>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.

>>Hello everybody. I am Toshihiko Nishimura from Stanford. University is there to TTT out here, super aging, global OMIM global transportation group about infections, uh, or major point of concerns. In addition, this year, we have the COVID-19 pandemic. As you can see here, while the why the new COVID-19 patients are still increasing, meanwhile, case count per day in the United state, uh, beginning to decrease this pandemic has changed our daily life to digital transformation. Even today, the micro segmentation is being conducted online and doctor and the nurse care, uh, now increase to telemedicine. Likewise, the drug development process is in need of major change paradigm shift, especially in vaccine in drug development for COVID-19 is, should be safe, effective, and faster >>In the >>Anastasia department, which is the biggest department in school of medicine. We have Stanford, a love for drug device development, regulatory science. So cold. Say the DDT RDS chairman is Ron Paul and this love leaderships are long mysel and stable shaper. In the drug development. We have three major pains, one exceedingly long duration that just 20 years huge budget, very low success rate general overview in the drug development. There are Discoverly but clinical clinical stage, as you see here, Tang. Yes. In clinical stage where we sit, say, what are the programs in D D D R S in each stages or mix program? Single cell programs, big data machine learning, deep learning, AI mathematics, statistics programs, humanized animal, the program SNS program engineering program. And we have annual symposium. Today's the, my talk, I do like to explain limitation of my science significance of humanized. My science out of separate out a program. I focused on humanized program. I believe this program is potent game changer for drug development mouse. When we think of animal experiment, many people think of immediately mouse. We have more than 30 kinds of inbred while the type such as chief 57, black KK yarrow, barber C white and so on using QA QC defined. Why did the type mice 18 of them gave him only one intervention using mouse, genomics analyzed, computational genetics. And then we succeeded to pick up fish one single gene in a week. >>We have another category of gene manipulated, mice transgenic, no clout, no Kamal's group. So far registered 40,000 kind as over today. Pretty critical requirement. Wrong FDA PMDA negative three sites are based on arteries. Two kinds of animal models, showing safety efficacy, combination of two animals and motel our mouse and the swine mouse and non-human primate. And so on mouse. Oh, Barry popular. Why? Because mouse are small enough, easy to handle big database we had and cost effective. However, it calls that low success rate. Why >>It, this issue speculation, low success rate came from a gap between preclinical the POC and the POC couldn't stay. Father divided into phase one. Phase two has the city FDA unsolved to our question. Speculation in nature biology using 7,372 new submissions, they found a 68 significant cradle out crazy too, to study approved by the process. And in total 90 per cent Radia in the clinical stages. What we can surmise from this study, FDA confirmed is that the big discrepancy between POC and clinical POC in another ward, any amount of data well, Ms. Representative for human, this nature bio report impacted our work significantly. >>What is a solution for this discrepancy? FDA standards require the people data from two species. One species is usually mice, but if the reported 90% in a preclinical data, then huge discrepancy between pretty critical POC in clinical POC. Our interpretation is data from mice, sometime representative, actually mice, and the humor of different especially immune system and the diva mice liver enzyme are missing, which human Liba has. This is one huge issue to be taught to overcome this problem. We started humanized mice program. What kind of human animals? We created one humanized, immune mice. The other is human eyes, DBA, mice. What is the definition of a humanized mice? They should have human gene or human cells or human tissues or human organs. Well, let me share one preclinical stages. Example of a humanized mouse that is polio receptor mice. This problem led by who was my mentor? Polio virus. Well, polio virus vaccine usually required no human primate to test in 13 years, collaboration with the FDA w H O polio eradication program. Finally FDA well as w H O R Purdue due to the place no human primate test to transgenic PVL. This is three. Our principle led by loss around the botch >>To move before this humanized mouse program, we need two other bonds donut outside your science, as well as the CPN mouse science >>human hormone, like GM CSF, Whoah, GCSF producing or human cytokine. those producing emoji mice are required in the long run. Two maintain human cells in their body under generation here, South the generation here, Dr. already created more than 100 kinds based on Z. The 100 kinds of Noe mice, we succeeded to create the human immune mice led the blood. The cell quite about the cell platelets are beautifully constituted in an mice, human and rebar MAs also succeeded to create using deparent human base. We have AGN diva, humanized mouse, American African human nine-thirty by mice co-case kitchen, humanized mice. These are Hennessy humanized, the immune and rebar model. On the other hand, we created disease rebar human either must to one example, congenital Liba disease, our guidance Schindel on patient model. >>The other model, we have infectious DDS and Waddell council Modell and GVH Modell. And so on creature stage or phase can a human itemize apply. Our objective is any stage. Any phase would be to, to propose. We propose experiment, pose a compound, which showed a huge discrepancy between. If Y you show the huge discrepancy, if Y is lucrative analog and the potent anti hepatitis B candidate in that predict clinical stage, it didn't show any toxicity in mice got dark and no human primate. On the other hand, weighing into clinical stage and crazy to October 15, salvage, five of people died and other 10 the show to very severe condition. >>Is that the reason why Nicole traditional the mice model is that throughout this, another mice Modell did not predict this severe side outcome. Why Zack humanized mouse, the Debar Modell demonstrate itself? Yes. Within few days that chemistry data and the puzzle physiology data phase two and phase the city requires huge number of a human subject. For example, COVID-19 vaccine development by Pfizer, AstraZeneca Moderna today, they are sample size are Southeast thousand vaccine development for COVID-19. She Novak UConn in China books for the us Erica Jones on the Johnson in unite United Kingdom. Well, there are now no box us Osaka Osaka, university hundred Japan. They are already in phase two industry discovery and predict clinical and regulatory stage foster in-app. However, clinical stage is a studious role because that phases required hugely number or the human subject 9,000 to 30,000. Even my conclusion, a humanized mouse model shortens the duration of drug development humanize, and most Isabel, uh, can be increase the success rate of drug development. Thank you for Ron Paul and to Steven YALI pelt at Stanford and and his team and or other colleagues. Thank you for listening.

>>Hello, everyone. My name is John Jane Shake. I work from Iran. Tous Andi. I am here this afternoon very gratefully with Anders Vulcan, who is VP of technology strategy for cloud bees, a Miranda's partner and a well known company in the space that we're going to be discussing. Anders is also a well known entity in this space, which is continuous integration and continuous delivery. Um, you've seen already today some sessions that focus on specific implementations of continuous integration and delivery, um, particularly around security. And, uh, we think this is a critically important topic for anyone in the cloud space, particularly in this increasingly complicated kubernetes space. To understand, um, Miranda's thanks, Uh, if I can recapitulate our own our own strategy and, uh, and language that with complexity on uncertainty consistently increasing with the depth of the technology stacks that we have to deal with consistently, um um elaborating themselves that navigating this requires, um first three implementation of automation to increase speed, which is what C and C d do. Um, and that this speed ba leveraged toe let us ship and iterate code faster. Since that's ultimately the business that all of us air in one way or another. I would like, I guess, toe open this conversation by asking Onders what does he think of that core strategy? >>You know, I think you know, hitting the security thing, right? Right off the bat. You know, security doesn't happen by accident. You know, security is not something that you know, Like a like a server in a restaurant. You know, Sprinkles a little bit of Parmesan cheese right before they serve you the the food. It's not something you Sprinkle on at the end. It's something that has to be baked in from the beginning, not just in the kitchen, but in the supply chain from from from the very beginning. So the you know it's a feature, and if you don't build it, if you're not going to get an outcome that you're not gonna be happy with and I think the you know it's increasingly it's obviously increasingly important and increasingly visible. You know, the you know, the kinds of security problems that we that we see these days can can be, you know, life altering, for for people that are subject to them and and can be, you know, life or death for a company that that's exposed to it. So it's it's it's very, very important. Thio pay attention to it and to work to achieve that as an explicit outcome of the software delivery process. And I think, you know, C i n c d as as process as tooling as culture plays a big part in that because ah, lot of it has to do with, you know, set things up, right? Um run them the same way over and over, you know, get the machine going. Turned the crane. Now, you wanna you wanna make improvements over over time. You know, it's not just, you know, set it and forget it. You know, we got that set up. We don't have to worry about it anymore, but it really is a question of, you know, get the human out of the loop a lot of the times because if if you're dealing with configuring complex systems, you wanna make sure that you get them set up configured, you know, documented Ideally, you know, as code, whether it's a domain specific language or or something like that. And then that's something that you contest against that you can verify against that you can that you can difficult. And then that becomes the basis for for your, you know, for yourself, for pipelines, for your automation around, you know, kind of the software factory floor. So I think automation is a key aspect of that because it, you know, it takes a lot of the drudgery out of it, for one thing, So now the humans have more time to spend on doing on the on the creative things on the things that we're good at a zoo. Humans and it also make sure that, you know, one of the things that computers are really good at is doing the same thing over and over and over and over. Eso that kind of puts that responsibility into the hands of the entity that that knows how to do that well, which is which is the machine eso I think it's, you know, it's a light. It's a deep, deep topic, obviously, but, you know, automation plays into it. Uh, you know, small batch sizes play into it, you know, being able to test very frequently whether that's testing in. You're kind of you're C I pipeline where you're sort of doing building mostly unit testing, maybe some integration testing, but also in layering in the mawr. Serious kinds of testing in terms of security scanning, penetration, testing, vulnerability, scanning. You know those sorts of things which, you know, maybe you do on every single see I Bill. But most people don't because those things tend toe take a little bit longer on. And you know you want your sea ice cycle to be as fast as possible because that's really in service of the developer who has committed code and wants toe kind of see the thumbs up from the system saying it. And, um, so most organizations most organizations are are are focusing on, you know, making sure that there's a follow on pipeline to follow on set of tests that happened after the C I passes successfully and and that's, you know, where a lot of the security scanning and those sorts of things happen. >>It's a It's an interesting problem. I mean, you mentioned, um, what almost sounds like a Lawrence Lessig Ian kind of idea that, you know, code is law in enterprises today, code particularly see, I code ends up being policy, but At the same time, there's, Ah, it seems to me there's a an alternative peril, which is, as you increase speed, particularly when you become more and more dependent on things like containers and layering technology to provide components and capabilities that you don't have to build yourself to your build pipeline, that there are new vulnerabilities, potentially that creep in and can creep in despite automation. Zor at least 1st. 1st order automation is attempts toe to prevent them from creeping in. You don't wanna you wanna freeze people on a six month old version of a key container image. But on the other hand, if the latest version has vulnerabilities, that could be a problem. >>Yeah, I mean, it's, you know, it's it's a it's a it's a double edged sword. It's two sides of the same coin. I think you know, when I talked to a lot of security people, um, you know, people to do it for a living is supposed to mean I just talk about it, um, that Z not completely true. But, um, the ah, lot of times the problem is old vulnerabilities. The thing that I think keeps a lot of people up at night isn't necessarily that the thing at the tip of the releases for particular, you know, well known open source, library or something like that. But that's gonna burn you all the vast majority of the time. And I want to say, like, 80 85% of the time. The vulnerability is that you that you get hosed by are ones that have been known about for years. And so I think the if I had to pick. So if you know, in that sort of two sides of that coin, if I had to pick, I would say Be aggressive in making sure that your third party dependencies are updated frequently and and continuously right, because that is the biggest, biggest cause of of of security vulnerabilities when it comes to third party code. Um, now you know the famous saying, You know, move fast and break things Well, there's certain things you don't want to break. You know you don't want to break a radiation machine that's going to deliver radio radiotherapy to someone because that will endanger their health. So So those sorts of systems, you know, naturally or subject a little bit more kind of caution and scrutiny and rigor and process those sorts of things. The micro service that I run that shows my little avatar when I log in, that one probably gets a little less group. You know, Andre rightfully so. So I think a lot of it has to do. And somebody once said in a I think it was, Ah, panel. I was on a PR say conference, which was, which was kind of a wise thing to say it was Don't spend a million dollars protecting a $5 assets. You know, you wanna be smart and you wanna you wanna figure out where your vulnerabilities they're going to come from and in my experience, and and you know, what I hear from a lot of the security professionals is pay attention to your supply chain. You're you want to make sure that you're up to date with the latest patches of, of all of your third party, you know, open source or close source. It doesn't really matter. I mean, if anything, you know, open source is is more open. Eso You could inspect things a little bit better than the close source, but with both kinds of streams of code that you consume and and use. You wanna make sure that you're you're more up to date as opposed to a less up to date? Um, that generally will be better. Now, can a new version of the library cause problems? You know, introduce bugs? You know, those sorts of things? Yes. That's why we have tests. That's what we have automated tests, regression, sweets, You know, those sorts of things. And so you wanna, you know, you wanna live in a in a world where you feel the confidence as a as a developer, that if I update this library from, you know, one debt owed at 3 to 1 debt owed at 10 to pick up a bunch of, you know, bug fixes and patches and those sorts of things. But that's not going to break some on demand in the test suites that that will run against that ought to cover that that sort of functionality. And I'd rather be in that world of Oh, yeah, we tried to update to that, but it But it broke the tests and then have to go spend time on that, then say, Oh, it broke the test. So let's not update. And then six months later, you do find out. Oh, geez. There was a problem in one that owed at three. And it was fixed in one. That about four. If only we had updated. Um, you know, you look at the, um you look at some of the highest profile security breaches that are out there that you sort of can trace toe third party libraries. It's almost always gonna be that it was out of date and hadn't been patched. That's so that's my you know, opinionated. Take on that. Sure. >>What are the parts of modern C I c D. As opposed to what one would encounter 56 years ago? Maybe if we can imagine that is being before the micro services and containers revolution really took off. >>You know, I think e think you're absolutely right that, you know, not the whole world is not doing. See, I Yeah, and certainly the whole world is not doing city yet. Um, you know, I think you know, as you say, we kind of live in a little bit of an ivory tower. You know, we live in an echo chamber in a little bit of a bubble Aziz vendors in this space. The truth is that I would say less than 50% of the software organizations out there do real. See, I do real CD. The number's probably less than that. Um, you know, I don't have anything to back that up other than just I talked to a lot of folks and work with, you know, with a lot of organizations and like, Yeah, that team does see I that team does Weekly builds You know, those sorts of things. It's it's really all over the place, Onda. Lot of times there's There's definitely, in my experience, a high correlation there with the amount of time that a team or a code base has been around, and the amount of sort of modern technologies and processes and and and so on that are that are brought to it on. And that sort of makes sense. I mean, if you if you're starting with the green field with a blank sheet of paper, you're gonna adopt, you know, the technologies and the processes and the cultures of today. A knot of 5, 10 15 15 years ago, Um but but most organizations air moving in that direction. Right? Andi, I think you know what? What? What? What's really changed in the last few years is the level of integration between the various tools between the various pieces and the amount of automation that you could bring to bear. I mean, I you know, I remember, you know, five or 10 years ago having all kinds of conversations with customers and prospects and and people of conferences and so on and they said, Oh, yeah, we'd like to automate our our software development life cycle, but, you know, we can't We have a manual thing here. We have a manual thing there. We do this kind of testing that we can automate it, and then we have this system, but it doesn't have any guy. So somebody has to sit and click on the screen. And, you know, and I used to say e used to say I don't accept No for an answer of can you automate this right? Everything. Anything can be automated. Even if you just get the little drinking bird. You know that just pokes the mouse. Everyone something. You can automate it, and I Actually, you know, I had one customer who was like, Okay, and we had a discussion and and and and they said, Well, we had this old Windows tool. We Its's an obscure tool. It's no longer updated, but it's it's it's used in a critical part of the life cycle and it can't be automated. And I said, Well, just install one of those Windows tools that allows you to peek and poke at the, you know, mass with my aunt I said so I don't accept your answer. And I said, Well, unfortunately, security won't allow us to install those tools, Eh? So I had to accept No, at that point, but But I think the big change were one of the biggest changes that's happened in the last few years is the systems now have all I'll have a p i s and they all talk to each other. So if you've gotta, you know, if you if you've got a scanning tool, if you've got a deployment tool, if you have a deployment, you know, infrastructure, you know, kubernetes based or, you know, kind of sitting in front of our around kubernetes thes things. I'll talk to each other and are all automated. So one of the things that's happened is we've taken out a lot of the weight states. A lot of the pauses, right? So if you you know, if you do something like a value stream mapping where you sit down and I'll date myself here and probably lose some of the audience with this analogy. But if you remember Schoolhouse Rock cartoons in in the late seventies, early eighties, there was one which was one of my favorites, and and the guy who did the music for this passed away last year, sadly, But, uh, the it was called How a bill Becomes a Law and they personified the bill. So the bill, you know, becomes a little person and, you know, first time passed by the house and then the Senate, and then the president either signs me or doesn't and or he vetoes, and it really sort of did this and what I always talk about with respect to sort of value stream mapping and talking about your processes, put a GoPro camera on your source codes head, and then follow that source code all the way through to your customer understand all of the stuff that happens to it, including nothing, right? Because a lot of times in that elapsed time, nothing keeps happening, right. If we build software the way we were sorry. If we build cars the way we build software, we would install the radio in a car, and then we would park it in a corner of the factory for three weeks. And then we might remember to test the radio before we ship the car out to the customer. Right, Because that's how a lot of us still develop some for. And I think one thing that's changed in the in the last few years is that we don't have these kind of, Well, we did the bill. So now we're waiting for somebody to create an environment and rack up some hardware and install an operating system and install. You know, this that and the other. You know, that that went from manual to we use Scheffer puppet to do it, which then went to we use containers to do it, which then went to we use containers and kubernetes to do it. So whole swaths of elapsed time in our software development life cycles basically went to nothing, right and went to the point where we can weaken, weaken, configure them way to the left and and and follow them all the way through. And that the artifact that we're delivering isn't necessarily and execute herbal. It could be a container, right? So now that starts to get interesting for us in terms of being able to test against that container scan against that container, def. Against that container, Um, you know, and it, you know, it does bring complexity to in terms of now you've got a layered file system in there. Well, what all is in there, you know, And so there's tools for scanning those kinds of things, But But I think that one of the biggest things that's happened is a lot of the natural pause. Points are no longer natural. Pause points their unnatural pause points, and they're now just delays in yourself for delivery. And so what? What a lot of organizations are working on is kind of getting to the point where those sorts of things get get automated and connected, and that's now possible. And it wasn't 55 or 10 years ago. >>So It sounds like a great deal of the speed benefit, which has been quantified many different ways. But is once you get one of these systems working, as we've all experienced enormous, um, is actually done by collapsing out what would have been unused time in a prior process or non paralyze herbal stuff has been made parallel. >>I remember doing a, uh, spent some time with a customer, and they did a value stream mapping, and they they found out at the end that of the 30 days of elapsed time they were spending three days on task. Everything else was waiting, waiting for a build waiting foran install, waiting for an environment, waiting for an approval, having meetings, you know, those sorts of things. And I thought to myself, Oh, my goodness, you know, 90% of the elapsed time is doing nothing. And I was talking to someone Gene Kim, actually, and I said, Oh my God, it was terrible that these you know, these people are screwed and he says, 0 90%. That's actually pretty good, you know? So So I think you know, if you if you think today, you know, if you If you if you look at the teams that are doing just really pure continuous delivery, you know, write some code committed, gets picked up by the sea ice system and passes through CIA goes through whatever coast, see I processing, you need to do security scanning and so on. It gets staged and it gets pushed into production. That stuff can happen in minutes, right? That's new. That's different. Now, if you do that without having the right automated gates in place around security and and and and those sorts of things you know, then you're living a little bit dangerously, although I would argue not necessarily any more dangerously, than just letting that insecure coat sit around for a week before your shipment, right? It's not like that problem is going to fix itself if you just let it sit there, Um, but But, you know, you definitely operated at a higher velocity. Now that's a lot of the benefit that you're tryingto trying to get out of it, right? You can get stuff out to the market faster, or if you take a little bit more time, you get more out to the market in, in in the same amount of time you could turn around and fix problems faster. Um, if you have a vulnerability, you can get it fixed and pushed out much more quickly. If you have a competitive threat that you need to address, you can you know, you could move that that much faster if you have a critical bug. You know, I mean, all security issues or bugs, sort of by definition. But, you know, if you have a functionality bug, you can you can get that pushed out faster. Eso So I think kind of all factors of the business benefit from from this increase in speed. And I think developers due to because anybody you know, any human that has a context switch and step away from something for for for, you know, duration of time longer than a few minutes, you know, you're gonna you're gonna you're gonna you're gonna have to load back up again. And so that's productivity loss. Now, that's a soft cost. But man, is