which is probably one of the most sort of data private places in the world. It's happening really fast. >> What Azure's doing? >> I feel like I can't even go to sleep. Because I got to keep up with it. It's crazy. >> Guys. >> This is awesome. >> So awesome having you back on. >> Yeah. >> Chris, thanks for co-hosting. Appreciate you stay here. >> Yep. >> Danielle, amazing. We'll see you. >> See you soon. >> A lot of action here. We're going to come out >> Great. >> Check out your venue. >> Yeah the Togi buses that are outside. >> The big buses. You got a great setup there. We're going to see you on Wednesday. Thanks again. >> Awesome. Thanks. >> All right. Keep it right there. We'll be back to wrap up day two from MWC 23 on theCUBE. (upbeat music)

(upbeat music) >> Hey, welcome back everyone, live coverage here. Re:invent 2022. I'm John Furrier, host of theCUBE. Two sets here. We got amazing content flowing. A third set upstairs in the executive briefing area. It's kind of a final review, day three. We got a special guest for do a re:Invent review. Muddu Sudhakar CEO founder of Aisera. Former multi-exit entrepreneur. Kind of a CUBE analyst who's always watching the floor, comes in, reports on our behalf. Thank you, you're seasoned veteran. Good to see you. Thanks for coming. >> Thank you John >> We've only got five minutes. Let's get into it. What's your report? What are you seeing here at re:Invent? What's the most important story? What's happening? What should people pay attention to? >> No, a lot of things. First all, thank you for having me John. But, most important thing what Amazon has announced is AIML. How they're doubling down on AIML. Amazon Connect for Wise. Watch out all the contact center vendors. Third, is in the area of workflow, low-code, no-code, workflow automation. I see these three are three big pillars. And, the fourth is ETL and ELTs. They're offering ETL as included as a part of S3 Redshift. I see those four areas are the big buckets. >> Well, it's not no ETL to S3. It's ETL into S3 or migration. >> That's right. >> Then the other one was Zero ETL Promise. >> Muddu: That's right. >> Which there's a skeptical group out there that think that's not possible. I do. I think ultimately that'll happen, but what's your take? >> I think it's going to happen. So, it's going to happen both within that data store as well as outside the data store, data coming in. I think that area, Amazon is going to slowly encroach into the whole thing will be part offered as a part of Redshift and S3. >> Got it. What else are you seeing? Security. >> Amazon Connect Amazon Connect is a big thing. >> John: Why is that so important? It seems like they already have that. >> They have it, but what they're doing now is to automate AI bots. They want to use AI bot to automate both agent assist, AI assist, and also WiseBot automation. So, all the contact center Wise to text they're doubling down. I think it's a good competition to Microsoft with the Nuance acquisition and what Zoom is doing today. So, I think within Microsoft, Zoom, and Amazon, it's a nice competition there. >> Okay, so we had Adam's keynote, a lot of security and data, that was big. Today, we had Swami, all ML, 13 announcements. Adam did telegraph to me that he was going to to share the love. Jassy would've probably taken most of those announcements, we know that. Adam shared the love. So, Adam, props to you for sharing the love with Swami and some of those announcements. We had 13. So, good for him. >> Yes. >> And then, we had Aruba with the partners. What's your take on the partner network? A revamp? >> No, I think Aruba did a very good job in terms of partners. Look at these, one of the best stores that Amazon does. Even the companies like me, I'm a startup company. They know how to include the partners, drive more revenue with partners, sell through it, more expansion. So, Amazon is still one of the best for startup to mid-market companies to go into enterprise. So, I love their partnership angle. >> One of the things I like that she said that resonated with me 'cause, I've been working with those teams, is it's unified, clear roles, but together. But, scaling the support for partners and making money for partners. >> That's right. >> That is a huge deal. Big road ahead. She's focused on it. She says, no problem. We want to scale up the business model of the channel. >> Muddu: That's right. >> The resources, so that the ecosystem can make money and serve customers or serve customers and make money. >> Muddu: That's right. And, I think one thing that they're always good is Marketplace. Now, they're doing is outside of market with ISV, co-sell, selling through. I think Amazon really understood that adding the value so that we make money as a partners and they make money, incrementally. So, I think Aruba is doing a very good job. I really like it. >> Okay, final question. What's going on with Werner? What do you expect to hear tomorrow from a developer front? Not a lot of developer productivity conversations at this re:Invent. Not a lot of people talking about software supply chain although Snyk was on theCUBE earlier. Developer productivity. Werner's going to speak to that tomorrow we think. Or, I don't know. What do you think? >> I think he's going talk something called generative AI. Rumored the people are talking about the code will be returned by the algorithms now. I think if I'm Werner, I'm going to talk about where the technology is going, where the humans will not be writing code. So, I think AI is going to double down with Amazon more on the generative AI. He's going to try a lot about that. >> Generative AI is hot. We could have generative CUBE, no hosts. >> Muddu: Yes, that would be good. >> No code, no host >> Muddu: Have an answer, John Software. (both laugh) >> We're going to automate everything. Muddu, great to hear from you. Thanks for reporting. Anything else on the ecosystem? Any observations on the ecosystem and their opportunity? >> So, coming from my side, if I'd to provide an answer, today we have like close to thousand leads that are good. Most of them are financial, healthcare. Healthcare is still one of the largest ones I saw in this conference. Financials, and then, I'm started seeing a lot more on the manufacturing. So, I think supply chain, they were not so. I think Amazon is doing fantastic job with financial, healthcare, and supply chain. >> Where is their blind spot if you had to point that one? >> I think media and entertainment. Media and entertainment is not that big on Amazon. So, I think we should see a lot more of those. >> Yeah, I think they need to look at that. Any other observations? Hallway conversations that are notable that you would like to share with folks watching? >> I think what needs to happen is with VMware, and Citrix desktop, and Endpoint Management. That's their blind spot. So far, nobody's really talking about the Endpoints. Your workstation, laptop, desktop. Remember, that was big with VMware. Nope, that's not a thought of conversation in email right now. So, I think that area is left behind by Amazon. Somebody needs to go after that white space. >> John: And, the audience here is over 50,000. Big numbers. >> Huge. One of the best shows, right? I mean after Covid. It's by far the best show I've seen in this year. >> All right, if you'd do a sizzle reel, what would it be? >> Sizzle reel. I think it's going to be a lot more on, as I said, generative to AI is the key word to watch. And, more than that, low-code no-code workflow automation. How do you automate the workflows? Which is where ServiceNow is fairly strong. I think you'll see Amazon and ServiceNow playing in the workflow automation. >> Muddu, thank you so much for coming on theCube sharing. That's a wrap up for day three here in theCUBE. I'm John Furrier, Dave Vellante for Lisa Martin, Savannah Peterson, all working on Paul Gillan and John Walls and the whole team. Thanks for all your support. Wrapping it up to the end of the day. Pulling the plug. We'll see you tomorrow. (upbeat music)

>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

(upbeat music) >> Welcome back to The Cube's coverage of Fal.Con 22. I'm Dave Vellante with Dave Nicholson. This is day one of our coverage. We had the big keynotes this morning. Derek Jeter was one of the keynotes. We have a big Yankee fan here: George Kurtz is the co-founder and CEO of CrowdStrike. George, thanks for coming on The Cube. >> It's great to be here. >> Boston fan, you know, I tweeted out Derek Jeter. He broke my heart many times, but I can't hate on Jeter. You got to have respect for the guy. >> Well, I still remember I was in Japan when Boston was down you know, by three games and came back to win. So I've got my own heartbreak as well. >> It did heal some wounds, but it almost changed the rivalry, you know? I mean, >> Yeah. >> Once, it's kind of neutralized it, you know? It's just not as interesting. I mean, I'm a season ticket holder. I go to all the games and Yankee games are great. A lot of it used to be, you would never walk into Fenway park with, you know pin stripes, when today there's as many Yankee fans as there are... >> I know. >> Boston fans. Anyway, at Fenway, I mean. >> Yeah. >> Why did you start CrowdStrike? >> Biggest thing for me was to really change the game in how people were looking at security. And at my previous company, I think a lot of people were buying security and not getting the outcome that they wanted. Not- I got acquired by a company, not my first company. So, to be clear, and before I started CrowdStrike, I was in the antivirus world, and they were spending a lot of money with antivirus vendors but not getting the outcome I thought they should achieve, which is to stop the breach, not just stop malware. And for me, security should be outcome based not sort of product based. And the biggest thing for us was how could we create the sales force of security that was focused on getting the right outcome: stopping the breach. >> And the premise, I've seen it, the unstoppable breach is a myth. No CSOs don't live by that mantra, but you do. How are you doing on that journey? >> Well I think, look, there's no 100% of anything in security, but what we've done is really created a platform that's focused on identifying and stopping breaches as well as now, extending that out into helping IT identify assets and their hygiene and basically providing more visibility into IT assets. So, we talked about the convergence of that. Maybe we'll get into it, but. >> Dave Vellante: Sure. >> We're doing pretty well. And from our standpoint, we've got a lot of customers, almost 20,000, that rely on us day to day to help stop the breach. >> Well, and when you dig into the CrowdStrike architecture, what's so fascinating is, you know, Dave, we've talked about this: agent bad. Well, not necessarily, if you can have a lightweight agent that can scale and support a number of modules, then you can consolidate all these point tools out there. You talked about in your keynote, your pillars, workloads, which really end points >> Right. >> ID, which we're going to talk about. Identity data and network security. You're not a network security specialist, >> Right. >> But the other three, >> Yes. >> You're knocking down. >> Yeah. >> You guys went deep into that today. Talk about that. >> We did, most folks are going to know us for endpoint and Cloud workload protection and visibility. We did an acquisition almost two years to the day on preempt. And that was our identity play, identity threat protection and detection. And that really turned out to be a smart move, because it's the hottest topic right now. If you look at all the breaches over the last couple years, it's all identity based. Big, big talking points in our keynotes today. >> Dave Vellante: Right. >> And then the third area is on data, and data is really the you know, the new currency that people trade in. So how do you identify and protect endpoints and workloads? How do you tie that together with identity, as well as understanding how you connect the dots and the data and where data flows? And that's really been our focus and we continue to deliver on that for customers. >> And you've had a real dogma, I'll call it, about Cloud Native. I've had this conversation with Frank Slootman, "No we're not going to do a halfway house." You, I think, said it really well today. I think it was you who said it. If you've got On-Prem and Cloud, you got two code bases, >> George Kurtz: Right. >> That you got to maintain. >> That's it, yeah. >> And that means you're taking away resources from one or the other. >> That's exactly right. And what a lot of our competitors have done is they started On-Prem as an AV vendor, and then they took what they had and they basically put it in a Cloud instance called a Cloud, which doesn't really scale. And then, you know, where they need to, they basically still keep their On-Prem, and that just diffuses your engineering team. And most of the On-Prem stuff doesn't even have the features of what they're trying to offer from the Cloud. So either you're Cloud Native or you're not. You can't be halfway. >> But it doesn't mean that you can't include and ingest On-Prem data- >> Well, absolutely. >> into your platform, and that's what I think most people just some reason don't seem to understand. >> Well our agents run wherever. They certainly run On-Prem. >> Dave Vellante: Right. Right. >> And they run in the Cloud, they run wherever. But the crowd in the CrowdStrike is the fact that we can crowdsource this threat information at scale into our threat graph, which gives us unique insight, 7 trillion events per week. And you can't do that if you're not Cloud Native. And that crowd gives the, we call, community immunity. We see all kinds of attacks across 176 different countries. That benefit accrues to all of our customers. >> But how do you envision and maintain and preserve a lightweight agent that can support so many modules? As you do more acquisitions and you knock down new areas and bring in new functionality, go after things like operations technology, how is it that you're able to keep that agent lightweight? >> Well, we started as a platform company, meaning that the whole idea was we're going to build a lightweight agent. First iteration had no security capabilities. It was collect data, get it into a common data architecture or threat graph, in one spot. And then once we had the data then we applied AI to it and we created different workflows. So, the first incarnation was get data into the Cloud at scale. And that still holds true today. So if you think about why we can actually have all these different modules without an impact on the performance, it's we collect data one time. It's a threat data, you know? We're not collecting user data, but threat data collection mechanism. Once we have all that data, then we can slice and dice and create other modules. So the new modules never have to even touch the agent 'cause we've already collected the data. >> I'm going to just keep going, Dave, unless you shove your way in. >> No, no, go ahead. No, no, no. I'm waiting to pounce. >> But okay, so, I think, George, but George, I need to ask you about a comment that you made about we're not just shoving it into a data lake. But you are collecting all the data. Can you explain that nuance? >> Yeah. So there's a difference between a collect and forward agent. It means they just collect a bunch of data. They'll probably store it in a lot of space on the endpoint. It's slow and cumbersome, and then they'll forward it up into another data lake. So you have no context going into no context. Our agent is a smart agent, which actually allows us to always track the context of all these processes in what's happening on the endpoint. And it's a mini graph, meaning we keep track of the relationships. And as we ship that contextual information to the Cloud, we never lose that context. And then it goes into the bigger graph database, always with the same level of context. So, we keep the context of each individual workload or endpoint, and then across the Cloud, we have the context of all of those put together. It's massive. And that allows us to create different insights rather than a data lake, which is, you know, you're looking for, you're creating a bigger needle stack looking for needles. >> And I'm envisioning almost an index that is super, super fast. I mean, you're talking about sub, well second kind of near real time responses, correct? >> Absolutely. So a lot of what we do in terms of protection is already pushed down to the endpoint , 'cause it has intelligence and the AI model. And then again, the Cloud is always looking for different anomalies, not only on each individual endpoint or workload, but across the entire spectrum of our customer base. And that's all real time. It continually self-learns from all the data we collect. >> So when, yeah, when you've made these architectural decisions over time, there was a time when saying that you needed to run an agent could be a deal killer somewhere for people who argued against that. >> George Kurtz: Right. >> You've made the right decision there, clearly. Having everything be crowdsourced into Cloud makes perfect sense. Has that, though, posed a challenge from a sovereignty perspective? If you were deploying stuff On-Prem all over the place, you don't need to worry about that. Everything is here >> George Kurtz: Yeah. >> in a given country. How do you address the challenges of sovereignty when these agents are sending data into some sort of centralized Cloud space that crosses boundaries? >> Well, yeah, I guess what we would, let me go back to the beginning. So I started company in 2011 and I had to convince people that delivering endpoint security from the Cloud was going to be a good thing. >> Dave Vellante: Right. (chuckles) >> You know, you go into a Swiss bank and a bunch of other places and they're like, you're crazy. Right? >> Dave Nicholson: Right. >> They all became customers afterwards, right? And you have to just look at what they're doing. And the question I would have in the early days is, well, let me ask you are you using Dropbox, Box? Are you using a Microsoft? You know, what are you using? Well, they're all sending data to the Cloud. So good news! You already have a model, you've already approved that, right? So let's talk about our benefit. And you know, you can either have an adversary steal your data or you can send threat data to our Cloud, which by the way is in a lot of sovereign Clouds that are out there. And when you actually break it down to what we're sending to the Cloud, it's threat data, right? It isn't user files and documents and stuff. It's threat data. So, we work through all of that. And the Cloud is bigger than CrowdStrike. So you look at Sales Force, Service Now, Workday, et cetera. That's being used all over the place, Box, Dropbox. We just tagged onto it. Like why shouldn't security be the platform of record, and why shouldn't CrowdStrike be the platform of record and be the pillar of Cloud security? >> Explain your observability strategy, 'cause you acquired Humio for, I mean, I think it was $400 million, which is a song. >> Yeah. >> And then Reposify is the latest acquisition. I see that as an extension, 'cause it gives you visibility. Is that part of your security, of your observability play? Explain where you do play and don't play. >> Sure. Well observability is a big, you know, fluffy word. Where we play is in probably the first two areas of observability, right? There's five, kind of, pillars. We're focused on event collection. Let's get events from the endpoints. Let's get events from really anywhere in the network. And we can do that with Humio is now log scale. And then the second piece is with our agents, let's get an understanding of their, the asset itself. What is the asset? What state is it in? Does it have vulnerabilities? Does it have, you know, is it running out of disc space? Is it have, does it have a performance issue? Those are really the first two, kind of, areas of observability. We're not in application performance, we're in let's collect data from the endpoint and other sources, and let's understand if the thing is working, right? And that's a huge value for customers. And we can do that because we already have a privileged spot on the endpoint with our agent. >> Got it. Question on the TAM. Like I look at your TAMs, your charts, I love it. You know, generally do. Were you taking known data from you know, firms like IDC >> George Kurtz: Yeah. >> and saying, okay we're going to play there, now we're made this acquisition. We're new modules, now we're playing there. Awesome. I think you got a big TAM. And I guess that's, that's the point. There's no lack of market for you. >> George Kurtz: Right. >> But I do feel like there's this unknown unquantifiable piece of your TAM. IDC can't see it, 'cause they're kind of looking back >> George Kurtz: Right. >> seein' what the market do last year and we'll forecast it out. It's almost, you got to be a futurist to see it. How do you think about your total available market and the opportunity that's out there? >> Well, it's well in excess of 120 billion and we've actually updated that recently. So it's even beyond that. But if you look at all the modules each module has a discreet TAM and again, for what, you know, what we're focused on is how do you give an outcome to a customer? So a lot of the modules map back into specific TAM and product categories. When you add 'em all up and when you look at, you know, some of the new things that we're coming out with, again, it's well in excess of 120 billion. So that's why we like to say like, you know, we're not an endpoint company. We're really, truly a security platform company that was born in the Cloud. And I think if you see the growth rates, and one of the things that we've talked about, and I think you might have pointed out in prior podcasts, is we're the second fastest company to 2 billion dollars in annual recurring revenue, only behind Zoom. And you know I would argue- great company, by the way, a customer- but that was a black Swan event in a pandemic, right? >> Dave Vellante: I'll say! >> Yeah. >> So we are rarefied air when you think about the capabilities that we have and the performance and the TAM that's available to us. >> The other thing I said in my breaking analysis was 'cause you guys aspire to be a generational company. And I think you got a really good shot at being one, but to be a generational company, you have to have an ecosystem. So I'd love you to talk about the ecosystem, but where you want to see it in five years. >> Well, it really is a good point and we are a partner first company. Ecosystem is really important. Cameras probably can't see all the vendors that are here that are our partners, right? It's a big part of this show that we're at. You see a lot of, well, you see some vendors behind us. >> Yep. >> We have to realize in 2022, and I think this is something that we did well and it's my philosophy, is we are not the only game in town. We like to be, and we are, for many companies the security platform on record, but we don't do everything. We talked about network in other areas. We can't do everything. You can't be good and try to do everything. So, for customers today, what they're looking at is best of platform. And in the early days of security, I've been in it over 30 years, it used to be best of breed products, then it was best of suite, now it's best of platform. So what do I mean by that? It means that customers don't want to engineer their own solution. They, like Lego blocks, they want to pull the platforms, and they want to stitch 'em together via API. And they want to say, okay, CrowdStrike works with Okta, works with Zscaler, works with Proofpoint, et cetera. And that's what customers want. So, ecosystem is incredibly important for us. >> Explain that. You mentioned Okta, I had another question for you. I was at Reinforce, and I saw this better together presentation, CrowdStrike and Okta talking about identity. You've got an identity module. Explain to people how you're not competing with Okta. You guys complement each other, there. >> Well, an identity kind of broker, if you will, is basically what Okta does in others, right? So you log in single sign on and you get access. They broker access to all these other applications. >> Dave Vellante: Right. >> That's not what we do. What we do is we look at those endpoints and workloads and domain controllers and directory services and we figure out, are there vulnerabilities and are there threats associated with them? And we call that out. The second