(gentle music) >> Welcome back to theCUBE's virtual program, covering VMware Explorer, 2022. The first time since 2019 that the VMware ecosystem is gathered in person. But in the post isolation economy, hybrid is the new format, cube plus digital, we call it. And so we're really happy to welcome Cal Al-Dhubaib who's the founder and CEO and AI strategist of Pandata. And Jonathan Seckler back in theCUBE, the senior director of product marketing at Dell Technologies. Guys, great to see you, thanks for coming on. >> Yeah, thanks a lot for having us. >> Yeah, thank you >> Cal, Pandata, cool name, what's it all about? >> Thanks for asking. Really excited to share our story. I'm a data scientist by training and I'm based here in Cleveland, Ohio. And Pandata is a company that helps organizations design and develop machine learning and AI technology. And when I started this here in Cleveland six years ago, I had people react to me with, what? So we help demystify AI and make it practical. And we specifically focus on trustworthy AI. So we work a lot in regulated industries like healthcare. And we help organizations navigate the complexities of building machine learning and AI technology when data's hard to work with, when there's risk on the potential outcomes, or high cost in the consequences. And that's what we do every day. >> Yeah, yeah timing is great given all the focus on privacy and what you're seeing with big tech and public policy, so we're going to get into that. Jonathan, I understand you guys got some hard news. What's your story around AI and AutoML? Share that with us. >> Yeah, thanks. So having the opportunity to speak with Cal today is really important because one of the hardest things that we find that our customers have is making that transition of experimenting with AI to making it really useful in real life. >> What is the tech underneath that? Are we talking VxRail here? Are you're talking servers? What do you got? >> Yeah, absolutely. So the Dell validated design for AI is a reference framework that is based on the optimized set of hardware for a given outcome. That includes it could be VxRail, VMware, vSphere and Nvidia GPUs and Nvidia software to make all of that happen. And for today, what we're working with is H2O.ai's solution to develop automatic machine learning. So take just that one more step to make it easier for customers to bring AI into production. >> Cool. >> So it's a full stack of software that includes automated machine learning, it includes NVIDIA's AI enterprise for deployment and development, and it's all built on an engineering validated set of hardware, including servers and storage and whatever else you need >> AI out of the box, I don't have to worry about cobbling it all together. >> Exactly. >> Cal, I want to come back to this trusted AI notion. A lot of people don't trust AI just by the very nature of it. I think about, okay, well how does it know it's a cat? And then you can never explain, it says black box. And so I'm like, what are they do with my data? And you mentioned healthcare, financial services, the government, they know everything about me. I just had to get a real ID and Massachusetts, I had to give all my data away. I don't trust it. So what is trusted AI? >> Well, so let me take a step back and talk about sobering statistics. There's a lot of different sources that report on this, but anywhere you look, you'll hear somewhere between 80 to 90% of AI projects fail to yield a return. That's pretty scary, that's a disappointing industry. And why is that? AI is hard. Versus traditional software, you're programming rules hard and fast. If I click this button, I expect A, B, C to happen. And we're talking about recognizing and reacting to patterns. It's not, will it be wrong? It's, when it's wrong, how wrong will it be? And what are it cost to accept related to that? So zooming back in on this lens of trustworthy AI, much of the last 10 years the development in AI has looked like this. Let's get the data, let's race to build the warehouses, okay we did that, no problem. Next was race to build the algorithms. Can we build more sophisticated models? Can we work with things like documents and images? And it used to be the exclusive domain of deep tech companies. You'd have to have teams of teams building the software, building the infrastructure, working on very specific components in this pipeline. And now we have this explosion of technologies, very much like what Jonathan was talking about with validated designs. So it removes the complexities of the infrastructure, it removes the complexities of being able to access the right data. And we have a ton of modeling capabilities and tools out there, so we can build a lot of things. Now, this is when we start to encounter risk in machine learning and AI. If you think about the models that are being used to replicate or learn from language like GPT-3 to create new content, it's training data set is everything that's on the internet. And if you haven't been on the internet recently, it's not all good. So how do you go about building technology to recognize specific patterns, pick up patterns that are desirable, and avoid unintended consequences? And no one's immune to this. So the discipline of trustworthy AI is building models that are easier to interrogate, that are useful for humans, and that minimize the risk of unintended consequences. >> I would add too, one of the good things about the Pandata solution is how it tries to enforce fairness and transparency in the models. We've done some studies recently with IDC, where we've tried to compare leaders in AI technology versus those who are just getting started. And I have to say, one of the biggest differences between a leader in AI and the rest of us is often that the leaders have a policy in place to deal with the risks and the ethics of using data through some kind of machine oriented model. And it's a really important part of making AI usable for the masses. >> You certainly hear a lot about, AI ultimately, there's algorithms which are built