it Is it expensive and is a painful So you see a lot of benefit there. Think >>if you have, you know, an organization that is just starting this journey What would you ask that organization to consider in orderto sort of move them down this path? >>It's by far the most frequent and almost always the first question I get at the end of the talk or or a presentation or something like that is where do we start? How do I know where to start? And and And there's a couple of answers to that. What one is Don't boil the ocean, right? Don't try to fix everything all at once. You know that because that's not agile, right? The be agile about your transformation Here, you know, pick, pick a set of problems that you have and and make a, you know, basically make a burn down list and and do them in order. So find find a pain point that you have right and, you know, just go address that and and try to make it small and actionable and especially early on when you're trying to affect change. And you're tryingto convinced teams that this is the way to go and you may have some naysayers, or you may have people who are skeptical or have been through these processes before that have been you know failures released, not the successes that they that they were supposed to be. You know, it's important to have some wind. So what I always say is look, you know, if you have a pebble in your shoe, you've got a pain point. You know how to address that. You know, you're not gonna address that by changing out your wardrobe or or by buying a new pair of shoes. You know, you're gonna address that by taking your shoe off, shaking it until the pebble falls out there putting the shoe back on. So look for those kinds of use cases, right? So if you're engineers are complaining that whenever I check in the build is broken and we're not doing see, I well, then let's look at doing C I Let's do see eye, right? If you're not doing that. And for most organizations, you know, setting up C I is a very manageable, very doable thing. There's lots of open source tooling out there. There's lots of commercial tooling out there. Thio do that to do it for small teams to do it for large teams and and everything in between. Um, if the problem is Gosh, Every time we push a change, we break something. You know where every time something works in staging it doesn't work in production. Then you gotta look at Well, how are these systems being configured? If you're If you're configuring them manually, stop automate the configuration of them. Um, you know, if you're if you're fixing system manually, don't you know, as a friend of mine says, don't fix, Repave? Um, you know, you don't wanna, you know, there's a story of, you know how how Google operates in their data centers. You know, they don't they don't go look for a broken disk drive and swap it out. You know, when it breaks, they just have a team of people that, like once a month or something, I don't know what the interval is. They just walked through the data center and they pull out all the dead stuff and they throw it out, and what they did was they assume that if the scale that they operate, things are always going to break physical things are always going to break. You have to build a software to assume that breakage and any system that assumes that we're going to step in when a disk drive is broken and fix it so that we can get back to running just isn't gonna work at scale. There's a similarity. There's sort of ah, parallel to that in in software, which is you know, any time you have these kinds of complex systems, you have to assume that they're gonna break and you have to put the things in place to catch those things. The automated testing, whether it's, you know, whether you have 10,000 tests that you that you've written already or whether you have no tests and you just need to go right, your first test that that journey, you've got to start somewhere. But my answer thio their questions generally always just start small, pick a very specific problem. Build a plan around it, you know, build a burned down list of things that you wanna address and just start working your way down that the same way that you would for any, you know, kind of agile project, your transformation of your own processes of your own internal systems. You should use agile processes for those as well, because if you if you go off for six months and and build something. By the time you come back, it's gonna be relevant. Probably thio the problems that you were facing six months ago. >>A Then let's consider the situation of, ah, company that's using C I and maybe sea ice and C d together. Um, and they want to reach what you might call the next level. Um, they've seen obvious benefits they're interested in, you know, in increasing their investment in, you know and cycles devoted to this technology. You don't have to sell them anymore, but they're looking for a next direction. What would you say that direction should be? I >>think oftentimes what organizations start to do is they start to look at feedback loops. So on DAT starts to go into the area of sort of metrics and analytics and those sorts of things. You know what we're we're always concerned about? You know, we're always affected by things like meantime to recovery. Meantime, the detection, what are our cycle times from, you know, ideation, toe codecommit. What's the cycle? Time from codecommit the production, those sorts of things. And you know you can't change what you don't measure eso so a lot of times the next step after kind of getting the rudimentary zoo of C I Orsini or some combination of both in places start to measure. Stop you, Um, and and then but But there. I think you know, you gotta be smart about it, because what you don't want to do is kind of just pull all the metrics out that exists. Barf them up on the dashboard. And the giant television screens say boom metrics, right. You know, Mike, drop go home. That's the wrong way to do it. You want to use metrics very specifically to achieve outcomes. So if you have an outcome that you want to achieve and you can tie it to a metric start looking at that metric and start working that problem once you saw that problem, you can take that metric. And you know, if that's the metric you're showing on the big you know, the big screen TV, you can pop that off and pick the next one and put it up there. I I always worry when you know a little different when you're in a knock or something like that. When when you're looking at the network stuff and so on. But I'm always leery of when I walk into to a software development organization. You know, just a Brazilian different metrics, this whole place because they're not all relevant. They're not all relevant at the same time. Some of them you wanna look at often, some of them you just want to kind of set an alarm on and make sure that, you know, I mean, you don't go down in your basement every day to check that the sump pump is working. What you do is you put a little water detector in there and you have an alarm go off if the water level ever rises above a certain amount. Well, you want to do the same thing with metrics, right? Once you've got in the water out of your basement, you don't have to go down there and look at it all the time. You put the little detector in, and then you move on and you worry about something else. And so organizations as they start to get a little bit more sophisticated and start to look at the analytics, the metrics, um, start to say, Hey, look, if our if our cycle time from from, you know, commit to deploy is this much. And we want it to be this much. What happens during that time, And where can we take slices out of that? You know, without without affecting the outcomes in terms of quality and so on, or or if it's, you know, from from ideation, toe codecommit. You know what? What can we do there? Um, you start to do that. And and then as you get those sort of virtuous cycles of feedback loops happening, you know, you get better and better and better, but you wanna be careful with metrics, you know, you don't wanna, you know, like I said, you don't wanna barf a bunch of metrics up just to say, Look, we got metrics. Metrics are there to serve a particular outcome. And once you've achieved that outcome, and you know that you can continue to achieve that outcome, you turn it into an alarm or a trigger, and you put it out of sight. And you know that. You know, you don't need to have, like, a code coverage metric prominently displayed you you pick a code coverage number that you're happy with you work to achieve that. Once you achieve it, you just worry about not going below that threshold again. So you can take that graph off and just put a trigger on this as if we ever get below this, you know, raising alarm or fail a build or fail a pipeline or something like that and then start to focus on improving another man. Uh, or another outcome using another matter >>makes enormous sense. So I'm afraid we are getting to be out of time. I want to thank you very much on this for joining us today. This has been certainly informative for me, and I hope for the audience, um, you know, thank you very, very much for sharing your insulin.

>> Narrator: From around the globe, It's theCube, with digital coverage, of Actifio data-driven 2020, brought to you by Actifio. >> Welcome back, I'm Stu Miniman, and this is theCube coverage of Actifio Data-driven 2020. Really excited to, dig into a fun topic. I have a Cube alumni with us he is a DevOps author, and researcher Gene Kim. Unicorn Project is the most recent, Gene, great to see you, thanks so much for joining us. >> Stu, great to see you again, here at the Actifio conference, this is all fantastic. >> Yeah, so your new book, it was much awaited out there, you know, Unicorn's always discussed out there, but you know, the Phoenix Project, as I said, is really this seminal, book when people say, What is that DevOps thing and how do I do it? So, why don't you give us a little bit as to The Unicorn Project, why is it important? Why we're excited to dig into this and, we'll, we'll tie it into the discussion we're having here for the next normal, at Actifio. >> For sure, yeah, in fact, yeah. As you might have heard in the keynote address, you know, the what, what vexed me, after the Phoenix project came out in 2013 is that there is still looming problems that still remain, seven years after the Phoenix project was written. And, you know, these problems I think are very important, around you and what does it really take to enable developers to truly be productive, instead of being locked in a tundra of technical debt. Two is, you know, how do we unlock truly the power of data so that we can help everyone make better decisions, whether it's a developer, or anyone, within the business units and the organizations that we serve. And then three is like, what are really the behaviors that we need from leadership to make these amazing transformations possible? And so The Unicorn Project really is, the fifth project retold, but instead of through the eyes of Ops leadership, is told through the eyes, of a phenomenal developer. And so it was amazing to revisit the, the Phoenix project universe, I in the same timeline, but told from a different point of view. And it was such a fun project to work on, just because, you know, to relive the story, and just expose all these other problems, not happening, not on the side, but from, the development and data side. >> Yeah. They've always these characters in there that, I know I personally, and many people I talked to can, you know, really associate with, there was a return of certain characters, quite prominent, like Brent, you know, don't be the bottleneck in your system. It's great, if you're a fighter firefighter, and can solve everything, but if everything has to come through you, you know, Pedro is always going off, he's getting no sleep and, you know, you'd just get stressed out. You talked a bit more, about the organization and there are the five ideals in the book. So maybe if you can, you know, strongly recommend, of course, anybody at ending active you, got a copy of the books they'll be able to read the whole thing, but, you know, give us the bumper sticker on some of those key learnings. >> Yeah, for sure, yeah. So the five ideals represents five ideas, I think are just very important, for everyone, the organization, serves, especially leadership. The first ideal is locality and simplicity. In other words, when you need to get something done, we should be able to get it done within our team, without having to do a lot of communication coordination, with people outside of our team. The worst, the most horrible feeling is that in order, to do a small little thing, you actually have, to have a, coordinated action that spans 15 teams, right. And that's why you can't get anything done, right? And so that's so much the hallmark of large complex organizations. The second ideal is that what I think the outcomes are, which is focused flow and joy, you know, I've not just now started to for the first time in 20 years, self identify, not as an ops person, but as a developer. And, I really now understand, why we got into technology in the first place. This so that we can solve the business problem at hand unencumbered by minute share. And that allows for a sense of focus flow and even joy. And I love how Dr. Mihaly Csikszentmihalyi, describe it. He said, flow is a state that we feel when we love our work, so much that we lose track of time, and maybe even sense of self. And so I think we all in technology understand, you know, that that is how it is on the best of days and how terrible it is, you know, when we don't have that sense of flow. Third ideal is improvement of daily work, being even more important than daily work itself. The notion is greatness is never free, we must create it and must prioritize it, for the psychological safety. And the fifth is customer focus. So those are all the things I think are so important, for modern leaders, because it really defines the future of work. >> Yeah, we love that flow and it happens otherwise we're stuck, in that waiting place as you quoted Dr. Csi. So one of my favorite books there, there also. So Gene, for this audience here, there was, you know, yes, CICD is wonderful and I need to be able to move and ship fast, but the real transformational power, for that organization was unlocking the value of data, which is, I think something that everybody here can. So maybe to talk a little bit about that you know, we, there there's, we've almost talked too much, you know, data is the new oil and things like that, but it's that, you know, that allowing everybody to tap in and leverage, you know, real time what's happening there were just at the early parts of the industry being able to unlock that future. >> Oh yeah, I love that phrase. Data is new oil, especially since oil, you know, the last 50 years, the standard Port 500 was dominated by, you know, resource extraction oil company and so forth. And now that is no longer true, it's dominated by the tech giants. And, Columbia there was a Columbia journalism review article that said, data's not only the new oil, is really the new soil. And for me, you know, my area of passion for the last seven years has been studying the DevOps enterprise community where, we're taking all the learnings that were really pioneered by the tech giants, Facebook, Amazon, Netflix, Google, Microsoft, and seeing how they're being adopted by the largest, most complex organizations on the planet, the best known brands across every industry vertical. And it's so true that, you know, where the real learning gets exploited right, is through data. I realized, this is how we get to know our customers better. This is how we understand their wants and needs. This is how we test, and make offers to them to see if they like it or not to see if they value it or not. And, and so for me, one of the best examples, of this was, the target transformation and Adidas how it was just an amazing example of, to what links they went to, to liberate developers from, being shackled by ancient systems of records, data warehouses, and truly enabled developers to get access to the data they need modify it, even delete information, all without having to be dependent on, you know, integration teams that were essentially holding them hostage for six to nine months. And, these programs really enable some of the most strategic programs at their organizations, you know, enabling hundreds of projects over the years. So, I think that is really, just showing to what extent, the value that is created by unlocking data for individuals. And sorry Stu, one more thing that I'm just always dazzled by my friend, Chris Berg. He told me that, somewhere between a third and a half of all company employees use data in their daily work. They either use data or manipulate data as part of the daily work, which, you know, that, population is actually larger than the number of developers in an organization. So it just shows you how big this problem is, and how much value we can create by addressing this problem. >> Well, it's interesting if it's only a third, we still have work to do. What we've been saying for years is, you know, when you talk about digital transformation, the thing that separates those that have transformed and those that haven't is data needs to be at the core. I just can't be doing things the way I was or doing things off intuition, you know, being data-driven, I'm sure you know, the same Gene, if you're not, if you don't have data, you know, you're just some other person with an opinion. >> Yeah, yeah. That's it this is a great point. And in Risto Siilasmaa's amazing book, Transforming Nokia, I mean, he was, he said exactly that. And he said something that was even more astonishing. He said, there's not only at the core, but data also has to be at the edges. You know, he was describing at Amazon, anyone can do an experiment @booking.com. Anyone can do an experiment to see, if they can create value for the customer. They don't need approvals from, committees or their manager. This is something that is really truly part of everyone's daily work. And so, to me, that was a huge aha moment that says, you know, to what degree, you know. Our cultures need to change so that we can not only, use data, but also create learnings and create new data, you know, that the rest of the organization can learn from as well. >> Yeah. One of the other things I definitely, you know, felt in your book, you synthesize so much of the learnings that you've had over the years from like the DevOps enterprise summit. The question I have for you is, you know, you hear some of these, you know, great stories, but the question is, our companies, are they moving fast enough? Have they transformed the entire business or have they taken, you know, we've got one slice of the business that is kind of modernized and we're going to get to the other 30 pieces along the way, but you know, there's wholesale change, you know, 2020 has had such a big impact. What's your thoughts on, you know, how we are doing in the enterprise on pace of change these days? >> That's a great question. I mean, I think some people, when they ask me, you know, how far are we into kind of total adoption of DevOps? It's a newer better way of working. And I would say probably somewhere between 5 and 7%, right, and the math I would take them through is, you know, there are about 20 million developers on the planet of which at best, I think, a million of them are working in a DevOps type way. But yet now that's only growing. I think it was an amazing presentation at DevOps surprise summit in London that was virtual from nationwide building society, the largest organization of its kind. It's a large financially mutually owned organization for housing in the UK. And, they touched about how, you know, post COVID post lockdown suddenly they found themselves able to do them reckless things that would have normally taken four years, in four weeks. And I think that's what almost every organization is learning these days is, when survival is at stake, you know, we can throw the rules out of the window, right. And do things in a way that are safe and responsible, but, you know, create satisfy the business urgent needs, like, you know, provisioning tens of thousand people to work from home safely. You know, I think the shows, I think it's such a powerful proof point of what technology can do when it is unleashed from, you know, perhaps unnecessarily burdensome rules and process. And I think the other point I would make Stu is that, what has been so rewarding is the population of these technology leaders presenting at DevOps enterprise, they're all being promoted, they're all being, being given new responsibilities because they, are demonstrating that they have the best longterm interest of the organization at heart. And, they're being given even more responsibilities because, to make a bigger impact through the organization. So I'm incredibly optimistic about the direction we're heading and even the pace we're going at. >> Well, Gene definitely 2020 has put a real highlight on how fast things have changed, not just work from home, but, but the homeschooling, you know, telehealth, there are so many things out there where there was no choice, but to move forward. So the, the second presentation you participated in was talking about that next normal. So give us a little bit of, you know, what does that mean? You know, what, what we should be looking at going forward? >> Yeah, it was great to catch up with my friend Paul Forte, who I've known for many, many years, and now, now a VP of sales at the Actifio and yeah, I think it is amazing that academic Dr. Colada Perez, she said, you know, in every turning point, you know, where, there's such a the stage for decades of economic prosperity usually comes, by something exactly like what we're going through now, a huge economic recession or depression, following a period of intense re regulations there's new, technology that's unlocking, you know, new ways of working. And she pointed exactly to what's happening in the Covid pandemic in terms of, how much, the way we're working is being revolutionized, not by choice, but out of necessity. And, you know, as she said, you know, we're now learning to what degree we can actually do our daily work without getting on airplanes or, you know, meeting people in person. So, I'm a hue, I have so many friends in the travel industry, right. I think we all want normalcy to return, but I think we are learning, you know, potentially, you know, there are more efficient ways to do things, that don't require a day of travel for a couple hour meeting and day to return, right. So, yeah, I think this is being demonstrated. I think this will unlock a whole bunch of ways of interacting that will create efficiency. So I don't think we're going, as you suggested, right. There will be a new normal, but the new normal is not going to be the same as your old normal. And I think it will be, in general for the better. >> So, Gene, you, you've gone to gotten to see some of the transformation happening in the organizations when it comes to developers, you know, the, the DevOps enterprise summit, the, the state of DevOps, you know. I think five years ago, we knew how important developers were, but there was such a gap between, well, the developers are kind of in the corner, they don't pay for anything. They're not tied to the enterprise. And today it feels like we have a more cohesive story that there, there is that if you put in The Unicorn Project, it's, you know, business and IT, you know. IT, and the developers can actually drive that change and the survival of the business. So, you know, are we there yet success or net developers now have a seat at the table? Or, you know, what do you see on that, that we still need to do? >> Yeah, I think we're still, I mean, I think we're getting there, we're closer than ever. And as my friend, Chris O'Malley the CEO of the famously resurgent mainframe vendor Compuware said, you know, it is, everyone is aware that you can't do any major initiatives these days without some investment in technology, right? In fact, you can't invest in anything without technology. So I think that is now better understood than ever. And, yeah, just the digital, it's a whole digital disruption, I think is really, no one needs to be convinced that if we organize large complex organizations, don't change, they're at a risk of, you know, being decimated by the organizations that can change using an exploiting technology, you know, to their benefit and to the other person's detriment. So, and that primarily comes through software and who creates software developers. So I, by the way, I love the Stripe it was a CFO for Stripe who said, the largest, constraint for them is, and their peers is not access to capital, it is access development talent. I think when you have CFOs talking like that, right. It does says it's suggested something really has changed in the economic environment that we all compete in. >> So, I mentioned that on the research side, one of the things I've loved reading over the years is that, fundamental discussion that, going faster does not mean, that I am sacrificing security, or, you know, the product itself, you know, in the last couple of years, it's, you know, what separates those really high performing companies, and, you know, just kind of the middle of the ground. So, what, what, what advice would you give out there, to make sure that I'm moving my company more along to those high performing methods. >> Yeah, but just to resonate with that, I was interviewing a friend of mine, Mike Nygaard, long time friend of mine, and we were talking on and we were recalling the first time we both heard the famous 2009 presentation doing 10 deploys a day, every day at flicker, by John Allspaw and Paul Hammond. And we were both incredulous, right there? We thought it was irresponsible reckless, and maybe even immoral what they were doing, because, you know, I think most organizations were doing three a year, and that was very problematic. How could one do 10 deploys a day. And I think, what we now know, with the size of evidence, especially through the state of DevOps research, is that, you know, for six years, 35,000 plus respondents, the only way that you can be reliable, and secure, is to do smaller deployments more frequently, right? It makes you, be able to respond quicker in the marketplace, allows you to have better stability and reliability in the operational environment, allows you to be more secure. It allows you to be able to, you know, increase market share, increase productivity, and, you know, have happier employees. So, you know, at this point, I think the research is so decisive, that, you know, we can, as a whole book accelerate, that really makes the case for that, that this is something that I now have moral certainty or even absolute certainty oh, right. It's, you know, self evident to me, and it, I think we should have confidence that that really is true. >> Wonderful work, Gene, thanks so much for giving us the update. I really appreciate it, some really good sessions here in Actifio, as well as the book. Thanks so much, great to talk to you. >> Stu is always a pleasure to see you again, and thank you so much. >> Alright, that's our coverage from Actifio Data-driven, be sure to check out thecube.net for all of the, on demand content, as well as, as I said, if you were part of the show, definitely recommend reading Gene's book, The Unicorn Project. I'm Stu Miniman. And thank you for watching the cube. (soft upbeat music)

