>>From San Francisco. It's the cube covering PagerDuty summit 2019 brought to you by PagerDuty. >>Hey, welcome back everybody. Jeff Frick here with the Q. We're a PagerDuty summit. It's the fourth year of the show. He's been here for three years. It's amazing to watch it grow. I think it's finally outgrown the Western Saint Francis here in lovely downtown San Francisco and we're really excited to be joined by our next guest. He's Alex Solomon, the co founder, co founder and CTO PagerDuty. Been at this over 10 years. Alex, first off, congratulations. And what a fantastic event. Thank you very much and thank you for having me on your show. So things have changed a lot since we had you on a year ago, this little thing called an IPO. So I'm just curious, you know, we have a lot of entrepreneurs. I watch a show as a founder and kind of go through this whole journey. What was that like? What are some of the things you'd like to share from that whole experience? >>Yeah, it was, it was incredible. I I, the word I like to use is surreal. Like just kind of going through it, not believing that it's real in a way. And adjoining by my, my lovely wife who came, came along for this festivities and just being able to celebrate that moment. I know it is just a moment in time and it's not, it's not the end of the journey certainly, but it is a big milestone for us and uh, being able to celebrate. We invited a lot of our customers, our early customers have been with us for years to join us in that, a celebration. Our investors who have believed in us from back in 2010. Right, right. We were just getting going and we just, we just had a great time. I love it. I love 10 year overnight success. 10 years in the making. >>One of my favorite expressions, and it was actually interesting when Jenn pulled up some of the statistics around kind of what the internet was, what the volume of traffic was, what the complexity in the systems are. And it's really changed a lot since you guys began this journey 10 years ago. Oh, it has. I mean back then, like the most popular monitoring tool is Nagios and new Relic was around but just barely. And now it's like Datadog has kind of taken over the world and the world has changed. We're talking about not just a microservices by containers and serverless and the cloud basically. Right. That's the kind of recurring theme that's changed over the last 10 years. But you guys made some early bets. You made bets on cloud. He made bets on dev ops. He made bets on automation. Yeah, those were pretty good. >>Uh, those, those turn out to be pretty good places to put your chips. Oh yeah. Right place, right time and um, you know, some, some experiential stuff and some just some raw luck. Right. All right, well let's get into it. On top of some of the product announcements that are happening today, what are some of the things you're excited to finally get to showcase to the world? Yeah, so one of the big ones is, uh, related to our event intelligence release. Uh, we launched the product last year, um, a few months before summit and this year we're making a big upgrade and we're announcing a big upgrade to the product where we have, uh, related incidents. So if you're debugging a problem and you have an incident that you're looking at, the question you're gonna ask is, uh, is it just my service or is there a bigger widespread problem happening at the same time? >>So we'll show you that very quickly. We'll show you are there other teams, uh, impacted by the same issue and we'll, we, we actually leveraged machine learning to draw those relationships between ongoing incidents. Right. I want to unpack a little bit kind of how you play with all these other tools. We, you know, we're just at Sumo logic a week or so ago. They're going to be on later their partner and people T I think it's confusing. There's like all these different types of tools. And do you guys partner with them all? I mean, the integration lists that you guys have built. Um, I wrote it down in service now. It's Splunk, it's Zendesk, it goes on and on. And on. Yeah. So explain to folks, how does the PagerDuty piece work within all these other systems? Sure. So, um, I would say we're really strong in terms of integrating with monitoring tools. >>So any sort of tool that's monitoring something and we'll admit an alert, uh, when something goes down or over an event when something's changed, we integrate and we have a very wide set of coverage with all, all of those tools. I think your like Datadog, uh, app dynamics, new Relic, even old school Nagios. Right. Um, and then we've also built a suite of integrations around all the ticketing systems out there. So service now a JIRA, JIRA service desk, um, a remedy as well. Uh, we also now have built a suite of integrations around the customer support side of things. So there'll be Zendesk and Salesforce. That's interesting. Jen. Megan had a good example in the keynote and kind of in this multi system world, you know, where's the system of record? Cause he used to be, you want it, everybody wanted it to be that system of record. >>They wanted to be the single player in the class. But it turns out that's not really the answer. There's different places for different solutions to add value within the journey within those other applications. Yeah, absolutely. I, I think the single pane of glass vision is something that a lot of companies have been chasing, but it's, it's, it's really hard to do because like for example, NewRelic, they started an APM and they got really good at that and that's kind of their specialty. Datadog's really good at metrics and they're all trying to converge and do everything and become the one monitoring solution to the Rooney rule them all right. But they're still the strongest in one area. Like Splunk for logs, new Relic and AppDynamics for APM and Datadog for metrics. And, um, I don't know where the world's going to take us. Like, are they, is there going to be one single monitoring tool or are, are you going to use four or five different tools? >>Right. My best guess is your, we're going to live in a world where you're still gonna use multiple tools. They each can do something really well, but it's about the integration. It's about building, bringing all that data together, right? That's from early days. We've called pager duty, the Switzerland monitoring, cause we're friends with everyone when we're partners with everyone and we sit on top right a work with all of these different roles. I thought her example, she gave him the keynote was pretty, it's kind of illustrative to me. She's talking about, you know, say your cables down and you know, you call Comcast and it's a Zendesk ticket. But >>you know then that integrates potentially with the PagerDuty piece that says, Hey we're, you know, we're working on a problem, you know, a backhoe clipped the cable down your street. And so to take kind of that triage and fix information and still pump that through to the Zen desk person who's engaging with the customer to actually give them a lot more information. So the two are different tracks, but they're really complimentary. >>Absolutely. And that's part of the incident life cycle is, is letting your customers know and helping them through customer support so that the support reps understand what's going on with the systems and can have an intelligent conversation with the customer. So that they're not surprised like a customer calls and says you're down. Oh, good to know. No, you want to know about that urge, which I think most people find out. Oh yeah. Another thing >>that struck me was this, this study that you guys have put together about unplanned work, the human impact of always on world. And you know, we talk a lot in tech about unplanned maintenance and unplanned downtime of machines, whether it's a, a computer or a military jet, you know, unplanned maintenance as a really destructive thing. I don't think I've ever heard anyone frame it for people and really to think about kind of the unplanned work that gets caused by an alert and notification that is so disruptive. And I thought