piece, which is critical, is we prevent lateral movement. So if credentials are stolen we can prevent those credentials from being laundered or used and moved laterally, which is a key part of how breaches happen. We then create a trust score on those endpoints and workloads. And we basically say, okay, do we think the trust on the endpoint and workload is high or low? Do we think the identity, you know, is it George on the endpoint, or not? We give that a score. And we pass that along to Okta or Ping or whoever, and they then use that as part of their calculus in how they broker access to other resources. So it really is better together. >> So your execution has been stellar. This is my competition question. You obviously have competition out there. I think architecturally, you've got some advantages. You have a great relationship with AWS. I don't know what's going on with Google, but Kevin's up on stage. >> George Kurtz: Yeah. >> They're now part of Google. >> George Kurtz: We have a great relationship with them. >> Microsoft obviously, a competitor. You obviously do some things in, >> Right. >> in Azure. Are you building the security Cloud? >> We are. We think we are, because when you look at the amount of data that we actually ingest, when you look at companies using us for critical decisions and critical protection, not only on their On-Prem, but also in their Cloud environment, and the knowledge we have, we think it is a security Cloud. You know, you had, you had Salesforce and Workday and ServiceNow and each of them had their respective Clouds. When I started the company, there was no security Cloud. You know, it wasn't any of the companies that you know. It wasn't the firewall companies, wasn't the AV companies. And I think we really defined ourselves as the security Cloud. And the level of knowledge and insights we have in our Cloud, I think, are world class. >> But you know, it's a difference of being those- 'cause you mentioned those other, you know, seminal Clouds. They, like Salesforce, Workday, they're building their own Clouds. Maybe not so much Workday, but certainly Salesforce and ServiceNow built their own >> Yeah. >> Clouds, their own data centers. You're building on top of hyperscalers, correct? >> Well, >> Well you have your own data centers, too. >> We have our own data centers, yeah. So when we first started, we started in AWS as many do, and we have a great relationship there. We continue to build out. We are a huge customer and we also have, you know, with data sovereignty and those sort of things, we've got a lot of our sort of data that sits in our private Cloud. So it's a hybrid approach and we think it's the best of both worlds. >> Okay. And you mean you can manage those costs and it's, how do you make the decision? Is it just sovereignty or is it cost as well? >> Well, there's an operational element. There's cost. There's everything. There's a lot that goes into it. >> Right. >> And at the end of the day we want to make sure that we're using the right technology in the right Clouds to solve the right problem. >> Well, George, congratulations on being back in person. That's got to feel good. >> It feels really good. >> Got a really good audience here. I don't know what the numbers are but there's many thousands here, >> Thousands, yeah. >> at the ARIA. Really appreciate your time. And thanks for having The Cube here. You guys built a great set for us. >> Well, we appreciate all you do. I enjoy your programs. And I think hopefully we've given the audience a good idea of what CrowdStrike's all about, the impact we have and certainly the growth trajectory that we're on. So thank you. >> Fantastic. All right, George Kurtz, Dave Vellante for Dave Nicholson. We're going to wrap up day one. We'll be back tomorrow, first thing in the morning, live from the ARIA. We'll see you then. (calm music)

(light upbeat music) (mouse clicks) >> Hey, everyone. Welcome back to the program. Lisa Martin here. I've got two guests joining me. Please welcome back to The Cube, Paula Hansen, the chief revenue officer and president at Alteryx. And Jacqui Van der Leij - Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the program. >> Thank you, Lisa. >> Thank you, Lisa. >> It's great to be here. >> Yeah, Paula. We're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation. With analytics as they talked about at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform but ultimately, we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >> Excellent. Sounds like a very strategic program. We're going to unpack that. Jacqui let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How, Jacqui, did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is just when we started out was, is that, you know, our, especially in finance they became spreadsheet professionals, instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no, we're not independent. You couldn't move forward. You would've been dependent on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. And finally, we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks because you always have, not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's our people that need to actually really embrace it and making that accessible for them, I would say is definitely not per se, a roadblock but basically some, a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula will start with you, and then Jacqui will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven? Paula? >> Yes. Well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting, all of our key performance metrics for business planning across our audit function to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter so it's really remained across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases. And so one of the other things that we've seen many companies do is to gamify that process to build a game that brings users into the experience for training and to work with each other, to problem solve, and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of you know, getting people excited about it but it's also understanding that this is a journey. And everybody is the different place in their journey. You have folks that's already really advanced who has done this every day, and then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the initial destination. I say initially, because I believe the journey is never really complete. What we have done is that we decided to invest in a... We build a proof of concepts and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom. And we told people, "Listen, we're going to teach you this tool, super easy. And let's just see what you can do." We ended up having 70 entries. We had only three weeks. So, and these are people that has... They do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon. From the 70 entries with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was people had a proof of concept, they knew that it worked, and they overcame that initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula will start with you. >> Absolutely. And Jacqui says it so well, which is that it really is a journey that organizations are on. And we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay, and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED, we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED just made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kicked that momentum from the hackathon. Like we don't lose that excitement, right? So we just launched a program called eBay Masterminds. And what it basically is, it's an inclusive innovation initiative, where we firmly believe that innovation is for upscaling for all analytics role. So it doesn't matter your background, doesn't matter which function you are in, come and participate in this, where we really focus on innovation, introducing new technologies and upscaling our people. We are... Apart from that, we also said... Well, we should just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter Alteryx. And we're working with actually, we're working with SparkED and they're helping us develop that program. And we really hope that, let us say, by the end of the year have a pilot and then also next, was hoping to roll it out in multiple locations, in multiple countries, and really, really focus on that whole concept of analytics role. >> Analytics role, sounds like Alteryx and eBay have a great synergistic relationship there, that is jointly aimed at, especially, kind of, going down the stuff and getting people when they're younger interested and understanding how they can be empowered with data across any industry. Paula let's go back to you. You were recently on The Cube's Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world? How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last, I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. (Paula clears throat) So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud, is to empower all of those people in every job function regardless of their skillset. As Jacqui pointed out from people that would, you know are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud and it operates in a multi-cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skills gap as you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues. And what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we started about getting excited about things when it comes to analytics, I can go on all day but I'll keep it short and sweet for you. I do think we are on the topic full of data scientists. And I really feel that that is your next step, for us anyways, it's just that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx would just release the AI/ML solution, allowing, you know, folks to not have a data scientist program but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses quite a few. And right now, through our mastermind program we're actually running a four-months program for all skill levels. Teaching them AI/ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services, we have even some of our engineers, are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all was able to develop a solution where, you know, there is a checkout feedback, checkout functionality on the eBay site, where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in. And now instead of us or somebody going to the bay to try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. And it's a beautiful tool, and I'm very impressed when you saw the demo and they've been developing that further. >> That sounds fantastic. And I think just the one word that keeps coming to mind and we've said this a number of times in the program today is, empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you >> Thank you, Lisa. >> Thank you so much. (light upbeat music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four E's that's, everyone, everything, everywhere and easy analytics. Those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics. Not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com, and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring The Cube. For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (light upbeat music)

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>>Hey, everyone, welcome back to the programme. Lisa Martin here. I've got two guests joining me. Please welcome back to the Q. Paula Hanson, the chief Revenue officer and president at all tricks. And Jackie Vanderlei Grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an all tricks is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the programme. >>Thank you, Lisa. Not great to be >>here. >>Yeah, Paula, we're gonna start with you in this programme. We've heard from Jason Klein. We've heard from Allan Jacobsen. They talked about the need to democratise analytics across any organisation to really drive innovation with analytics as they talked about at the forefront of software investments. House all tricks, helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. Absolutely is about our customers success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform. But ultimately we help our customers to create a culture of data literacy and analytics from the top of the organisation starting with the C suite and we partner with our customers to build their road maps for scaling that culture of analytics through things like enablement programmes, skills assessments, hackathons, uh, setting up centres of excellence to help their organisation scale and drive governance of this, uh, analytics capability across the Enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practises so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic programme. We're gonna unpack that, Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the I. D. C report that showed that 93% of organisations are not utilising the analytic skills of their employees. But then there's eBay. How Jackie did eBay become one of the 7% of organisations who's really maturing and how are you using analytics across the organisation at bay? >>So I think the main thing for us is when we started out was is that you know our especially in finance. They became spreadsheet professionals instead of the things that we really want our influence to add value to. And we realised we have to address that. And we also knew we couldn't wait for all our data to be centralised until we actually start using the data or start automating and be more effective. Um, so ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >>Starting with people is really critical jacket continuing with you. What was in the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think you know, Eva is a very data driven company. We have a lot of data. I think we are 27 years around this year. So we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them, um, to move forward. The other thing is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no we're not independent. You couldn't move forward. You're dependent on somebody else's roadmap to get to data to get the information you want it. So really finding something that everybody could access analytics or access data. And finally we have to realise, is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would I would call those out as your as your major roadblocks, because you always have always. But most of the times you have support from the top. In our case we have. But in the end of the day, it's it's our people that need to actually really embrace it and making that accessible for them. I would say it's not to say a road block a block you want to be able to do. >>It's really all about putting people first question for both of you and Paula will start with you and then Jackie will go to you. I think the message in this programme that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organisations are empowering people, those in the organisation that may not have technical expertise to be able to leverage data so that they can actually be data driven colour. >>Yes, well, we leverage our platform across all of our business functions here at all tricks. And just like Jackie explained that eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data, uh, flowing through our enterprise, and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Ruben has been a key sponsor for using our own technology. We use all tricks for forecasting all of our key performance metrics for business planning across our audit function, uh, to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to How do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other to problem solve and, along the way, maybe earn badges, depending on the capabilities and trainings that they take and just have a little healthy competition, Uh, as an employee based around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable that they feel supportive, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>I think it means to what Paula has said in terms of, you know, getting people excited about it. But it's also understanding that this is a journey and everybody is the different place in their journey. You have folks that's already really advanced. Who's done this every day. And then you have really some folks that this is brand new and, um, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the the initial destination. And I say initial because I believe the journey is never really complete. Um, what we have done is that we decided to invest in a group of concept when we got our CFO to sponsor a hackathon. Um, we open it up to everybody in finance, um, in the middle of the pandemic. So everybody was on Zoom, um, and we had and we told people, Listen, we're gonna teach you this tool. It's super easy, and let's just see what you can do. We ended up having 70 injuries. We had only three weeks. So these are people that that do not have a background. They are not engineers and not data scientists and we ended up with 25,000 our savings at the end of the hackathon. Um, from the 70 countries with people that I've never, ever done anything like this before. And there you have the results. And they just went from there because people had a proof of concept. They knew that it worked and they overcame the initial barrier of change. Um, and that's what we are seeing things really, really picking up now >>that's fantastic. And the business outcome that you mentioned that the business impact is massive, helping folks get that confidence to be able to overcome. Sometimes the cultural barriers is key there. I think another thing that this programme has really highlighted is there is a clear demand for data literacy in the job market, regardless of organisation. Can each of you share more about how your empowering the next generation of data workers Paula will start with you? >>Absolutely. And Jackie says it so well, which is that it really is a journey that organisations are on and we, as people in society, are on in terms of up skilling our capabilities. Uh, so one of the things that we're doing here at all tricks to help address the skill set gap on a global level is through a programme that we call Sparked, which is essentially a no cost analyst education programme that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this programme is really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises when we close gap and empower more people with the necessary analytic skills to solve all the problems that data can help solve. >>So >>I just made a really big impact in such a short time period is gonna be fun to watch the progress of that. Jackie, let's go over to you now Talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we definitely wanted to make sure that we kept implemented from the hackathon that we don't lose that excitement life. So we just launched a programme for evil masterminds and what it basically is. It's an inclusive innovation initiative where we firmly believe that innovation is all upscaling for all analytics role. So it doesn't matter. Your background doesn't matter which function you are in. Come and participate in this where we really focus on innovation, introducing these technologies and upscaling of people. Um, we are apart from that. We also said, Well, we should just keep it to inside the way we have to share this innovation with the community. So we are actually working on developing an analytics high school programme which we hope to pilot by the end of this year. We will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, But also, um, how to use all tricks and we're working with Actually, we're working with spark and they're helping us develop that programme. And we really hope that it is said by the end of the year, have a pilot and then also makes you must have been rolled out in multiple locations in multiple countries and really, really, uh, focused on that whole concept of analytic school >>analytics. Girl sounds like ultra and everybody have a great synergistic relationship there that is jointly aimed at especially kind of going down the stock and getting people when they're younger, interested and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the cubes Super Cloud event just a couple of weeks ago and you talked about the challenges the companies are facing as they are navigating what is by default, a multi cloud world. How does the all tricks analytics cloud platform enable CEO s to democratise analytics across their organisation? >>Yes, business leaders and CEO s across all industries are realising that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organisations. Last I checked, there was two million data scientists in the world. So that's, uh, woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CEO s with business leaders is that they are integrating data analysis and the skill set of data analysis into virtually every job function. Uh, and that is what we think of when we think of analytics for all. And so our mission with all tricks analytics cloud is to empower all of those people in every job function, regardless of their skill set, as Jackie pointed out, from people that would are just getting started all the way to the most sophisticated of technical users. Um, every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organisations. So that's our goal with all tricks, analytics cloud and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyse and report out so that we can break down data silos across the Enterprise and Dr Real Business Outcomes. As a result, of unlocking the potential of data >>as well as really listening that skills gap. As you were saying, There's only two million data scientists. You don't need to be a data scientist. That's the beauty of what all tricks is enabling. And eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where all tricks fits in as that analytics maturity journey continues. And what are some of the things that you're most excited about as analytics truly gets democratised across eBay >>when we start about getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. Um, I do think we're on the topic full of data scientists, and I really feel that that is your next step for us, anyway. Is that how do we get folks to not see data scientist as this big thing like a rocket scientist it's something completely different and it's something that is in everybody in a certain extent. So, um, game partnering with all tricks to just release uh, ai ml um, solution allowing. You know, folks do not have a data scientist programme but actually build models and be able to solve problems that way. So we have engaged with all turrets and we purchase the licence is quite a few. And right now, through our masterminds programme, we're actually running a four months programme. Um, for all skill levels, um, teaching them ai ml and machine learning and how they can build their own models. Um, we are really excited about that. We have over 50 participants without the background from all over the organisation. We have members from our customer services. We have even some of our engineers are actually participating in the programme will just kick it off. And I really believe that that is our next step. Um, I want to give you a quick example of the beauty of this is where we actually, um, just allow people to go out and think about ideas and come up with things and one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution. Where, um, you know there is a checkout feedback checkout functionality on the eBay side, There's sellers or buyers can pervade them at information. And she built a model to be able to determine what relates to tax specific what is the type of problem and even predict how that problem can be solved before we as human, even stepped in. And now, instead of us or somebody going to debate and try to figure out what's going on there, we can focus on fixing their versus, um, actually just reading through things and not adding any value and its a beautiful tool. And I'm very impressed when we saw the demo and they've been developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind. And we've said this a number of times in the programme. Today's empowerment, what you're actually really doing to truly empower people across the organisation with with varying degrees of skill level, going down to the high school level really exciting. We'll have so stay tuned to see what some of the great things are that come from this continued partnership? Ladies, I wanna thank you so much for joining me on the programme today and talking about how all tricks and eBay are really partnering together to democratise analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>Thank you so much.