>> Narrator: From around the globe, It's theCUBE with digital coverage of Actifio Data Driven 2020. Brought to you by Actifio. >> Hi, my name is Gene Kim and I am looking forward to the amazing Actifio Data Summit. Everyone who applies... Three, two, one. Hi, my name is Gene Kim. I'm going to smile one more time. Three, two, one. Hi, my name is Gene Kim. I'm looking forward to the Actifio Data Summit, where we're going to learn all about the power of data, everyone who registers between now and then will receive a copy of my book, "The Unicorn Project." I look forward to seeing you there, thank you. (upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of Actifio Data Driven 2020, brought to you by Actifio. >> Hi everybody this is Dave Vellante, full of preview of Actifio Data Driven, and with me is Brian Reagan who is a long time cube alumni, good friend. Brian, awesome to see you thanks for coming on and help us set up Data Driven >> Dave it's always a pleasure to be here, thanks for having me. >> So this is one of our favorite events of the season, not only because it's historically been in Boston, but it's a really good intimate event, lot of customer content. Unfortunately this year, of course everything has gone virtual but tell us about that, what do you guys got planned for Data Driven this year? >> Well again we're delighted to be able to put the show on, in spite of all of the challenges of travel and face to face. As you know from years past, Data Driven has always been sort of by the customers for the customers, very much an event that is driven around understanding how customers are using data strategically, and how Actifio is helping them do that to power their businesses. This year is no different, I think what we've done is we've taken the best of the physical events, which is really facilitating fireside chats and panels of people using our technology to move the business forward with data, but also added a lot of things that frankly are impossible to do when you're strained by a physical event, which is be able to run a series of on demand technical sessions. Our technical tracks are always standing room only, so now we can offer more content, more discreet package content that can be consumed the day of the event and on for a year plus after the event. So we're excited to really sort of mix the best of both worlds virtual and the forums that have worked so well for us in the physical events. >> Well it's like I said I mean, lots of these events are sort of vendor fests, but what you do with Data Driven is you bring in the customer's voice. And I remember last year in theCUBE, we had Holly st. Clair who was with the state of Massachusetts, she was awesome. We had a guest from DraftKings, which was really, really tremendous. Of course, you see what's happening with those guys now just exploding. >> Exactly. >> But we also had a lot of fun, when of course Ash comes on, and all the Actifio folk, but we had Frank Gens on, the first and only time we've ever had him on theCUBE, he's now retired from IDC, I guess semiretired. We had Duplessie on, which was a lot of fun. So it's just a good vibe. >> Yeah, we made a conscious decision to your point not to avoid the traditional vendor fest, and bludgeoning people with PowerPoint throughout the day, and really wanted to make it spin it around, and have the customers tell their stories in their own words, and really talk about the themes that are both common, in terms of challenges, ways that they've addressed those challenges, but also dig into the real implications of when they do solve these challenges, what are the unintended consequences? It's sort of like the... In a lot of ways I think about the journey that customers went through with VMware and with the ability to spin up VMs effortlessly, was a fantastic first step, and then all of a sudden they realized they had all of these spun up Vms that were consuming resources that they didn't necessarily had thought about at the very beginning. I think that our customers as they progress through their journey with Actifio, once they realize the power of being able to access data and deliver data, no matter how big it is, in any form factor in any cloud, there's incredible power there, but there also comes with that a real need to make sure that the governance and controls and management systems are in place to properly deliver that. Particularly today when everything is distributed, everything is essentially at arms length, so that's part of the fun of these events is really being able to hear all of the ways these unique customers are, adding value, delivering value, gaining value, from the platform. >> What's it's interesting you mentioned VMs, it was like life changing when you saw your first VM get spun up and you're like, wow, this is unbelievable, and then it was so easy to spin up. and then you just save VM creep and copy creep. >> Right. >> And you're seeing some similar things now with cloud I mean example is the cloud data warehouses is so easy to spin those things up now. The CFOs are looking at the bill going Whoa, what are we doing here? >> (laughs) >> You're going to see the same thing >> Exactly. >> with containers as you begin to persist containers, you're going to have the same problem. So you guys created the category, it's always a marketing executives dreams to be able to create a category. You guys created the Copy Data Management category, and of course, you've extended that. But that was really good, it was something that you guys set forth and then all the analysts picked up on it, people now use that as a term and it kind of resonates with everybody. >> Right, right. It was bittersweet but also very satisfying to start to see other vendors come out with their own Copy Data Management offerings, and so yes the validating that in fact this is a real problem in the enterprise continues to be a real problem in the enterprise, and by using technologies that Actifio really pioneered and patented quite a bit of foundational technologies around, we're able to help customers address those copy data challenges, those spiraling costs of managing all of these duplicate, physical instances of data. And to your point, to some degree when you're on-prem in a data center and you've already bought your storage array. Okay, I'm consuming 20% more of the Ray or 100% more of the array than I really need to be, but I've already paid for the array. When it comes to cloud, those bills are adding up hourly, daily, weekly, monthly, and those are real costs, and so in many ways cloud is actually highlighting the power and frankly the problem of copy data, far more than the on-prem phenomenon ever did. >> Yeah I was on the phone with a former CIO, COO now of a healthcare organization, and he was saying to me there's a dark side of CapEx to OPEX, which is now that he's a COO he's like really concerned about the income statement and the variability of those costs, and so to your point I mean it's a big issue, the convenience seems to be outweighing some of that concern but nonetheless lack of predictability is a real concern there. >> Absolutely, absolutely. And I think we see that... You mentioned data lakes, and whether you call it a data lake or you just call it a massive data instance, one of the speakers of Data Driven this year is a customer of our Century Data Systems down in Florida. And they have 120 terabyte database that actually they're using, and this is an incredible story that we're excited to have them share with the world during Data Driven. They're using it to help the federal government get better data faster on COVID treatments and the efficacy of those treatments, and so to even consider being able to rapidly access and manage 120 terabyte instance. It breaks the laws of physics frankly. But again with Copy Data Management, we have the ability to help them really extend and really enhance their business and ultimately enhance the data flows that are hopefully going to accelerate the access to a vaccine for us in North American and worldwide, quite frankly. >> That's awesome, that's awesome. Now let's talk a little bit more about Data Driven what we can expect. Of course, the last couple of years you've been the host of Data Driven. They pulled a Ricky gervais' on you >> (Laughs loudly) like get the golden gloves, he's no longer being invited to host, but I think probably for different reasons, but what are some the major themes that we can expect this year? >> Yeah, we were disappointed that we couldn't get Tina Fey and Amy Poehler. >> (laughs quietly) I think we decided that in a virtual construct, the host duties were pretty amenable. So among the many things I talked about Sentry Data Systems and we have many customers who are going to be joining us and telling their stories. And again from accelerating data analytics to accelerating DevOps initiatives, to accelerating a move to the cloud, we're going to hear all of those different use cases described. One of the things that is different this year and we're really excited. Gene Kim sort of the author and noted DevOps guru, author of The Phoenix Project and The Unicorn Project, he's going to be joining us. We had previously intended to do a road show with Gene this year and obviously those plans got changed a bit. So really excited to have him join us, talk about his point of view around DevOps. Certainly it's a hugely important use case for us, really important for many of our customers, and actually registrant's between now and the event, which is September 15th and 16th, we'll get an eCopy an e-book copy of his Unicorn Project book. So we're eager to have people register and if they haven't already read him then I think they're going to be really pleasantly surprised to see how accessible his materials are, and yet how meaningful and how powerful they can be in terms of articulating the journeys that many of these businesses are going through. >> Yeah, I'm glad you brought that up. I'm stucked I have not read that material, but I've heard a lot about it, and when I signed up I saw that, said great I'm going to get the free book. So I'm going to check that out, >> Yeah It's obviously a very, very hot topic. Well Brian, I really appreciate you coming on, and setting up the event. What are the details? So where do I go to sign up? When is the event? What's the format? Give us the lowdown. >> It is September 15th and 16th, actifio.com will guide you through the registration process. You'll be able to create the event based on the content that you're eager to participate in. And again not only on the 15th and 16th, but then into the future, you'll be able to go back and re access or access content that you didn't have the time to do during the event window. So we're really excited to be able to offer that as an important part of the event. >> Fantastic and of course theCUBE will be there doing its normal wall to wall coverage. Of course, this time virtual, and you'll see us on social media with all the clips and all the work on Silicon Angle. So Brian great to see you and we will see you online in September. >> Thanks, Dave. >> All right, and thank you. Go to actifio.com, sign up register for Data Driven, this is Dave Vellante for theCUBE, we'll see you next time. (upbeat music)

>>from around the globe. It's the queue with digital coverage of active eo data driven 2020 Brought to you by activity. >>Hi, I'm Brian Reagan from Active Seo. And I'd like to welcome you to join us at Data Driven 2020 this year. Online as in years past, it's all about the customer from the bear voice to you talking about how they're solving their cloud Dev Ops Analytics and data protection challenges using the activity of platform and helping move their business forward this year. We're also excited to welcome Gene Kim Noted Dev Ops author in Guru on his E book. The Unicorn Project is available for free if you register today, so join us September 15th and 16th for data driven 2020. We look forward to seeing you online. >>Yeah, yeah, yeah, yeah, yeah

>>Live from Barcelona, Spain. It's the Cube covering Cisco Live 2020 right to you by Cisco and its ecosystem partners. >>Welcome back, everyone to the Cube's live coverage Day four of four days of wall to wall action here in Barcelona, Spain, for Cisco Live. 2020. I'm John Furrier with my co host Dave Volante, with a very special guest here to wrap up Cisco Live. The president of Europe, Middle East Africa and Russia. Francisco Wendy Mars Cube Alumni. Great to see you. Thanks for coming on to. I kind of put a book into the show here. Thanks for joining us. >>It's absolutely great to be here. Thank you. >>So what a transformation. As Cisco's business model of continues to evolve, we've been saying brick by brick, we still think big move coming. I think there's more action. I can sense the walls talking to us like Cisco live in the US and more technical announcement. In the next 24 months, you can see you can see where it's going. It's cloud, it's APS. It's policy based program ability. It's really a whole another business model shift for you and your customers. Technology shift in the business model shift. So I want to get your perspective this year. Opening. Keynote. Oh, you let it off Talking about the philosophy of the business model, but also the first presenter was not a networking guy. It was an application person. App dynamics. Yep, this is a shift. What's going on with Cisco? What's happening? What's the story? >>You know, if if you look for all of the work that we're doing is is really driven by what we see from requirements from our customers to change, that's happening in the market and it is all around. You know, if you think digital transformation is the driver organizations now are incredibly interested in, how do they capture that opportunity? How do they use technology to help them? But, you know, if you look at it, really, there's the three items that are so important it's the business model evolution. It's actually the business operations for for organizations. Plus, there people, they're people in the communities within that those three things working together. And if you look at it with, it's so exciting with application dynamics there because if you look for us within Cisco, that linkage off the application layer through into the infrastructure into the network. And bringing that linkage together is the most powerful thing because that's the insights and the value our customers are looking for. >>You know, we've been talking about the the innovation sandwich, you know, you got data in the middle and you've got technology and applications underneath. That's kind of what's going on here, but I'm glad you brought up the part about business model. This is operations and people in communities. During your keynote, you had a slide that laid out three kind of pillars. Yes, people in communities, business model and business operations. There was no 800 series in there. There was no product discussions. This is fundamentally the big shift that business models are changing. I tweeted provocatively, the killer wrap in digital business model. Because you think about it. The applications are the business. What's running under the covers is the technology, but it's all shifting and changing, so every single vertical every single business is impacted by. This is not like a certain secular thing in the industry. This is a real change. Can you describe how those three things are operating with that can >>sure. I think if you look from, you know, so thinking through those three areas. If you look at the actual business model itself, our business models is organizations are fundamentally changing and they're changing towards as consumers. We are all much more specific about what we want. We have incredible choice in the market. We are more informed than ever before. But also we are interested in the values of the organizations that we're getting the capability from us as well as the products and the services that naturally we're looking to gain. So if you look in that business model itself, this is about, you know, organizations making sure they stay ahead from a competitive standpoint about the innovation of portfolio that they're able to bring, but also that they have a strong, strong focus around the experience, that they're customer gains from an application, a touch standpoint that all comes through those different channels, which is at the end of the day, the application. Then if you look as to how do you deliver that capability through the systems, the tools, the processes? As we all evolve, our businesses have to change the dynamic within your organization to cope with that. And then, of course, in driving any transformation, the critical success factor is your people and your culture. You need your teams with you. The way teams operate now is incredibly different. It's no longer command and control. It's agile capability coming together. You need that to deliver on any transformation. Never, never mind. Let it be smooth, you know, in the execution they're all three together. >>But what I like about that model and I have to say, this is, you know, 10 years of doing the Cube, you see that marketing in the vendor community often leads what actually happens. Not surprising as we entered the last decade, there's a lot of talk about Cloud. Well, it kind of was a good predictor. We heard a lot about digital transformation. A lot of people roll their eyes and think it's a buzzword, but we really are. I feel like exiting this cloud era into the digital era. It feels, really, and there are companies that get it and are leaning in. There are others that maybe you're complacent. I'm wondering what you're seeing in Europe just in terms of everybody talks digital, every CEO wants to get it right. But there is complacency. Their financial services said Well, I'm doing pretty well, not on my watch. Others say, Hey, we want to be the disruptors and not get disrupted. What are you seeing in the region? In terms of that sentiment, >>I would say across the region, you know, there will always be verticals and industries that slightly more advanced than others. But I would say that the bulk of conversations that I'm engaged in independence of the industry or the country in which we're having that conversation in there is a acceptance off transfer. Digital transformation is here. It is affecting my business. I if I don't disrupt, I myself will be disrupted and we challenged Help me. So I You know, I'm not disputing the end state and the guidance and support soon drive the transition and risk mitigated manner, and they're looking for help in that there's actually pressure in the board room now around a what are we doing within within organizations within the enterprise service, right of the public sector, any type of style of company. There's that pressure point in the board room of Come on, we need to move it speed. >>Now the other thing about your model is technology plays a role and contribute. It's not the be all end. All that plays a role in each of those the business model of business operations developing and nurturing communities. Can you add more specifics? What role do you see technology in terms of advancing those three years? >>So I think, you know, if you look at it, technology is fundamental to all of those fears in regard. Teoh Theo innovation that differentiation technology could bring the key challenges. One being able to apply it in a manner where you can really see differentiation of value within the business. So and then the customer's organization. Otherwise, it's technology for the sake of technology. So we see very much a movement now to this conversation of talk about the use case, the use cases, the way by which that innovation could be used to deliver value to the organization on also different ways by which a company will work. Look at the collaboration Kate Capability that we announced earlier this week of helping to bring to life that agility. Look at the the APP D discussion of helping the link the layer of the application into the infrastructure of the network to get to root, cause identification quickly and to understand where you may have a problem before you actually arises and causes downtime many, many ways. >>I think the agility message has always been a technical conversation. Agile methodology, technology, softer development, No problem check. That's 10 years ago. But business agility is moving from a buzz word to reality. Exactly. That's what you're kind of getting. >>Their teams have. Teams operate, how they work and being able to be quick, efficient, stand up, stand down and operate in that way. >>You know, we were kind of thinking out loud on the Cube and just riffing with Fabio Gori on your team on Cisco's team about clarification with you, Gene Kim around kind of real time. What was interesting is we're like, Okay, it's been 13 years since the iPhone, and so 13 years of mobile in your territory in Europe, Middle East Africa mobility has been around before the iPhone, so more advanced data privacy much more advanced in your region. So you you you have a region that's pretty much I think, the tell signs for what's going on North American around the world. And so you think about that. You say Okay, how is value created? How the economics changing this is really the conversation about the business model is okay. If the value activities are shifting and being more agile and the economics are changing with SAS, if someone's not on this bandwagon is not an end state discussion, very. It's done Deal. >>Yeah, it's But I think also there were some other conversation which, which are very prevalent here, is in the region so around trust around privacy law, understanding compliance. If you look at data where data resides, portability of that data GDP our came from Europe has pushed out on those conversations will continue as we go over time. And if I also look at, you know, the dialogue that you saw, you know, within World Economic Forum around sustainability that is becoming a key discussion now within government here in Spain, you know, from a climate standpoint and many other areas >>as well. David, I've been riffing around this whole where the innovation is coming from. It's coming from your region, not so much the us US. We've got some great innovations. But look at Blockchain. Us is like, don't touch it pretty progressive outside United States. A little dangerous to, But that's where innovation is coming from, and this is really the key that we're focused on. I want to get your thoughts on. How do you see it going? Next level? The next level. Next. Gen Business model. What's your What's your vision? >>So I think there'll be lots of things if we look at things like it with the introduction. Introduction of artificial intelligence, Robotics capability five g of course, you know, on the horizon we have Mobile World Congress here in Barcelona a few weeks time. And if you talked about with the iPhone, the smartphone, of course, when four g was introduced, no one knew what the use case where that would be. It was the smartphone, which wasn't around at that time. So with five G and the capability there, that will bring again yet more change to the business model for different organizations and capability and what we can bring to market >>the way we think about AI privacy data ownership becomes more important. Some of the things you were talking about before. It's interesting what you're saying. John and Wendy, the GDP are set this standard and and you're seeing in the US they're stovepipes for that standard California is gonna do want every state is gonna have a difference, and that's going to slow things down. It's going to slow down progress. Do you see sort of an extension of GDP, our like framework of being adopted across the region, potentially accelerating some of these sticky issues and public policy issues that can actually move the market forward? >>I think I think that will because I think there'll be more and more if you look at this is terminology of data. Is the new oil What do you do with data? How do you actually get value from that data? Make intelligent business decisions around that? So, yeah, that's critical. But yet if you look for all of ours, we are extremely passionate about where's our data used again? Back to trust and privacy. You need compliance, you need regulation. And I think this is just the beginning off how we will see that >>evolving. You know, when you get your thoughts. David, I've been riffing for 10 years around the death of storage. Long live storage. But data needs to be stored somewhere. Networking is the same kind of conversation just doesn't go away. In fact, there's more pressure now to get the smartphone. That was 13 years ago, before that. Mobility, data and Video. Now super important driver. That's putting more pressure on you guys. And so hey, we did well, networking. So it's kind of like Moore's Law. More networking, more networking. So video and data are now big your thoughts on video and data video. >>But if you look out the Internet of the future, you know what? So if you look for all of us now, we are also demanding as individuals around capability and access of. That's an Internet of the future. The next phase. We want even more so they'll be more more requirement for speed availability, that reliability of service, the way by which we engage in we communicate. There's some fundamentals there, so continuing to grow, which is which is so, so exciting force. >>So you talk about digital transformation that's obviously in the mind of C level executives. I got to believe security is up. There is a topic one other. What's the conversation like in the corner office when you go visit your customers? >>So I think there's a There's a huge excitement around the opportunity, realizing the value of the of the opportunity on. You know, if you look at top of mind conversations around security around, making sure that you can make taint, maintain that fantastic customer experience because if you don't the customer go elsewhere, How do you do that? How do you enrich at all times and also looking at market? Jason sees, you know, as you go in a new tour at senior levels, within, within organizations independent of the industry in which they're in. They're a huge amount of commonalities that we see across those of consistent problems by which organizations are trying to solve. And actually, one of the big questions is what's the pace of change that I should operate us on? When is it too fast? And one is one of my too slow and trying to balance that is exciting but also a challenge for a company. >>So you feel like sentiment. There's still strong, even though we're 10 years into this, this bull market you get Brexit, China tensions with US US elections. But but generally you see sentiment still pretty strong demand. >>So I would say that the the the excitement around technology, the opportunity that is there around technology in its broader sense is greater than ever before. And I think it's on all of us to be able to help organizations to understand how they can consume and see value from us. But it's a fantastic times, >>gets economic indicators way. So >>I know you >>have to be careful, >>but really, the real I think I'm trying to get to is is the mindset of the CEO. The corner office right now is it is that we're gonna we're gonna grow short term by cutting or do we going to be aggressive and go after this incremental opportunity? And it's probably both. You see a lot of automation in cars >>both, and I think if you look fundamentally for organizations, it's it's the three things helped me to make money, how to save money, keep me out of trouble. So those are the pivots they all operate with on, you know, depending on where an organization is in its journey, whether they're start up there in the middle, the more mature and some of the different dynamics and the markets in which they operate in a well, there's all different variables, you know? So it's it's it's mixed. >>Wendy, thanks so much to spend the time to come on. The Cube really appreciate great keynote folks watching. If you haven't seen the keynote opening section, that's good. Second, the business model. I think it's really right on. I think that's gonna be a conversation will continue. So thanks for sharing that before we look. Before we leave, I want to just ask a question around, What? What's going on for you here in Barcelona? As the show winds down, you had all your activities. Take us in the day in the life of what you do. Customer meetings. What were some of those conversations? Take us inside inside. What? What goes on for you here? >>I tell you, it's been an amazing It's been amazing few days, So it's a combination of customer conversations around some of the themes We just talked about conversations with partners. There's investor companies that we invest in a Cisco that I've been spending some time with on also spending time with the teams as well. The definite zone, you know, is amazing. We have this afternoon the closing session where we got a fantastic, um, external guests who's coming in is going to be really exciting as well. And then, of course, the party tonight and will be announcing the next location, which I'm not going to reveal now. Later on today, >>we kind of figured it out because that's our job is to break news, but we're not gonna break it for you to have that. Hey, thank you so much for coming on. Really appreciate. When any market in Europe, Middle East Africa and Russia for Cisco she's got her hand on the pulse and the future is the business model. That's what's going on. Fundamentally radical change across the board in all areas. This is the Cube, bringing you all the action here in Barcelona. Thanks for watching. >>Yeah, yeah,