that was a really interesting way to frame the problem and thinking of it from an employee centric point of view to, to reduce the nastiness of unplanned work. >>Absolutely. And that's, that V is very related to that journey of going from being reactive and just reacting to these situations to becoming proactive and being able to predict and, and, uh, address things before they impact the customer. Uh, I would say it's anywhere between 20 to 40 or even higher percent of your time. Maybe looking at software engineers is spent on the some plant work. So what you want to do is you want to minimize that. You want to make sure that, uh, there's a lot of automation in the process that you know what's going on, that you have visibility and that the easy things, the, the repetitive things are easy to automate and the system could just do it for you so that you, you focus on innovating and not on fixing fires. Right? Or if you did to fix the fire, you at least >>to get the fire to the right person who's got the right tone to fix the type. So why don't we just, you know, we see that all the time in incidents, especially at early days for triage. You know, what's happening? Who did it, you know, who's the right people to work on this problem. And you guys are putting a lot of the effort into AI and modeling and your 10 years of data history to get ahead of the curve in assigning that alerted that triage when it comes across the, the, uh, the trans though. >>Yeah, absolutely. And that's, that's another issues. Uh, not having the right ownership, get it, getting people, um, notified when they don't own it and there's nothing they can do about it. Like the old ways of, of uh, sending the alert to everyone and having a hundred people on a call bridge that just doesn't work anymore because they're just sitting there and they're not going to be productive the next day I work cause they're sitting there all night just kind of waiting for, for something to happen. And uh, that's kinda the, the old way of lack of ownership just blasted out to everyone and we have to be a lot more target and understand who owns what and what's, what, which systems are being impacted and they only let getting the right people on the auto call as quickly as possible. The other thing that came up, which I thought, you know, probably a lot of people are thinking of, they only think of the fixing guy that has to wear the pager. >>Sure. But there's a whole lot of other people that might need to be informed, be informed. We talked about in the Comcast example that people interacting with the customer, ABC senior executives need to be in for maybe people that are, you know, on the hook for the SLA on some of the softer things. So the assembly that team goes in need, who needs to know what goes well beyond just the two or three people that are the fixing people? Right. And that's, that's actually tied to one of our announcements, uh, at summit a business, our business response product. So it's all about, um, yes, we notify the people who are on call and are responsible for fixing the problem. You know, the hands on keyboard folks, the technical folks. But we've expanded our workflow solution to also Lupin stakeholders. So think like executives, business owners, people who, um, maybe they run a division but they're not going to go on call to fix the problem themselves, but they need to know what's going on. >>They need to know what the impact is. They need to know is there a revenue impact? Is there a customer impact? Is there a reputational brand impact to, to the business they're running. Which is another thing you guys have brought up, which is so important. It's not just about fixing, fixing the stuck server, it's, it is what is the brand impact, what is the business impact is a much broader conversation, which is interesting to pull it out of just the, just the poor guy in the pager waiting for it to buzz versus now the whole company really being engaged to what's going on. Absolutely. Like connecting the technical, what's happening with the technical services and, and uh, infrastructure to what is the, the impact on the business if something goes wrong. And how much, like are you actually losing revenue? There's certain businesses like e-commerce where you could actually measure your revenue loss on a per minute or per five minute basis. >>Right. And pretty important. Yeah. All right Alex. So you talked about the IPO is a milestone. It's, it's fading, it's fading in the rear view mirror. Now you're on the 90 day shot clock. So right. You gotta keep moving forward. So as you look forward now for your CTO role, what are some of your priorities over the next year or so that you kind of want to drive this shit? Absolutely. So, um, I think just focusing on making the system smarter and make it, uh, so that you can get to that predictive Holy grail where we can know that you're going to have a big incident before it impacts our customers. So you can actually prevent it and get ahead of it based on the leading indicators. So if we've seen this pattern before and last time it causes like an hour of downtime, let's try to catch it early this time and so that you can address it before it impacts for customers. >>So that's one big area of investment for us. And the other one I would say is more on the, uh, the realtime work outside of managing software systems. So, uh, security, customer support. There's all of these other use cases where people need to know, like, signals are, are being generated by machines. People need to know what's going on with those signals. And you want to be proactive and preventative around there. Like think a, a factory with lots and lots of sensors. You don't want to be surprised by something breaking. You want to like get proactive about the maintenance of those systems. If they don't have that, uh, you know, like say a multi-day outage in a factory, it can cost maybe millions of dollars. Right. >>All right, well, Alex, thanks a lot. Again, congratulations on the journey. We, uh, we're enjoying watching it and we'll continue to watch it evolve. So thank you for coming on. Alright, he's Alex. I'm Jeff. You're watching the cube. We're at PagerDuty summit 2019 in downtown San Francisco. Thanks for watching. We'll see you next time.

>> Announcer: From New York, it's theCUBE. Covering Blockchain Week. Now, here's John Furrier. >> Hello everyone and welcome back to theCUBE coverage here exclusively at the block party, at the Crypto-House's part of Blockchain Week in New York City, Blockchain New York. Also, Consensus 2018 is having a variety of other events. I'm here with Allan Rothstein, the co-founder of Strategic Coin, also managing partner at Decentralized Ventures. Hey welcome to this Cube conversation. Nights, night party here, exclusive event here in the East Village, thanks for joining me. >> Thank you, thank you for having me. >> So, co-founder of Strategic Coins doing some great work in the maturization of this sector. Still in the first in the half inning, bottom of the first, some would say but also Decentralized Ventures, which I love the name because what does it mean? I mean, it means crypto, token economics, block chain, brand new field. >> Exactly. >> Emerging very very fast. >> And it's global, so it's decentralized. Right now we're in Malta, but we're going all over the world, Estonia, other countries because that's where this market is going. >> So for the folks that don't really grock all that, how would you describe it to your friend that says Hey Allan, what is this all about? What is this decentralized tokens, ICOs, blockchain, bottom line me, what's going on? >> Blockchain is probably the first really global business model that is not controlled by anybody, by any single government, by any single company, by any single industry. It dis-intermediates all of these industries that are filled with middle-men and which prevent end users and peers from interacting with each other. >> I was told by some guy I was interviewing in Puerto Rico, you know the United States is the place where all the money went into