(upbeat music) >> Good morning, everyone. Welcome back to "theCUBE." Lisa Martin here with John Furrier. This is day three of our wall-to-wall coverage of VMware Explore. John and I are pleased to welcome back one of our alumni, Muddu Sudhakar, the CEO of AISERA. Welcome to the program, Muddu. It's great to meet you. >> Thank you, Lisa. Thanks for having me. Thank you, John. >> Great to see you again. You're like an industry analyst coming on "theCUBE". You should be like a guest analyst, breaking down. I know you got your own company to run, and by the way, the recent funding you had, congratulations. >> Thank you. >> In a market that's not getting a lot of funding. You get an up around. Congratulations on that. >> Thank you. >> Business is good? >> Very good, thank you. Look, Goldman Sachs Investing, along with Zoom and Thoma Bravo, it was great for us. >> Great stuff. Well, I'm glad we could get you in. This day three, Lisa and I and Dave Vellante and Dave Nicholson have all been talking to everyone for two days here at VMware Explore, formerly VMworld, our 12th year covering their annual conference, as you know, and we've been telling the executives, but day three is more of, we're going to mix it up. We're going to bring people in and get their opinions about Supercloud, does VMware go post-Broadcom? Obviously, that's going to happen. Looks like nothing's going to stop that from happening. What's next? What's the impact? Who wins? Who loses? VMware certainly not acting like they're going to get gutted. They're all full throttle ahead. They're laying down some announcements, vSphere 8, you got vSAN 8, they got cloud-native, they're talking multi-cloud. VMware's not looking like they're flinching. What's going on, in your view, outside of the bubble that we're here in San Francisco, out in the real world, in the trenches. What are people talking about? What do you see? >> Lot to unpack. (all laugh) >> Start at wherever you want. >> Yes. You know, I was a VMware alumni too. >> Yes >> You sold the company to VMware. You know the inside. Okay, So then, even then- >> I worked with Paul and Pat and Raghu. It's great to be back at VMware now. I think there's a lot going on in VMware. VMware is here to stay. The brand will stay. The VMware customers will stay for years to come. I think Broadcom and VMware, I think it's a great industry consolidation, the way in which I see it. And it is going to help all the customers too, right? Broadcom, having such a large foot play into both CA, the software business, the hardware business. I think what will happen is that Broadcom will try to create a hybrid cloud of their own with VMware. So there'll be a fourth player in the cloud industry. And then back to John, your Supercloud. The Supercloud by definition, there'll be private clouds, public clouds, hybrid clouds. I think Broadcom with VMware will help your vision of the Supercloud and what your customers are asking. >> Yeah, one of the things I want to get your thoughts on, Lisa and I were talking yesterday with the executives, AJ Patel in particular, he's a middleware guy. >> Right. >> So what he did was Oracle. He did a lot of the fusion stuff at Oracle. He now runs Modern Apps. And you came in at the time, I think, when they were just getting that app vision going, and Paul Moritz actually had it early with his 2010 vision, but too early on the app side. But that ended up happening too. So the question is, is Broadcom going to be this middleware layer, and treat the cloud like hardware. And then, apps or apps. Companies are apps. In a digital transformation, technology is the company. >> Right >> So the company is the app. >> That's right, >> Is an application. So apps and hardware, middle, a middleware model emerging. Do you think they're going for that? Or am I just making this up in my head? >> No, I think to me, I see Broadcom as much more, they're like a peer company at the high level. So they're funded by- >> Like a private equity company. >> Private equity company. >> You mean from a dollar standpoint. >> From a dollar standpoint. So Broadcom is going to fund companies. They're going to buy companies. They bought CA, they bought all the other assets. So Broadcom will have always hardware. The middle level could be VMware, but they also have CA, right? They have a bunch of apps here. So I see the Broadcom is also using VMware to run applications. So the consolidation will be they'll create a Supercloud using VMware. They're going to own their own apps. I don't think Broadcom's story is stopped. Its journey to come. They're going to buy more acquisitions, more apps companies. I won't be surprised, in the future, they buy Zendesk. I won't be surprised, in the future, they buy other apps companies, SaaS companies and cloud enterprise companies. Right? So that's where the P is coming. So the broad conversion is, I need a base middleware, like you're saying. There's no other middleware on top of hardware better than VMware. >> So do you think that they'll keep the stuff that's coming out of the other? 'Cause we've been speculating on "theCUBE" this week. They have the core business, but there's all this stuff that's kind of coming out of the oven that's not EBITDA-oriented yet. Do you think they keep that or they let it go? >> I think that's a great question to hang their CEO of Broadcom. But to me, I think, knowing them, they're going to keep, and if you look at Symantec, they kept parts of Symantec, this whole parts of it. So I think all options are on the table for them, right? They'll do whatever it is. But I think it has to be the ones that high growth companies they may give it. It all goes back to is it a profitability to it or not? But his vision is very good. I want to own the middleware, right? He will own the middleware using VMware to your vision, create a Supercloud and own the apps. So I think you'll see Broadcom is the fourth vendor in the cloud race. You have Microsoft, AWS, Google, and Broadcom is actually going to compete with this four. >> So you think there'll be a hyper scale? They'll be in the top three or four. >> There'll be top four. >> Okay. >> Along with Oracle. So now, we are talking about the five vendors will be Amazon, Azure, Google, Oracle, and Broadcom. >> We had Amazon guy on, Steve Jones. I should have asked him that question. I just don't see that happening yet. They have to have the full hardware side. How do you see that coming in? 'Cause Amazon's innovating at the atom level and they're working on stuff that's physical, transit, physics stuff, like down to the root level. >> I think Broadcom figure, look, they own the chips out right, at the end of the day. They also have a lot of chips such to supply to both mobile and this. So if there's anybody who can figure out the hardware, it will be Broadcom. That is their core of area. They didn't have the core in the software and the middleware. VMware is going to give them the OS, the Kubernetes, the VMs. Once you have that layer, I think you can innovate both up and below, right? So I think, John, I think Broadcom VMware will be a force to reckon with and I think these guys are going to get into healthcare space though. So if you see the way they battle, you and me are talking Lisa, like Microsoft bought new ones, Oracle bought Cerner. So they all paid 30 billion each. So the next battle ground will be, they'll start in the healthcare industry. Somebody's going to go look at the healthcare apps like Epic, right? They're going to look at how we can do the hospitals. They're going to look at hospital healthcare professionals. That area will be disrupted a lot in the same. >> What other industries do you think, besides healthcare, are ripe for disruption with Broadcom VMware? >> I think endpoint management, like remember VMware bought AirWatch when I was there back then, right? That whole area is called digital experience management. So that endpoint mainly will be disrupted. So Broadcom with VMware will go again into endpoint. I'm talking endpoint could be the servers, desktops, VMware Max, right? Virtual Desktop VDI. So that whole management of mobile devices to desktop, that whole industry will be disrupted. A lot of players are there trying to do more consulting services. I think VMware is a great assets and tools. If I'm Broadcom, my chip sets are going into the endpoint. So that area will be disrupted a lot with Broadcom in VMware. >> Yeah, one of the things that VMware, people have been talking about, is that the CA acquisition that Broadcom did was the playbooks public. Everyone saw what they did. They killed sales and market and they killed all the execs, metaphorically speaking. They fired them. VMware's got a different vibe here. I'm feeling like it could go one way or the other. I think they should keep them, personally. But you don't know. If they're a PE company, they EBIDA driven, maybe it's just simply numbers. >> Right. >> If that's the case, then I'm worried. But VMware's got pride, they got mojo, and they've got expertise in software. Maybe a little bit different circumstance? What's take on this? Or do you think it's going to be black and white to the numbers? >> I think, knowing Hank's playbook, if he knows what he's going to do, right? His playbook will be consistent with Symantec. >> You think he already knows what he wants to do? >> I think so. I think at that level, both with Simulink and Broadcom, they already know the playbook. At this stage the games, people already know their game. It's like a chess move. They already know. They'll look at VMware and see which assets to keep, which one not to keep, which organization, but I think Hank is a master at this one. To me, I'm personally excited with the VMware Broadcom combination. It's a great thing for the industry. It's great for VMware and VMware customers and partners. >> Well, John, you and Dave had a chance to sit down with Raghu. What were some of the things that he unpacked about the Broadcom acquisition? >> He was on talking points. He was on message. He was saying the things that any CEO was going to make a lot of cash on this deal. And he's proud. I think it wasn't about the money for him. I sensed that he's certainly going to make a lot of cash on this deal as an executive, but he's a long time VMware employee and a well loved and revered person. He's done a lot of great work, technically set the agenda. So I think their mindset is we're going to just continue to do an amazing job as VMware as we are and then let Broadcom, let the chips fall where they may, and hopefully, if they do a good job, maybe they'll either refactor some of their base plans or they laid it all out in the field, so to speak. So that's my vibe. Now specifically, he made some comments, like, "Yeah, we're really proud." And he staying technical. He's still like, "This is really happening." So I think he's going to, essentially, to the very end, be like, "Cross cloud and hybrid cloud. This is our third generation." So there he's hanging onto the VMware third act that they're saying, and he hopes that it comes home. And I think he's going to just deal with it. He didn't seem flustered and he didn't seem overly confident. >> Okay. >> I guess that's my opinion. What do you think? >> Personally worked with Raghu, worked for Raghu, so I think of him as the greatest CEO for VMware ever could have, right? It's a journey. It was Paul Maritz, then Pat Gelsinger, now Raghu. I think he's in the right place, right time to lead VMware, and Raghu's doing a fantastic job. And personally, getting these two companies married, I think Raghu did the right partnership with Broadcom. >> Well, I think if this event's any indication if they're just sitting back and waiting, they're not, and this event was well done, it was pulled off. The branding's amazing. I thought they did a good job with the name change. And then in light of all the Broadcom issues, the execution was great. It was not a bad show here. It was a good show. It wasn't terrible at all. People were excited. I think the ecosystem also felt that Broadcom, like an electronic shock to the system, like something's going to happen. Let's wait and see. I'm going to go to the event to see if it's going to be around and kind of getting a feel first party, in person, what's happening. Again, remember VMware didn't have an event since 2019. This is a community that thrives on physical, face to face camaraderie, community. And so, I think the show was a success. And I think that's a result of Raghu and his team. >> Because we have a booth there for AISERA, my company, we have a booth. We are offering coffee and donuts. You guys should come by and tell people. You'll get a free coffee and a donut, but it's one of the best shows I've seen. Well, I think people after pandemic are back, people are interacting. We have 500 people in one day at our booth. So for a startup company like us, getting that much crowd is unheard of. So it's great. We're very excited. >> The vibe from the partner community, I had a chance to talk with a lot of partners, AWS, NetApp, Rackspace, really seems like the partnerships side of VMware is very, very strong and the partners are excited about what's next for VMware. Did you have a chance to talk with any of the partners? >> Actually, look. I'm actually meeting with Karen. So Karen Egan is my contact at VMware too, and Sumit, (indistinct) a bunch of the customer success organization. We talk to people in their digital experience management team. We are very excited to be partner with both VMware's customer, partner, and all experts, right? I'll need the VMware ecosystem for my company to thrive. So for us, VMware customers are my customers and leveraging VMware APIs into VMware, that's that's important for us. >> Lisa, that's a great question because that brings us to the question of, okay, clearly this show also proves to us from our conversations and exploring the floor, the wave is coming. This next cloud wave is here. We're calling it Supercloud, whatever you want to call it, it's coming and it's real, and people know it. And also the lines of sight into economics around where people can fit in this next level ecosystem is becoming clear. So I think people kind of know what's the right side of the street to be on in this next shift. So that's coming. That's independent of Broadcom. So the floor represents to me the excitement for not only the VMware workload powering software, with or without Broadcom, but the next wave. So the question is if Broadcom goes down their path and Hank does what he does, who wins and who loses on where things flow? Because this energy is going to flow somewhere. Is it going to flow to AWS? Is it going to flow to Microsoft? Is it going to flow to HPE with Green Lake getting some great traction? NetApp's doing great. We just heard from them. So the partners aren't hurting. It's only going to get better. re:Invent's right around the corner. That's a packed house. Their ecosystem's growing like a weed. Who wins? 'Cause the customers at VMware are enterprise customers. They're used to being serviced. They have sales reps from Microsoft, they got sales reps from Hewlett Packard Enterprise, real senior enterprise stakeholders there. So someone's going to end up filling in as VMware settles into their broad composition. Who wins and who loses, in your mind? >> A Very good question. So my thing is, I think it's... Well, I put Microsoft and Amazon the winners. In that way, actually mean Microsoft will win because in a true Supercloud, your vision, back to hybrid cloud on-prem and public cloud, VMware disruption with Broadcom, as if there's any bridge in the market, Microsoft will take advantage of it. Azure, right? Amazon VMware is there. Then, you have Google and VMware. So I think Azure will probably try to take advantage of this, but very next will be Amazon, right away there. That leaves you with Google Cloud, right? Google Cloud is the one. So they're the people that are able to figure out what to do in this equation. And then, obviously, the other one is Oracle. Oracle has no hearts in this game. So to me, the people who are going to probably lose impact model will be Oracle if the Broadcom and VMware will happen. So it's Azure, Amazon winning the race, probably Google is right behind them. Oracle will be distinct. Other side is Dell. Actually, Dell has no game in this. Our Broadcom and VMware, Dell should be the one. >> Dell might have a little secret sauce on the table with Michael Dell. >> That's true. >> If he convert his shares, he might be the largest shareholder at Broadcom. >> That's true. >> He could end up owning all the back. >> So he may be the winner all the time. (all laugh) >> Don't count him out. Well, this is a good question. I want to just double click on this. So you get customer dynamic. Where do they go? You get the community, which is a big force multiplier in this world, and if you had to bet on community between Microsoft and Amazon Web Services, Amazon trumps Microsoft on force multiplier community. Ecosystem, AWS beats Microsoft on that one. So it's interesting because it's now multiple dimensions we're talking about here. It's customers. That's the top order, right? The customers. But also, you got community, the people who put on sessions, the people in the community that are the influencers that are leading the trends, and developers are very trending, relative to what kind of code they use, what's their environments? So the developers is changing that landscape and, ultimately, the ecosystem of partners, right? 'Cause there's a lot more overlap between AWS and VMware's ecosystem than there is between Microsoft and that. And HPE is just starting an ecosystem. So it's going to be very interesting. >> It is. It is. I think Broadcom and VMware cannot be any best time for the industry, right? As you said. HP is coming in. Oracle is coming in. And to your point, VMware and AWS are another best partners. Now, this going to create any gap for Microsoft to enter for Azure? I think that's where the market is saying that it's going to open up a hybrid cloud player for Microsoft to enter what is to be a tight relationship with VMware and Amazon. Right? So people will rethink through their apps. And more importantly, the end point to me. See, the key is, like you talk about with Supercloud, nobody's talking about Supercloud for the endpoint. >> You mean Edge or security? >> Not an Edge endpoint. Endpoint could be your devices, laptop, desktop. >> Or a building or a light bulb or whatever. >> Desktop or VDI desktop services servers, right? So we call it endpoint cloud. There's no endpoint Supercloud. John, that's an area that you should double click on. Super cloud for the servers is different from Supercloud for endpoint. >> Well, SuperCloud.World is the URL out there. If you're interested in Supercloud, we are adding tracks to that body of work. So we had our event on August 9th. It was virtual event, where Dave and I are going to add a data track, we're going to add a security track, and we should add, maybe, an endpoint workspace, work. >> That's a VMware brand, Workspace and Horizon. So that whole workspace endpoint for Supercloud is going to happen. >> Yes. >> Right. That kind of deviates from- >> Do you like Supercloud? Are you bullish on Supercloud? >> I'm very bullish on Supercloud because I, myself, is running on-prem in VPCs, public clouds, private clouds. Supercloud kind of composites it so app should be designed. 'Cause I don't want to design an app for one cloud. It's not going to work. So it's like how Java came and I can run it on any platform. The ideas you build it on Supercloud, run it, whatever you want. Right? >> That's exactly it. So what would you want to see in Supercloud as it evolves? And we were part of this open conversation. This is our point for today. We're going to have a great panel come up later today. We're going to have the influencers come on to debate what Supercloud should or shouldn't be. If you want to add to the contribution, we'll add this into the work, what should what's needed in Supercloud? What's table stakes. >> I think we need a Java compiler that will happen for Supercloud. I build it once, execute in any place I want, right? Using the Terraform, HashiCorp (indistinct) So what I don't want is keep building this thing for every cloud. I want to abstract that out. The whole idea of Supercloud is how Java gave me the abstraction for hardware 20 years back or 30 years back, we need the same abstraction for the cloud today. Otherwise, I'm customizing for VM Cloud, I'm customizing for AWS, Azure, Google Cloud. We, as an application vendor, it's too hard to keep doing it. I have now thousand tuners. I don't need thousand DevOps people. I need maybe 10 DevOps people. So there's a clear abstraction complexity that industry should develop, and your concept Supercloud with everybody thinking that, and it has to start from the grassroots with ecosystem. >> What do you think about the participants in this abstraction layer? Because someone said on "theCUBE" here this week, the people in the abstraction layer shouldn't be participants in the below or above the abstraction. >> I think it should be everybody, right? It's all inclusive. You need the apps guys to come in. You need the OS players to come in. You need the cloud vendors to come in, infrastructure. So you need everybody. >> Okay, let's just say that you were the spokesperson for the Supercloud organization, Supercloud.World. How would you sell AWS on why it's important for them? >> It's because they can build it and sell it in AWS and multiple AWS Gov Cloud, AWS On-prem, VPCs. It's even important for them, their expansion, their market time upfront. If I'm (indistinct), if I'm built on Supercloud, I can increase my time share. Otherwise I'm bringing only to public cloud. >> Okay, so I'll say, I'm Amazon and we have a concept called "One Way Doors." We don't want to go through a one way door. Is Supercloud a one way door for them? What's in it for them? Do they make more? Does it help their ecosystem? And the same question from Microsoft Azure and Google cloud. >> They're make more money. They're making their apps run in multiple places. It's a natural expansion. You are solving your customer problems for Amazon and DGC, right? My job is give people choices. I give choice to Lisa. Lisa can run it on public cloud. John, you can run it on VPC, AWS. >> So you're saying, so you think customers are asking for this right now? >> Everybody's asking. >> But don't really know how to say it? >> Customers are asking. Partners are asking. All of us are asking. >> Okay, what's the ask? >> Ask is give me a one place to build applications and run it anywhere without adding the complexity. >> Okay. Done. That's Supercloud. It'll ship tomorrow. (Lisa laughs) Well done. (John laughs) All right, well done. Final question for you. Lisa and I have been talking with folks here. What advice would you give the folks that are in here? 'Cause we have a lot of activity, people with marketing their solutions and products. They're trying to put a voice out there around thought leadership and trying to figure out what side of the street they should be on relative to the next 10 years as they're here at VMware Explore, as the next gen cloud comes around. What's the right narrative? What's the right positioning for companies to be on right now to be the most relevant and in the flow? >> I don't know about 10 years, but right now we are in difficult economic times, right? Markets are down. Inflation is up. So I think the fastest cost, people should focus on cost. How can it take cost? Automation is the key, right? Whether you use AI or automation , like you and me talking, John, last week, right? That's important. Every CEO I talk to is focused on cost. How do I cut my cost? How can I do with fewer resources? How can I do with fewer people, right? So the new budget right now is cut your budget in half. So every company, every exec should think about how can you be a good citizen? How can I get growth and scale? How can I do more with less? And that should be the next 12 months. >> That was a lot of the theme of conversations that I had with the VMware ecosystem, doing more with less. So that's definitely on everyone's minds. >> Right, and that's what my company is fully focused on. AISERA is all about AI automation. How can we solve your thing? We want to be solving customer problem. We are like your automation engine for your enterprise, right? We are a platform of platform. That's why I like the Supercloud. I can run AISERA as a platform on top of Supercloud. >> Excellent. >> Wow! If only we had more time! I know that you guys could really dig into Supercloud and take it even further. So you have to come back, Muddu. >> I will. >> He always wants to come back. >> I will be back. >> He's on the team. He's has contributed to the open source effort of Supercloud. Thank you. >> Yes. >> All right, thank you so much for joining John and me and kind of breaking down your vision on VMware Broadcom and the future. Next step, we've got to get some customers on here. I really want to understand what the customer experience is going to be like, but we'll have to another segment on that one. >> We will do that. Thank you, Lisa, for having me. >> My pleasure. >> John. >> Thank you very much. Thank you. >> For our guest and John Furrier, I'm Lisa Martin. You're watching "theCUBE" live on day three of our coverage of VMware Explore. We'll be back after a short break. (upbeat corporate music)