>>Live from Barcelona, Spain. It's the Cube covering Cisco Live 2020 right to you by Cisco and its ecosystem partners. >>Welcome back to the Cube's live coverage here at Cisco Live 2020 in Barcelona, Spain. I'm jumpers student of cube coverage. We've got a lot of stuff going on in Cisco Multi cloud and cloud technology. Quantification of Cisco's happening in real time is happening right now. Cloud is here here to stay. We got two great guests unpack what's going on in cloud native and networking and applications as the modern infrastructure and software evolves. We got you. Gene Kim, global product marketing. Compute Storage at Cisco Global marketing manager and Rob Gori, senior director. Cloud Solution Marketing Guys come back. Thanks for coming back. Appreciate it. Great to see you Barcelona guys. So, Bobby, we've had multiple conversations and you see that from the sales force given kind of the the discussion in the motivation Cloud is big. It's here. It's here to stay. It's changing. Cisco AP I first week here in all the products, it's changing everything. What's the story now? What's going on? >>I would say you know the reason why we're so excited about the launch here in Barcelona is because this time it's all about the application of spirits. I mean, the last two years we've being announcing some really exciting stuff in the cloud space where I think about all the announcements with AWS is the Googles the azure, so the world. But this time it really boils down to making sure that is incredibly hyper distributive world. There is an application explosion. Ultimately, we will help for the right operation stools and infrastructure management tools to ensure that the right application experience will be guaranteed for the end customer. And that's incredibly important because at the end, what really really matters is that you will ensure the best possible digital experience to your customer. Otherwise, ultimately nothing's gonna work. And, of course, you're gonna lose your brand and your customers. >>One of the main stories that we're covering is the transformation of the industry. Also, Cisco and one of the highlights to me was the opening keynote. You had APP dynamics first, not networking. Normally it's like what's in the hood? Routers and the gear. No, it was about the applications. This is the story we're seeing. It's kind of a quiet unveiling. Its not get a launch, but it's evolving very quickly. Can you share what's going on behind this? All this? >>Absolutely. It's exactly along the lines of what I was saying a second ago, in the end that the reason why we're driving the announcement, if you want from the application experience side of the House, is because with Appdynamics, we already have very, very powerful application performance management, which it's evolving extremely rapidly. First of all, Appdynamics can correlate not just the application for four months to some technology, maybe eyes, but through actual business KP eyes. So app dynamics can give you, for instance, serial time visibility off, say, a marketing funnel conversion rates transactions that you're having in your in your business operation. Now we're introducing an incredibly powerful new capability that takes the bar to a whole new level. And that's the Appdynamics experience. Journey maps. What are those? It's actually the ability off, focusing not so much on front ends and back ends and the business performances, but really focusing on what the user is seen in front of his or her screen. And so what really matters is capturing the journey that given user of your application is being and understanding whether the experience is the one that you want to deliver or you have, like, a sudden drop off somewhere. And you know why this is important because in the end we've been talking about is the problem of the application, performance issues or performance. It could be a badly designed page. How do you know? And so this is a very precious information they were giving to application developers know, just through the idea. Ops, guys, that is incredibly gracious. >>Okay, you want to get this in. So you just brought up that journey. So that's part of the news. Just break down real quick. One minute what the news is. >>Yeah, so we have three components. The 1st 1 as you as you correctly pointed out, is really the introduction of the application. The journey maps, right. The experience journey maps. That's very, very important. The second he's way are actually integrating Appdynamics with the inter site. Actually, inter site the optimization manager, the workload optimization, workload, optimizer. And so because there is exchange of data between the two now, you are in a position to immediately understand whether you have an application problem. We have a worker problem for structure problem, which is after me, where you really need to do as quickly as you can. And thirdly, way have introduced a new version of our hyper flex platform, which is hyper converge flagship platform for Cisco with a fully containerized version, the tax free if you want as well, that is a great platform for containerized applications. >>So you do and what I've been talking to customers last few years. When they go through their transformational journey, there's the modernization they need to do. The pattern I've seen most successful is first, modernize the platform often HD I is, you know, an option for that. It really simplifies the environment, reduces the silos on, has more of that operational model that looks closer to what the cloud experience is. And then, if I've got a good platform, then I can modernize the applications on top of it. But often those two have been a little bit disconnected. It feels like the announcements now that they are coming together. What are you seeing? What're you hearing? How your solutions at solving this issue >>exactly. I mean, as we've been talking to our customers, a lot of them are going through a different application. Modernizations and kubernetes and containers is extremely important to them. And to build a container cloud on Prem is extremely one of their needs. And so there's three distinctive requirements that they've kind of talk to us about. A lot of it has to be ableto it's got to be very simple, very turnkey, fully integrated, ready to turn on the other. One is something that's very agile, right? Very Dev Ops friendly and the third being a very economic container cloud on prim. So as you mentioned, High Flex Application Platform takes our hyper converge system and build on top of it a integrated kubernetes platform to deliver a container as a service type capability. And it provides a full stack, fully supported element platform for our customers, and one of the best great aspects of it is it's all managed from inter site, from the physical infrastructure to the hyper converge layer to all the way to the container management. So it's very exciting to have that full stack management and inter site as well. >>It's great to see you, John and I have been following this kubernetes wave since the early early days. Fabio mentioned integrations with the Amazons and Googles of the world because, you know, a few years ago you talk to customers and they're like, Oh, well, I'm just going to build my own community. Nobody ever said that is easy now. Just delivering as a service seems to be the way most people want it. So if I'm doing it on Amazon or Google, they've got their manage service that I could do that or that there partners we're working with. So explain what you're doing to make it simpler in the data center environment. Because on Prem absolutely is a piece of that hybrid equation that customers need. >>Yes, so, essentially from the customer experience perspective, as I mentioned, very fairly turnkey right from the hyper flex application platform we're taking are happening for software were integrating a application virtualization layer on top of it analytics k VM based. And then on top of that, we're integrating the kubernetes stack on top of as well. And so, in essence, right? It's a fully curated kubernetes stack that has all the different elements from the networking from the storage elements and provide that in a very turnkey way. And as I mentioned, the inter site management is really providing that simplicity that customers need for that management. >>Fabio This is the previous announcements you've made with the public clouds. This just ties into those hybrid environments. That's exactly a few years ago. People like, Oh, is there going to be a distribution that wins in kubernetes? We don't think that's the answer, but still, I can't just move between kubernetes. You know seamlessly yet. But this is moving toward that >>direct. Absolutely. A lot of customers want to have a very simple implementation. At the same time, they weren't off course a multi cloud approach and I really care about marking the difference between multi cloud hybrid Cloud has been a lot of confusion. But if you think about a multi cloud is re routed into the business need or harnessing innovation from wherever it comes from, you know the different clouds capability from things, and you know what they do today. Tomorrow it could even change, so people want optionality, so they want a very simple implementation that's integrated with public cloud providers that simplifies their life in terms of networking, security and application of workload management. And we've been executing towards that goal so fundamentally simplify the operations of these pretty complex kind of hybrid apartments. >>And once you nail that operations on hybrid, that's where multi cloud comes in. That's really just a connection point. >>Absolutely, you know, you might know is an issue. So in order to fulfill your business, your line of business needs you. Then you have a hybrid problem, and you want to really kind of have a consistent production grade environment between things on Prem that you own and control versus things that you use and you want to control better. Now, of course, they're different school thoughts. But most of the customers who are speaking with really want to expand their governance and technology model right to the cloud, as opposed to absorb in different ways of doing things from each and every time. >>I want to unpack a little bit of what you said earlier about the knowing where the problem is, because a lot of times it's a point, the finger at the other first, it's the application promising the problem, so I want to get into that. But first I want to understand the hyper flex application platform. Eugene, if you could just share the main problem that you guys solve, what are some of the pain points that customers had? What problem does the AP solved? >>Yeah, as I mentioned, it's really the platform for our customers to modernize the applications on right, and it addresses those things that they're looking for as far as the economics right, really? The ability to provide a full stack container experience without having to, you know, but bringing any third party hyper visor licenses as well support costs that's well integrated. There you have your integrated, hyper converged storage capability. You have the cloud based management, and that's really developing. You provide that developer dev ops simplicity from that agility that they're looking for internally as well as for their production environments. And then the other aspect is the simplicity to manage all this right and the entire life cycle management >>as well. So it's the operational side of the hole in under the covers hobby on the application side where the problem is because this is where I'm a bit skeptical, Normal rightfully so. But I can see a problem where it's like Whose fault is it? Applications, problem or the network? I mean, it runs on where? Sears Workloads, Banking app. It's having trouble. How do you know where the problem is? And how do you solve that problem with what's going on for that specific issue? >>Absolutely. And you know, the name of the game here is breaking down this operational side, right? And I love what are appdynamics VP? GM Any? Whitaker said. You know, he has this terminology. Beast develops, which it may sound like an interesting acrobatics, but it's absolutely too. The business has to be part of this operational kind of innovation because, as you said, you know, developer just drops their containers and their code to the I T. Ops team, but you don't really know whether the problem a certain point is going to be in the code or in the application is actually deployed. Or maybe a server that doesn't have enough CPU. So in the end, it boils down to one very important thing. You have to have visibility, insights and take action at every layer of the stack. Instrumentation. Absolutely. There are players that only do it in their software overlay domain. The problem is, very often these kind of players assume they're underneath. Things are fine, and very often they're not. So in the end, this visibility inside in action is the loop that everybody's going after these days, too, Really get to the next. If you want a generational operation, where you gotta have a constant feedback loop and making it more faster and faster because in the end you can only win in the marketplace, right? So your I T ops, if you're faster than your competitors, >>will still still questioning the GM of APP Dynamics. Run, observe, ability. And he's like, No, it's not a feature, it's everywhere. So he's comment was observe. Abilities don't really talk about it because it's a big in. You agree with that? >>Absolutely. It has to be at every layer of the stack, and only if you have visibility inside an action through the entire stock, from the software all the way to the infrastructure level that you can solve the problems. Otherwise, the finger pointing quote unquote will continue, and you will not be able to gain the speed you need. >>Okay, so The question on my mind I want to get both of you guys could weigh in on this is that if you look at Cisco as a company, you got a lot going on. You guys huge customer base core routers to know applications. There's a lot going on a lot of a lot of complexity. You got I o. T. Security members talking about that. You got the WebEx rooms totally popular. It's got a lot of glam, too, and having the WebEx kind of, I guess, what virtual presence was telepresence kind of model. And then you get cloud. Is there a mind share within the company around how cloud is baked into everything? Because you can't do I ot edge without having some sort of cloud operational things. Stuff we're talking about is not just a division. It's kind of it's kind of threads everywhere across Cisco. What's the what's the mind share right now within the Cisco teams and also customers around cloud ification? >>Well, I would say it's it's a couple of dimensions. The 1st 1 is the cloud is one of the critical domains of this multi domain architecture. That, of course, is the cornerstone of Cisco's. The knowledge is strategy, right? If you think about it, it's all about connecting users to applications wherever they are and not just the users to the applications themselves. Like if you look at the latest US from I. D. C. 58% of workloads is heading to a public cloud, and the edge is like the data center is exploding many different directions. So you have this highly distributed kind of fabric. Guess what sits in between. All these applications and micro services is a secure network, and that's exactly what we're executing upon. Now that's the first kind of consideration. The second is if you look at the other civil line. Most of the Cisco technology innovation is also going a direction of absorbing cloud as a simplified way of managing all the components or the infrastructure. You look at the hyper flex. AP is actually managed by Inter site, which is a SAS kind of component. This journey started long time ago with Cisco Iraqi on then, of course, we have sass properties like WebEx. Everything else absolutely migrate borders. >>We've been reporting Eugene that five years ago we saw the movement where AP, eyes were starting to come in when you go back five years ago. Not a lot of the gear and stuff that Cisco had AP eyes. Now you got AP eyes building in all the new products that you see the software shift with you intent based networking to APP dynamics. It's interesting. It's you're seeing kind of the agile mindset. This is something you and I talk all the time. But agile now is the new model. Is it ready for customers? I mean, the normal enterprises still have the infrastructure and separated, and they're like, Okay, how do I bring it together? What do you guys see in the customer base? What's going on with that early adopters, Heavy duty hardcore pioneers out there. But you know, the general mainstream enterprise. Are they there yet? Have they had that moment of awakening? >>Yeah, I mean, I think they they are there because fundamentally, it's all about ensuring that application experience. And you could only ensure the application experience right by having your application teams and infrastructure teams work together. And that's what's exciting. You mentioned Ap eyes and what we've done. They were with APP dynamics, integrating with inner sight workload. Optimizer as you mentioned all the visibility inside in action and what APP Dynamics has provides. Provide that business and end user application performance experience. Visibility Inter site. It's giving you visibility on the underlining workload, and the resource is whether it's on prim in your private data center environment or in a different type of cloud providers. So you get that full stack visibility right from the application all the way down to the bottom and then inter site local optimizer is then also optimizing the resource is to proactively ensure that application experience. So before you know, if we talk about someone at a check out and they're about there's of abandonment because the function is not working, we're able to proactively prevent that and take a look at all that. So, you know, in the end, I think it's all about ensuring that application experience and what we're providing with APP Dynamics is for the application team is kind of that horizontal visibility of how that application performing and at the same time, if there's an issue, the infrastructure team could see exactly within the workload topology, where the issue is and entertain safely, whether it be manual intervention or even automatically our ops capability. Go ahead and provide that action so the action could be, you know, scaling out the VM that's on Prem or looking at new, different type of easy to template in the cloud. That's a very exciting about this. It's really the application experience is now driving and optimize the infrastructure in real >>time. And let me flip your question like, Do you even have a choice, John, when you think about in the next two years 50% more applications? If you're a large enterprise here, 5 to 7000 apps you have another 2 3000 applications just coming into into the and then 50% of the existing ones that are going to be re factor lifted and shifted the replace or retired by SAS application. It's just like a tsunami that's that's coming on you and oh, by the way, because again the micro services kind of effect the number of dependencies between all these applications is growing incredibly rapidly, Like last year, we were eight average interdependencies for applications. Now we have 20 so in Beijing imaginable happens as you are literally flooded with this can really you have to ensure that your application infrastructure fundamentally will get tied up as quickly as you can >>see. You and I have been talking for at least five years now, if not longer. Networking has been the key kind of last change over clarification. I would agree with you guys. I think last question because I wanted to get your perspective. But think about it. It's 13 years since the iPhone so mobile has shown people that mobile app can change business. But now you get the pressure of the networks. Bringing that pressure on the network or the pressure of the network to be better than programmable is the rise of video and data. I mean, you got mobile check now you got it. Video. I mean more people doing video now than ever before. Videos of consumer. Well, it's streaming. You got data? These two things absolutely forced customers to deal with it. >>But what really tipped the balance? John is actually the SAS effect is the cloud effect because, as you know, it's an I t. So the inflection points. Nothing gets a linear right. So once you reach a certain critical mass of cloud apps, and we're absolutely they're already all of a sudden your traffic pattern on your network changes dramatically. So why in the world are you continuing? Kind of, you know, concentrating all of your traffic in your data center and then going to the Internet. You have to absolutely open the floodgates at the branch level and as close to the users this possible, and that it implies a radical change of the >>way I would even add to that. And I think you guys are right on where you guys are going. It may be hard to kind of tease out with all the complexity with Cisco, but in the keynote, the business model shifts come from SAS. So you got all this technical stuff going on. You have the sass ification, or cloud changes the business models so new entrants can come in and existing players get better. So I think that whole business model conversation never was discussed at Cisco Live before in depth. Okay, run your business, connect your hubs campus move packets around Dallas applications in business model, >>but also the fact that there is increasing number off software capabilities and so fundamental. You want to simplify the life of your customers through subscription models that help the customer buying a using what they really need the right at any given point in time, all the way to having enterprise agreements. >>I also think that's about delivering these application experiences free for small, different experience. That's really what's differentiating you from your competitors, right? And so that's a different type of >>shift as well. Well, you guys have got a good That's a good angle on this cloud. I love it. I got to ask the question. What can we expect next from Cisco? More progression along cloud ification? What's next? >>Well, I would say we've been incredibly consistent, I believe in the last few years in executing on our cloud strategy, which again is sent around helping customers really gluing this mix, set off data centers and clouds to make it work as one right as much as possible. And so what we really deliver is networking security and application performance management, and we're integrating this more and more on the two sides of the equation, right? The data center side and the public cloud side and more more integrated in between all of these layers again, to fundamentally give you this operational capability to get faster and faster. We'll continue doing so and >>we'll get you set up before we came on camera that you were talking to sales teams. What are they? What's the vibe with sales team? They get excited by this. What's the >>oh yeah, feedback. And absolutely, from the inter site work optimizer and the app Dynamics side. It's very exciting for them. Switch the conversation they're having with their customers, really from that application experience and proactively ensuring it. And on the hyper flex application platform side, this is extreme exciting with providing a container cloud to our customers. And you know what's coming down is more and more capabilities for our customers to modernize the applications on hyper >>flex. You guys are riding a pretty big waves here at Cisco in a cloud way to get the i o t. Security wave. Great stuff. Thanks for coming in. Thanks for sharing the insights. Appreciate it. >>Thank you for having >>coverage here in Barcelona. I'm John. First, Minutemen back with more coverage. Fourth day of four days of cube coverage. Be right back after this short break. >>Yeah, yeah, yeah.