because that's where the entrepreneurial energy was. And Europe was the entity that was slow, antiquated, all these rules, hard to make money, hard to be a capitalist. He goes: "now, the United States is turning into Europe." We are the new Europe in the US and all the money is going outside the US, into massively growing middle-class economies outside the United States. And the perfect storm is the crypto token economic model, where money is just running hard. Your thoughts on that comment and reaction. >> I think it's exactly right, and more importantly the road blocks being set up by the US government are not only sending the economics to other places in the world, they're actually sending the technologies to other places in the world. So I've lived in New York all of my life, I've been on Wall Street; the reason I'm setting up in Malta is exactly for that reason. Because it is very difficult to work in Blockchain and crypto here. We don't know what the definition is. The IRS says that cryptos are property. SEC says that they're securities. SFTC says they're commodities. The FED says they're currencies. So you have four different agencies claiming jurisdiction and you don't know who to report to. You don't know what the rules are. >> And all the service providers like law firms, and advisories, accountings, they all come to a screeching halt because they don't know what to say. They don't want to get sued. Entrepreneurs give up, that stifles innovation. >> It stifles innovation, but it, more importantly, it's really sending potentially the most important technology overseas. And you have other jurisdictions that are grabbing at it. You've got Bermuda, I work with the government in Malta, and they are setting up what they call Blockchain Island. They are setting up a crypto-friendly regime. This will be the first EU country with a full set of regulations. It's not that the regulations are easy but you know what the rules are. And at the moment, that's the only EU country that you know all the rules. >> As all these regulations, I mean GDPR is happening this month, I still think that's a shit show, in my opinion, but we'll see what happens there. This is, all these regulations, I get it, but I think that as the economy starts to go global, it's a competitive opportunity for our country and nation to be a digital nation and do it right. And also, people need advisory. What the hell is the playbook? You can't just go to the manual, there's no manual for this. There's no playbook. Strategic Coin, Decentralized Ventures, other leaders in the community on the finance side are pushing the envelope to try and lead by example. Because, as you just said, things are pretty much sideways from a regulatory standpoint. >> Yeah, that's exactly what we do. So at Strategic Coin, we help with jurisdiction. We help with the regulations, we try and direct companies to understand what they're dealing with. We do deep research for companies, we help them work on the corporate side, we really help them navigate some very difficult and choppy waters. >> What's the biggest challenge that companies have right now? Is it domicile, is it token economics? >> The biggest challenge is, there are two. One is regulation, knowing what the rules are. Second one is banking. Without regulation, bank will not allow companies who are getting funding from crypto to open accounts and accept funds. Once regulation is in place, the banks understand that they're no longer at risk of violating laws because they know what the laws are. So banking, in particular is a real issue around the world. >> What's the overseas outlook, obviously age is booming, there's been some, you know here sound here and there, shut it down, build it out, other countries are saying we're going to be the first global Wall Street, clearing out crypto, the Fiat, moving it around. This is all up in the air. Who's leading and who's not leading? >> Right now, obviously Malta's leading because of the first EU country with a full set of regulations that they've proposed. Singapore is looking to do this. South Korea is starting to now turn. They were looking to shut down exchanges and they're actually now starting to realize that they're just sending business and technology overseas. >> What's your story these days, what are you working on? What did you do last week? Did you fly to South Korea, I mean you traveling a lot? What kind of, what are you working on? What kind of things? Give me a little taste of how your life goes every day? What are some of the challenges, opportunities you're working on? >> Well, one of the challenges is trying to filter all of the business that is actually coming to us with Strategic Coin and with Decentralized Ventures. We can handle the business because we have a lot of the answers that people are looking for. >> So you need to hire people? >> We are continuing to hire people. What's important with Strategic Coin is that we're hiring Wall Street people. We're hiring veterans in the industry. Many of these companies out there now are 25 year old kids, mom and pops, who really don't even understand what they're looking at. >> You know, baseball, the old expression about a five tool player, what's the equivalent, crypto young gun that you look for? What are the attributes that you look for in a candidate that really can handle the pressure. I mean it's not pressure, it's really just more of the pace. You need smarts, you got to have energy, got to have integrity but also you got to push the envelope. >> They have to work about 35 hours a day. They have to have the capacity to really continue to learn very very quickly to understand, to take direction. And to really understand what this business looks like and where it's going. >> And good money making opportunities as well. >> There are tremendous money making opportunities as there are in any new industry, in any new technology. >> Before we came on camera, we were talking about your background, some of the things you've done entrepreneurially and also growth. What's your assessment of the current wave we're in? Compared, you seen many waves, of all the waves, compare and contrast order of magnitude, this wave versus other waves. >> What's interesting about this wave is there have been paradigm changes in industry, technology, and they've taken generations. So, an understanding of how that change happens, generally is from text books, you had the industrial revolution and first software revolution in these generations for people my age, or people in their 40's. You've seen the software revolution then you've seen the internet revolution and now you're seeing this, so you actually have experience in seeing how these play out. And that's part of the reason that this technology is moving so quickly. I know how it's going to go, I've seen how it's going because I was involved in the internet. >> Software economics, you've seen software economics before, you know what it looks like. >> I've seen software and I've seen internet. And with blockchain, we know blockchain is here, and we don't know what use it's going to be, we know a lot of these companies are going to fall by the wayside. We know a lot of these companies set up a mom and pop will disappear and we know a lot of these ICOs will be acquired by bigger ICOs who have more experience. >> Well you know, just to add two things to that list of awesome commentary is add in open source software and cloud computing and you got the perfect storm. On top of what you just said, that is the magic. Alright, so I got to ask you for the young people out there, what's your advise, or if you could talk to your 22 year old self right now, what would you say to yourself, walking into this new landscape that's exploding with opportunity, change in all theaters? >> That's a really good question. I would say to try and find mentors, learn from industry veterans, as opposed to setting up your own shop, setting up your own ICO, thinking you're going to raise 50 million dollars and you're going to conquer the world by the time you're 25. >> Allan, thanks for coming on to share. I know you had a big party, we're having a great time here. Thanks for taking a minute out of the networking and schmoozing and to come in and speak with us on theCUBE here in New York City. >> Thank you. >> Alright, I'm John Furrier, we're here at Blockchain Week, New York, of course theCUBE's continuing coverage. Go to siliconangle.com, thecube.net for all the videos. We'll be at Consensus 2018 all week. More coverage on Silicon Angle and thecube.net. I'm John Furrier, thanks for watching.