by humans. Although of course, there's algorithms to build algorithms, we know that today. >> Right, exactly. >> But humans are biased, there's inherent bias, and so this is a big problem. Obviously Dell, you have a giant observation space in terms of customers. But I wonder, Cal, if you can share with us how you're working with your customers at Pandata? What kind of customers are you working with? What are they asking? What problems are they asking you to solve? And how does it manifest itself? >> So when I like to talk about AI and where it's useful, it usually has to do with taking a repetitive task that humans are tasked with, but they're starting to act more like machines than humans. There's not much creativity in the process, it's handling something that's fairly routine, and it ends up being a bottleneck to scaling. And just a year ago even, we'd have to start approaching our clients with conversations around trustworthy AI, and now they're starting to approach us. Really example, this actually just happened earlier today, we're partnering with one of our clients that basically scans medical claims from insurance providers. And what they're trying to do is identify members that qualify for certain government subsidies. And this isn't as straightforward as it seems because there's a lot of complexities in how the rules are implemented, how judges look at these cases. Long story short, we help them build machine learning to identify these patients that qualify. And a question that comes up, and that we're starting to hear from the insurance companies they serve is how do you go about making sure that your decisions are fair and you're not selecting certain groups of individuals over others to get this assistance? And so clients are starting to wise up to that and ask questions. Other things that we've done include identifying potential private health information that's contained in medical images so that you can create curated research data sets. We've helped organizations identify anomalies in cybersecurity logs. And go from an exploration space of billions of eventual events to what are the top 100 that I should look at today? And so it's all about, how do you find these routine processes that humans are bottlenecked from getting to, we're starting to act more like machines and insert a little bit of outer recognition intelligence to get them to spend more time on the creative side. >> Can you talk a little bit more about how? A lot of people talk about augmented AI. AI is amazing. My daughter the other day was, I'm sure as an AI expert, you've seen it, where the machine actually creates standup comedy which it's so hilarious because it is and it isn't. Some of the jokes are actually really funny. Some of them are so funny 'cause they're not funny and they're weird. So it really underscored the gap. And so how do you do it? Is it augmented? Is it you're focusing on the mundane things that you want to take humans out of the loop? Explain how. >> So there's this great Wall Street Journal article by Jennifer Strong that she published I think four years ago now. And she says, "For AI to become more useful, it needs to become more boring." And I really truly believe in that. So you hear about these cutting edge use cases. And there's certainly some room for these generative AI applications inspiring new designs, inspiring new approaches. But the reality is, most successful use cases that we encounter in our business have to do with augmenting human decisions. How do you make arriving at a decision easier? How do you prioritize from millions of options, hundreds of thousands of options down to three or four that a human can then take the last stretch and really consider or think about? So a really cool story, I've been playing around with DALL.E 2. And for those of you who haven't heard, it's this algorithm that can create images from props. And they're just painting I really wish I had bought when I was in Paris a few years ago. And I gave it a description, skyline of the Sacre-Coeur Church in Montmartre with pink and white hues. And it came up with a handful of examples that I can now go take to an artist and say paint me this. So at the end of the day, automation, it's not really, yes, there's certain applications where you really are truly getting to that automated AI in action. But in my experience, most of the use cases have to do with using AI to make humans more effective, more creative, more valuable. >> I'd also add, I think Cal, is that the opportunity to make AI real here is to automate these things and simplify the languages so that can get what we call citizen data scientists out there. I say ordinary, ordinary employees or people who are at the front line of making these decisions, working with the data directly. We've done this with customers who have done this on farms, where the growers are able to use AI to monitor and to manage the yield of crops. I think some of the other examples that you had mentioned just recently Cal I think are great. The other examples is where you can make this technology available to anyone. And maybe that's part of the message of making it boring, it's making it so simple that any of us can use it. >> I love that. John Furrier likes to say that traditionally in IT, we solve complexity with more complexity. So anything that simplifies things is goodness. So how do you use automated machine learning at Pandata? Where does that fit in here? >> So really excited that the connection here through H2O that Jonathan had mentioned earlier. So H2O.ai is one of the leading AutoML platforms. And what's really cool is if you think about the traditional way you would approach machine learning, is you need to have data scientists. These patterns might exist in documents or images or boring old spreadsheets. And the way you'd approach this is, okay, get these expensive data scientists, and 80% of what they do is clean up the data. And I'm yet to encounter a situation where there isn't cleaning data. Now, I'll get through the cleaning up the data step, you