(upbeat music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Hello everyone, welcome to theCUBE studio here in Palo Alto. I'm John Furrier your host of theCUBE. We're here introducing a new format for CUBE panel discussions, it's called Around theCUBE and we have a special segment here called Get Smart: Unpacking AI with some great with some great guests in the industry. Gene Santos, Professor of Engineering in College of Engineering Dartmouth College. Bob Friday, Vice President CTO at Mist at Juniper Company. And Ed Henry, Senior Scientist and Distinguished Member of the Technical Staff for Machine Learning at Dell EMC. Guys this is a format, we're going to keep score and we're going to throw out some interesting conversations around Unpacking AI. Thanks for joining us here, appreciate your time. >> Yeah, glad to be here. >> Okay, first question, as we all know AI is on the rise, we're seeing AI everywhere. You can't go to a show or see marketing literature from any company, whether it's consumer or tech company around, they all have AI, AI something. So AI is on the rise. The question is, is it real AI, is AI relevant from a reality standpoint, what really is going on with AI, Gene, is AI real? >> I think a good chunk of AI is real there. It depends on what you apply it to. If it's making some sort of decisions for you, that is AI that's blowing into play. But there's also a lot of AI left out there potentially is just simply a script. So, you know, one of the challenges that you'll always have is that, if it were scripted, is it scripted because, somebody's already developed the AI and now just pulled out all the answers and just using the answers straight? Or is it active learning and changing on its own? I would tend to say that anything that's learning and changing on its own, that's where you're having the evolving AI and that's where you get the most power from. >> Bob what's your take on this, AI real? >> Yeah, if you look at Google, What you see is AI really became real in 2014. That's when the AI and ML really became a thing in the industry and when you look why did it become a thing in 2014? It's really back when we actually saw TensorFlow, open source technology really become available. It's all that Amazon Compute story. You know, you look what we're doing here at Mist, I really don't have to worry about compute storage, except for the Amazon bill I get every month now. So I think you're really seeing AI become real, because of some key turning points in the industry. >> Ed, your take, AI real? >> Yeah, so it depends on what lens you want to kind of look at it through. The notion of intelligence is something that's kind of ill defined and depending how how you want to interpret that will kind of guide whether or not you think it's real. I tend to all things AI if it has a notion of agency. So if it can navigate its problem space without human intervention. So, really it depends on, again, what lens you kind of want to look at it through? It's a set of moving goalposts, right? If you take your smartphone back to Turing When he was coming up with the Turing test and asked them if this intelligent, or some value intelligent device was AI, would that be AI, to him probably back then. So really it depends on how you kind of want to look at it. >> Is AI the same as it was in 1988? Or has it changed, what's the change point with AI because some are saying, AI's been around for a while but there's more AI now than ever before, Ed we'll start with you, what's different with AI now versus say in the late 80s, early 90s? >> See what's funny is some of the methods that we're using aren't different, I think the big push that happened in the last decade or so has been the ability to store as much data as we can along with the ability to have as much compute readily disposable as we have today. Some of the methodologies I mean there was a great Wired article that was published and somebody referenced called, method called Eigenvector Decomposition they said it was from quantum mechanic, that came out in 1888 right? So it really a lot of the methodologies that we're using aren't much different, it's the amount of data that we have available to us that represents reality and the amount of compute that we have. >> Bob. >> Yeah so for me back in the 80s when I did my masters I actually did a masters on neural networks so yeah it's been around for a while but when I started Mist what really changed was a couple things. One is this modern cloud stack right so if you're going to have to build an AI solution really have to have all the pieces ingest tons of data and process it in real time so that is one big thing that's changed that we didn't have 20 years ago. The other big thing is we had access to all this open source TensorFlow stuff right now. People like Google and Facebook have made it so easy for the average person to actually do an AI project right? You know anyone here, anyone in the audience here could actually train a machine learning model over the weekend right now, you just have to go to Google, you have to find kind of the, you know they have the data sets you want to basically build a model to recognize letters and numbers, those data sets are on the internet right now and you personally yourself could go become a data scientist over the weekend. >> Gene, your take. >> Yeah I think also on top of that because of all that availability on the open software anybody can come in and start playing with AI, it's also building a really large experience base of what works and what doesn't work and because they have that now you can actually better define the problem you're shooting for and when you do that you increase you know what's going to work, what's not going to work and people can also tell you that on the part that's not going to work, how's it going to expand but I think overall though this comes back to the question of when people ask what is AI, and a lot of that is just being focused on machine learning and if it's just machine learning that's kind of a little limited use in terms of what you're classifying or not. Back in the early 80s AI back then is really what people are trying to call artificial general intelligence nowadays but it's that all encompassing piece. All the things that you know us humans can do, us humans can reason about, all the decision sequences that we make and so you know that's the part that we haven't quite gotten to but there is all the things that's why the applications that the AI with machine learning classification has gotten us this far. >> Okay machine learning is certainly relevant, it's been one of the most hottest, the hottest topic I think in computer science and with AI becoming much more democratized you guys mentioned TensorFlow, a variety of other open source initiatives been a great wave of innovation and again motivation, younger generations is easier to code now than ever before but machine learning seems to be at the heart of AI and there's really two schools of thought in the machine learning world, is it just math or is there more of a cognition learning machine kind of a thing going on? This has been a big debate in the industry, I want to get your guys' take on this, Gene is machine learning just math and running algorithms or is there more to it like cognition, where do you guys fall on this, what's real? >> If I look at the applications and look what people are using it for it's mostly just algorithms it's mostly that you know you've managed to do the pattern recognition, you've managed to compute out the things and find something interesting from it but then on the other side of it the folks working in say neurosciences, the first people working in cogno-sciences. You know I have the interest in that when we look at that, that machine learning does it correspond to what we're doing as human beings, now because the reason I fall more on the algorithm side is that a lot of those algorithms they don't match what we're often thinking so if they're not matching that it's like okay something else is coming up but then what do we do with it, you know you can get an answer and work from it but then if we want to build true human intelligence how does that all stack together to get to the human intelligence and I think that's the challenge at this point. >> Bob, machine learning, math, cognition is there more to do there, what's your take? >> Yeah I think right now you look at machine learning, machine learning are the algorithms we use, I mean I think the big thing that happened to machine learning is the neural network and deep learning, that was kind of a mild stepping stone where we got through and actually building kind of these AI behavior things. You know when you look what's really happening out there you look at the self driving car, what we don't realize is like it's kind of scary right now, you go to Vegas you can actually get on a driving bus now, you know so this AI machine learning stuff is starting to happen right before our eyes, you know when you go to the health care now and you get your diagnosis for cancer right, we're starting to see AI in image recognition really start to change how we get our diagnosis. And that's really starting to affect people's lives. So those are cases where we're starting to see this AI machine learning stuff is starting to make a difference. When we think about the AI singularity discussion right when are we finally going to build something that really has human behavior. I mean right now we're building AI that can actually play Jeopardy right, and that was kind of one of the inspirations for my company Mist was hey, if they can build something to play Jeopardy we should be able to build something answer questions on par with network domain experts. So I think we're seeing people build solutions now that do a lot of behaviors that mimic humans. I do think we're probably on the path to building something that is truly going to be on par with human thinking right, you know whether it's 50 years or a thousand years I think it's inevitable on how man is progressing right now if you look at the technologically exponential growth we're seeing in human evolution. >> Well we're going to get to that in the next question so you're jumping ahead, hold that thought. Ed, machine learning just math, pattern recognition or is there more cognition there to be had? Where do fall in this? >> Right now it's, I mean it's all math, so we collect something some data set about the world and then we use algorithms and some representation of mathematics to find some pattern, which is new and interesting, don't get me wrong, when you say cognition though we have to understand that we have a fundamentally flawed perspective on how maybe the one guiding light that we have on what intelligence could be would be ourselves right. Computers don't work like brains, brains are what we determine embody our intelligence right, computers, our brains don't have a clock, there's no state that's actually between different clock cycles that light up in the brain so when you start using words like cognition we end up trying to measure ourselves or use ourselves as a ruler and most of the methodologies that we have today don't necessarily head down that path. So yeah that's kind of how I view it. >> Yeah I mean stateless those are API kind of mindsets, you can't run Kubernetes in the brain. Maybe we will in the future, stateful applications are always harder than stateless as we all know but again when I'm sleeping, I'm still dreaming. So cognition in the question of human replacement. This has been a huge conversation. This is one, the singularity conversation you know the fear of most average people and then some technical people as well on the job front, will AI replace my job will it take over the world is there going to be a Skynet Terminator moment? This is a big conversation point because it just teases out what could be and tech for good tech for bad. Some say tech is neutral but it can be shaped. So the question is will AI replace humans and where does that line come from. We'll start with Ed on this one. What do you see this singularity discussion where humans are going to be replaced with AI? >> So replace is an interesting term, so there I mean we look at the last kind of Industrial Revolution that happened and people I think are most worried about the potential of job loss and when you look at what happened during the Industrial Revolution this concept of creative destruction kind of came about and the idea is that yes technology has taken some jobs out of the market in some way shape or form but more jobs were created because of that technology, that's kind of our one again lighthouse that we have with respect to measuring that singularity in and of itself. Again the ill defined definition, or the ill defined notion of intelligence that we have today, I mean when you go back and you read some of the early papers from psychologists from the early 1900s the experiment specifically who came up with this idea of intelligence he uses the term general intelligence as kind of the first time that all of civilization has tried to assign a definition to what is intelligent right? And it's only been roughly 100 years or so or maybe a little longer since we have had this understanding that's been normalized at least within western culture of what this notion of intelligence is so singularity this idea of the singularity is interesting because we just don't understand enough about the one measure ruler or yardstick that we have that we consider intelligence ourselves to be able to go and then embed that inside of a thing. >> Gene what's your thoughts on this, reasoning is a big part of your research you're doing a lot of research around intent and contextual, all these cool behavioral things you know this is where machines are there to augment or replace, this is the conversation, your view on this? >> I think one of the things with this is that that's where the downs still lie, if we have bad intentions, if we can actually start communicating then we can start getting the general intelligence yeah I mean sort of like what Ed was referring to how people have been trying to define this but I think one of the problems that comes up is that computers and stuff like that don't really capture that at this time, the intentions that they have are still at a low level, but if we start tying it to you know the question of the terminator moment to the singularity, one of the things is that autonomy, you know how much autonomy that we give to the algorithm, how much does the algorithm have access to? Now there could be you know just to be on an extreme there could be a disaster situation where you know we weren't very careful and we provided an API that gives full autonomy to whatever AI we have to run it and so you can start seeing elements of Skynet that can come from that but I also tend to come to analysis that hey even with APIs, while it's not AI, APIs a lot of that also we have the intentions of what you're going to give us to control. Then you have the AI itself where if you've defined the intentions of what it is supposed to do then you can avoid that terminator moment in terms of that's more of an act. So I'm seeing it at this point. And so overall singularity I still think we're a ways off and you know when people worry about job loss probably the closest thing that I think that can match that in recent history is the whole thing on automation, I grew up at the time in Ohio when the steel industry was collapsing and that was a trade off between automation and what the current jobs are and if you have something like that okay that's one thing that we go forward dealing with and I think that this is something that state governments, our national government something we should be considering. If you're going to have that job loss you know what better study, what better form can you do from that and I've heard different proposals from different people like, well if we need to retrain people where do you get the resources from it could be something even like AI job pack. And so there's a lot of things to discuss, we're not there yet but I do believe the lower, repetitive jobs out there, I should say the things where we can easily define, those can be replaceable but that's still close to the automation side. >> Yeah and there's a lot of opportunities there. Bob, you mentioned in the last segment the singularity, cognition learning machines, you mentioned deep learning, as the machines learn this needs more data, data informs. If it's biased data or real data how do you become cognitive, how do you become human if you don't have the data or the algorithms? The data's the-- >> I mean and I think that's one of the big ethical debates going on right now right you know are we basically going to basically take our human biases and train them into our next generation of AI devices right. But I think from my point of view I think it's inevitable that we will build something as complex as the brain eventually, don't know if it's 50 years or 500 years from now but if you look at kind of the evolution of man where we've been over the last hundred thousand years or so, you kind of see this exponential rise in technology right from, you know for thousands of years our technology was relatively flat. So in the last 200 years where we've seen this exponential growth in technology that's taking off and you know what's amazing is when you look at quantum computing what's scary is, I always thought of quantum computing as being a research lab thing but when you start to see VC's and investing in quantum computing startups you know we're going from university research discussions to I guess we're starting to commercialize quantum computing, you know when you look at the complexity of what a brain does it's inevitable that we will build something that has basic complexity of a neuron and I think you know if you look how people neural science looks at the brain, we really don't understand how it encodes, but it's clear that it does encode memories which is very similar to what we're doing right now with our AI machine right? We're building things that takes data and memories and encodes in some certain way. So yeah I'm convinced that we will start to see more AI cognizance and it starts to really happen as we start with the next hundred years going forward. >> Guys, this has been a great conversation, AI is real based upon this around theCUBE conversation. Look at I mean you've seen the evidence there you guys pointed it out and I think cloud computing has been a real accelerant with the combination of machine learning and open source so you guys have illustrated and so that brings up kind of the final question I'd love to get each of you's thought on this because Bob just brought up quantum computing which as the race to quantum supremacy goes on around the world this becomes maybe that next step function, kind of what cloud computing did for revitalizing or creating a renaissance in AI. What does quantum do? So that begs the question, five ten years out if machine learning is the beginning of it and it starts to solve some of these problems as quantum comes in, more compute, unlimited resource applied with software, where does that go, five ten years? We'll go start with Gene, Bob, then Ed. Let's wrap this up. >> Yeah I think if quantum becomes a reality that you know when you have the exponential growth this is going to be exponential and exponential. Quantum is going to address a lot of the harder AI problems that were from complexity you know when you talk about this regular search regular approaches of looking up stuff quantum is the one that allows you now to potentially take something that was exponential and make it quantum. And so that's going to be a big driver. That'll be a big enabler where you know a lot of the problems I look at trying to do intentions is that I have an exponential number of intentions that might be possible if I'm going to choose it as an explanation. But, quantum will allow me to narrow it down to one if that technology can work out and of course the real challenge if I can rephrase it into say a quantum program while doing it. But that's I think the advance is just beyond the step function. >> Beyond a step function you see. Okay Bob your take on this 'cause you brought it up, quantum step function revolution what's your view on this? >> I mean your quantum computing changes the whole paradigm right because it kind of goes from a paradigm of what we know, this binary if this then that type of computing. So I think quantum computing is more than just a step function, I think it's going to take a whole paradigm shift of you know and it's going to be another decade or two before we actually get all the tools we need to actually start leveraging quantum computing but I think that is going to be one of those step functions that basically takes our AI efforts into a whole different realm right? Let us solve another whole set of classic problems and that's why they're doing it right now because it starts to let you be able to crack all the encryption codes right? You know where you have millions of billions of choices and you have to basically find that one needle in the haystack so quantum computing's going to basically open that piece of the puzzle up and when you look at these AI solutions it's really a collection of different things going underneath the hood. It's not this one algorithm that you're doing and trying to mimic human behavior, so quantum computing's going to be yet one more tool in the AI toolbox that's going to move the whole industry forward. >> Ed, you're up, quantum. >> Cool, yeah so I think it'll, like Gene and Bob had alluded to fundamentally change the way we approach these problems and the reason is combinatorial problems that everybody's talking about so if I want to evaluate the state space of anything using modern binary based computers we have to kind of iteratively make that search over that search space where quantum computing allows you to kind of evaluate the entire search space at once. When you talk about games like AlphaGo, you talk about having more moves on a blank 19 by 19 AlphaGo board than you have if you put 1,000 universes on every proton of our universe. So the state space is absolutely massive so searching that is impossible. Using today's binary based computers but quantum computing allows you to evaluate kind of search spaces like that in one big chunk to really simplify the aspect but I think it will kind of change how we approach these problems to Bob and Gene's point with respect to how we approach, the technology once we crack that quantum nut I don't think will look anything like what we have today. >> Okay thank you guys, looks like we have a winner. Bob you're up by one point, we had a tie for second but Ed and Gene of course I'm the arbiter but I've decided Bob you nailed this one so since you're the winner, Gene you guys did a great job coming in second place, Ed good job, Bob you get the last word. Unpacking AI, what's the summary from your perspective as the winner of Around theCUBE. >> Yeah no I think you know from a societal point of view I think AI's going to be on par with kind of the internet. It's going to be one of these next big technology things. I think it'll start to impact our lives and people when you look around it it's kind of sneaking up on us, whether it's the self driving car the healthcare cancer, the self driving bus, so I think it's here, I think we're just at the beginnings of it. I think it's going to be one of these technologies that's going to basically impact our whole lives or our next one or two decades. Next 10, 20 years is just going to be exponentially growing everywhere in all our segments. >> Thanks so much for playing guys really appreciate it we have an inventor entrepreneur, Gene doing great research at Dartmouth check him out, Gene Santos at Dartmouth Computer Science. And Ed, technical genius at Dell, figuring out how to make those machines smarter and with the software abstractions growing you guys are doing some good work over there as well. Gentlemen thank you for joining us on this inaugural Around theCUBE unpacking AI Get Smart series, thanks for joining us. >> Thank you. >> Thank you. >> Okay, that's a wrap everyone this is theCUBE in Palo Alto, I'm John Furrier thanks for watching. (upbeat funk music)