>> Hi, I'm Peter Burris and once again, welcome to a Wikibon Action Item. (lively electronic music) We are again broadcasting from the beautiful theCUBE Studios here in Palo Alto, California, and we're joined today by a relatively larger group. So, let me take everybody through who's here in the studio with us. David Floyer, George Gilbert, once again, we've been joined by John Furrier, who's one of the key CUBE hosts, and on the remote system is Jim Kobielus, Neil Raden, and another CUBE host, Dave Vellante. Hey guys. >> Hi there. >> Good to be here. >> Hey. >> So, one of the things we're, one of the reasons why we have a little bit larger group here is because we're going to be talking about a community gathering that's taking place in the big data universe in a couple of weeks. Large numbers of big data professionals are going to be descending upon Strata for the purposes of better understanding what's going on within the big data universe. Now we have run a CUBE show next to that event, in which we get the best thought leaders that are possible at Strata, bring them in onto theCUBE, and really to help separate the signal from the noise that Strata has historically represented. We want to use this show to preview what we think that signal's going to be, so that we can help the community better understand what to look for, where to go, what kinds of things to be talking about with each other so that it can get more out of that important event. Now, George, with that in mind, what are kind of the top level thing? If it was one thing that we'd identify as something that was different two years ago or a year ago, and it's going to be different from this show, what would we say it would be? >> Well, I think the big realization that's here is that we're starting with the end in mind. We know the modern operational analytic applications that we want to build, that anticipate or influence a user interaction or inform or automate a business transaction. And for several years, we were experimenting with big data infrastructure, but that was, it wasn't solution-centric, it was technology-centric. And we kind of realized that the do it yourself, assemble your own kit, opensource big data infrastructure created too big a burden on admins. Now we're at the point where we're beginning to see a more converged set of offerings take place. And by converged, I mean an end to end analytic pipeline that is uniform for developers, uniform for admins, and because it's pre-integrated, is lower latency. It helps you put more data through one single analytic latency budget. That's what we think people should look for. Right now, though, the hottest new tech-centric activity is around Machine Learning, and I think the big thing we have to do is recognize that we're sort of at the same maturity level as we were with big data several years ago. And people should, if they're going to work with it, start with the knowledge, for the most part, that they're going to be experimenting, 'cause the tooling isn't quite mature enough, we don't have enough data scientists for people to be building all these pipelines bespoke. And the third-party applications, we don't have a high volume of them where this is embedded yet. >> So if I can kind of summarize what you're saying, we're seeing bifurcation occur within the ecosystem associated with big data that's driving toward simplification on the infrastructure side, which increasingly is being associated with the term big data, and new technologies that can apply that infrastructure and that data to new applications, including things like AI, ML, DL, where we think about modeling and services, and a new way of building value. Now that suggests that one or the other is more or less hot, but Neil Raden, I think the practical reality is that here in Silicon Valley, we got to be careful about getting too far out in front of our skis. At the end of the day, there's still a lot of work to be done inside how you simply do things like move data from one place to the other in a lot of big enterprises. Would you agree with that? >> Oh absolutely. I've been talking to a lot clients this week and, you know, we don't talk about the fact that they're still running their business on what we would call legacy systems, and they don't know how to, you know, get out of them or transform from them. So they're still starting to plan for this, but the problem is, you know, it's like talking about the 27 rocket engines on the whatever it was that he launched into space, launching a Tesla into space. But you can talk about the engineering of those engines and that's great, but what about all the other things you're going to have to do to get that (laughs) car into space? And it's the same thing. A year ago, we were talking about Hadoop and big data and, to a certain extent, Machine Learning, maybe more data science. But now people are really starting to say, How do we actually do this, how do we secure it, how do we govern it, how do we get some sort of metadata or semantics on the data we're working with so people know what they're using. I think that's where we are in a lot of companies. >> Great, so that's great feedback, Neil. So as we look forward, Jim Kobielus, the challenges associated with what it means to better improve the facilities of your infrastructure, but also use that as a basis for increasing your capability on some of the new applications services, what are we looking for, what should folks be looking for as they explore the show in the next couple of weeks on the ML side? What new technologies, what new approaches? Going back to what George said, we're in experimentation mode. What are going to be the experiments that are going to generate greatest results over the course of the next year? >> Yeah, for the data scientists, who flock to Strata and similar conferences, automation of the Machine Learning pipeline is super hot in terms of investments by the solution providers. Everybody from Google to IBM to AWS, and others, are investing very heavily in automation of, not just the data engine, that problem's been had a long time ago. It's automation of more of the feature engineering and the trending. These very manual, often labor intensive, jobs have to be sped up and automated to a great degree to enable the magic of productivity by the data scientists in the new generation of app developers. So look for automation of Machine Learning to be a super hot focus. Related to that is, look for a new generation of development suites that focus on DevOps, speeding the Machine Learning in DL and AI from modeling through training and evaluation deployment in iteration. We've seen a fair upswing in the number of such toolkits on the market from a variety of startup vendors, like the DataRobots of the world. But also coming to say, AWS with SageMaker, for example, that's hot. Also, look for development toolkits that automate more of the cogeneration, you know, a low-code tools, but the new generation of low-code tools, as highlighted in a recent Wikibons study, use ML to drive more of the actual production of fairly decent, good enough code, as a first rough prototype for a broad range of applications. And finally we're seeing a fair amount of ML-generated code generation inside of things like robotic process automation, RPA, which I believe will probably be a super hot theme at Strata and other shows this year going forward. So there's a, you mentioned the idea of better tooling for DevOps and the relationship between big data and ML, and what not, and DevOps. One of the key things that we've been seeing over the