actually have to consider, all right, am I working with language? Am I working with financial forecasts? What are the statistical modeling approaches I want to use? And there's a lot of creativity involved in that. And you have to set up a whole experiment, and that takes a lot of time and effort. And then you might test one, two or three models because you know to use those or those are the go to for this type of problem. And you see which one performs best and you iterate from there. The AutoML framework basically allows you to cut through all of that. It can reduce the amount of time you're spending on those steps to 1/10 of the time. You're able to very quickly profile data, understand anomalies, understand what data you want to work with, what data you don't want to work with. And then when it comes to the modeling steps, instead of iterating through three or four AutoML is throwing the whole kitchen sink at it. Anything that's appropriate to the task, maybe you're trying to predict a category or label something, maybe you're trying to predict a value like a financial forecast or even generate test. And it tests all of the models that it has at its disposal that are appropriate to the task and says, here are the top 10. You can use features like let me make this more explainable, let me make the model more accurate. I don't necessarily care about interrogating the results because the risk here is low, I want to a model that predicts things with a higher accuracy. So you can use these dials instead of having to approach it from a development perspective. You can approach it from more of an experimental mindset. So you still need that expertise, you still need to understand what you're looking at, but it makes it really quick. And so you're not spending all that expensive data science time cleaning up data. >> Makes sense. Last question, so Cal, obviously you guys go deep into AI, Jonathan Dell works with every customer on the planet, all sizes, all industries. So what are you hearing and doing with customers that are best practices that you can share for people that want to get into it, that are concerned about AI, they want to simplify it? What would you tell them? Go ahead, Cal. >> Okay, you go first, Cal. >> And Jonathan, you're going to bring us home. >> Sure. >> This sounds good. So as far as where people get scared, I see two sides of it. One, our data's not clean enough, not enough quality, I'm going to stay away from this. So one, I combat that with, you've got to experiment, you got to iterate, And that's the only way your data's going to improve. Two, there's organizations that worry too much about managing the risk. We don't have the data science expertise that can help us uncover potential biases we have. We are now entering a new stage of AI development and machine learning development, And I use those terms interchangeably anymore. I know some folks will differentiate between them. But machine learning is the discipline driving most of the advances. The toolkits that we have at our disposal to quickly profile and manage and mitigate against the risk that data can bring to the table is really giving organizations more comfort, should give organizations more comfort to start to build mission critical applications. The thing that I would encourage organizations to look for, is organizations that put trustworthy AI, ethical AI first as a consideration, not as an afterthought or not as a we're going to sweep this on the carpet. When you're intentional with that, when you bring that up front and you make it a part of your design, it sets you up for success. And we saw this when GDPR changed the IT world a few years ago. Organizations that built for privacy first to begin with, adapting to GDPR was relatively straightforward. Organizations that made that an afterthought or had that as an afterthought, it was a huge lift, a huge cost to adapt and adjust to those changes. >> Great example. All right, John, I said bring us home, put a bow on this. >> Last bit. So I think beyond the mechanics of how to make a AI better and more workable, one of the big challenges with the AI is this concern that you're going to isolate and spend too much effort and dollars on the infrastructure itself. And that's one of the benefits that Dell brings to the table here with validated designs. Is that our AI validated design is built on a VMware vSphere architecture. So your backup, your migration, all of the management and the operational tools that IT is most comfortable with can be used to maintain and develop and deploy artificial intelligence projects without having to create unique infrastructure, unique stacks of hardware, and then which potentially isolates the data, potentially makes things unavailable to the rest of the organization. So when you run it all in a VMware environment, that means you can put it in the cloud, you can put it in your data center. Just really makes it easier for IT to build AI into their everyday process >> Silo busting. All right, guys, thanks Cal, John. I really appreciate you guys coming on theCUBE. >> Yeah, it's been a great time, thanks. >> All right. And thank you for watching theCUBE's coverage of VMware Explorer, 2022. Keep it right there for more action from the show floor with myself, Dave Velante, John Furrier, Lisa Martin and David Nicholson, keep it right there. (gentle music)