>>live from Seattle, Washington. It's the key nude covering Smartsheet engaged 2019. Brought to you by smartsheet. >>Welcome back, everyone to the cubes. Live coverage of smartsheet engaged here in Seattle, Washington. I'm your host along with my co host, Jeff Rick. We're joined by Jean Farrell. He is the CPO of smartsheet. Thanks for coming on the show. >>Thanks for being here. >>Great to be here here last year and even bigger and better. You moved out of the hotel and convention center. That gets something. Did >>we did, We were. We have almost 4000 strong this year and we're super excited. We've been looking forward to this for a while. So >>So this is the third, the third annual conference yet. Just tell us a little bit. Let's let's open it up by telling our viewers a little bit about what this means to you, how big the show is. Give us a few stats. >>Yeah, well, you know, we ran our first customer conference, our first engaged really three years ago in in Bellevue at a conference center attached to a hotel that's right next to our headquarters, which is so super convenient, and I think we had 5 700 people there, and it was a great start andan. Last year we doubled in size and we actually outgrew the facility in Bellevue on. So when we planned for this year, we said, You know, let's go Big way felt this momentum building. We had such great feedback from customers what they learned and what they came away and could do after coming to engage that we felt we could. We were ready to kind of take it to a big stage. And so it was really exciting. I spent before joining Smartsheet two and half years ago. I spent five years that Amazon Web service is, and I was fortunate enough to be there when they did their first reinvent in Las Vegas, and it was roughly 5000 people, and I had a very interesting deja vu moment walking into the main auditorium here yesterday, Andi, it just brought back all the memories of Oh my gosh, this is like the size of remain so in three years we should be. Roughly 25,000 will be >>in Vegas >>today, up on the main stage. A lot of great new product announcements I want it, I want you to sort of break it down for our viewers. He started talking about how you really served three core customers and these new product announcements are really targeted. Each of these >>Yeah, we kind of broke it out. And what we find >>your way, sir? Customers of all sizes. So from startups, toe, medium sized businesses to large enterprise and within almost every one of those customers, we really see three distinct user groups really work force, which is at the core kind of where we started the I T teams, which many times there to support the workforce but also drive a lot of their own work clothes. And then the business decision makers. Folks that are really looking at, How do I drive overall organizational effectiveness and improve efficiency? And so what we tried to do was make sure we were delivering a set of capabilities for everybody on DSO for the workforce. We announced a bunch of new capabilities. Probably the highlight was our new conversations in context, which we're really excited about. It's gonna enable ah, whole new level of collaboration and engagement within the platform, and >>it was really >>grounded in customer feedback. That said they wanted the ability to actually interact in the context of their work and too many times what they were forced to do is they would have a question and they would have to go send an email or they go send a chat and then the response is disconnected. So it just wasn't as efficient. That could be. So we took that signal and work very closely with customers to design the new experience. So really excited about those those capabilities. We launched new forms, capabilities and multi select dropped down a lot of things that our customers are really excited around. From the workforce perspective on the I t front, we've introduced a ton of new things all year. The two big announcements today were around our accelerator for GDP are which it actually affects almost anybody that does business with an EU citizen. So a lot of folks don't really connect the dots ago. I'm in. You know, I'm in Redmond, Oregon. Why do I need to comply with GDP? Are well, if you sell the anybody in the you need to figure that out, um, and and then, um beyond GDP are. We talked about our federal offering on our new govcloud, which is really key for government agencies but also all the contractors to support government agencies. And so a lot of our customers are very interested in that. And then the final piece was really business leaders. Andi talked there about new enhancements to control center. Do it really let it scale and move across the organization roll ups, ability to do multi tier on then. Importantly, we talked about the new content collaboration capability, which is which is a really big it integrates are our slope technology. So marketing and other types of, uh, disciplines can use content collaboration in their work. I'd be remiss if I didn't mention 10,000 feet. >>So lots to talk about a lot. But you clearly, this is the customers, right? Because I think it was at the pasting. Widgets between Dashboard was a standing ovation. It's amazing the power of copy and paste when you can pull that work, you know, it's it's what the people want. It's funny you say that I am constantly >>amazed with that. The things that when you saw little problems that unlock all sorts of new use cases and many times that cheer you here is because customers have been trying to work around those problems, right? So multi select Drop Down is a great example where they had to do all sorts of gyrations in how they configure their work to support multiple selections. And so now we've made that much more elegant for them, and they're like, ecstatic because they no longer have to invest that time and >>I can't >>let you go. >>Wow, Is that all it took? I would sooner. It is a lot of times right, the simple things that have the huge, a huge improvement in kind of getting away from this repetitive work, which is under the theme we keep hearing over and over and over again. >>No, that's absolute. That's absolutely true. And it is really little things can have a big impact or Or or the analogy I sometimes will use is if you're creating a puzzle or if you have kids and you've ever built, you know, the X wing fighter set. If you're missing a few pieces, it's just not the same, right It just right. You can't kind of complete the work and so sometimes just completing that play for customers, giving them that that last piece they need to really go in power. Their workflow is is really cute. >>And I also think because we're living at a time where we have way demand so much from technology in our personal lives, and it delivers most for most. For the most part, our lives are pretty seamless and the way we can order things from anywhere. And so when we have, when we deal with these little aggravations at work, it's just that much more so. One of the things you said on the main stage is that customers are not shy about telling you what they want. So I want to hear from you how you solicit feedback and your process for making these changes for >>way actually, have >>we actually have a bunch of different mechanisms? We used to listen a customer, and I actually call it customer signal because it comes from a lot of different places. Way have kind of foundation. Aly we have a process actually called enhancement request. So many of our customers can go in our community and actually submit a form and say I really want you to build this Andi, That's very intentional, like there's no confusion, and usually they're very straightforward. But beyond that, we also we have the community in general. So we monitor that we get feedback on on kind of a freefall flowing forum where they give us feedback. We have user groups that this year will due north of 40 user groups around the world, where we bring collections of customers together, many time hosted at different customer locations, and customs will talk and share best practices and give us feedback on things that they'd like to see. I spend a ton of time out in the field with customers just visiting with them, talking about their use cases, helping themselves problems on and importantly, we have AH product advisory Council and a customer advisory board. And these air both specific groups of customer smaller groups that we've recruited and we actually use them tow, consult with us very closely to give us kind of overall direction. And then probably the most valuable feedback once we know where we want to go is once we start building, we have a private beta program, and then what we call an early adopter program. Both of those enroll customers in interacting with things were building before they're launched. And that gives us a chance to get real time feedback into what they like. What? They don't know what we need to improve. And sometimes the product will stay in in that private beta phase for longer than we expected, because the signal we get requires that we make changes. So we think that's really important to make sure we actually hit the mark. Because if you if you're on, if you're not satisfied, customer need or solving a problem, >>they're not gonna buy. What's the point? You're >>surely gonna get a lot of customers signal here at >>engaged over the next couple of Absolutely. And they're absolutely not shy. Every time I'm running some, it's like, Oh, we love this. And here's the 10 things I want that exactly. >>Thank you so much for coming on the Cubans. Pleasure having you >>my pleasure. Thanks for having me. And thanks for being here. It engaged. Thanks >>for having us. Great. >>I'm Rebecca Knight for Jeff. Rick, You are watching the cube. Stay tuned

>> live from Anaheim, California. It's the queue covering nutanix dot next twenty nineteen Brought to you by nutanix. >> Hello, everyone. You are watching the Cube and we are live at nutanix dot Next here in Anaheim. I'm your host, Rebecca Night, along with my co host, John Farrier. We're joined by Michael Bushong. He is the vice president Enterprise marketing at Juniper Networks. Thank you so much for returning to the Cube, Your Cuba Lem. >> So thank you for this is this is awesome and you can't see it on the cameras. But this is a, like, just amazing. >> It's very We are in the clouds up here. It's a very high stage. Everything's coming full circle. >> Jim Cramer. Ask a little bit >> serious. Okay. >> Of course. I'm going to ask the tough questions >> going on. He's going to start slamming everything very soon, >> But we've known each other for a long time, Jennifer Going back ten years ago. So look, a tangle started. We're in our tenth year. You know, if you've seen the journey, I am a juniper. You left juniper startup brocade, then back to juniper. So you've seen that circle? You've seen the couple waves? I mean one of the things we were talking about before we came on camera was saw. Network fabrics to Dover had Juno's and then be anywhere. But you know, So this arrow, which became the ESPN Wave, are now suffer to find data center. So you've been in that journey is a product person. And now marking juniper, it's actually goes back about a decade. This whole esti n stuff networking. So what's What's the role now that you're doing? What's juniper doing? Why Nutanix? What's your story year? >> Sure. So I run enterprise marketing at Juniper, so my goal is effectively toe to make some of the hype makes sense, right? It goes back a decade. Actually, the early days of the only ESPN movement we didn't call it s tiene right. Juniper started with open flow and PC and alto and all these acronyms, and we actually, we're a great engineering company. Maybe not so great marketing company. And we actually call it network program ability. That didn't take off. But the technology's kind of endured. And I think what we saw was this lengthy incubation period to the point that now, as we sit here dot next in twenty nineteen. We're starting to see now some of the attraction of the last couple of years. That's a junipers general position. So we wantto dr Adoption. Certainly there's products and technology that underpins that, but But fundamentally, we're looking at a huge operational shift. And if that operational shift doesn't happen, then that's to the detriment of everyone in the industry. >> What's the relationship with NUTANIX? Can you talk about how you guys work together? What's the connection? >> Sure. So nutanix obviously does the whole hyper converge space. We provide the networking components to that. So whether that's the top Iraq connectivity, how do you get your traffic into the rest of the network? We've done some security stuff which we can talk more about. And then, if you look at the overall management piece, we've got integrations at the management policy layer as well. >> So your relationship you both got a very similar world view. How you see technology, you're both taken on VM. Where to? Can you talk a little bit about the relationships there and and why it works? >> Sure, fundamentally, if you look at what Nutanix is trying to do, it's this whole idea of one click. It ties ing everything right. They talk a lot in their keynote sessions. You hear the executives talk, You look at their collateral, the messages they take, the customers. It's about making things simple. Junipers Strategy is this idea of engineering simplicity. So just a top level? What's our purpose? What's our role in this industry at large? I think we have a very common worldview. Of course, driving simplicity is going to happen in the context of real architectural change on the change That's kind of everywhere is cloud and increasingly multi cloud. And so both Nutanix and Juniper about really driving simplicity in the context of Cloud multi cloud, giving customers the opportunity, toe run workloads wherever they need Teo without taking on additional operational burden. That's kind of cesarean unwanted in enterprises networking. >> So the Big Tran, this multi cloud you guys. That's a key part of the strategy. Dave along tonight and Stew Minutemen were arguing on the cute couple events ago. There are not one of our sessions about the hype around multi cloud. The reality of it. The reality is, is that everyone kind of has multiple clouds. It's not like that the clouds aren't talking to each other, and then we're just kind of riffing on the cloud is just big. One big distributed network, different computing, distributed networks. These air knew these aren't new paradigms. These are existing things that have computer science behind them. Engineering behind it. So juniper, you have been around for a long time. Connecting networks. The cloud is like some of the same concert on premise Hybrid Cloud and multiplied it basically a distributed network. It's all cloud operations. We get that, but the technology issue is not that hard, but I won't say that that hard, but it's similar to what you guys have done in the past. Just differently. How are you guys looking at that? Because multiple clouds, just like Internet working the switches routers, you move from packet that point A and point B get storage. His store stuff So concepts are all the same. How do you guys seeing the multi cloud opportunity within juniper? >> So I would make the distinction between multiple clouds and multi cloud? I agree with you. If you look at most enterprises, they have a workload in Amazon. They're using sales force, and so you know, they're multi cloud, right? They have multiple clouds, multi clouds, more of an operational condition. It's about taking disparate pools of resource is and managing. That is one thing. So think of it more about how you do stuff and less about where you host an application. If you look it even like describing Amazon, some people say, Well, Amazon is just, you know, Cloud is just using other people servers. It's not. You're not renting their servers. What you're leveraging is their operations. That's the transformation. That's this kind of underfoot. And so while some of the technology bits are common, the ability to do abstracted control moving to declare it over intent based management, right, these air right technology building blocks. What you're seeing now is the operational models are coming along, and that's really that's the change we have to drive on. I'll just kind of close with when you change technology. If it's just about deploying a piece of software, if it's just about deploying a piece of hardware like candidly, that challenge isn't that it's not that hard, right? We know how to deploy stuff when you start talking about changing how people fundamentally do their jobs. When you started talking about changing, you know how businesses operate. That's that's the piece that takes some time and I would venture. That's why you know, you look a decade ago why we're where we started. If you look at what's taking a decade, it's the operational change, not the technology piece >> and the cultural jobs movement. Certainly forcing function on that, which is awesome. And that's the tale when I think. And then again, Gene Came was on yesterday Who wrote The Devil's Handbook and also does that death. The Devil Enterprise. Someone said, We're three percent in. I would agree with him. I think it's so early, but But the challenge. I want to get your thoughts, Michael. And this is that Connecting multiple on disparity environments is great, but late in C kills now. So now late and see these air old school concepts, you know, get a time can't change the laws of physics. Right? So Leighton sees matters s l A's matter. So these air network challenges these air software challenges. What's your view on that piece of the puzzle? >> We leave when we say cloud, you know a lot of people probably think, um, you know, G C P Azure. They might think a WSB probably picture in your head, you know, some logically central cloud. First, we need to disavow people of the notion that cloud is this thing that somehow sits at the center of everything. It's not. There are centralized clouds. If you're optimizing for economics, that makes perfect sense. Tow To do that. There's distributed clouds. The whole rise of multi axis edge computing is about changing the paradigm from moving data to the application. Right. If your applications in Amazon and you're going to send your data there, that's one model Teo. Sometimes you might want to move the application to the data. If you have a lot of data like an i o t. Use case as an example, I was used oil platforms is a really good example. I don't know if you know, but you know how they get all their. They have all these mining and manufacturing bits. They've got lots of data. How did they get that data off the oil platforms? Snowball. So what they do is the helicopters come in, they take the drives off and they they they leave right. The reason they do that because if your reliance on satellite links just too much data, you can't statue >> is going to get a helicopter to ransom helicopter to come in, >> we'LL know when they're swapping the crew out every fourteen days, that's what happens. So here's the thing, right? If in that kind of model than the cloud, the data center exists on premises. And if that's the case, then when we think about you know kind of what the cloud is, cloud is, it's It's a lot. It's a lot more than what we most of us probably think about. Certainly, we see it with Outpost as a WS is starting to move on premises versions, and there's a lot of reasons you might wanna have a distributed cloud. Certainly it could be, you know, your comfort and security and control. There's real privacy implications, country of origin, so subpoenas can access your information depending on where it resides. >> What you're saying is, basically, it's all cloud. It's operational is the new definition. So you figured from an operational standpoint, Ops and Dev's That's it. The rest is just all connected somehow through the text, >> and then you need to have it. Yes. So we we understand the connectivity, bitch, you've gotta have the right, you know, elements. But if it's operational, it's about how do you do policy management? So part of the whole nutanix thing and kind of what drove us together was this idea that if I want a one click everything. If you could do that within the hyper converge space, you still have to do that over the connected environment, which means managing policy from a single location, regardless of where it is. And of course, using that policy to Dr Security >> and their strategy is to take what that worked for. The CIA and the data center move that into this new operator operating model, which spans multiple quote, disparity, environments or clouds or edges. It's similar similar concept, but different environmental. Yeah, >> that's exactly right. And so then what Nutanix needs that is a strong networking partner because they have tto do the bits that they do. They need other people to do the bits that that you know that we can do. We pull those things together and then you can provide essentially a secure environment for hybrid workload. >> So you guys embed it into their product? You guys joined cell together. Is it more of a partnership? How deep is the partnership with you With Nutanix >> s all just They'LL say yes, we get along s o and it kind of the most surface level you know, you need to have top Iraq switches. You gotta connect to the network and so we do qualification there. So if you deploy nutanix, you can deploy juniper alongside and that looks more like a kind of a co selling meat in the channel type model. Beyond that, if you look at how we provide security over like a workload environment, the question is, then you know what's the security element? So we've taken our virtual firewall. We cut our V s are axe, which essentially runs in the V M. And we can run it on a V, and so that gives them a segmentation strategies. So if you look it workloads that air distributed across the cluster by having a firewall element that we can enforce policy. Of course, that firewall element is then integrated with prism. So if I want to deploy these things when I spin up a new V M. What I want to do is spin up the security with it, and so you see management integration. Then if we continue this too, it's kind of full conclusion. We have, ah, product suite We call contrail in the enterprise version Contra Enterprise Multi Cloud, which is all about policy management and underlay management. And so, as we extend the partnership, it gives us additional opportunity to take um to provide routed elements which provide policy enforcement points and then to give us a way of managing policy over a diverse environment. >> And you guys can bring in that platform element for nutanix. Is there now a platform? They have a full stack of software on Lee. So you guys, you cannot take their stuff, put it there and vice versa. >> That's exactly right. So whether the workload resides in a ws on two or whether it resides kind of on premises in a jiffy, weaken one, we're kind of co managed and then to it gives us the security elements toe play across that >> one of the things that we're talking a lot about at this rinse it and at a lot of other events like it, it's sort of or the dark side of technology. We're at a time where major presidential candidates are talking about breaking up. Big tech were becoming much more aware of the privacy concerns. The biases that are built into algorithms. Exactly. I want to hear your thoughts as a technology veteran. Do you? Are you still a technology optimist or do you did? Does this stuff keep you up at night? I mean, how where do you fit your personal views? I was >> somewhat of a technology optimists, but I'm a skeptic when it comes to the people. I think if the technology existed in a vacuum, I think some of the problems go away. I think privacy is a major concern. I think it's going to shape regulatory action, especially in Europe. Well, so I think we'LL see similar actions in the US I don't have quite a strong connection to what's happening in Asia. Um, I think that the regulatory, the challenge I have from a technology perspective is that if the regulations come in the absence of understanding how the technology works, then you end up with some really terrifying outcomes on DSO I'm Sam. I'm a fan of the technology. I'm nervous of the people on that in terms of like, our overall Ruelas is cos here, I think, you know, we need to do a candidate a better job of, of making sure things land before we move on to the next big thing on DH. You know, we're talking cloud. We're ten years into cloud and people were always talking about the next frontier. To some extent, I think the world doesn't move as fast as we like to think it does. I don't think that the even like the mark, I'm in a marketing role. I don't think that the marketing hype necessary. I don't think it serves us by moving too far ahead because I will tell you when the gap between the promise and the reality becomes insurmountable e wide. I think it's Ah, I think I think everyone loses Andi. You run the risk of stranding an entire generation of people who who gets stuck behind it, and I don't you know, I'm nervous about about what that means, and I think it's you asked the question that you're the dark side. I think it's Certainly it plays out in our industry. I think it plays out. You know, there's a digital divide that's growing in the U. S. Based on broadband access. By the way, that's gonna widen with five G. I think it plays out between different nation states. So I Yeah, I don't know. I'm an optimist. Maybe I'm a pragmatist. >> Realist. >> Yeah, I'm I'm I'm I'm a little scared. >> Little cloud definitely happened, and that's a good point. And we took a lot of heat at looking ankle. Keep