course of the last few years, and it's consistent with the trends that we're talking about, is increasing specialization in a lot of the perspectives associated with changes within this marketplace, so we've seen other shows that have emerged that have been very, very important, that we, for example, are participating in. Places like Splunk, for example, that is the vanguard, in many respects, of a lot of these trends in big data and how big data can applied to business problems. Dave Vellante, I know you've been associated with a number of, participating in these shows, how does this notion of specialization inform what's going to happen in San Jose, and what kind of advice and counsel should we tell people to continue to explore beyond just what's going to happen in San Jose in a couple weeks? >> Well, you mentioned Splunk as an example, a very sort of narrow and specialized company that solves a particular problem and has a very enthusiastic ecosystem and customer base around that problem. LAN files to solve security problems, for example. I would say Tableau is another example, you know, heavily focused on Viz. So what you're seeing is these specialized skillsets that go deep within a particular domain. I think the thing to think about, especially when we're in San Jose next week, is as we talk about digital disruption, what are the skillsets required beyond just the domain expertise. So you're sort of seeing this bifurcated skillsets really coming into vogue, where if somebody understands, for example, traditional marketing, but they also need to understand digital marketing in great depth, and the skills that go around it, so there's sort of a two-tool player. We talk about five-tool player in baseball. At least a multidimensional skillset in digital. >> And that's likely to occur not just in a place like marketing, but across the board. David Floyer, as folks go to the show and start to look more specifically about this notion of convergence, are there particular things that they should think about that, to come back to the notion of, well, you know, hardware is going to make things more or less difficult for what the software can do, and software is going to be created that will fill up the capabilities of hardware. What are some of the underlying hardware realities that folks going to the show need to keep in mind as they evaluate, especially the infrastructure side, these different infrastructure technologies that are getting more specialized? >> Well, if we look historically at the big data area, the solution has been to put in very low cost equipment as nodes, lots of different nodes, and move the data to those nodes so that you get a parallelization of the, of the data handling. That is not the only way of doing it. There are good ways now where you can, in fact, have a single version of that data in one place in very high speed storage, on flash storage, for example, and where you can allow very fast communication from all of the nodes directly to that data. And that makes things a lot simpler from an operational point of view. So using current Batch Automation techniques that are in existence, and looking at those from a new perspective, which is I do IUs apply these to big data, how do I automate these things, can make a huge difference in just the practicality in the elapsed time for some of these large training things, for example. >> Yeah, I was going to say that to many respects, what you're talking about is bringing things like training under a more traditional >> David: Operational, yeah. >> approach and operational set of disciplines. >> David: Yes, that's right. >> Very, very important. So John Furrier, I want to come back to you, or I want to come to you, and say that there are some other technologies that, while they're the bright shiny objects and people think that they're going to be the new kind of Harry Potter technologies of magic everywhere, Blockchain is certainly going to become folded into this big data concept, because Blockchain describes how contracts, ownership, authority ultimately get distributed. What should folks look for as the, as Blockchain starts to become part of these conversations? >> That's a good point, Peter. My summary of the preview for BigData SV Silicon Valley, which includes the Strata show, is two things: Blockchain points to the future and GDPR points to the present. GDPR is probably the most, one of the most fundamental impacts to the big data market in a long time. People have been working on it for a year. It is a nightmare. The technical underpinnings of what companies have to do to comply with GDPR is a moving train, and it's complete BS. There's no real solutions out there, so if I was going to tell everyone to think about that and what to look for: What is happening with GDPR, what's the impact of the databases, what's the impact of the architectures? Everyone is faking it 'til they make it. No one really has anything, in my opinion from what I can see, so it's a technical nightmare. Where was that database? So it's going to impact how you store the data, and the sovereignty issue is another issue. So the Blockchain then points to the sovereignty issue of the data, both in terms of the company, the country, and the user. These things are going to impact software development, application development, and, ultimately, cloud choice and the IoT. So to me, GDPR is not just a one and done thing and Blockchain is kind of a future thing to look at. So I would look out of those two lenses and say, Do you have a direction or a narrative that supports me today with what GDPR will impact throughout the organization. And then, what's going on with this new decentralized infrastructure and the role of data, and the sovereignty of that data, with respect to company, country, and user. So to me, that's the big issue. >> So George Gilbert, if we think about this question of these fundamental technologies that are going to become increasingly important here, database managers are not dead as a technology. We've seen a relative explosion over the last few years in at least invention, even if it hasn't been followed with, as Neil talked about, very practical ways of bringing new types of disciplines into a lot of enterprises. What's going to happen with the database world, and what should people be looking for in a couple of weeks to better understand how some of these data management technologies are going to converge and, or involve? >> It's a topic that will be of intense interest and relevance to IT professionals, because it's become the common foundation of all modern apps. But I think what we can do is we can see, for instance, a leading indicator of what's going to happen with the legacy vendors, where we have in-memory technologies from both transaction processing and analytics, and we have more advanced analytics embedded in the database engine, including Machine Learning, the model training, as well as model serving. But the, what happened in the big data community is that we disassembled the DBMS into the data manipulation language, which is an analytic language, like, could be Spark, could be Flink, even Hive. We had the Catalog, which I think Jim has talked about or will be talking about, where we're not looking, it's not just a dictionary of what's in one DBMS, but it's a whole way of tracking and governing data across many stores. And then there's the Storage Manager, could be the file system, an object store, could be just something like Kudu, which is a MPP way of, in parallel, performing a bunch of operations on data that's stored. The reason I bring all this up is, following on David's comment about the evolution of hardware, databases are fundamentally meant to expose capabilities in the hardware and to mediate access to data, using these hardware capabilities. And now that we have this, what's emerging as this unigrid, with memory-intensive architectures and super low latency to get from any point or node on that cluster to any other node, like with only a five microsecond lag, relative to previous architectures. We can now build databases