(upbeat music) >> Welcome back everyone to Supercloud22, I'm John Furrier, host of theCUBE here in Palo Alto. For this next ecosystem's segment we have Muddu Sudhakar, who is the co-founder and CEO of Aisera, a friend of theCUBE, Cube alumni, serial entrepreneur, multiple exits, been on multiple times with great commentary. Muddu, thank you for coming on, and supporting our- >> Also thank you for having me, John. >> Yeah, thank you. Great handshake there, I love to do it. One, I wanted you here because, two reasons, one is, congratulations on your new funding. >> Thank you. >> For $90 million, Series D funding. >> Series D funding. >> So, huge validation in this market. >> It is. >> You have been experienced software so, it's a real testament to your team. But also, you're kind of in the Supercloud vortex. This new wave that Supercloud is part of is, I call it the pretext to what's coming with multi-clouds. It is the next level. >> I see. >> Structural change and we have been reporting on it, Dave and I, and we are being challenged. So, we decided to open it up. >> Very good, I would love it. >> And have a conversation rather than waiting eight months to prove that we are right. Which, we are right, but that is a long story. >> You're always right. (both laughs) >> What do you think of Supercloud, that's going on? What is the big trend? Because its public cloud is great, so there is no conflict there. >> Right. >> It's got great business, it's integrated, IaaS, to SaaS, PaaS, all in the beginning, or the middle. All that is called good. Now you have on-premise high rate cloud. >> Right. >> Edge is right around the corner. Exploding in new capabilities. So, complexity is still here. >> That's right, I think, you nailed it. We talk about hybrid cloud, and multi cloud. Supercloud is kind of elevates the message even better. Because you still have to leave for some of our clouds, public clouds. There will be some of our clouds, still running on the Edge. That's where, the Edge cloud comes in. Some will still be on-prem. So, the Supercloud as a concept is beyond hybrid and multi cloud. To me, I will run some of our cloud on Amazon. Some could be on Aisera, some could be running only on Edge, right? >> Mm hm >> And we still have, what we call remote executors. Some leaders of service now. You have, what we call the mid-server, is what I think it was called. Where you put in a small code and run it. >> Yeah. >> So, I think all those things will be running on-prem environment and VMware cloud, et cetera. >> And if you look back at, I think it has been five years now, maybe four or five years since Andy Jassy at reInvent announced Outposts. Think that was the moment in time that Dave and I took this pause back and said "Okay, that's Amazon." who listens to their customers. Acknowledging Hybrid. >> Right. >> Then we saw the rise of Snowflakes, the Databricks, specialty clouds. You start to see people who are building on top of AWS. But at MongoDB, it is a database, now they are a full blown, large scale data platform. These companies took advantage of the public cloud to build, as Jerry Chen calls it, "Castles in the cloud." >> Right. >> That seems to be happening in all areas. What do you think about that? >> Right, so what is driving the cloud? To me, we talk about machine learning in AI, right? Versus clouded options. We used to call it lift and shift. The outposts and lift and shift. Initially this was to get the data into the cloud. I think if you see, the vendor that I like the most, is, I'm not picking any favorite but, Microsoft Azure, they're thinking like your Supercloud, right? Amazon is other things, but Azure is a lot more because they run on-prem. They are also on Azure CloudFront, Amazon CloudFront. So I think, Azure and Amazon are doing a lot more in the area of Supercloud. What is really helping is the machine learning environment, needs Superclouds. Because I will be running some on the Edge, some compute, some will be running on the public cloud, some could be running on my data center. So, I think the Supercloud is really suited for AI and automation really well. >> Yeah, it is a good point about Microsoft, too. And I think Microsoft's existing install base saved Azure. >> Okay. >> They brought Office 365, Sequel Server, cause their customers weren't leaving Microsoft. They had the productivity thing nailed down as well as the ability to catch up >> That's right. >> To AWS. So, natural extension to on-premise with Microsoft. >> I think... >> Tell us- >> Your Supercloud is what Microsoft did. Right? Azure. If you think of, like, they had an Office 365, their SharePoint, their Dynamics, taking all of those properties, running on the Azure. And still giving the migration path into a data center. Is Supercloud. So, the early days Supercloud came from Azure. >> Well, that's a good point, we will certainly debate that. I will also say that Snowflake built on AWS. >> That's right. >> Okay, and became a super powerhouse with the data business. As did Databricks. >> That's right. >> Then went to Azure >> That's right. >> So, you're seeing kind of the Playbook. >> Right. >> Go fast on Cloud Native, the native cloud. Get that fly wheel going, then get going, somewhere else. >> It is, and to that point I think you and me are talking, right? If you are to start at one cloud and go to another cloud, the amount of work as a vendor for us to use for implement. Today, like we use all three clouds, including the Gov Cloud. It's a lot of work. So, what will happen, the next toolkit we use? Even services like Elastic. People will not, the word commoditize, is not the word, but people will create an abstraction layer, even for S3. >> Explain that, explain that in detail. So, elastic? What do you mean by that? >> Yeah, so what that means is today, Elasticsearch, if you do an Elasticsearch on Amazon, if I go to Azure, I don't want enter another Elasticsearch layer. Ideally I want us to write an abstracted search layer. So, that when I move my services into a different cloud I don't want to re-compute and re-calculate everything. That's a lot of work. Particularly once you have a production customer, if I were to shift the workloads, even to the point of infrastructure, take S3, if I read infrastructure to S3 and tomorrow I go to Azure. Azure will have its own objects store. I don't want to re-validate that. So what will happen is digital component, Kubernetes is already there, we want storage, we want network layer, we want VPM services, elastic as well as all fundamental stuff, including MongoDB, should be abstracted to run. On the Superclouds. >> Okay, well that is a little bit of a unicorn fantasy. But let's break that down. >> Sure. >> Do you think that's possible? >> It is. Because I think, if I am on MongoDB, I should be able to give a horizontal layer to MongoDB that is optimized for all three of them. I don't want MongoDB. >> First of all, everyone will buy that. >> Sure. >> I'm skeptical that that's possible. Given where we are at right now. So, you're saying that a vendor will provide an abstraction layer. >> No, I'm saying that either MongoDB, itself will do it, or a third party layer will come as a service which will abstract all this layer so that we will write to an AP layer. >> So what do you guys doing? How do you handle multiple clouds? You guys are taking that burden on, because it makes sense, you should build the abstraction layer. Not rely on a third party vendor right? >> We are doing it because there is no third party available offer it. But if you offer a third party tomorrow, I will use that as a Supercloud service. >> If they're 100% reliable? >> That's right. That's exactly it. >> They have to do the work. >> They have to do the work because if today I am doing it because no one else is offering it- >> Okay so what people might not know is that you are an angel investor as well as an entrepreneur been very successful, so you're rich, you have a lot of money. If I were a startup and I said, Muddu, I want to build this abstraction layer. What would be funding advice that you would give me as an entrepreneur? As a company to do that? >> I would do it like an Apigee that Google acquired, you should create an Apigee-like layer, for infrastructure upfront services, I think that is a very good option. >> And you think that is viable? >> It is very much viable. >> Would that be part of Supercloud architecture, in your opinion? >> It is. Right? And that will abstract all the clouds to some level. Like it is like Kubernetes abstract, so that if I am running on Kubernetes I can transfer to any cloud. >> Yeah >> But that should go from computer into other infrastructures. >> It's seems to me, Muddu, and I want to get your thoughts about this whole Supercloud defacto standard opportunity. It feels like we are waiting for a moment where there is some sort of defacto unification, whether it is in the distraction layer, or a standards body. There is no W3C here going on. I mean, W3C was for web consortium, for world wide web. The Supercloud seems to be having the same impact the web had. Transformative, disruptive, re-factoring business operations. Is there a standardized body or an opportunity for a defacto? Like Kubernetes was a great example of a unification around something for orchestration. Is there a better version in the Supercloud model where we need a standard? >> Yes and no. The reason is because by the time you come to standard, take time to look what happened. First, we started with VMs, then became Docker and Containers then we came to Kubernetes. So it goes through a journey. I think the next few years will be stood on SuperCloud let's make customers happy, let's make enough services going, and then the standards will come. Standards will be almost 2-3 years later. So I don't think standards should happen right now. Right now, all we need is, we need enough start ups to create the super layer abstraction, with the goal in mind of AI automation. The reason, AI is because AI needs to be able to run that. Automated because running a work flow is, I can either run a workflow in the cloud services, I can run it on on-prem, I can run it on database, so you have two good applications, take AI and automation with Supercloud and make enough enough noise on that make enough applications, then the standards will come. >> On this project we have been with SuperCloud these past day we have heard a lot of people talking. The themes that developers are okay, they are doing great. Open source is booming. >> Yes >> Cloud Native's got major traction. Developers are going fast and they love it, shifting left, all these great things. They're putting a lot of data, DevOps and the security teams, they're the ones who are leveling up. We are hearing a lot of conversations around how they can be faster. What is your view on this as relative to that Supercloud nirvana getting there? How are DevOps and security teams leveling up to devs? >> A couple of things. I think that in the world of DevSecOps and security ops. The reason security is important, right? Given what is going on, but you don't need to do security the manual way. I think that whole new operation that you and me talked about, AI ops should happen. Where the AI ops is for service operation, for performance, for incident or for security. Nobody thinks of AI security. So, the DevOps people should think more world of AI ops, so that I can predict, prevent things before they happen. Then the security will be much better. So AI ops with Supercloud will probably be that nirvana. But that is what should happen. >> In the AI side of things, what you guys are doing, what are you learning, on scale, relative to data? Is there, you said machine learning needs data, it needs scale operation. What's your view on the automation piece of all this? >> I think to me, the data is the single, underrated, unsung kind of hero in the whole machine learning. Everyone talks about AI and machine learning algorithms. Algorithms are as important, but even more important is data. Lack of data I can't do algorithms. So my advice to customers is don't lose your data. That is why I see, Frank, my old boss, setting everything up into the data cloud, in Snowflake. Data is so important, store the data, analyze the data. Data is the new AI. You and me talk so many times- >> Yeah >> It's underrated, people are not anticipating how important it is. But the data is coming from logs, events, whether there is knowledge documents, any data in any form. I think keep the data, analyze the data, data patterns, and then things like SuperCloud can really take advantage of that. >> So, in the Supercloud equation one of the things that has come up is that the native clouds do great. Their IaaS to SaaS is interactions that solve a lot of problems. There is integration that is good. >> Right. >> Now when you go off cloud, you get regions, get latency issues- >> Right >> You have more complexity. So what's the trade off in the Supercloud journey, if you had to guess? And just thinking out loud here, what would be some of the architectural trade offs of how you do it, what's the sequence? What's the order of operations to get Superclouding going? >> Yeah, very good questions here. I think once you start going from the public cloud, the clouds there scale to lets say, even a regional data center onto an Edge, latency will kick in. The lack of computer function will kick in. So there I think everything should become asynchronous, right? You will run the application in a limited environment. You should anticipate for small memories, small compute, long latencies, but still following should happen. So some operations should become the old-school following, like, it's like the email. I send an email, it's an asynchronous thing, I made a sponsor, I think most of message passing should go back to the old-school architectures They should become asynchronous where thing can rely. I think, as long as algorithms can take that into Edge, I think that Superclouds can really bridge between the public cloud to the edge. >> Muddu, thanks for coming, we really appreciate your insights here. You've always been a great friend, great commentator. If you weren't the CEO and a famous angel investor, we would certainly love to have you as a theCUBE analyst, here on theCUBE. >> I am always available for you. (John laughs) >> When you retire, you can come back. Final point, we've got time left. We'll give you a chance to talk about the company. I'm really intrigued by the success of your ninety million dollar financing realm because we are in a climate where people aren't getting those kinds of investments. It's usually down-rounds. >> Okay >> 409 adjustments, people are struggling. You got an up-round and you got a big number. Why the success? What is going on with the company? Why are you guys getting such great validation? Goldman Sachs, Thoma Bravo, Zoom, these are big names, these are the next gen winners. >> It is. >> Why are they picking you? Why are they investing in you? >> I think it is not one thing, it is many things. First all, I think it is a four-year journey for us where we are right now. So, the company started late 2017. It is getting the right customers, partners, employees, team members. So it is a lot hard work went in. So a lot of thanks to the Aisera community for where we are. Why customers and where we are? Look, fundamentally there is a problem to solve. Like, what Aisera is trying to solve is can we automate customer service? Whether internal employees, external customer support. Do it for IT, HR, sales, marketing, all the way to ops. Like you talk about DevSecOps, I don't want thousands of tune ups for ops. If I can make that job better, >> Yeah >> I want to, any job I want to automate. I call it, elevate the human, right? >> Yeah. >> And that's the reason- >> 'Cause you're saying people have to learn specialty tools, and there are consequences to that. >> Right, and to me, people should focus on more important tasks and use AI as a tool to automate those things right? It's like thinking of offering Apple City as Alexa as a service, that is how we are trying to offer customer service, like, right? And if it can do that consistently, and reduce costs, cost is a big reason why customers like us a lot, we have eliminated the cost in this down economy, I will amplify our message even more, right? I am going to take a bite out of their expense. Whether it is tool expense, it's on resources. Second, is user productivity And finally, experience. People want experience. >> Final question, folks out there, first of all, what do you think about Supercloud? And if someone asks you what is this Supercloud thing? How would you answer? >> Supercloud, is, to me, beyond multi cloud and hybrid cloud. It is to bridge applications that are build in Supercloud can run on all clouds seamlessly. You don't need to compile them, re-clear them. Supercloud is one place to build, develop, and deploy. >> Great, Muddu. Thank you for coming on. Supercloud22 here breaking it down with the ecosystem commentary, we have a lot of people coming to the small group of experts in our network, bringing you in open conversation around the future of cloud computing and applications globally. And again, it is all about the next generation cloud. This is theCUBE, thanks for watching. (upbeat music)

(upbeat music) >> Full stack observability is all the rage today. As businesses lean into digital, customer experience becomes ever more important. Why? Well, it's obvious, fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades old software companies that have traditionally done monitoring or log analytics and or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose-built tools that attack one particular segment of the marketplace. And now they're pivoting through M&A and some organic development trying to fill gaps in their portfolio. And then, you got all these new entrants coming to the market, claiming end to end visibility across the so-called modern cloud and now edge native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem. But, you know, recent survey research from ETR confirms our thesis that no one company has it all. Here's the thing. Customers just want to figure out the root cause as quickly and as efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante and welcome to this special Cube presentation where we dig into root cause analysis, and specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. And in this session, we have two deep dives. First, we're going to dig into this exciting new field of RCaaS, Root Cause As A Service with two of the founders and technical experts behind Zebrium. And then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well known Cisco product lines, including WebEx Client and UCS. I was pretty amazed at the results and I think you'll be impressed as well. So thanks for being here. Let's get started. With me right now is Larry Lancaster, who's a founder and CTO of Zebrium. And he's joined by Rod Bagg, who's the founder and vice president of engineering at the company. Gents, welcome. Thanks for coming on. >> Thanks. >> Okay. >> It's good to be here. >> It's good to be here >> All right Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO. What do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive uptime and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web and that's how you get a point click. Or the business depends on, you know, internal systems to drive their business and to run it. When that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic and maybe it took a couple of people to maintain it and keep it running. There wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it But there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong but you got to know why. And it's our contention here that, you know, really, when you take a look at the observability space, you have metrics, that's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know where it's happening or where something is running slow, potentially. So that's great. But again, the root cause of why it's happening is going to be buried in log files. And I can expand on that a little bit more but you know, when you're a software developer and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing, or why it went wrong. And it's that that really gets you to the root cause very fast. And that's our contention, is that these software systems are so complex nowadays and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you are just doomed for failure. And that's where we come in. >> Great. >> Getting to that root cause. >> Thank you, Rod. You know, it's interesting you talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose probably closer to a trillion dollars a year in breaches. And there's a similar analogy here. 20 billion could be 5X in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCaaS. What does it mean? What problems does it solve, and how does it solve the problem? Let's get into it. >> Yeah. Hey, thanks, Dave. So I think when you said, you know, who's automating the observer, that that's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience. That's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time. And until Zebrium came along, I would argue, no one's really done it right. So, you know, I think it's also important you know, as we step back, we can probably look forward five to 10 years and say, everyone's going to look back and say how did we do all this manually? You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just... They're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard and we don't care what kind of a dashboard it is. It could be, you know Datadog, New Relic, Elastic, Dynatrace, Grafana AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff. Yep. >> Yeah. So, interesting. Again, another analogy I think about. You know, you talked about automation. If we're to look back and say this is what... We're never going to do this again, it's like provisioning loans. Nobody provisions loans anymore, it's all automated. >> Larry: (chuckling) That's right. >> So Larry, I'll stay with you, then the skeptic in me says, this sounds amazing, but if I, you know... It might be too good to be true. Tell us how it works. >> Larry: (chuckling) Yeah. So that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months and they did a very detailed study. And they got together 192 incidents across four product lines, where they knew that the root cause was in the logs. And they knew what that root cause was because they had had their best engineers, you know work on those cases and take detailed notes of the incidents that had taken place. And so they ran that data through the Zebrium software. And what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo command center, you know when they finally, you know, touchdown on the moon kind of thing. So, you know, it's really an exciting point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business, they're an