on the cube. Was too many Men in the team put out the first private cloud report People like this is nonsense. Well, well. And our thesis was clouds grade if you want. If you're in the cloud as a cloud native or, you know, new startup, why wouldn't you go on Amazon? Everyone, we did that. But if once you taste cloud operations, you go Wow. This is so much awesome. Right? Then go into a modern and enterprise. It's not going to be overnight. Change over. I mean, we might say it's going to take about a decade. We fell from the beginning that cloud operations once you taste cloud you realize this is a new operating model. There's a lot of benefits to that, but to change it over in the enterprise, and that turned out to be what everyone's now do it. But that was three years ago. >> Well, there's implications. So if its operations then operations is inherently an end end proposition, you can't have operations in a silo. Things like you're monitoring tools. How do you do cloud monitoring it on premises monitoring. How do you do workflow Execution? How do you do? You know, automation, whether that's event driven or even just scripted. If you have wildly different environments that require you to buy for Kate, your investment, then there's a very real There's a complexity that comes with that your people have tto do more than one thing that's that's hard. There's a cost that comes with that because you have different teams for different things. There's a lack of coordination. I don't think you unlock the value of cloud in that in that environment. And I think that operational pieces really around converging on >> Michael your point about people in technology. It's so right on. We see that all the time where I'm a technology Optimus. I love technology, but I totally agree that people can really destroy it looked fake news. It's just, you know, it's infrastructure network effect with bad content policy because Facebook's immediate company not a platform >> well, technology's only is good on our end are >> gonna run. The government don't even have the Internet work. So you know when you when you go to the cloud, same >> knowledge just also want the government to come away with that we do it >> where the government just doesn't know how the Internet works. Some people that do but like the good hearings, it's ridiculous. But you know, there's a real D o. D project going on future military Jet I contract. We've been reporting on where modern data driven application workloads. I could use a soul, cloud or multi class so that the dogma of what multi vendor was in the old days is changing. >> I don't I actually don't know if you look at multi cloud. If it's an end end proposition, then by definition it's also going to be multi vendor like there's no future where it's like end in all one vendor. I think we have to come to grips with that is an industry. But I think if you're clinging to your you know, kind of I want my single procurement vehicle. I want my single certification. By the way, I think if you believe fundamentally that incumbency is going to be that your path forward, I think it's a dangerous place to be. That's not to say that. I think the incumbents all go away. I don't There's a there's a heavy rule to play but certainly were going to open things up. And >> you see procurement modernized. I mean, I mean, government goes back to nineteen ninety five procurement standards, but either the enterprise procurement moving So the text moves so fast. Procurement still has rules from >> so no, I don't think all >> of the second right. >> Then there's a whole A procurement in our industry is driven by our peace. Our peace tend to be derivative. I take my last r p. I had some new lines. If you want Esti n so you take the cup copy and paste five hundred seventy four lines at the five hundred seventy fifth line. S T n. You're gonna end up in the same solution because the first five seventy four of the same I do think we should learn a little bit from what the big public cloud cos they're doing, which is, you know, tightening refreshed cycles, retiring things with as much passion as they introduced new things tightening up. Ultimately, what gets deployed? Maintaining diversity of underlying components so you could maintain economic leverage when you're doing procurement. But then solidifying on operationally streamlined model, That's I think that's the future. That's certainly what we've been on as a company. I think that's what we're betting on with Nutanix From a partnership point of view, I think we'LL be on the right side of change on that, and I think it's going to, you know, it may take some time to play out. That's where I think things go >> well. Michael Bushong. Always a pleasure having you on the Cube. Thank you for coming on. >> Thank you very much. >> I'm Rebecca Knight for John Furrier. You are watching the Cube

>> Announcer: Live from Anaheim, California. It's theCUBE, covering Nutanix.NEXT, 2019. Brought to you by Nutanix. >> Welcome back the theCUBE's live coverage of Nutanix.NEXT here in Anaheim California. I'm your host, Rebecca Knight. Along with my co-host John Furrier. Here we are, we're at day two, John, this conference, I gotta say it's pretty cool. 6500 people, we're steps away from Disneyland, and, you go to a lot of these things every year. I also do about a dozen or so for theCUBE. So in other words, we're veterans of this kind of thing. This does seem to have a different vibe and I think it really gets to the kind of company Nutanix is, and where it is in its journey. >> Nutanix is still a small company even though they're 10 years old, as Dheeraj talks about. The numbers aren't massive, I mean, we go to a lot of other shows where it's 15,000, Amazon Web Services just had an event in London, Dave Vellante was out there covering, Stu was covering Red Hat summit in Boston this week, tons of events going on. Amazon Web Services' summit in comparison was 12,500 people, 22,000 registered, that's a summit in London. It's not the re:Invent main conferences like 30,000 people. And that's always sold out, so they got a lot, in terms of attendees numbers they're still in the entry level, mid range growth. But I think that's okay, they like that culture and I think the story here at this show is intimacy, they would rather err on the side of better content and more intimate opportunities for their customers to really get the straight scoop. And I think it's less of a conference slash trade show, more of an intimate relationships where they can provide feedback, for customers to give feedback, and for Nutanix to figure out with the customers how to connect to them. So, I think the story here is, Nutanix is growing up as a company, they're 10 years old and they gotta go the next level and the management team has technical chops, and they have a long term view. They have that 20 mile stare, they can see out and they're trying to figure it out. I still think that the numbers are light on their forecast I still think that there's some sandbagging going on there, I'm not saying they're sandbagging, but I mean, I think, you look at Essentials, which is the enterprise and then multi-cloud, the numbers that we're seeing at Wikibon are much bigger, and Amazon reflects that. So I think they're being cautious but smart about how they execute off their success they've had in the first 10 years to go the next 10 to 20 years and I think that's clear in the management team, that they wanna build a durable company. >> Well exactly, and I think that that's what's really coming through, is that this is, as you said, they're growing up. This is a real coming of age moment for them, they've celebrated the 10 years. Okay, so what kind of company are we? Who do we want to be? And what's coming through is that from the technology side, they get it. They say, I'm sort of reminded of the Henry David Thoreau quote, our life is frittered away by detail, simplify simplify simplify, that's what customers want. They want this one click data recovery, they want their credentials to be assumed. You know who I am, I'm safe to be in here. Fixing things, dealing with that. So I think that they get that, that simplicity is key. They also get customer service. I mean their Net Promoter scores, as we've noted, are in the 90s, that's just unheard of. >> It's monster, monster numbers. >> It really is and so they get it. We need to be responsive to customers, we need to have a personal relationship with these, because it's not just organizations, it's people at the other end of these transactions. >> I mean, I think Nutanix, one of the stories that's popping out in the hallways as I walk around and talk to customers and people and the company and partners, is that Nutanix has a lot of headroom in their growth. I think Wall Street is interesting and you heard Dheeraj talk about that yesterday, about having a new customer, you asked him about his management style and he said quote, I have a new customer called Wall Street. And I have to balance that against mainstream enterprise which is his core business. And so he as a CEO and the company are dealing with this new stakeholder called public company customer retail stock buyers. That's a short term cycle and I think, if you look at their stock, they had a big knife edge drop in the past quarter. And I think the shorts are circling, it's a whole nother dynamic, it's a whole nother theater for Nutanix to deal with, and I think that's something that they gotta get used to. And he was clear, he said I'm addressing it, we're gonna balance it, but they gotta be thinking long term because this company has a lot more to do and their customer base are risk takers. Because everyone we talk to has this different style or persona. They're smart, they're usually engineering oriented, they love engineered solutions. And they're taking chances. And everyone who's taken the chance with Nutanix, has paid off. That seems to be the theme. And as we were talking before we came on camera, Mark Hamill, Jedi knight, you know, Star Wars, was on stage giving the keynote, their customer base, is a lot like the Jedi order, right? I mean they see themselves as, elite, technically, they're not afraid to take organizational risks and push that DevOps culture. And we heard that from Sunil, the chief product officer that they're really looking at, this new way to do things, like they did with hyperconvergence, they pioneered that, set the table on that and foundationally built that. They wanna take that same playbook of HCI, hyperconverged infrastructure, and apply it to the cloud. And provide an abstraction layer advantage and I think that is clearly their strategy and that's, to me, the top story here. >> I couldn't agree more and I also think that, what is also coming through is this idea of we don't wanna be safe. What's clear is that, consumer technologies have leapfrogged IT enterprise vendors. The things that we hold in our pockets are so much more sophisticated than what businesses and organizations, multi-billion dollar businesses and organizations, are using, what their employees are using on a day to day basis. So we expect a certain kind of design and ease of use, in our personal lives and they're bringing it to enterprises and think that that is really what's exciting and interesting about this company. >> What's interesting about their story is that, the consistent theme about the customers is that it's kind of a consolidation story but that's not the real story because back in the old days of IT, consolidation was the strategy. Consolidate vendors, consolidate footprint to reduce cost, clearly a cost reduction. With Nutanix what they get is they get consolidation, and they enable advantages so the real value of Nutanix is to be positioned for those new kinds of app developers, so. This is like, you get consolidation as a side benefit for enabling the value, and that's the theme that's coming out of all the customer testimonials and interviews is, we gotta do more, we gotta create more enablement for the app developers and we gotta provide more performant storage servers and software for the customers. And that's their main focus and they consolidation as a benefit. That's gonna scare a lot of people and customers that I've talked to said, hey I got all the stuff but I can't just throw it away tomorrow, I gotta move it out over time, so, this is the Nutanix sales challenge, how do you move faster with all that incumbent, legacy stuff in these datacenters, while enabling the multi-cloud capability? >> And we're gonna be talking about that more today with Chris Kaddaras on the show. We have a lot of great guests, we have the CIO, Wendy Pfeiffer, I was reading an article about her today, she answered an ad as a teenager to work for NASA. She had an idea for NASA and so we're gonna hear much more about her story, we've got a lot of great guests. >> Well what's your take? I mean, you've been here, you're getting immersed in. What's your take of the show, what's your analysis? >> Well, what's really interesting to me is that we're having this conversation against this backdrop where, the technology industry is really under fire. I mean, we heard Ayanna Howard here on the show yesterday and then she was up on the main stage today, talking about the good, the bad, and then the really scary elements of AI and how it really has these powers that can do a lot of wonderful things and help children with special needs and help workers be more productive and engaged and collaborate. But yet, there's also this much darker side that AI's really only as good as its creators. And then the other difficulty is that, because we have become so trusting of these machines, we disregard our own intuition. And that is a really scary element, so. What I think is exciting, and it goes back to this risk taking mentality, that Nutanix has, is, we're gonna talk about these things. We're just going to forget about them or they're gonna be a sideshow, this is really on the main stage, let's talk about our values, let's talk about the humanity of technology and this is really an important part of the conversation. >> It's interesting, the culture, we talked about the culture a lot yesterday. And you can see from the mix of the guests we've had here and how they're putting their content together across the show portfolio, it's not just speeds and feeds. There's a lot of tech for good angle but they're not tech for good stories like hey, look, here's a tech for good story. Look how good we are because we promote it. They're authentic people that have a great story that has a tech involvement. But it's not a pure Nutanix messaging kind of thing. >> Right, and it goes to back to their values, the humble, hungry, honest, and have a lot of heart. I mean I think that that is, you really see how important culture is, when it is top down. When Dheeraj embodies certain characteristics and traits, you see that employees then look up and they say okay, this is what we're about, this is who we are. >> You know, we also talked yesterday about our analysis in the keynote, what's interesting about culture is, there's also a culture shift going on inside their customer base. And again, it's back to this kind of Star Wars theme, Jedi knights and the revolution continuing for Nutanix, their opportunity is to continue to stay on the course, and this is gonna be a big bet for them, they gotta make some big bets on the technology side, which they're making, but also they have an opportunity because a lot of their installed base are rebels, right? So you have this rebellion IT guy, generational shift where you have DevOps coming in and Gene Kim who wrote the book on DevOps, runs the biggest DevOps event in the world, series of events, DevOps Enterprise Summit, he's even saying it's about 3% changeover. So I think there's a big tailwind coming for Nutanix. Around DevOps, operating models, in the enterprise and cloud where, the convergence of those two worlds coming together, and it's gonna be a younger generation, it's gonna be a different world. If that happens, I think that's gonna be something that Wall Street might not see. I think that's kind of an area. And that's gonna be a good tailwind for Nutanix. The other notable thing that I would point out from this show is, the presence of VMware visibly in the conversation. And I think Dheeraj was talking about, hey we don't mind talking about VMware because they validate the marketplace, they're the big 800 pound gorilla. And we're gonna continue to innovate around them. We don't need their Hypervisor, customers don't need to pay their vTax, that's his messaging, so that was a key notable. The other one was the challenge that Nutanix has, this is, again, might be a Wall Street insight for some of the Wall Street folks out there is that, their challenge has been getting new logos. Their cost to sales is a little bit high because they require POCs and once they get in there they usually win. And then their cost per sales, cost per order dollar on the sales side once they have a customer, is very low, they get more renewals and they have more net contract value so they have great customer economics on that side. The Hewlett Packard Enterprise deal for them, could bring them a tsunami of new logos. That could give them a lot of leverage and bring their customer base well above their 12,000 number now. And bring them up into a whole nother level. So I think the HPE deal will be a tell sign on the numbers, and if they can get more new logos in there, the big accounts that HP has through their channel, that's a big story. So VMware, HPE, culture, all the main story here. >> And of course we had HPE on the show yesterday, talking about that very development, so. We have lots more great content, great guests to come today, this has been just a ball hosting with you, so I'm really for another day. >> Very intimate show, I mean, Nutanix are a very intimate show they don't really care about the big numbers, they want the right numbers and that speaks to their culture. >> And they know their people. Because as we talked about many times, Mark Hamill, up on the stage yesterday, so, they know their community. Please stay tuned for more of the coverage from theCUBE of .NEXT here in Anaheim. I'm Rebecca Knight for John Furrier, stay tuned. (electronic music)

>> live from Anaheim, California. It's the queue covering nutanix dot Next twenty nineteen. Brought to you by Nutanix. >> Welcome back, everyone to the cubes. Live coverage of Nutanix Stott next here in Anaheim, California. I'm your host, Rebecca Night, along with my co host, John Farrier. We're joined by Jean Kim. He is an author, researcher, entrepreneur and founder of Revolution. Thank you so much for coming back on the Cube, Gene. >> Oh, thanks so much for Becca and always great seeing you and John. >> So you are a prolific author. You've written many books, including the Phoenix Project, The Deb Ops Handbook, given new one coming out. But this is this is the latest one we have here the Dev Ops Handbook >> twenty sixteen. And then we came up with a little bit cool accelerate based on the state of Davis report. And yeah, it's been a fun ride. Just what a great space to be writing about >> Dev ops has been. I'LL see that covered going back years. Now it's mainstream, and you started to see the impact of people who have taken the devil's mentality put promise and the place we see all the you know, Web scales from Facebook, you name. But now the enterprises is now really looking at agility scenario. You've been working a lot on you Host the Devil Devil Enterprise Summit. What's that been like? I mean, it seems to be well taken longer than some of the hard core cloud guys. So what's the State of the Union, if you will, for the enterprise from a devil standpoint? >> Yeah, What a great question. I mean, I think there's no doubt that the devil's principles and practices were pioneered in the tech giant's Facebook's Amazon necklace and Google's, but I've long believed with a certain level certainty that a CZ much economic values they've created, uh, that's just the tip of the iceberg. The real value will be created when you know the largest, most complex organization, the planet adopting same principles of patterns. And when you have Ah yeah, I think I. D. C said there's eighteen million developers on the planet of which, at maximum, no half million at the tech trying and the rest are in, you know, the largest brands across every industry vertical. And if we could get those seventeen and a half million developers as productive as if there were at Facebook Amazon, that for school I'm not, generates trillions of dollars of economic value per year. And when you know what, that much, um, economically being created. I mean, we'LL have undoubtedly, you know, incredible societal improving outcomes as well. So it has been such a treat to help chronicle that journey. >> One of the things I want to ask you. Genes that doesn't impressive numbers, but also UV factor and net new developers, younger generation, re skilled workers used to be a network. I now I'm a developer. You seeing developers really at the infrastructure level now. But show like this where Nutanix is a heart was a hardware company there now a software company. So they're ato heart of Jeb ops. In terms of their target audience, they're implementing this stuff, So this is a refreshing change. So I gotta ask you when you walk into an enterprise, what is the current temperature of our I Q of Dev ops are they are their percentage. That's you know, they're some are learning. Take us through kind of the progress. >> If I would guess right? This has much as I love statistics and you know, comprehensive benchmarking. Yeah, I think we're three percent of the way there. Alright, I percent Yeah, you know, we're in the earliest stages of it, Which means the best is yet to come. I think develops is an aspiration for many on DH. No, but having to change the I think Dave is often a rebellious group rebelling against agent powerful order right now, uh, forces far beyond their control. Conservative groups protecting their turf. I think that's kind of the, uh, probably a typical situation. And so, you know, we're a long way away from Devil's being the dominant orthodoxy. >> So if that's the case, just probably some people who have adopted it had success we're seeing in these new, innovative shifts. The early adopters have massive value extraction from that. So and that's an advantage. Committed advantage. Can you give us some examples of people who did that took the rebellion that went to Dev Ops were successful and then doubled down on it? >> Yeah, I think the one that come to mind immediately are like Capital one. Yeah, they went from eighty percent outsourcing to now. Almost hundred cent Insourced. Same with target, where they're really started off as a uh ah bottom up movement and then gain the support of the highest levels of leadership. And it has been so exciting to see the story's not just told by technology leaders, but increasingly shared and being told by both the technology leader and a business counterpart were the business leader is saying, I am wholly reliant upon my technology, Pierre, to achieve all the goals, dreams and aspirations of our organization. And that's what a treat, to be able to see that kind of recognition and appreciation. >> It's an operational shift to They have to buy into changing how they operate as a company. Yes, and believe me, they're like clutching on to the old ways. And that's just the way it is. A >> wonderful phrase from the NUTANIX CEO that Loved is that way often characterized that developers as the builders, but operation infrastructure, they are builders, too. In fact, you know, developers cannot be productive if they are mired in infrastructure, right? And so, uh, you know, uh, you know, you get a peek. Productivity focus flown joy when you don't have to deal with concerns outside of the business feature and the visibility. One solved. And I know that from personal experience where the frustration you have when you just want to do one thing and you just carved out a door ten things that you just can't do because you have two. Puzzle is a puzzle. They have solved >> it. Love to get your reaction, tio some of the trends that I'm seeing because Kev Ops has been such an important movement, at least from my standpoint, because people could get lost in the what the word means at the end of the day program ability, making infrastructures code, which is the original ethos. Making the officer programmable and invisible, which is one of the themes of nutanix was the dream. That kind of is the objective, right? I mean, to make it programmable. So you don't that stand up all these services and prep and provisions Hard infrastructure stuff? >> Yeah. Yeah. In November, the Unicorn project is coming out. So it's the follow into the Phoenix project, and I'm really trying to capture how great it feels when you could be productive and all of infrastructures taken care of for you by your friends and infrastructure. Right then allows youto you know, have your best