that scale up with the same knowledge base that we built databases... I'm sorry, that scale out, that we used to build databases that scale up. In other words, it democratizes the ability to build databases of enormous scale, and that means that we can have analytics and the transactions working together at very low latency. >> Without binding them. Alright, so I think it's time for the action items. We got a lot to do, so guys, keep it really tight, really simple. David Floyer, let me start with you. Action item. >> So action item on big data should be focus on technologies that are going to reduce the elapse time of solutions in the data center, and those are many and many of them, but it's a production problem, it's becoming a production problem, treat it as a production problem, and put it in the fundamental procedures and technologies to succeed. >> And look for vendors >> Who can do that, yes. >> that do that. George Gilbert, action item. >> So I talked about convergence before. The converged platform now is shifting, it's center of gravity is shifting to continuous processing, where the data lake is a reference data repository that helps inform the creation of models, but then you run the models against the streaming continuous data for the freshest insights-- >> Okay, Jim Kobielus, action item. >> Yeah, focus on developer productivity in this new era of big data analytics. Specifically focus on the next generation of developers, who are data scientists, and specifically focus on automating most of what they do, so they can focus on solving problems and sifting through data. Put all the grunt work or training, and all that stuff, take and carry it by the infrastructure, the tooling. >> Peter: Neil Raden, action item. >> Well, one thing I learned this week is that everything we're talking about is about the analytical problem, which is how do you make better decisions and take action? But companies still run on transactions, and it seems like we're running on two different tracks and no one's talking about the transactions anymore. We're like the tail wagging the dog. >> Okay, John Furrier, action item. >> Action item is dig into GDPR. It is a really big issue. If you're not proactive, it could be a nightmare. It's going to have implications that are going to be far-reaching in the technical infrastructure, and it's the Sarbanes-Oxley, what they did for public companies, this is going to be a nightmare. And evaluate the impact of Blockchains. Two things. >> David Vellante, action item. >> So we often say that digital is data, and just because your industry hasn't been upended by digital transformations, don't think it's not coming. So it's maybe comfortable to sit back and say, Well, we're going to wait and see. Don't sit back and wait and see. All industries are susceptible to digital transformation. >> Alright, so I'll give the action item for the team. We've talked a lot about what to look for in the community gathering that's taking place next week in Silicon Valley around strata. Our observations as the community, it descends upon us, and what to look for is, number one, we're seeing a bifurcation in the marketplace, in the thought leadership, and in the tooling. One set of group, one group is going more after the infrastructure, where it's focused more on simplification, convergence; another group is going more after the developer, AI, ML, where it's focused more on how to create models, training those models, and building applications with the services associated with those models. Look for that. Don't, you know, be careful about vendors who say that they do it all. Be careful about vendors that say that they don't have to participate in a converged approach to doing this. The second thing I think we need to look for, very importantly, is that the role of data is evolving, and data is becoming an asset. And the tooling for driving velocity of data through systems and applications is going to become increasingly important, and the discipline that is necessary to ensure that the business can successfully do that with a high degree of predictability, bringing new production systems are also very important. A third area that we take a look at is that, ultimately, the impact of this notion of data as an asset is going to really come home to roost in 2018 through things like GDPR. As you scan the show, ask a simple question: Who here is going to help me get up to compliance and sustain compliance, as the understanding of privacy, ownership, etc. of data, in a big data context, starts to evolve, because there's going to be a lot of specialization over the next few years. And there's a final one that we might add: When you go to the show, do not just focus on your favorite brands. There's a lot of new technology out there, including things like Blockchain. They're going to have an enormous impact, ultimately, on how this marketplace unfolds. The kind of miasma that's occurred in big data is starting to specialize, it's starting to break down, and that's creating new niches and new opportunities for new sources of technology, while at the same time, reducing the focus that we currently have on things like Hadoop as a centerpiece. A lot of convergence is going to create a lot of new niches, and that's going to require new partnerships, new practices, new business models. Once again, guys, I want to thank you very much for joining me on Action Item today. This is Peter Burris from our beautiful Palo Alto theCUBE Studio. This has been Action Item. (lively electronic music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering VMworld 2017, brought to you by VMware and its ecosystem partners. (upbeat techno music) >> Welcome back to theCUBE's continuing coverage of VMworld 2017. Nearing the end of day two. Lots of topics going on, my goodness. I'm Lisa Martin with my co-host, Dave Vellante. And we're excited to have Ed Walsh, General Manager of IBM Storage, back on theCUBE. Welcome back. >> Thank you very much, it's nice to be back. >> Yeah, so two really strong quarters of IBM Storage revenue growth. >> Ed: Shh, don't let that get out. (laughs) It'd make my job too easy. But thank you for noticing. >> You didn't bring your crystal ball for the third quarter? >> But I do appreciate it. We do like to quietly just do it. But thank you. >> All right. So, what are some of the big trends? What's coming down the pike for you at IBM? >> I think if you look at, one the reason we're doing so well is, I think, the innovation we're driving the market now which will take you into the future. But also, just how we're approaching clients is kind of resonating. And it does play into future trends. And we can talk about especially on the show floor. But I think clients are just challenged right now with all the complexity innovation. We could talk about it until the nth degree or bring in dev ops environment. But it's the complexity of IT, and all the change they're dealing with. In fact, if anything, because all the competition like the Uber my Business coming into my industry and disrupting me. But we find all of our customers are on the heels a little bit in technology. Instead they need to kind of lean in. And so the trend that we're seeing is people trying to simultaneously modernize their traditional application environment, which is how do you free up your people and time through automation and agility so that you can move those people and resource and start transforming the business on higher value type of thing? So we see that consistently. So you see a lot of API type of automation tools. That just frees up the current team to do other things. You'll see that in our portfolio. One of our big themes is to modernize the traditional application environment. It's what we do on true private cloud, allow you to have all the capabilities of public cloud in a hybrid cloud environment. So, bring everything you do in the public cloud on prem. It's the same automation capabilities, same dev ops tools, and use it on prem. And then go to the cloud when you need to in hybrid cloud. That's all about automation, API temp