S3 competitor. Zoom has their files stored on Lyve Cloud, you know, to let you know who they are. So essentially, what happened was they were in alpha, their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored. And it was, you know, fortunately for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on. But they were scared, because they realized, if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium. They went and did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they had had. And what they saw was immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Dave: Yeah. That's great. I mean, you guys are jumping up and down, I'm sure. We're going to hear from Cisco later. I bet you, they were jumping up and down too because they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that, or actually, you guys both talked about that your tool is agnostic. So how does one actually use the service? How do I deploy it? >> Yeah. So let me step back. So when we talk about logs right? Like, you know, all these bread crumbs being in logs and everything else? So, you know, they are a great wealth of you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our... Or we've heard from several of our customers now prior to using Zebrium, when they, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metric has, you know, taken a blip or something's happened that they know there's a problem. We've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are, to get to them, maybe searching in a log manager. Just to get into the right context, even, can take hours. So, you know, that's obviously the problem we solve but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put them back in the thing they don't like doing because people don't do that. They don't like doing it. So we put it up on the dashboard. So if something is going wrong with your metrics and that's the indicator, or maybe it's something with tracing that you're sort of digging through that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs, you click on one of our integrations and we integrate with all these tools that Larry's talked about. And when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. No other work could be... You can, you know, also click down and click through to us so that you land up in our portal, if you want to do some more digging around, if you need to or whatever, maybe to get some context what have you, but it's fair that if you ever need to do that, the answer should be right there on your dashboard. And that that's how we expect people to use it. We don't want them digging in logs and going through things, we want it to be right in their workflow. >> Great. Thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment in Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AI ops. Do you have some examples of those types of firms leaning into this? >> Rod: Yeah, a couple of great ones. Well, I mean, we've got many of them, but a couple that I'll touch on. We have an actual AI ops company that was looking for, you know, sort of some complimentary technology and so on. And so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment, and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know signed up and then, you know, started sending us logs. And, you know, he was hewing and hawing, saying that he was busy, like every SRE is, and that he didn't have a chance to really do much with us yet. And, you know, we were just, you know, having this conversation on the phone, and he comes to tell us that, yeah I've been busy because we had this, you know, terrible outage, like, you know, five days ago. And we said like, "Okay did you actually look on the Zebrium dashboard?" (chuckles) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company, he hadn't put that integration in, so it wasn't in his dashboard yet, but it was certainly on ours. So he went there, and he looks and he looks on the day, you know, on the time range of when he had had this incident. And right at the very top of the page on our portal was that incident with that root cause. And he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours. And we had the answer right there in five minutes, and it was crazy. And we get that kind of stories. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it. And you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Alchera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google, Google cloud, and so on. But they use our software, and they have a lot of interaction, obviously with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out your costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking. And we had that root cause report right on the screen, again within five minutes, that was pointing to an API problem with Google. And they had changed one of their APIs and Alchera was not aware of it. So their stuff was breaking because of a change downstream that we had caught. And I'll just tell you one last one because it's somewhat related to one of these cloud vendors. You know, it was a big cloud vendor who had an outage a couple of months ago. And it's interesting because, you know, a lot of our customers will set up shared Slack channels with us, where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage, and the root cause of what was going on there in AWS that was impacting our customers that was showing up in our incidents. Now we didn't obviously, you know, have the very root cause of what was going on in AWS, per se but we were getting to the root cause of why our customer's applications were failing. And that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenges is going to be getting people's attention because these SREs are so busy, their hair's on fire. >> Rod: That's it. Right. (chuckling). You know, when you say, hey, (indistinct). >> I tell you, if you get their attention, they love it. I mean, this AI ops company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found. And quite literally, the next week, they ended up signing up as a paid customer. So... >> Dave: that's great. And Larry, to give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs and you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs that people are trying not to leave. >> Larry: That's right. Absolutely. >> Dave: But close it out here. >> Yeah. I mean, that's right, you can run it on-prem. Just like we run it in our cloud, you can run it in your cloud or on your own infrastructure. Now that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it, do a POC, try it yourself. And you know, people have become so jaded by the lack of, you know, real, sort of, innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot, I'm telling you. I'm telling you right now, it works. And you'll hear more about that from one of our customers in a minute. >> All right guys, thanks so much. Great story. Really appreciate you sharing. >> Thank you. >> Yeah. Thanks Dave. Appreciate the time. >> Okay. In a moment, we're going to hear from Cisco who is the customer in this case example and a company that has... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of, like WebEx. So stay tuned and learn about how you can really take advantage of this new technology called Root Cause As A Service. You're watching theCube, the leader in enterprise and emerging tech coverage. (upbeat music)

(bright intro music) >> Full stack observability is all the rage today. As businesses lean in to digital, customer experience becomes ever more important, why? Well, it's obvious. Fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action, and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades-old software companies that have traditionally done monitoring or log analytics and/or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose built tools that attack one particular segment of the marketplace, and now, they're pivoting through M&A and some organic development trying to fill gaps in their portfolio, and then you got all these new entrants coming to the market claiming end to end visibility across the so-called modern cloud and now edge-native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem, but, you know, recent survey research from ETR confirms our thesis that no one company has at all. Here's the thing. Customers just want to figure out the root cause as quickly and efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante, and welcome to this special "CUBE" presentation where we dig into root cause analysis and, specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. In this session, we have two deep dives. First, we're going to dig into this exciting new field of RCA, root cause as a service, with two of the founders and technical experts behind Zebrium, and then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well-known Cisco product lines including Webex client and UCS. I was pretty amazed at the results, and I think you'll be impressed as well. So thanks for being here. Let's get started with me right now is Larry Lancaster who's a founder and CTO of Zebrium, and he's joined by Rod Bagg who's a founder and Vice-President of Engineering at the company. Gents, welcome, thanks for coming on. >> Thanks. >> (indistinct). >> To be here. >> Great to be here. >> All right, Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO, what do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive up time and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web, and that that's how you get a point click or their business depends on it and, you know, internal systems to drive their business and to run it. Now, when that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic, and maybe it took a couple of people to maintain it and keep it running. It wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it, but there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong, but you got to know why, and it it's our contention here that, you know, really, when you take a look at the observability space, you have metrics. That's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know, where it's happening or where something is running slow potentially. So that's great, but again, the root cause of why it's happening is going to be buried in log files, and I can expand on that a little bit more, but, you know, when you're a software developer, and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing or why it went wrong, and it's that that really gets you to the root cause very fast, and that's, our contention is that these software systems are so complex nowadays, and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you're just doomed for failure, and that's where we come in. >> Great. >> Getting to that request. >> Thank you, Rod. You know, it's interesting. You talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose, probably, closer to a trillion dollars a year in breaches, and there's a similar analogy here. 20 billion could be 5x in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCAs. What does it mean? What problems does it solve? And how does it solve the problem? Let's get into it. >> Yeah, hey, thanks, Dave. So I think when you said, you know, who's automating the observer? That's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state, and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience, that's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time, and until Zebrium came along, I would argue no one's really done it right. So, you know, I think it's also important, you know, as we step back, we can probably look forward five to 10 years and say, "Everyone's going to look back and say, 'How did we do all this manually?'" You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just, they're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology, but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard, and we don't care what kind of a dashboard it is. It could be, you know, Datadog, New Relic, Elastic, Dynatrace, Grafana, AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff, yeah. >> Yeah, so interesting. Again, another analogy I think about, you know, you talked about automation, where to look back, and say, "This is what- We're never going to do this again." It's like provisioning LANs. Nobody provisioned LANs anymore. It's all automated. >> That's correct. >> So, Larry, stay with you. The skeptic in me says, "This sounds amazing," but if, you know, it probably too good to be true. Tell us how it works. >> Yeah, so that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months, and they did a very detailed study, and they got together 192 incidents across four product lines where they knew that the root cause was in the logs, and they knew what that root cause was because they'd had their best engineers, you know, work on those cases and take detailed notes of the incidents that had taken place, and so they ran that data through the Zebrium software, and what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo Command Center, you know, when they finally, (Dave laughs) you know, touchdown on the moon kind of thing. So, you know, it's really exciting at a point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story, which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business. They're an S3 competitor. Zoom has their files stored on Lyve Cloud to give, you know, to let you know who they are. So, essentially, what happened was they were in alpha, in their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored, and it was, you know, fortunately, for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on, but they were scared because they realized if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium, they did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they'd had, and what they saw was, immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Yeah, that's great. I mean, you guys are jumping up and down. I'm sure, we're going to hear from Cisco later. I bet you, they were jumping up and down, too, 'cause they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that or, actually, you guys both talked about that your tool's agnostic. So how does one actually use the service? How do I deploy it? >> Yeah, so let me step back. So when we talk about logs, right? Like, you know, all these red crumbs being in logs and everything else. So, you know, they are a great wealth of, you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our, or we've heard from several of our customers now prior to using Zebrium, but when they're, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metrics is, you know, taken a blip or something's happened that they know there's a problem, we've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are to get to them, maybe searching in a log manager, just to get into the right context even can take hours. So, you know, that's obviously the problem we solve, but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put 'em back in the thing they don't like doing 'cause people don't do what they don't like doing. So we put it up on the dashboard. So if something is going wrong with your metrics, and that's the indicator or maybe it's something with tracing that you're sort of digging through now that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs. You click on one of our integrations, and we integrate with all these tools that Larry's talked about, and when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong, and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. Not no other work could be- You can, you know, also click down and click through to us so that you land up in our portal if you want to do some more digging around if you need to or whatever, maybe to get some context, what have you, but it's fair that you ever need to do that. The answer should be right there on your dashboard, and that's how we expect people to use it. We don't want them digging in logs and going through things. We want it to be right in their workflow. >> Great, thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment and Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AIOps, do you have some examples of those types of firms leaning into this? >> Yeah, a couple of great, well, I mean, we got many of them, but couple that I'll touch on. We have an actual AIOps company that was looking for, you know, sort of some complimentary technology and so on, and so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know, signed up, and then, you know, started sending us logs, and, you know, he was hemming and hawing saying that he was busy like, you know, like every SRE is, and that he didn't have a chance to really do much with us yet, and, you know, we just, you know, having this conversation on the phone, and he comes to tell us that, "Yeah, I've been busy because we had this, you know, terrible outage like, you know, five days ago," and we said like, "Okay, did you actually look on the Zebrium dashboard?" (laughs) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company. He hadn't put that integration in so it wasn't in his dashboard yet, but it was certainly on ours. So he went there and he looks on the day like, you know, on the time range of when he had this incident, and right at the very top of the page on our portal was the incident with the root cause, and he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours, and we had the answer right there in five minutes, and it was crazy, and we get that kind of story. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it, and you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Archera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google cloud, and so on, but they use our software, and they have a lot of interaction, obviously, with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out you're costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking and we had that root cause report right on the screen, again, within five minutes that was pointing to an API problem with Google, and they had changed one of their APIs, and Archera was not aware of it. So their stuff was breaking because of a change downstream that we had caught, and I'll just tell you one last one because it's somewhat related to one of these cloud vendors of, you know, big cloud vendor who had an outage couple of months ago, and it's interesting because, you know, lot of our customers will set up shared Slack channels with us where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we've detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage and the root cause of what was going on there in AWS that was impacting our customers, that was showing up in our incidents. Now, we didn't obviously, you know, have the very root cause of what was going on in AWS per se, but we were getting to the root cause of why our customer's applications were failing, and that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenge is going to be getting people's attention because these SREs is so busy, their hair's on fire. (all laughs) You know, he's like, "Hey, chap, I'm going to show you, look at this." >> I tell you. You get their attention, they love it. I mean, this AIOps company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found and, quite literally, the next week, they ended up signing up as a paid customer, so. >> That's great, and Larry, give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs, and, you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs and people don't want to leave. >> That's right, absolutely. >> But, yeah, close it out here. >> Yeah, I mean, you can, that's right, you can run it on-prem, just like we run it in our cloud. You can run it in your cloud or on your own infrastructure. Now, that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it? Do a POC, try it yourself. And, you know, people have become so jaded by the lack of, you know, real sort of innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot. I'm telling you. I'm telling you right now, it works, and you'll hear more about that from one of our customers in a minute. >> Alright guys, thanks so much. Great story, really appreciate you sharing. >> Thank you. >> Yeah, thanks, Dave. Appreciate the time. >> Okay, in a moment, we're going to hear from Cisco who is the customer in this case example, and a company that is... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of like Webex. So stay tuned and learn about how you can really take advantage of this new technology called root cause as a service. You're watching "theCUBE", the leader in enterprise and emerging tech coverage. (bright outro music)

>> theCUBE presents KubeCon and CloudNativeCon, Europe, 2022. Brought to you by Red Hat, the cloud-native computing foundation and its ecosystem partners. >> Welcome to Valencia, Spain in KubeCon, CloudNativeCon, Europe, 2022. I'm Keith Townsend with my cohosts, Enrico Signoretti, Senior IT Analyst at GigaOm. >> Exactly. >> 7,500 people I'm told, Enrico. What's the flavor of the show so far? >> It's a fantastic mood, I mean, I found a lot of people wanting to track, talk about what they're doing with Kubernetes, sharing their you know, stories, some war stories that bit tough. And you know, this is where you learn actually. Because we had a lot of Zoom calls, webinar and stuff. But it is when you talk a video, "Oh, I did it this way, and it didn't work out very well." So, and, you start a conversation like this that is really different from learning from Zoom, when, you know, everybody talks about things that work it well, they did it right. No, it's here that you learn from other experiences. >> So we're talking to amazing people the whole week, talking about those experiences here on theCUBE. Fresh on the theCUBE for the first time, Chris Voss, senior software engineer at Microsoft Xbox. Chris, welcome to the theCUBE. >> Thank you so much for having me. >> So first off, give us a high level picture of the environment that you're running at Microsoft. >> Yeah. So, you know, we've got 20 well probably close to 30 clusters at this point around the globe, you know 700 to 1,000 pods per cluster, roughly. So about 22,000 pods total. So yeah, it's pretty, pretty sizable footprint and yeah. So we've been running on Kubernetes since 2018 and well actually might be 2017, but anyways, so yeah, that's kind of our footprint. Yeah. >> So all of that, let's talk about the basics which is security across multiple I'm assuming containers, microservices, etcetera. Why did you and the team settle on Linkerd? >> Yeah, so previously we had our own kind of solution for managing TLS certs and things like that. And we found it to be pretty painful, pretty quickly. And so we knew, you know we wanted something that was a little bit more abstracted away from the developers and things like that, that allowed us to move quickly. And so we began investigating, you know, solutions to that. And a few of our colleagues went to Kubecon in San Diego in 2019, Cloudnativecon as well. And basically they just, you know, sponged it all up. And actually funny enough, my old manager was one of the people who was there and he went to the Linkerd booth and they had a thing going that was like, "Hey, get set up with MTLS in five minutes." And he was like, "This is something we want to do, why not check this out?" And he was able to do it. And so that put it on our radar. And so yeah, we investigated several others and Linkerd just perfectly fit exactly what we needed. >> So, in general we are talking about, you know, security at scale. So how you manage security scale and also flexibility. Right? So, but you know, what is the... You told us about the five minutes to start using there but you know, again, we are talking about war stories. We're talking about, you know, all these. So what kind of challenges you found at the beginning when you started adopting this technology? >> So the biggest ones were around getting up and running with like a new service, especially in the beginning, right, we were, you know, adding a new service almost every day. It felt like. And so, you know, basically it took someone going through a whole bunch of different repos, getting approvals from everyone to get the certs minted, all that fun stuff getting them put into the right environments and in the right clusters, to