energy focusing on solving a business problem, not on how to connect a to B. And we need to expect to see in the yamma files and configuring. You know, all these things that you don't really care about, but you're forced to write, and I think that allows ah, level of productivity and joy. But also, >> uh, >> of, uh, >> is that the idea working relationship between development and infrastructure, where developers are costly thanking their infrastructure, appears for making their life easy >> way. We're joking. Rebecca and I were joking about how we use Siri ate Siri. What's the weather in Palo Alto? This should be an app for the enterprises says Hey, Cube or whatever at NUTANIX or whatever. Give me some more storage. Why isn't it happening? But that's that's that's That's kind of a joke, but it's kind of goal. Oh, increasing the right >> that's just available on demand right on. You certainly don't have to open up thirty tickets these days. Like was so typical ten years ago that that's a modern miracle. >> My question for you is why books? I mean, so here here we have were in this very fast changing technological environment and landscape. And as you said, the Dev Ops is still relatively new. There's it's not. It's a three percent really who understand it. Why use a bunch of dead tree just to get your message across? I was like writing, in fact and an ideal >> month, and I get to spend half the time writing and half the time hanging out with the best in the game, studying now that the greatest in the field. And I think even in this day and age, there's still no Maur effective and viral mechanism spread ideas and books. You know, when people someone says, Hey, I love the finished project I'd loved reading it. It says a couple things right. They probably spent eight hours reading it on. You know, that's a serious commitment. And so I think, Imagine how many impression minutes, you know it takes a purchase. Eight minutes, eight hours of someone's time. And so for things like this, I really do think that you know, the written form is still won most effective ways. Tio communicate ideas. >> Your dream job. You're writing out the best people. What did you What have you learned from the these people. >> Oh, my goodness, >> you could write a book. Yeah, >> but for twenty years, I self identified as an operations person. Even that well, I was formally trained to develop Our got my graduate degree in compiler design in nineteen ninety five. And so for twenty years, I just loved operations. This because that's where the action was. That's what saves happened. But something changed. About four years ago. I learned at programming language called Closure. It's a functional programming languages, a list so very alien to me, the hardest thing I've ever learned. I mean, I must have read and watched eighty hours of video before I wrote one line of code, but it has been the most rewarding thing. And it's just that, uh, exactly brought the joy of development and encoding back into my daily life. So So I guess I should amend my answer. I would say it's half the time writing half the time hand with the best of game and twenty percent coding just because I love to solve problems, right? Yeah, my own problems. So So I have I would thank people I get I you know, I've been able to hang out with and had the privilege to watch because, um, if it weren't for that, I think I would been happy. No, just saying that coding was a thing of the past. Right? S o for that. I'm so grateful. >> How do you use what you learn about in terms of your writing and in your coding and vice a versa. I mean, So how are they different in how are they the same? >> Uh, that's a great question. You >> know, I think >> what's really nice about coding is that it's, uh that's very formal. I mean, in fact, the most extreme. It's all mathematics, right? The books are just a pile of words that may or may not have order and structure. And so, in the worst days, I felt like with the Unicorn Project, I wrote one hundred fifty thousand words. Target work count is one hundred thousand, and I was telling friends I wrote one hundred fifty thousand words that say nothing of significance, right? What have I done The best days and that's I think that's because you have to impose upon it a structure and a point right on the best days is very much like coding. Everything has a spot, right? Uh uh, And you know what to get rid of. So, uh, yeah, I think the fact that coding has structure, I think makes it in some ways an easier for me to work >> with. And what brings you to new tenants next this week? What's the story? Which >> I gotta say I had the privilege and was delighted to take part in what they called deaf days. So if they were gathering developers to learn about educate everyone on how to use, uh, the new Tanis capabilities through AP eyes just like he said, right to help enable automation, and, uh, I just find it very rewarding and fulfilling. I just because even though I think nutanix er as a community is known for being the, uh, the innovators and the, uh so the rebellion a cz productive as you know, that technology's made them to turn into an automated platform. And I think that's another order of magnitude gain in terms of value they could create for their organization. So that was a >> tree. And they've transformed from an operations oriented box company years ago and now officially subscription based software. They're going all software. They're flipping their model upside down, too. >> And it was just a delight to see the developers who are attracted to that one day thing I would recommend to anyone who's interested in development on just being on the cutting edge of what could be done with it. For example, if you have cameras in every store is their way to automate the analysis that you compute dwell times and, you know, Q abandonment rates. I mean, it's like a crash course in modern business practices that I thought was absolutely amazing. >> Well, Jean, you do great work. I've been following you for years. I know you're very humbles. Well, but give a plug. Take a minute to explain the things you're working on. You got a great event. You run, you gotta books. What other things you got going on? Shared the audience. >> Just those two things that were just Everything is about the book right now. The Unicorn project is coming in November. Uh, and so accepts Will be available at the Devil sent five summit in London s O. That's a conference for technology leaders from large, complex organizations and over the years, we've now chronicle of over two hundred case studies by technology leaders from almost every brand across every industry vertical. And it has been such a privilege toe. See, hear the stories and to see how they're being rewarded for their achievements. I mean there being promoted on being given more responsibility. So that is, Ah, treat beyond words >> and it's a revolution. It's a shift that's definitely happening. You're in the bin and doing it for years, and we're documenting it so and you are a CZ. Well, >> I'm looking forward to see you there. >> I just have one final question and this is about something you were saying about how Nutanix is the insurgent and the rebel the rebel in office. How does it How do you recommend it? As a researcher, as an entrepreneur yourself and as someone who's really in this mindset, how do you recommend it? Stay feisty and scrappy and with that mentality at it, especially as it grows and becomes more and more of a behemoth itself? >> Um, there was some statements made about, like how, ten years ago, virtual ization was the one key certification that was guaranteed. You relevant stuff forever in the future. And, yeah, I think there's some basis to say that, you know, that alone is not enough to guarantee lifetime employment. And I think the big lesson is you know, we all have to be continual learners and, you know, every year that goes by, you know, they're Mohr miracles being >> ah ah, >> being created for us to be able to use to solve problems. And if that doesn't think the lesson is if we're not, uh, always focused on being a continual Lerner, Yeah, there's great joy that comes with it and a great peril, You know, if we choose to forego it. >> Well, that's a great note to end. Thank you so much for coming back on the Cube. Gene. >> Thank you so much. And not great CD. Both. Thanks. >> I'm Rebecca Knight for John Furrier. We will have much more from dot next, just after this

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back it ready Jeff Rick here with the cube we're in our Palo Alto studios today for a cube conversation a little bit of a break from the road we'd like to have guests come into the palo alto studio and have a little bit calmer conversation without all the buzz of the show and we're excited to have a return guest he hasn't been on for like two and a half years which i find extremely hard to believe it's been too long maria tar she's the CMO of keysight technologies really great to see you wonderful yeah so last time we had you on i had to look it up it was it was october 2016 and you were the CMO of Ixia which is a little bit different or really not that different tell us how you got from ixia to to keysight so keysight technologies acquired Exia and i was fortunate enough to be chosen to be the CMO for keysight technologies so it was a great evolution both for me personally and professionally right and a very kind of similar product and solutions portfolio bigger obviously than what you were doing at Ixia but for people that aren't familiar with keysight give them kind of the quick overview sure so Ixia served two audiences they really targeted the QA engineer as well as the IT infrastructure and keysight actually targets I would say the design engineer the manufacturing engineer part of the Ixia business which is very closely aligned to keysight's is in the test and measurement space so keysight technologies really helped any electrical engineer develop and innovate and bring products to market that that basically have an electric signal going through them what keysight delivers are things like oscilloscopes Network analyzers you know power supplies signal generators and and anything in terms of test and measurement right of design of electronics so you guys in companies been around for a while is four billion in revenue so you guys are basically testing and measuring pretty much everything right this as you say has an electronic signal go through it we have a broad area that we cover and we also have a very very long history in terms of being in this space our heritage started off as the original heel at Packard evolved into Agilent and keysight was spent out about four four or five years ago as an independent company and we're doing really well in terms of raising our awareness and visibility of a new name because anytime you change names you have to re-educate the market right hey this is us you've worked with us for a very long time and we continue to be leaders in this space right good opportunity for you though right that's the that's what they can good see in Mo's four I love my so the cool thing is not only are you working with stuff that's shipping today but you guys have good visibility into the future and as we talked about all the time you know there's some really massive mega trends that are that are coming down the pike that would love to you know kind of get your thoughts off one of them is is 5g and where World Congress was just a couple weeks ago I think you're also at RSA 5g has been getting talked about for a while but it's it's coming and and we see more and more parts I think there's actually been a couple hands that's delivered you probably know way more than I intended tower so wonder if you can explain to people a little bit about 5g when you think about five gene their potential because I don't think many people know much beyond kind of the buzzword that it's you know bigger faster stronger but it's a pretty significant leap over the Kern LTE it's truly a revolutionary and disruptive technology and it enables so much more than what's available today which has really been what I would call incremental evolution with 5g it is it's truly transformative because it you know in addition to faster it is going into spectrum that was traditionally reserved for organizations getting into millimeter-wave so it really changes the technology that we're all used to with the big cell towers 5g uses much smaller antennas and multiple antennas that actually sit on buildings it's you know in terms of because you're using millimeter wave it doesn't travel as long distances there's what you have with LTE which is sub 6 gigahertz that's all on the technology front what's really amazing about 5g is it has capabilities such as ultra-low latency and it's supposed to consume a lot less power so you could almost see it as as really disrupting and transforming everything and how we think about everything whether it's enabling the car of the future and autonomous driving because now all of a sudden your car can actually communicate to everything with vehicle to everything communication or cellular vehicle to everything communications you can think about it as a way that it's transforming IOT and the evolution of everything that's happening in IOT right so yes it's bigger faster better much more reliable you know much more lower latency and and for for those of us who care a lot about sustainability it's supposed to also deliver much lower power consumption right just interesting right because LTE was I think kind of the first step into real data space and and people figured out that we're using our phones for a lot more than talk in fact you know the data transmission rates are way higher than then the voice course on voice over IP and people watched football on their on their TV switches or on their screens which is unimaginable a couple years ago but in 5g now that's really not necessarily optimized for but really an enabler for as you said IOT and kind of this next level of you know kind of machine to machine communication it's not just me texting you with a data input but more these super-high fast really require low latency applications in this IOT and in the industrial IOT world that everybody's so psyched about it can't happen without this type of technology it really can't I mean the whole industry 4.0 and in terms of manufacturing and robotics and real-time communication that can happen in in in that if you think about a lot of the the cars that are out there if you look at Tesla they're doing ongoing updates and ongoing communications with all their cars all the time and so something like 5g enables even a higher degree of communication and understanding of what's going on with the vehicle and as you get into more of autonomous vehicles understanding what all the sensors and the radar in the car is seeing basically communicating that to what's happening with edge computing having all of that processing happen there and being able to you know send that back and and be able to adapt to the environment is going to be pretty significant and revolutionary I mean I think in every area this new technology in some ways just in terms of what it opens up will enable us to think of really transformative and disruptive ways of how we do things right and it does require going along for the ride investing early understanding what it means and I would say it crosses so many vertical industries right we definitely have to have lunch with you and Sandra Rivera from Intel it would be a really really fun lunch but I one of the things you touched on with that I don't think people really appreciate is this kind of new age of connected device and clearly Tesla's an easy example right it checks in every night but as we see more and more devices being connected kind of back to the mothership and and the ability for a maker of something to actually know now how are people using it it's not just I build it I ship it to my distributor and maybe I'll get a few back every now and then and we can we can take it apart and see how people used it but just the whole kind of product management lifecycle when you've got connected devices that actually report home and to how they're actually being used and how people are using them is such a transformational both the relationship between the user and the device but now the device back to the man you that they never never used to have before yeah and it has both kind of technological as well as I would say society oriented ramifications if you think about in the Tesla example you're effectively saying hey it's okay for Tesla to constantly talk to my car a lot of times we're used to the model of once I buy something it's mine you know this is my device not something that's part of your ongoing network so to speak and so with with a lot of these evolutions that are going on there's going to be both a capability shift in terms of what we can enable but there's also going to come with it somewhat of a society shift of what's now accessed about you so for example with IOT if you choose to move towards this concept of body area networks and having sensors all over you or potentially even embedded in you how that is being leveraged to provide you information how do you protect that from a security standpoint from someone tapping into that to abuse that information so a lot of those topics were really big topics at Mobile World Congress in terms of the coming of 5g and you know just even kind of there the the completion of the standard because it's not yet fully ratified yet right so there's ongoing evolutions and not there's obviously a lot of hype out there on this we are very much involved with the whole ecosystem that's involved in 5g all the way from chipsets to the devices to the networks that carry them you know sort of looking at the whole end-to-end eCos to the antennas you name it to the base stations we're involved in in that whole ecosystem and you as keysight we actually have to get in really early because all of those innovators are depending on our technology to test and validate that it will perform as expected because you're working with all those pieces of electronics in that hole that holes system yeah well Mobile World Congress is interesting last week or the week before was our essay and a lot of the things you're talking about I would argue are probably gonna be more important on the RS a type of kind of view of the world versus the Mobile World Congress assuming you get everything to work which which which I'm sure everybody will but but kind of the legal ramifications and the moral ramifications and the data privacy ramifications when there is so many more connected devices and as you said body area network right now it's my heart rate I went to an interesting Wall Street Journal conference where people can sell back their 23andme genomic data back into a pool for researchers who are looking for certain profiles so they can do their clinical trials and you know that's basically it's basically an electronic representation of literally who you are and so again I think you I think you touch on a lot of really important points that it's the security and David privacy and and in the the moral issues around how that's used treated stored protected are gonna be the bigger issues as we just get more and more of these things becoming really its software and data which we see in the products tehsils a lot more software than it is a car and that's why they can do updates all the time and keep updating the features well even in our business we're becoming much more of a software oriented business in terms of our test and measurement and how we look at the whole design workflow and to end so in many ways everything is is becoming software right just because if you think about this concept of the digitization that's going on of everything there's a lot of discussions about this concept of digital twins right where there's enough information derived from something physical that you can essentially replicate the digital twin and you can do the simulations and in in what you're describing you know you basically you could potentially have it model and represent whether it's a robotic process or a car process and anticipate hey this is time when this is going to wear down you know this is what I'm seeing out there and and it's almost becomes predictive right in terms of what's going on in the real world so it's it's really exciting stuff and it's wonderful to be at the because of this right going to RSA i agree with you all of those topics we're front and center very important to understand and have the visibility in terms of a lot of these 5g networks there's so much throughput going in how do you you know let's say you're a service provider and you want to offer this service how do you actually measure and have visibility in terms of really that is the service that you're offering so there's a lot of discussion in terms of providing that visibility and that security in terms of for those types of customers right it's funny we've done a lot of stuff with GE and back with the software group with Bill ruin team and they've talked about gee talks about digital twins a lot in the context of the industrial products that they built whether it's a turbine engine or whatever to the point that you said so you can do testing and you can do maintenance scheduling and all this other stuff what was weird at the Wall Street Journal conferences they're talking about digital twins for people your digital twins so now I can test you know how would you respond to certain drug treatments how might you respond to a different diet regime how might you respond differently to a different exercise regime and I'd never kind of heard that digital twin concept applied to a person and it's that's really interesting it's really interesting times but before I let you go I imagine your business has changed quite a bit as the kind of percentage of make up of all these devices has shifted from you know kind of dedicated purpose-built hardware which is probably relatively easy to test to kind of hardware platforms that are supporting a larger and increasing amount of software that actually drive the functionality must be good for your business because I'm sure the testing has got to be much more complex not to mention people are pushing updates all of the time really different models and just testing a box well it has changed and actually what's you know when I talk to our customers their goal is to innovate and bring their products to market faster and as a company that supports them our goal is to accelerate their innovation and a lot of times it's how do you share the information as it's going from the design engineer - you know sort of the the quality and test - then go to manufacturing because a designer will build his product and then he'll send it off and say ok I'm kind of done how do you then make sure that at every cog of the wheel you're basically able to share back what his expectation were when he was building it in a CAD system versus what what they're actually seeing when they test the real-life product versus what they actually see when they're manufacturing and applying the same tests so having that consistent software which at keysight we call path wave it really allows that acceleration and the sharing across all of those different groups so that you can optimize the flow so to speak of your design the other exciting part is is you're right there's just so much innovation and evolution in terms of the areas that we participate in because all of these technologies are changing you know we talked about sort of the the autonomous vehicle just as important as the electric vehicle and and the growth in terms of how do you manufacture and test batteries in a scale that's going to be required to keep up with the demand because traditional methods it takes a long time to to test a battery to make sure it's available and can be used and we have some really innovative technology that allows us to to expedite and accelerate that testing so customers of ours like BMW are leveraging this technology so that they can accelerate their their battery production testing and deployment right well we'll have to have you back another time we're out of time dig just just I'm so excited by the whole kind of change of mobility which is driven by really high capacity inexpensive batteries and these really powerful little brushless motors and and as those things kind of permeate and all these different form factors thankfully driven by the high bania fact or the high volume car manufacturers since it's the same little cells that run a lot of these things it's pretty pretty cool space but but we can't get deep into that this time I'll have to say throw for next time so hopefully it won't be another two and a half years I hope very well thanks for stopping by and really appreciate catching up thanks a lot Jeff good see you alright she's Marie I'm Jeff you're watching the key we're in her cube Studios in Palo Alto thanks for watching we'll see you next time [Music]