automation, it's all about freeing up your team. So, what kills the team as far as the automation around dev ops or test dev? Also, things just like backup protection. So, how do you backup your environment? It can be just a complete manual task that really doesn't add a lot of value. Or if you use a new technology and innovate, you can actually use it to drive newer innovations, and drive new use case for that secondary storage. So, we see those trends happening. That's where I would say our clients kind of responding to the innovation we're bringing to market. And that's where you see us growing above market. >> Dave: You know I want to pick up on the growth and talk about you're clearly gaining share. The numbers were high single digits, right? >> Ed: Yeah, 7% in key one, 8% with growing margins. So, expanding margins. That's dramatically over market. And the market's growing at low to mid-single digits? >> 1%. >> Dave: Yeah, okay. Basically, flat. >> Ed: Yep. >> So, that's significant gains. But one could say, okay, if IBM has been losing share and sort of hitting off the bottom and now it's gaining share, we'll see if you can sustain that. But I'm more interested in the attributes of a leader in the storage business. I'm just listing them here. Certainly, you've got to be relevant. I want to come back to that. You got to have a complete portfolio. You got to have strong product cycles. You got to have a great go-to-market, strong leadership, and maybe a little bit of luck. I don't know. I'm probably missing some things there. Not a bad list. >> Ed: Yeah. So, relevance. I want to go back, I said to Eric when he was on, that interview that you did with Peter Burris at our studio. And you were talking about digital transformation and data and storage being an active element. It seemed like a very relevant conversation for the C-suite. >> Ed: Sure. >> And as Eric was pointing out, C-level executives don't like to talk about storage cause it's just a cost. >> Ed: Right, right. >> So, you've got the relevance piece going for you cause you're IBM. >> Ed: Sure. >> Talk about some of those other ones. Complete portfolio, end of product cycles have been very important in the past. And IBM hasn't had that as an advantage but it seems like you brought that to IBM and others. So, talk about that a little bit, that cadence. >> So I've talked about coming here 12 months ago, it was to really bring innovation and drive growth for division. I had the hypothesis, and we talked about this, so, I think clients are challenged. They're looking for a partner to help them out. And I think where IBM's unique, which gets to your question, one, we have the right vision. How do you talk cloud and cognitive? How do you leverage your data? Whatever metaphor you use to get more out of your data, leverage it for decisions, that's what we do both in hybrid cloud and public clouds. But we also help people through these multiple eras, and IBM's very unique. Very few of our competitors actually say they can go through multiple eras. IBM's been through every era in compute, and we calmly go through it. And clients give us credit for that. You mentioned the broad portfolio. When I first started here, people said, "You're portfolio's board." And I kind of say, if you really want to be meaningful, and help people modernize, get from where they are to where they need to get to, you need a broad portfolio to do exactly that. And IBM has the broadest portfolio in the industry for storage. And then, last but not least, which is innovation, I actually think my secret weapon is, not because I'm the storage company, but if I could ever get the rest of IBM, all the innovation, all the capabilities from Watson or analytics and cloud into my portfolio, all of a sudden now I kind of distanced myself from other storage. In fact, I would say it's a big boy or big girl environment where you need to actually, it's not about the next array, which I'll provide, it's actually how do you actually help people get from here to there. And a single product company just can't do that. Although, it's easier to market, it's the complexity. I think it is the innovation. In each segment we're in, we're either number one or number two in all the segments. So, number two in overall storage, number one in software, number one in software-defined, number two in data protection, number one in analytics. Each one of those is highly competitive and you need to drive innovation. And what we do is, we leverage not only our development expense or developers, but we have probably the only company in storage left that has primary research. So, we have our classic IBM research doing fundamental what's going to be next, and that's what we're bringing to market. >> So, what have you learned, second time around at IBM, what have you learned about your ability to leverage those other pieces of IBM? Cause every general manager talks about all the great things at IBM, but few have been able to bring that in. I remember when IBM bought Storwize, I was so frustrated. It was like two years before you took this secret weapon. You know, put it in! Do it! Ship it! And it took too long. What have you learned about how to leverage those innovations? >> So, I think the power of IBM is you do have, I've said a couple times, I'm honored to be the one they chose to help drive this transformation of storage. But also, I'm kind of blown away by the team. So, in very short order, we relaunched an entire new portfolio. We refreshed the entire portfolio, hardware and software, late last year. That's where you're seeing the growth. We're also launching new product that are really hitting this innovation. We're also, as you said how do we leverage research, is think about what we're just doing on flash. So, everyone's talking about NVMe. Well, because we're already doing primary research we already have NVMe capabilities. So NVMe is a way to do an IO, and you're cutting through the IO path. And your latencies go down in order of magnitude. So everything's faster. >> Dave: Eliminating all that over head of the scuzzy stack of just the simplify the-- >> So, we already have that in all our storage products. And also we've just did it in the mainframe. So, we have the ability to do mainframe storage. It does 12 microseconds access time. Which if you think about it that's NVMe performance. But that's exactly what we're bringing from research into our product line. You'll see more, so we'll bring in Watson. So the one thing my predecessors, how do you bring Watson in everything you do? Cognition or AI should be in your product's hardware/software on prem, in the cloud as a service. How about how you do services support? You call, chatbot should be able to help you out. Do an analytics on the different data patterns. So, that's exactly what we're doing. And all that's really from either research or from IBM Greater. I'll give you one just a tactical thing. People are trying to back up to the cloud. It's just hard. How do you get all that data through a little straw. Well, I can either re-architect Spectrum Protect, which we did a lot of re-architect. We just announced a big part here today. But instead, I just leveraged a product called Aspera. IBM had this company they acquired called Aspera that does a lot of, basically, file transfer to the cloud. By doing an API integration in 30 days, my Spectrum Protect clients now do 10 times faster back up to the cloud. That's a good example of just leveraging the Greater IBM. And it was just literally asset sitting there. But how do I bring it to bear for the benefits of my clients? >> So, how did that happen? That was really, if I recall, a cloud acquisition to be more competitive with AWS. And same thing with the Cleversafe acquisition, really fit into that portfolio, round out the Bluemix Cloud. How did you go about leveraging that? Was it just knocking on a colleague's door or was it as simple as picking up a phone call? Or did you have to get people in a headlock and give them a noogie? >> So, I think it's more collaborative than that. I think the the past there