make sure that, you know, everybody is talking appropriately. And just the amount of work that that took alone was just a huge headache and a huge barrier to entry for us to, quickly move up the number of services we have. >> So, I'm trying to wrap my head around the scale of the challenge. When I think about certification or certificate management, I have to do it on a small scale. And every now and again, when a certificate expires it is just a troubleshooting pain. >> Yes. >> So as I think about that, it costs it's not just certificates across 22,000 pods, or it's certificates across 22,000 pods in multiple applications. How were you doing that before Linkerd? Like, what was the... And what were the pain points? Like what happens when a certificate either fails? Or expired up? Not updated? >> So, I mean, to be completely honest, the biggest thing is we're just unable to make the calls, you know, out or in, based on yeah, what is failing basically. But, you know, we saw essentially an uptick in failures around a certain service and pretty quickly, pretty quickly, we got used to the fact that it was like, oh, it's probably a cert expiration issue. And so we tried, you know, a few things in order to make that a little bit more automated and things like that. But we never came to a solution that like didn't require every engineer on the team to know essentially quite a bit about this, just to get into it, which was a huge issue. >> So talk about day two, after you've deployed Linkerd, how did this alleviate software engineers? And what was like the benefits of now having this automated way of managing certs? >> So the biggest thing is like, there is no touch from developers, everyone on our team... Well, I mean, there are a lot of people who are familiar with security and certs and all of that stuff. But no one has to know it. Like it's not a requirement. Like for instance, I knew nothing about it when I joined the team. And even when I was setting up our newer clusters, I knew very little about it. And I was still able to really quickly set up Linkerd, which was really nice. And it's been, you know, essentially we've been able to just kind of set it, and not think about it too much. Obviously, you know, there're parts of it that you have to think about, we monitor it and all that fun stuff, but yeah, it's been pretty painless almost day one. It took a long time to trust it for developers. You know, anytime there was a failure, it's like, "Oh, could this be Linkerd?" you know. But after a while, like now we don't have that immediate assumption because people have built up that trust, but. >> Also you have this massive infrastructure I mean, 30 clusters. So, I guess, that it's quite different to manage a single cluster in 30. So what are the, you know, consideration that you have to do to install this software on, you know, 30 different cluster, manage different, you know versions probably, et cetera, et cetera, et cetera. >> So, I mean, you know, as far as like... I guess, just to clarify, are you asking specifically with Linkerd? Or are you just asking in more in general? >> Well, I mean, you can take that the question in two ways. >> Okay. >> Sure, yeah, so Linkerd in particular but the 30 cluster also quite interesting. >> Yeah. So, I mean, you know, more generally, you know how we manage our clusters and things like that. We have, you know, a CLI tool that we use in order to like change context very quickly, and switch and communicate with whatever cluster we're trying to connect to and you know, are we debugging or getting logs, whatever. And then, you know, with Linkerd it's nice because again, you know, we aren't having to worry about like, oh, how is this cert being inserted in the right node? Or not the right node, but in the right cluster or things like that. Whereas with Linkerd, we don't really have that concern. When we spin up our clusters, essentially we get the route certificate and everything like that packaged up, passed along to Linkerd on installation. And then essentially, there's not much we have to do after that. >> So talk to me about your upcoming section here at Kubecon. what's the high level talking points? Like what attendees learn? >> Yeah. So it's a journey. Those are the sorts of talks that I find useful. Having not been, you know, I'm not a deep Kubernetes expert from, you know decades or whatever of experience, but-- >> I think nobody is. >> (indistinct). >> True, yes. >> That's also true. >> That's another story >> That's a job posting decades of requirements for-- >> Of course, yeah. But so, you know, it's a journey. It's really just like, hey, what made us decide on a service mesh in the first place? What made us choose Linkerd? And then what are the ways in which, you know, we use Linkerd? So what are those, you know we use some of the extra plugins and things like that. And then finally, a little bit about more what we're going to do in the future. >> Let's talk about not just necessarily the future as in two or three days from now, or two or three years from now. Well, the future after you immediately solve the low level problems with Linkerd, what were some of the surprises? Because Linkerd in service mesh and in general have side benefits. Do you experience any of those side benefits as well? >> Yeah, it's funny, you know, writing the blog post, you know, I hadn't really looked at a lot of the data in years on, you know when we did our investigations and things like that. And we had seen that we like had very low latency and low CPU utilization and things like that. And looking at some of that, I found that we were actually saving time off of requests. And I couldn't really think of why that was and I was talking with someone else and the biggest, unfortunately all that data's gone now, like the source data. So I can't go back and verify this but it makes sense, you know, there's the availability zone routing that Linkerd supports. And so I think that's actually doing it where, you know essentially, if a node is closer to another node, it's essentially, you know, routing to those ones. So when one service is talking to another service and maybe they're on the same node, you know, it short circuits that and allows us to gain some time there. It's not huge, but it adds up after, you know, 10, 20 calls down the line. >> Right. In general, so you are saying that it's smooth operations at this very, you know, simplifying your life. >> And again, we didn't have to really do anything for that. It handled that for us. >> It was there? >> Yep. Yeah, exactly. >> So we know one thing when I do it on my laptop it works fine. When I do it with across 22,000 pods, that's a different experience. What were some of the lessons learned coming out of Kubecon 2018 in San Diego? I was there. I wish I would've ran into the Microsoft folks, but what were some of the hard lessons learned scaling Linkerd across the 22,000 nodes? >> So, you know, the first one and this seems pretty obvious, but was just not something I knew about was the high availability mode of Linkerd. So obviously makes sense. You would want that in, you know a large scale environment. So like, that's one of the big lessons that like, we didn't ride away. No. Like one of the mistakes we made in one of our pre-production clusters was not turning that on. And we were kind of surprised. We were like, whoa, like all of these pods are spinning up but they're having issues, like actually getting injected and things like that. And we found, oh, okay. Yeah, you need to actually give it some more resources. But it's still very lightweight considering, you know, they have high availability mode but it's just a few instances still. >> So from, even from, you know, binary perspective and running Linkerd how much overhead is it? >> That is a great question. So I don't remember off the top of my head, the numbers but it's very lightweight. We evaluated a few different service missions and it was the lightest weight that we encountered at that point. >> And then from a resource perspective, is it a team of Linkerd people? Is it a couple of people? Like how? >> To be completely honest for a long time, it was one person Abraham, who actually is the person who proposed this talk. He couldn't make it to Valencia, but he essentially did probably 95% of the work to get into production. And then this was before, we even had a team dedicated to our infrastructure. And so we have, now we have a team dedicated, we're all kind of Linkerd folks, if not Linkerd experts, we at least can troubleshoot basically. And things like that. So it's, I think a group of six people on our team and then, you know various people who've had experience with it on other teams. >> But others, dedicated just to that. >> No one is dedicated just to it. No, it's pretty like pretty light touch once it's up and running. It took a very long time for us to really understand it and to, you know, get like not getting started, but like getting to where we really felt comfortable letting it go in production. But once it was there, like, it is very, very light touch. >> Well, I really appreciate you stopping by Chris. It's been an amazing conversation to hear how Microsoft is using a open source project. >> Exactly. >> At scale, it's just a few years ago when you would've heard the concept of Microsoft and open source together and like OS, just, you know-- >> They have changed a lot in the last few years. Now, there are huge contributors. And, you know, if you go to Azure, it's full of open source stuff, everywhere so. >> Yeah. >> Wow. The Kubecon 2022, how the world has changed in so many ways. From Valencia Spain, I'm Keith Townsend, along with Enrico Signoretti. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(bright music) >> Hey, welcome to this "CUBE Conversation." I'm your host, Lisa Martin. I've got two guests from NETSCOUT here with me today. Eileen Haggerty joins us, the AVP of Product and Solutions Marketing and Jason Chaffee, Senior Product Manager. We're going to be talking about the importance of quality end user experience with UC&C, Unified Communications and Collaborations services for something that will be near and dear to all of our hearts, employee productivity. Eileen, let's go ahead and start with you and the impact of COVID on UC&C, what has it been? >> Oh, Lisa, great question, because we really have seen an evolution in the importance and reliance on UCC. COVID would not have allowed us to go to work, do business continuity, any of those things had it not been for strong communications platforms to help us do that. And in fact, really the hero of all of this has been what's called Unified Communications as a Service or UCaaS. Enterprise businesses really depended entirely on the communications between the home office and the employees remotely. This is also known to be the way we all went to work. It was no longer a car. We picked up the phone basically or the computer. So Zoom, WebEx, Teams, Google Meets, they've all become household names really over the last two years. That's kind of exciting for them. And businesses during that period of time expanded their tools to keep business running and employees in communication using these very platforms, and we'll refer to this a couple of times during this conversation too, Lisa. We did a survey at the end of 2021, IT leaders, about their use of UCaaS and UCC during this period of time. We found that almost of them had used collaboration tools, and in fact, added to their arsenal of tools during this period of time to such an extent that they're now ranging, the majority of them, between three and nine different platforms that their corporate employees use. This became unwieldy, of course, during that time, and so their strategy going forward is going to be to reduce some of that number, but pretty interesting details. >> Yeah, between three and nine is a lot, and certainly, UC&C became a lifeline for all of us, professionally and personally. Even my mom learned how to use Zoom during this time. I was pretty proud of helping her with that. But, Jason, talk to us about all these new communication services. We're completely dependent on them, but overall what have you found out in terms of how they worked out? >> Well, to be honest with you, I think from the IT organization, it's been a challenge. It's been difficult. I think every IT organization is really motivated to ensure the quality of the services throughout the whole company, but as you can imagine, the increase of these communications Eileen just talked about during the pandemic is just significantly increasing the number of IT help desk tickets that have come through. And in that survey that Eileen just talked about, in fact, a third of those that responded said that 50 to 75% of their help desk tickets right now are related to UC&C or UCaaS services, and in fact, they say that over half of them have said that they get those tickets at least once a day, if not multiple times a day. And I think another big aspect of this that's been a challenge is everybody working from home now and the whole hybrid environment, and IT teams are really trying to understand and make sure that they get the same delivery of services if they were in the corporate headquarters, and I think they felt a loss of control and visibility in the services that are being delivered. I think the other thing that came out of this survey was about 25% of those said that they could get these issues if and when they happen, resolved in just a matter of minutes, but most said that it can take hours or even days to get through those, and that's obviously a really bad look for the company and really hinders productivity. So overall, I'd say it's been a challenge. I think as this onslaught of services that have come through and hampered and that everyone's trying to manage and get through, along with the lack of visibility when everybody's working from home. Of course, it's been fantastic for those of us that are working from home and made everything easier, but I think it's just made it that much more difficult for the IT teams that are trying to manage this new environment. >> Right, definitely difficulty behind the scenes there. You talked about the 25% of IT organizations being able to resolve quickly, but that leaves 75% of organizations where it takes more than a few minutes, and I can imagine individually, that might not be a big impact, but, Eileen, overall if it's taking more than a few minutes to resolve UC&C IT help desk issues, what's the overall impact to a business? >> It can be significant, and we hear a lot of little stories sadly sometimes on Lester Holt's evening news, but really what you are looking at here are longer periods of time where employees can't talk to each other. We've got email. We can probably compensate a different manner, but when it happens to be your customers not being able to talk to customer service reps in the contact center, couple of hours, that can be a big issue. Partners and suppliers who might be trying to get you important information very quickly. Maybe it's a supply chain issue item that they want to alert you to that you need to act on. That's a long period of time. And I think it's kind of important here to call out one special group, and that would be corporate executives. I think we've all heard about these big town hall meetings that corporate executives may be holding with employees or investors and all of a sudden their UCaaS support freezes, or it doesn't connect the voice in the video, and all of a sudden, you've got a very embarrassing situation. It really gets the attention of the public. Losing communication for a couple of hours, bottom line, it is going to impact productivity, customer service, and it could impact reputation, especially with those social media influencers that we all both favor and fear. So, when we were talking about our survey results, that is actually a top concern of IT executives, that productivity will get hit if communications problems do exist. So I think really ultimately for all of us in the business, disruptions and communication, it's going to be bad for business, any length. >> It is bad for business at any length, and that's a huge risk for businesses in any industry. I've been on those executive town halls where video wouldn't connect, and you just think, as much as we wanted that human connection during this time, and you couldn't get it, it made the the interaction not as ideal and obviously a risk for the organization. So, Jason, how can IT then jump in and resolve these disruptions faster, because time is of the essence here? >> Well, yeah, exactly. As we've discussed and Eileen just talked about, I think resolving issues quickly is really the key. I think we all know issues are going to happen, they just will, but it's really the IT team that can solve those the fastest is the team that's going to win, and so I think that's really the key to all of that. And one of the things that comes out of that is, again, from this survey is that only about 54% of the respondents said that they felt confident that they could understand root cause and be able to get to those issues quickly, which leaves about 43%, almost as many, that said they were less than confident or somewhat confident in finding that root cause, and so I think that's really the key there is really having the confidence to be able to find that, and to get that confidence, you need to be able to understand root cause quickly. And in order to get that, I think you need a combination of two things, which is passive, packet-based monitoring as well as continuous active testing or monitoring of those solutions. So, what I mean by that is being able to automatically and continuously test these services, even if nobody's on the system and nobody's on trying to make a phone call. So you have somebody who's trying to host, an active agent that's trying to host a meeting and others that are trying to join the meeting and sending an audio and sending and receiving video and looking at the measurements and trying to take all of that data in to really proactively understand what's going on and doing this every 15 minutes or every once an hour to really, again, get ahead of things before they become a problem. But I think beyond that, it's really about being able to take that data and the packets from those transactions that you were just testing and be able to trend that data and define problems and diagnose issues proactively. Again, as Eileen just said, before the CEO gets on there and tries to make his town hall call, so that that's really important to be able to solve those things more quickly. I think it's really a combination of a passive, scalable monitoring solution along with scheduled automatic testing of those, and along with the packets that go with that, that's really a combination of both. It's kind of a best of both worlds in order to get those things solved quickly. >> To get them solved quickly, I want to go back to something that Eileen said. You mentioned the word 'confidence,' and that I think it's important to point out that you're not saying that trivially, that IT needs to have the confidence that it has the right solutions in place to discover these faster. Eileen, from your perspective, talk to me about what that confidence means to IT and how it can shift up the stack to the C-suite. >> You know, honestly, processes and policies in these organizations are critical. They need to be able to notice when the trouble ticket comes in, and there's a lot of 'em, let's face it, and they're coming from all kinds of locations. Now, it's some of the remote offices. Some of 'em are still people at home. You've got to be able to know where to turn, what screen to use, what tool to adjust, what workflow to process, and that does come with practice, but it also comes with a solid set of tools and visibility strategies, and then you follow that process through, you work together. Maybe the voice, people in the network, people have to work together, maybe the cloud people, 'cause it's a contract with UCaaS, work together, gather the evidence and pinpoint the solution that's going to fix the problem with those locations. And it is, it becomes then a confidence builder, proof points. >> Right, proof points are critical. So, the solution that you both talked about, Jason, you elaborated on this, I'd love to get some real world examples. Tell me how you've seen this in practice. Jason, we'll start with you and then, Eileen, we'll go to you. >> Okay, yeah, great, I was just thinking of one that we had that really was one of the largest insurance companies in the country, if not the world, and when the pandemic hit, they suddenly had to send everybody home, and this is the lifeblood of their company, the contact centers that are answering these calls and the ones that were processing these claims. And as everybody went home, their strategy really was to actually go buy new laptops for everyone and implement VPNs that had a little bit of, but not fully and then implement SD-WAN, and so they had all of this traffic going over VPNs and through SD-WANs and new UCaaS solutions and all of this and what they quickly learned and found out was they just didn't have the visibility to be able to fuel, again, that word confidence that they were serving their their customers very well. So, they actually implemented one of our solutions and put these agents out at all their different desktops and started watching and doing these proactive calls and making going through the meeting life cycle and actually testing the bandwidths of their SD-WAN and ensuring all of those services. And what they found was they were able to solve some of the solutions that are even harder to solve normally, because it was affecting some users, but not all of them, and that's often harder to try and get their arms around. And so as they continued to do this, and just got their arms more around it and got more visibility, they really feel like everything's under control. And as of now, they're actually planning on leaving all those users working from home now, because they can actually ensure the same type of experience for both the users and for their customers as if those people were working from their corporate headquarters. >> Jason, that sort of sounds like a bit of a COVID silver lining. >> (laughs) Yeah, I think so. I think a lot of us actually started working from home and so there was kind of the silver lining of flexibility for the employee, but for the customer and the company itself, they learned this new visibility and this new way to ensure that across everywhere, wherever they may be, and I don't know that that would've come out without the COVID silver lining, as you just said. So I think it was something that really came out of it that might've been a good thing. >> And there are a few of those, which is nice. Eileen, talk to me about some of the experiences that you've had. What have you seen out in the field? >> Yeah, we have one really terrific energy company that was talking with us the other day, and their employees use Microsoft Office 365 which has the teams collaboration and communications system with it. And, what they've been doing for those at-home employees was configuring tests on their works stations, much like Jason explained, but it mimics exactly how an employee might be making their call and joining the sessions from video to audio, to going through login and log out. What's interesting is, and this is a compelling differentiator, a lot of tools may just watch traffic as it's happening, and certainly that's a value, but these tests even run when our agents are asleep. And what that does is these are all 24 hour a day businesses, and so maybe they have followed-the-sun contact centers or whatnot and something's happening in one part of the world, but then it's rolling to others, and we have all heard those disaster stories online when we wake up and we're hearing it on the morning news. So, if an organization can find the problem and detect it early enough and then get it when it's a few people that are involved, they can actually resolve it with our tools, find the root cause, implement a corrective action before the majority of their agents are even logging in in the