were maybe sharp elbows. But I think this is more collaborative. The cloud and the AI team inside IBM is wildly collaborative with me because I bring capabilities that I can bring to them as far as what we can do around storage. So, I think that collaboration's working. It's probably me more helping them out initially to make sure I'm building that bridge, but then it's reciprocated. It's very easy. And the key thing is also being able to understand all that capability from research, and actually try to bring it into offering management team. So getting my offering management team to be more open. to be outside-in. Outside-in from the industry but also from outside-in from the rest of IBM in. And if I leverage these pieces, all of a sudden my portfolio and all of my development expense just gets multiplied. It's a force multiplier that I'm bringing in. And that's where the clients are really responding to it. >> Dave: That's great. >> Lisa: Eric Kurzog >> talked about that, the outside-in, as did Steve. So, it sounds like quite a cultural shift has happened. shift probably isn't a strong enough word, within IBM. You talk about, and everyone has talked about, this message of clients want simplicity. So, as a GM how are you simplifying this cross-function collaboration? What are like the top three things you'd recommend to other GM's to bring the simplicity that clients want internal to be able to get to market faster and iterate. >> So one, you have to look for what's in the industry. The other thing is really listen to clients. The clients will talk about simplicity but then it's the nuances, so really the details of what they mean by that. We use NPS, Net Promoter Score. But we actually get feedback on every service call or inside our own offerings. So you actually get the feedback but more importantly you actually get detailed feedback of what they want to change. So one, you can listen to that. You bring the outside in. That's directly from the clients. We use the term feedback's a gift. Sometimes it's not... But we respond within 24 hours to each and every one of those customers, and that gets you into a nice circle of feedback. The other thing is bring in the right team. So, on my team of about 50% of them has changed. So I brought in basically professional storage team from the inside and outside of IBM so that we can actually have our own outside-in inside. And then really, you need to align your organization to be what the clients need to see. For instance I did a reorganization as far as how I did offering management and go to market that they were aligned. So, instead of being product line driven, what people are purchasing. So people are doing distributed storage. That should be one offering management line, one owner instead of maybe three or four. Cause I have three different, four product lines. And that allows you to simplify what happens in the market. So if you can align your organization to what you actually need to leverage that's pretty easy. >> Lisa: Fantastic. >> Dave: So, I got to ask you. >> So, you're a unique executive. I call you a five tool player. >> Okay. >> You've technical chops. >> A lot of people don't know that about you. I do. You can go toe to toe, which probably scares the crap out of a lot of guys that work for you. You've got financial acumen. >> Ed: Sure. >> You've got a really strong network. You're a visionary and you can inspire people both with that vision but you can also push them. >> Ed: Oh, thanks. >> Hard. >> You know, I've seen that. And that's kind of your reputation, and people have a great deal of respect. So, you've got that sort of perspective. I want to get your perspective on what's happening in the world of VMware, generally in data protection specifically. >> Ed: Okay, sure. >> You've had a lot of experience in that area. You were the CEO of Avamar. You sold that company. Spectrum Protect is a big focus of your business today. What's your sense as to what's happening here? Why is data protection exploding so much? I've been asking this question all week. And I'm still not sure I understand why. Maybe this is a cloud effect. But what's your take on it? >> So, you mentioned simplicity. It fits into the modernizing, how do you free up your people from all these manual tasks? I would say backup is one of those crazy manual tasks that's more of an insurance policy. And then recovery was always a very big challenge. So, what you're seeing is new technologies come out that not only solve all the manual processes. So, what we did in Spectrum Protect is really dramatically simplify what you do, you set up an SLA and it literally self-monitors and keeps track and literally backs up to SLA, and recoveries are instantaneous. That used to be hours of work, every single day by someone. And recoveries would take days or hours days. Could be a long time. And now you're easily be able to come up and running. But also now you have the secondary storage which is a cost. What else can I do with that which has always been the dream. Now what you have is scale architecture's maybe all flash. And what you're doing on prem in the cloud, you have an image copy of everything in your environment for recovery purposes, availability. What else would you do with it? One, you want to make it easy, so the ease thing. SLA management for recovery. So you can do instant availability for if there is an outage. But all of a sudden what else would you do with it? Now what you're able to do, with orchestration, you're able to take that secondary copy, it's instantaneously mountable or bootable copies. All of a sudden you can take a snapshot of that. You can do data masking of that. Now you have this gold copy you can use for test dev or dev ops. It could also be the way that you gather on premises and you get a data copy into the cloud. And backup is a very good way to keep a history of data on a day to day basis or a couple times a day. So now you actually have an index of how your environment is changing over time, that you can use for analytics for other things. So, what's really happening is, it's going from a cost center that used to be a manual headache to everyone. And you're taking the exact same requirement. You have to do that anyway. And know you're making an asset and also you're freeing up your team for doing it. So I think you're going to see a huge investment. In fact, I would say probably the number one area people are investing. But it's past dedupe. So Avamar was the last, well dedupe was the last thing that really changed backup recovery because it was just you can't be moving all that data. Just change the amount of data you're moving so you can do it faster easier. You know, check. But now it's more about the agility. In a secret way, your backup's now the best way to feed test dev. Or the best way to feed dev ops. It's the best way to feed a cloud, if done correctly. So that's what we now suspect in Protect Plus. Literally, just do a backup and we can give you all these other use cases by leveraging the same investment. If you're trying to modernize, and free up your team, and get more for what you already have to do, it's probably the biggest low hanging fruit for clients. >> Yeah, so I mean I think that's the answer. Backup has been historically been crappy insurance that's not cloud-like. The industry's demanding, the customers are demanding a change. >> And then also, how do you do dev ops and test dev, and use production data in a data mass format. You don't want to do that in your primary. You want to take a copy. Backup does that. And you want to use that data. So, it actually solves another area of agility for the same dollars. >> Wow, fantastic. Thank you so much for joining us and sharing your insight. And we'll look for those next quarter results. And hope that trend >> We'll be back. keeps going-- >> We like them. >> Outstanding. Well, for Ed Walsh and my co-host Dave Vellante, I'm Lisa Martin. You've been watching the CUBE's continuing coverage of day two from VMworld 2017. Stick around, we'll be right back with the show wrap. (upbeat techno music)