morning. Nobody even knew that there was a problem overnight, because they were able to get to it and resolve it faster, and when you can do that, you're being proactive. And this, again, builds on the confidence that you get doing this kind of activity over and over and over again. But at the same time, it's also enormously beneficial from a business productivity perspective for the employees and certainly reputationally in revenue-based customer service, making sure that things are available whenever they're necessary. So, making sure they can perform their jobs, I know it sounds trite, but it's really the most critical thing we can help 'em with. >> Absolutely, 'cause I think, Eileen, one of the things that I've always thought for years is that employee productivity and employee satisfaction is directly tied to customer satisfaction, customer delight, and as you talked about, there's plenty of social media influencers who are happy to share news, good or bad, so that employee productivity is a direct relation on the customer satisfaction, the brand reputation. Jason, what are your thoughts there? >> Well, I think that's exactly right. I think it's, again, being able to continuously have your arms around that and make sure, because if you can't make phone calls or customers can't call in or things aren't working then it is, it's really a revenue impact, but it's also reputation impact, and you're going to remember that company that just didn't have their act together if you will, so I think it's important to, again, invest in this and make sure that no matter what, wherever your end users are or wherever your employees are, you're providing that experience just as if they were in the corporate office, and even when they're in the corporate office, being able to, as Eileen talked about, know ahead of time and proactively when issues happen in these very complex UCaaS and UC&C solutions that are out there now. >> And last question, Eileen for you, I imagine that these solutions are horizontal across every industry, every type of business, every size of business? >> Yeah, it's one of those phenomenon that's really critical is the ability to be ubiquitous in any environment, not being vendor-specific or dependent because now look at it, we shot that stat, three to nine different platforms in one company. If you had to buy three or nine different platforms to resolve problems, that reduces your ability to build workflows, consistent ones and know what you're doing every single time. You'd have to learn nine different platforms. That's not productive and that's certainly not realistic. So yeah, I think that this is really key. You have to be able to look at all of the traffic and be able to resolve the problems, regardless of what they happen to be running on. >> And the great thing is hearing the tools and the capabilities and solutions that NETSCOUT has to help businesses in any industry, at any size be able to identify these issues, resolve them faster and then create some silver linings. Guys, thank you so much for joining me today. Always a pleasure talking to you. This was really interesting to talk about the importance of quality end user experience with communication services for the employee productivity and of course, ultimately consumer customer satisfaction. We appreciate your insights. >> Thank you so much. >> Thank you. >> For Eileen Haggerty and Jason Chaffee, I'm Lisa Martin, you're watching a "CUBE Conversation." (bright music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> New data from ETR's soon to be released April survey, shows a clear deceleration in spending and a more cautious posture from technology buyers. Just this week, we saw sell side downgrades in hardware companies like Dell and HP and revised guidance from high flyer UiPath, citing exposures to Russia, Europe and certain sales execution challenges, but these headlines, we think are a canary in the coal mine. According to ETR analysis and channel checks in theCUBE, the real story is these issues are not isolated. Rather we're seeing signs of caution from buyers across the board in enterprise tech. Hello and welcome to this week's Wikibon CUBE insights powered by ETR. In this Breaking Analysis, we are the bearers of bad news. Don't shoot the messenger. We'll share a first look at fresh data that suggests a tightening in tech spending calling for 6% growth this year which is below our January prediction of 8% for 2022. Now, unfortunately the party may be coming to an end at least for a while. You know, it's really not surprising, right? We've had a two year record run in tech spending and meteoric rises in high flying technology stocks. Hybrid work, equipping and securing remote workers. The forced march to digital that we talk about sometimes. These were all significant tailwinds for tech companies. The NASDAQ peaked late last year and then as you can see in this chart, bottomed in mid-March of 2022, and it made a nice run up through the 29th of last month, but the mini rally appears to be in jeopardy with FED rate hikes, Russia, supply chain challenges. There's a lot of uncertainty so we should expect the C-suite to be saying, hey, wait slow down. Now we don't think the concerns are confined to companies with exposure to Russia and Europe. We think it's more broad based than that and we're seeing caution from technology companies and tech buyers that we think is prudent, given the conditions. You know, looks like the two year party has ended and as my ETR colleague Erik Bradley said, a little hangover shouldn't be a surprise to anybody. So let's get right to the new spending data. I'm limited to what I can share with you today because ETR is in its quiet period and hasn't released full results yet outside of its client base. But, they did put out an alert today and I can share this slide. It shows the expectation on spending growth from more than a thousand CIOs and IT buyers who responded in the most recent survey. It measures their expectations for spending. The key focus areas that I want you to pay attention to in this data are the yellow bars. The most recent survey is the yellow compared to the blue and the gray bars, which are the December and September '21 surveys respectively. And you can see a steep drop from last year in Q1, lowered expectations for Q2 in the far right, a drop from nearly 9% last September to around 6% today. Now you may think a 200 basis point downgrade from our prediction in January of 8% seems somewhat benign, but in a $4 trillion IT market, that's 80 billion coming off the income statements of some tech companies. Now the good news is that 6% growth is still very healthy and higher than pre pandemic spending levels. And the buyers we've talked to this week are saying, look, we're still spending money. We just have to be more circumspect about where and how fast. Now, there were a few other callouts in the ETR data and in my discussions today with Erik Bradley on this. First, it looks like in response to expected supply chain constraints that buyers pulled forward their orders late last year and earlier this year. You remember when we couldn't buy toilet paper, people started the stockpile and it created this rubber banding effect. So we see clear signs of receding momentum in the PC and laptop market. But as we said, this is not isolated to PCs, UiPath's earning guidance confirm this but the story doesn't end there. This isn't isolated to UiPath in our view, rather it's a more based slowdown. The other big sign is spending in outsourced IT which is showing a meaningful deceleration in the last survey, showing a net score drop from 13% in January to 6% today. Net score remember is a measure of the net percentage of customers in the survey that on balance are spending more than last survey. It's derived by subtracting the percent of customers spending less from those spending more. And there's a, that's a 700 basis point drop in three months. This isn't a market where you can't hire enough people. The percent of companies hiring has gone from 10% during the pandemic to 50% today according to recent data from ETR. And we know there's still an acute skills shortage. So you would expect more IT outsourcing, but you don't see that in the data, it's down. And as this quote from Erik Bradley explains, historically, when outsourced IT drops like this, especially in a tight labor market, it's not good news for IT spending. All right, now, the other interesting callout from ETR were some specific company names that appear to be seeing the biggest change in spending momentum. Here's the list of those companies that all have meaningful exposure to Europe. That's really where the focus was. SAP has big exposure to on-premises installations and of course, Europe as well. ServiceNow has European exposure and also broad based exposure in IT in across the globe, especially in the US. Zoom didn't go to the moon, no surprise there given the quasi return to work and Zoom fatigue. McAfee is a bit of a concern because security seemed to be one of those areas, when you look at some of the other data, that is per actually insulated from all the spending caution. Of course we saw the Okta hack and we're going to cover that next week with hopefully some new data from ETR, but generally security's been holding up pretty well. You look at CrowdStrike, you look at Zscaler in particular. Adobe's another company that's had a nice bounce in the last couple of weeks. Accenture, again, speaks to that outsourcing headwinds that we mentioned earlier. And now the Google Cloud platform is a bit of a concern. It's still elevated overall, you know but down and well down in Europe. Under that magic, you know we often show that magic 40% dotted line, that red dotted line of net score anything above that we cite as elevated. Well, some important callouts to hear that you see companies that have Euro exposure. And again, we see this as just not confined to Europe and this is something we're going to pay close attention to and continue to report on in the next several weeks and months. All right, so what should we expect from here? The Ark investment stocks of Cathie Wood fame have been tracking in a downward trend since last November, meaning, you know, these high PE stocks are making lower lows and higher, sorry, lower highs and lower lows since then, right? The trend is not their friend. Investors I talk to are being much more cautious about buying the dip. They're raising cash and being a little bit more patient. You know, traders can trade in this environment but unless you can pay attention to in a minute by minute you're going to get whipsawed. Investors tell me that they're still eyeing big tech even though Apple has been on a recent tear and has some exposure with supply change challenges, they're looking for maybe entry points in, within that chop for Apple, Amazon, Microsoft, and Alphabet. And look, as I've been stressing, 6% spending growth is still very solid. It's a case of resetting the outlook relative to previous expectations. So when you zoom out and look at the growth in data, getting digital right, security investments, automation, cloud, AI containers, all the fundamentals are really strong and they have not changed. They're all powering this new digital economy and we believe it's just prudence versus a shift in the importance of IT. Now, one point of caution is there's a lot of discussion around a shift in global economies. Supply chain uncertainty, persistent semiconductor shortages especially in areas like, you know driver ICs and boring things like parts for displays and analog and micro controllers and power regulators. Stuff that's, you know, just not playing nice these days and wreaking havoc. And this creates uncertainty, which sometimes can pick up momentum in a snowballing effect. And that's something that we're watching closely and we're going to be vigilant reporting to you when we see changes in the data and in our forecast even when we think our forecast are wrong. Okay, that's it for today. Thanks to Alex Merson who does the production and podcasts for Breaking Analysis and Stephanie Chan who provides background research. Kristen Martin and Cheryl Knight, and all theCUBE writers they help get the word out, and thanks to Rob Hof, our EIC over at SiliconANGLE. Remember I publish weekly on wikibon.com and siliconangle.com. These episodes are all available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. etr.ai that's where you can get access to all this survey data and make your own cuts. It's awesome, check that out. Keep in touch with me. You can email me at dave.vellante@siliconangle.com. You can hit me up on LinkedIn. This is Dave Vellante for theCUBE insights powered by ETR. Be safe, stay well, and we'll see you next time. (gentle music)

(upbeat ambient music) >> Hey everyone, welcome to this CUBE Conversation. I'm your host, Lisa Martin. I've got NETSCOUT guests here with me today. Eileen Haggerty joins us, the AVP of product and solutions marketing and Jason Chaffee as well, senior product manager. We're going to be talking about gaps in edge visibility. Guys, great to have you on theCube. >> Yeah, thanks Lisa, I really appreciate it. I appreciate the time to be able to talk with everyone. >> Good to be here. >> Yeah. All right, Eileen, we're going to start with you. Oh, what a last two years we have had, COVID, digital transformation massively accelerated, it also both changed networking dynamics over the last couple of years. How has that changed? >> Yeah, and that's the absolute truth. I think we've really seen it in the huge swings where people are performing their jobs right now. You know, I think when people went home two years ago to do their jobs, no one ever expected we where we would be two years later, right? There's really been a variety of different stages from totally working at home to now where you see an awful lot of hybrid work. People splitting their time between the offices and home. That's really where we're at right now. And in fact, some of the studies that we've been reading up on and seeing, majority of workers actually really prefer a hybrid work model, I can understand that. (chuckles) As well the managers believe they are going to have some of their employees that work from a remote location on a regular basis going forward too. So that becomes one of the biggest issues that we have to support them from an IT perspective and a corporate of going forward. One aspect was interesting, two thirds of high revenue growth companies are really embracing hybrid work. This is going to require a couple of things though. Business continuity has depended on this model now, remote workers have been a part of it and we need applications in the network to support that as well as it used to when they were all based in one set of buildings, right? So one of the things that we find IT executives lamenting, some think that they have a lot of confidence in being able to troubleshoot problems when employees are having them remotely, others are actually not quite so confident. So we're going to have to look at this as an industry and help them assure IT infrastructure and services are performing flawlessly so that the hybrid workforce can be successful. >> Yeah, that hybrid environment, it's kind of like must embrace at this point. But Jason, there brings some network complexity to this. The digital transformation was absolutely essential, right, the last couple of years for businesses to first survive and then to thrive, but network complexity has increased. Jason, walk us through what the communications path looks like in today's hybrid environment. >> Yeah, Lisa, it really has. It's just become more complex, you know, in today's hybrid environment and the whole digital transformation, there's really three areas of visibility or three location types if you will that they really need to have to focus on. And one is sort of that data center, cloud services edge and then there's the network edge. And now the ever expanding and growing client edge and really what's common about all of these different edges is this is where the traffic gets altered and crosses across those two domains or those multiple domains really. And so what happens there is those are areas where problems can occur and these are possibly, if not probably blind spots for IT. So when you think about these different edges, like the service edge, just as your private data center or the cloud where applications that are actually hosted or the network edge are going through colocations and WANs and through the internet and your typical kind of network throughout the whole organization. And then lastly is the client edge. And the client edge is again, just continues to grow. And this, people now working from home as Eileen was just talking about and remote offices or their home one day and a remote office the next day and whatever that might be and heck, they might be working in coffee shops or in the corporate headquarters. So it's just really added complexity. And as we get further away from the data center, we start to lose all of that infrastructure that we own and can control. And so it makes it difficult to really manage and understand that. In fact, I think that's probably one of the biggest consequences or challenges of this whole digital transformation. You know, it's made it real easy for those of us to work from home and all these new systems, and it's real simple to work from literally anywhere, but it's just made it that much more complex and challenging for the IT organization to really be able to manage and kind of provide that ubiquitous end user experience regardless of where the users are. You know, kind of last point, I was just thinking about this is, when you think about an organization that maybe has 30,000 employees and if 80,000 of those sudden, or 80% of those suddenly got sent home and had to work during COVID and the whole pandemic, and maybe they're hybrid now, well, that's 24 to 25,000 employees that are really key to your revenue and customer satisfaction. So IT organizations just simply can't afford not to invest in all of this and really try and to understand these complexities and make sure that everything's working the way it should for productivity for the company. >> That's a great point, Jason, as consumers, we are so demanding. That's I think one of the things in COVID that went away was patients and maybe it's slowly coming back but the customer satisfaction, the brand reputation, those are all things that are dependent on solid networking. And of course IT challenges, IT is challenged to to really smooth out those challenges. But Eileen, as employees and end users, we've faced a lot of challenges. I know I have in the last couple of years. Walk us through some of those main pain points that the employees and the end users have been through in the last two years. >> You couldn't be more on spot there. So we really haven't. The irony is all of us on this call have been amongst the ones who have probably suffered from some of these issues as well. You know, one of the things that we found during this period is all of us were coming in over VPN or on video desktop interfaces like Citrix and others. And we were connecting to data center applications and software as service apps for everything. You know, it could be customer order processing, customer records, emails, and in any time or place that we were accessing, we could have slow responsiveness, we could have log issues, we had timeouts. I think one of the interesting ones was communications apps that became huge overnight, Teams, Zoom, WebEx, and those have had issues for us too. They had connection issues, poor quality voice, terrible video. So it became a very frustrating period of time in many cases for employees, they're there to deliver customer care, protect the corporate revenue. But networks and application disruptions counter that. So leading to productivity loss, that's a big issue and a concern. And certainly one of the bigger worries is customer dissatisfaction. But I'd say, you know what's fascinating here too is IT staffs were equally frustrated but for different reasons during this period. They were combating network and application issues for these employees. And usually, they were used to everybody being in one location or to a few buildings and they had total control if you will. Now they're managing 100s and sometimes 1000s of locations known as homes and those staff members we've heard them say things like, they felt like they were losing sight of the remote workforce or simply losing control. And hybrid work models, as they become the norm for many of these organizations, groups of IT professionals still have to ensure the quality of service performance for those employees wherever they do their jobs, home, remote offices or headquarters, and for any application wherever it happens to be hosted. So this is a big challenge. >> Big challenge for IT. You talked about that customer satisfaction. Reminded me of one time I was on the phone with a contact center and I heard a dog barking in the background and I first I thought was that my dog and I thought, no, that customer contact center person is also stuck working from home. Talk about losing control of your environment. But Jason, next question is actually for both of you and Jason, I'll start with you, how does IT assure performance? I mean, it's hard to manage, talk to us about that. >> Well, yeah, Lisa, really kind of as Eileen just said, we used to all sort of be in the same common area in the headquarters. And so people, you know, the IT organization was looking at things like the data center or server farms or internet links just going into and out of the headquarters or off to the data center itself. And so, but that's just not really the case anymore. And as people continue again, as I said before, work from literally anywhere, it's just made the ecosystem that much more challenging and much more complex and bigger frankly to try to manage. And so I think what you really need to do is you see something where it's challenging because the old adage is you just can't manage what you can't see. And so that's become that challenge. And I think what you need is visibility at every edge including up to the client edge that we've been talking about so that you can do things like track and trend volumes and bandwidth and capacity and application utilization and all the different things that make up that end user experience. You need that visibility from all of those locations to really understand and see what's going on from there. >> Eileen, what's your take? >> Well, Jason makes a bunch of valid points. I think what triggers in my mind as he was speaking was that there are other enterprises that have very specific remote locations which present themselves a very different kind of importance for value of the performance assurance. There's banks. They have financial transactions that are going on there, which are instantaneous in nature or need to be for a variety of different reasons, right? Factory plants they've been now wirelessly or WiFi driven production lines. And as a result, any disruption in that production line could have it turned off for 20 minutes an hour. And that has a deep impact to the business as well. Retail stores and distribution centers. This one rings probably for everybody, 'cause during this period of time, we were all online and we were ordering things, right? And so any issues with disruptions, slow downs from those types of remote locations for touchless pickup for the ability to go to a store or get something picked up that day, this was critical. And we all know those services broke down for one reason or another and it created a bit of a problem if you didn't have the right snack for the four year old today. >> Right, definitely the four year old losing control or losing patients, the poor parent. Jason, you talked about visibility and you said something really poignant, you can't manage what you can't see, what is needed for IT to have that visibility as this environment just scattered, what's needed to effectively manage it? >> Yeah. Lisa, you know I think as you just said, and as I said earlier, I think the real key is visibility at every edge and all of the different edges that we've talked about including the home user and it's really been impractical and expensive to instrument at every one of those, especially at all the home locations which are now everybody's home work office. And you just really can't get a view into it. And of course there's some solutions out there that sort of gives you a view of what's going on, what's that end user experience. And, but it doesn't really tell you why. And I think that's one of the key components of that. So as I think about this large new hybrid ecosystem, I think there's really three main things that you need in order to do that. And the first of all, again, is that complete visibility at every edge. And to me that means a combination of both passive and active synthetic based monitoring. So you're passive monitoring where you're actually looking at the real user traffic, and detecting trends and being able to understand what's going on there. But then you also do need, there's a time and a place for that synthetic active testing where we're getting an understanding and a baseline where we're testing continuously and automatically to understand what that end user experience is and understand what performance should look like. But as I mentioned, I think that's just not necessarily enough to do just do synthetics from those synthetic locations. I think it's really key to be able to get deep down into the wire day or the packets of that to really understand why something is happening. You know, for instance, today there might be an issue and you can say, well, I see it's a DNS issue. Hey, DNS guy, go off and try to fix this and figure out what's going on. Well, again, I think you need that visibility, you need a solution that can pull the packets back and give you that combination of both of those things. The next thing I think. >> So. >> Oh, sorry, go ahead. >> Go ahead. >> Well, the next thing I was going to say that I think that's really critical and key is tools that can manage the complexity as you go across all of these. I mean, there's just so many tools out there that are, SaaS and Ucast, your WebEx, Zoom teams, all of those. And it's just frankly, almost impossible to be an expert on all of those different solutions that you might have. And of course they have their own management platform forms that make it, so you can kind of see what's going on but being able to understand and see how to fix WebEx for instance, doesn't really help you when one of your users happens to be having a problem with teams. And so I think again, you need a solution that can go across all of those different applications to be able to see what's going on. And then thirdly, I think is the key, one of the key components is service and application collaboration. And what I mean by this is you need a tool that can give you the ability to have proof and evidence that you can share with your service providers, your application providers because they're very complex, right? They all have dozens of servers in different parts of the world, in different parts of the country. And frankly, they're going to probably blame you first, they're going to say, no, this is something on your end. And it really adds to the time of troubleshooting and get resolution. But if you can actually have that data to say, hey, I can see exactly what's going on. And it's this server at this data center and it's causing high retransmissions or latency. That just makes again more of a collaborative effort but allows you to sort of put all of those things together and stop the finger pointing and blame game and be able to solve those solutions much more quickly. So again, I think it's really a combination of active and passive together all in one console or one solution that really gives you that visibility across all of the different environments that we might have today. >> All those different environments, and there still are so many. Eileen, how have you seen this? How has NETSCOUT seen this actually in practice and how have the tool that you and talked about, how is it actually helping to give the visibility, to reduce the complexity and to ensure that ultimately the end users and the employees are productive so that the customers can be happy? >> Yeah, and you know, it's interesting as he was talking, I was thinking one of the accounts that I've talked to, an organization that's based in software development and they literally have offices all over the world. The hybrid workforce model is their choice going forward. And most of those worldwide employees are part of the sales and support organization for local prospects and customers. So one of the biggest things that's critical to them is communications. And that has to be top of their concerns for quality. The other business related applications are equally important because as you're talking to them, you're pulling those services up and they are in fact using solutions for looking at those edges, the WAN links are key for visibility. They're able to look at the inbound and outbound traffic at those locations. And then what they're able to do is to do two things, one, like Jason was talking about, collaborate, work with those local WAN providers. They're all different over the world. So you really need to build a relationship with them, you have to have some evidence and they're able to do that now. It helps them cost effectively and proactively plan bandwidth changes, and that's really important too. They're also using the synthetic testing that Jason referred to. These locations have the buildings able to test for different applications that are going to be important to the business that's at that location. They do it over ethernet, so for the people with hardwired desks, they can see what the traffic experience is. And then for those that are in open spaces or conference rooms on using WiFi, they're measuring there as well. They want to make sure that no matter where you sit in the office and how you connect, the quality is the same and that's important. Bottom line, they're being able to reduce dramatically the time it's taken to troubleshoot and resolve issues as they emerge. It's great. >> That is great. And of course, as we all have that patience limitation, that speed is key there. Guys, thank you so much for joining me talking about not just the gaps in edge visibility but the ways that they can be remedied and fixed so that ultimately customer satisfaction, employee productivity, all things are harmonious. We appreciate your insights. >> Absolutely, thank you. >> Thank you. >> For Eileen Haggerty and Jason Chaffee I'm Lisa Martin, you're watching a CUBE Conversation. 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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 predictions are all the rage at this time of year now on december 29th 2020 in collaboration with eric porter bradley of enterprise technology research etr we put forth our predictions for 2021 and the focus of our prognostications included tech spending remote work productivity apps cyber security ipos specs m a data architecture cloud hybrid cloud multi-cloud ai containers automation and semiconductors we covered a lot of ground now over the past several weeks we've been inundated with literally thousands of inbound emails pitching us on various predictions and trends in these and other areas here's my predictions folder and this is only a portion of the documents that i've received by email obviously printed them out killed a few trees sorry hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we're going to review briefly each of our predictions for this past year 2021 and suggest a grade as to how we did we're going to do this as a little warm up for our 2022 predictions which we'll be doing in the next over the next couple of weeks now before we dig in i want to make an observation many of the predictions that we received they were observations of trends and sometimes not really predictions or you know or not surprising we got a lot of self-serving marketing statements you know predictions in our view they should be measurable so you can look back and say okay did they get it right now granted there are gray areas so that's why we'll use a grading system today now there are also many really well done and thought-provoking predictions and there's an example of one that we received that is strong it's from equinix cio milan waglay who said within the decade data centers will be powered by a hundred percent renewable energy okay so you know that's clear and we can measure that but anyway thanks to all the pr folks who sent along like i said literally thousands of predictions we tried to read them all but the volume over the past week or so was just so overwhelming and we'll try to scan them before we do our 2022 predictions but today we want to do that warm up by evaluating how we did in 2021 so let's get started our first prediction was that tech spending would increase by four percent this year coming off of what we had thought was a contraction in 2020 and depending on which data you look at you know best case maybe was flat we definitely correctly called the continuation into 2022 of the remote work trend and the positive impact it would have on pcs and the like but we underestimated the shape of that rebound that that spend back curve idc has tech spending wrote this year at five and a half percent so we feel like while we called the bounce back it was more pronounced than we had thought in fact you know we think that idc number is probably going to go up even higher and we'll address that in our 2022 predictions so so we'll give ourselves a b minus here okay next prediction was remote worker trends become fossilized settling in at an average of 34 percent by year end 2021. so on average 34 of the workers would be remote by the end of this year now you know we made the call but we missed delta no we missed omacrom we said 34 remote which would be 2x the historical norms now the etr data suggests it was 52 in september and it's probably going to be somewhere in the 40 to 45 range by by the end of this month into december and the thing is 75 of the workforce is probably still working either fully remote or in a hybrid model and hybrid work is probably going to be the dominant trend and we're going to have to revisit that framework or how we think about this whole structure and we'll do that again in our 2022 predictions so we'll give ourselves a c on that one we'll take some credit for the permanence of the trend but the percentage was well off the mark you know thanks to the variance as well as some cultural shifts that whole hybrid notion okay so hey not really a great start for eric and me but we rebound with the next one the productivity increases we said seen in 2020 will lead organizations to double down on the successes and certain productivity apps will benefit so to measure this we said let's take a look at the most recent quarterly earnings and gauge the revenue growth year on year as an indicator docusign was up 42 smartsheet who we also called up was up 46 in revenue twilio up 65 zoom growth was 35 down from 325 confirming our layup call the zoom growth would moderate it had nowhere to go but down and microsoft teams has never been more ubiquitous has never seen greater adoption with hundreds of companies having a hundred thousand or more users and thousands of companies with ten thousand users or more so we really feel like we nailed this one so we're gonna give us give ourselves an a plus okay so now on to cyber it's an area that we've been making calls in for a couple of years now and we're really pleased looking back here we said permanent shifts in cso strategies are going to lead to share shifts in network security now we said to give you more detail maybe that sounds like an easy one but we said specifically identity cloud security and endpoint security would continue to benefit and we specifically named crowdstrike octa zscaler and a few others that are targeting their growth rates now gartner has the security market growing at 11 percent octa and zscaler revenues last quarter grew at 62 percent year over year crowdstrike 63 illumia we also called out they raised 225 million dollars on a 2.75 billion valuation on the strength of its growth that was in september now akamai acquired guardiocor for 600 million dollars another company we called out that they would do it they did that as a ransomware protection play and they paid a huge revenue multiple for the company and it seems the guys listed on the last line are all talking about subscriptions sas arr remaining performance obligations or rpo so we feel very good about this look back we'll take an a on this one no it's not an a plus because we're too conservative on the growth of octa crowdstrike and zscaler topping at 50 they they blew that away by another 10 points or so 10 to 15. but look pretty good call nonetheless okay again the next one you might feel like is a layup but not really so we said the increased tech spend would drive even more ipos spax and m a according to spac analytics ipos were up 109 this year the spac attack continued up 109 percent in 2021 on top of a record 2020 and according to kpmg m a dollar volume was up 19 okay you might say uh that was easy call but there was much more underneath this prediction we called out uipass ipo which was a lock but also said automation anywhere would go public uipath did aa didn't we did correctly call the hashicorp ipo we said they'd either get go ipo or get acquired and cloud flare grew revenue 219 percent last quarter but akamai was not acquired so the degree of difficulty on the overall prediction wasn't high but the automation anywhere in akamai events we made those calls that didn't happen and those were you know obviously tougher calls so we think this still deserves a b grade all right as you know data is one of our favorite subjects and we've reported extensively in the successes and failures of so-called big data we said next in the next prediction that in the 2020s 75 percent of large organizations will re-architect their big data platforms and we said this would occur you know in earnest over the next four to five years now again you may say duh dave but you have to evaluate the prediction based on the underlying comments here the jury is still out on things like snowflakes data cloud but we absolutely believe that it's the right direction but then you have then you have data bricks coming in taking a different approach they're coming at the problem from a data science angle trying to take on traditional bi and then you get snowflake coming from the analytics space and moving into ai and data science and you know we asked at aws aws re invent we asked benoit dejaville on the cube if there needs to be a semantic layer to bring these two worlds together and he said yes and that's what he claims snowflake is building meanwhile you got the big whales like oracle they continue to invest in their capabilities to try to eliminate data movement and then there's aws taking a totally different approach to data where it gives customers maximum optionality of offerings and database and other services and you can't forget microsoft and google so many customers might not take the steps that we predicted because they're comfortable where they are specifically we're talking about here a shift toward domain ownership and data product thinking and the reorganization of hyper-specialized technical teams many of the principles put forth by data mesh and we've said this change is going to take a number of years to play out four to five years so we start noticing in 2021 that that's clearly been the case as we reported on parts of jpmorgan chase uh rethinking its data architecture hellofresh and many others so this is still an incomplete the professor we'll give ourselves an incomplete on this one but we think it's trending in the right direction okay the next one is always fun discussion that's the battle to define hybrid and multi-cloud we said that's going to escalate in 2021 and we'll create bifurcated cio strategies now here we go aws sees the world as bringing its apis and primitives and model to the edge and the data center to aws is just another edge node and the company says that in still believes in the fullness of time that all data will be in the cloud however that's defined and aws awareness would say all this talk about hybrid of connecting on-prem to a cloud they would flat out say adam silipsky told us this that's not cloud is what he said then on the other side of the table you have the likes of cisco dell hpe etc saying hold on cloud is an operating model it's not a place and aws might say yeah and aws along with its customers is defining that operating model and these other guys would say no actually you're not we are with our customers and this battle 100 percent escalated in 2021 with the launch of apex by dell hp e double down on green lake cisco's as the service models and then of course oracle which actually announced a true same same public to on-prem hybrid capability two years before aws announced outpost and of course oracle's executing on that strategy in earnest in 2021 and the other nuance here is a concept that we introduced called super cloud which refers to the notion that look something like for example multi-cloud is not about running within a respective cloud it's not about cloud compatibility rather it's about abstracting the complexity of the underlying cloud primitives and building value on top of those cloud services on top of the investments in capex that the hyperscalers have made now some people didn't like the term super cloud maybe uber cloud would be a better term we're going to continue to use it to describe this capability we think it has meaning and we're seeing new examples like goldman sachs's financial cloud running on top of aws so a super cloud is not as an application or a suite of applications running on a single cloud now if those applications span multiple clouds like like snowflake is trying to do okay that's a service that could span multiple clouds or in the case of goldman sachs it's a portfolio of data tools and software that's made accessible as a service that floats on top of a single or even multiple clouds regardless we feel that this was a correct call given the evidence and we'll give ourselves an a minus taking points off for the somewhat anecdotal and observational measurement system that we apply to look back at this prediction okay the next prediction was we made was cloud containers ai and ml automation uh are gonna power that those big four are gonna power 2021 spending here's a graphic we use to predict that it plots survey data for the various technologies within the etr taxonomy net score or spending momentum on the vertical axis and market share or presence in the data set it's a pervasive measurement on the horizontal axis the one that matters here is the vertical that dotted line of 40 percent anything above that is considered highly elevated and these four areas have held served this year based on recent etr survey data that we're not showing here we'll we'll bring that into our 2022 prediction so this prediction came in correctly for the most recent survey data and that's our measurement system on this one so we're going to take an a for this one too now on the penelope ultimate prediction here we came back to automation saying that the automation mandate accelerates in 2021 uipath and automation anywhere we said would go public but microsoft remains a threat to these pure play rpa vendors well we gave ourselves a b on this one doubling down on automation anywhere going public you know that was wrong but we definitely saw this year companies leaning hard into automation and microsoft despite the fact that it doesn't have as feature rich a product and offering as uipath and automation anywhere microsoft remains a very large presence you know we spoke to a lot of customers at the uipath forward four event in october in las vegas physical event and they confirmed you know this is true but at the same time so they're using power automate from microsoft but also using in this case uipath so they've kind of confirmed that yeah it's not the same we use that for some of our productivity we're an azure customer it's easy for us but they're still leaning heavily and investing heavily into uipath and i think the same can be said for automation anywhere but autom but power automate shows up as a big time leader in the magic gartner magic quadrant so it can't be ignored but clearly the two leaders in rpa have a sizable product advantage relative to the legacy software players now if you look at the comment on pega systems they cooled off a bit as measured by their stock price their revenue grew 13 percent last quarter on a year-on-year basis but perhaps we overestimated the tailwind effect and the company's momentum so we'll take a b on this prediction correct call on the automation trend and the big software vendors piling in ibm et cetera but the chance we took on automation anywhere again was a miss so we'll dig ourselves on that and our last prediction for 2021 was 5g rollouts push new edge iot workloads and necessitate new system architectures now much of this prediction you can see in the underlying bullets here really related to the observation that arm was dominating at the edge it would find its way into the mainstream enterprise workloads and we've been asking a lot of the mainstream you know companies the oems you know what do you what do you see with with arm in the enterprise and they say yeah we don't see it yet but very clearly this came into focus in 2021 is aws announced graviton 3 now and new inference and new training silicon these are different types of workloads that are emerging in the enterprise these are all based on arm microsoft google alibaba oracle and others are now shipping or readying arm-based systems for the enterprise when you look at new storage network and security appliances and other systems they're very offering and often including arm-based processors to assist with the offloads and look intel is definitely under product under pressure as we've predicted many times not just in our predictions post even pat gelsinger has admitted this is a turnaround it's going to take at least five years that's kind of new and recent data that he's made public so we're going to take an a minus on this one we're going to take off some points for the fact that you know 5g rollouts in edge are evolving and this is a longer term trend but the underlying points that we made on this slide are still pretty solid now if we use the following scale where a plus is a hundred out of a hundred a minus is a 90 a b is an 85 a b minus is an 80 and a c is a 75 out of 100 and we exclude that incomplete prediction on data architectures we average out to an 87.8 so that's a solid b plus and so the professor in us said hey little yellow sticky good effort as most of the predictions could be quantified and or you know we tried to object objectively score them there were some layups in there so yeah maybe we'll try to take more risks uh you know or not you know we we we'll see we like winning and so you know you always have to couch some of these things with some obvious ones but but really try to give some detail underneath that's maybe non-obvious um and we'll try to keep it down in the legs we did this year to one or two multi-year predictions so what's next well eric bradley and i were working on our 2022 predictions we're going to release those in the next couple of weeks so stay tuned for that you know what do you think how did we do you know we're grading ourselves here love to know you know for we're off base on base we're too hard on ourselves too easy give us your feedback don't forget these episodes are all available as podcasts wherever you listen all you do is search breaking analysis podcast check out etr's website at etr dot plus remember we also publish a full report every week on wikibon.com and siliconangle.com you can always get in touch with email david.velante at siliconangle.com you can dm me at divalante or comment on our linkedin posts this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well we'll see you next time [Music] you