thecube presents dell technologies world brought to you by dell good afternoon everyone welcome back to thecube's third day of coverage live from the show floor at dell technologies world 2022 lisa martin here with dave vellante we've been having lots of great conversations the last day and a half one of the things we love to do is really hear from the voice of dell's customers and we're going to do that next please welcome jonathan suckler the senior director of product marketing for dell and keith bradley the vp of i.t at nature fresh farms guys welcome hey great to be here thank you great thank you for letting us be here of course thanks for joining us so jonathan we're going to start with you we've been hearing a lot about we've been talking about ai for decades we've been hearing a lot about ai at the show it's it's so it's pervasive right it's in our refrigerators and our thermostats and our cars and that hockey puck thing that's in the kitchen that plays music when you're cooking right what's going on what is do you think from dell's perspective is fueling the adoption of ai now you know there's it i think that there's this huge interest in ai right now and you and you you're definitely pointed out a lot of the great success stories around ai but the the real benefit of is that you know with with with artificial intelligence applied to a lot of business problems you can solve them in ways that are that are much quicker than you would expect you know and you can solve them in ways you wouldn't have expected uh uh you know then than than you do what's really surprising though is as a as many as many people are interested in in using it and and all of the benefits that come from it though is that we really don't see the adoption being as quick as we would like to right i mean i want to say that like 80 percent of companies out there want to use ai they're testing ai you know they're they're they're planning uh projects around ai applications but when you ask them what's in production it really is still it's an innovator's game like you know companies like like nature fresh farms with uh what they're doing is truly at the tip of the spear what are some of the challenges jonathan that you're seeing from an adoption perspective of 80 say we want to actually be able to leverage this emerging technology in production the challenges are i think the pers it's a perceived challenge issue right i think there's like three big issues that people perceive as being uh barriers to adoption um the first one is pretty obvious it's cost right they they see artificial intelligence you they hear about all of the uh you know specialized hardware and and the software and the new and the people and the talent you've got to acquire to uh as being a barrier to that and they don't see the benefit or they they balance that against the benefit i think there's an issue also with uh complexity right because at the same time that you know you're building these these infrastructures around what you need to do for an artificial intelligence-enabled application there's this expectation that it needs to be separate and different and special and that becomes an issue from a management perspective right uh and i think finally uh it's uh it's change right i mean you you're you're bringing in new talent new new skill sets you're bringing in new technology and i think a lot of companies still today you know look at that as being like well what if if i do this am i really going to see the benefit if i am i stuck going down a path that i that i'm going to change later on and i think that's really the issue uh you know those but they're all perceived issues they're they're in in reality they're really not that true i mean keith has this done that nature fresh farms has done some incredible stuff right with with ai in an area that i i would never have guessed being a ripe for that kind of innovation you know so lisa keith knows that i love you know fresh tomatoes i live in the northeast where it's cold six months a year so we plant our tomatoes at memorial day weekend yeah right and then maybe you're lucky if you get tomatoes late august september and then you're done however you and i met a couple years ago you sent me all these vegetables i think i was popping the tomatoes like candy and then i interviewed you you were live in the giant greenhouse and it's just amazing what you guys have going to jonathan's point you're using ai to really create you know sustainable continuing flow of awesome vegetables tell us more about nature fresh so at nature fresh farms we're a 200 acre greenhouse just shy of 200 acres growing bell peppers and tomatoes and one of the biggest use cases for us in our ai is everything we do we need to be proactive so we need that ai to not be reactive to climate change to what happens to the weather to be proactive so it changes before the plant reacts because every time the plant will doesn't do as great we've lost production from it so we're always using our ai to help increase the yield per square meter inside of our greenhouses so everything from the growth the length the weight of the plant we monitor everything we want to know every aspect of that plant's life it's almost like doing an ekg on a plant 24 by 7 and wanting to know everything out of it how old is is the company nature fresh farms started in 1999 so we're just hitting 23 years now so we started off as a 16 acre little greenhouse our owner kind of got into it saying i think this is going to be new and he was one of the first ones to say i want to be all computers i want to do it culturally this is this was not an upsell or a hard sell for you from the vp of i.t perspective no no he's always been one saying that technology will change the greenhouse industry and that by adding technology the expertise is in the growers and letting technology help them do more because when we first started in the greenhouse industry you'd need a grower for every range so every 16 acre range would need a very senior grower now we have one grower that does 64 or almost 100 acres of greenhouse he'll have junior growers but he's able to do so much more so where do you specifically apply the ai can you talk about that uh so we talk specifically we apply the ai in almost all areas anything from picking the plant to the climate of the plant we'll do all those areas even on the packing line we actually have uh one robot well not a robot story a machine that looks at a box of tomatoes and basically tells us which one doesn't match the proper red because how you see red how you guys see red is slightly different so it'll tell us that this red tomato doesn't match so change out the right one so when it goes down the line into the consumers they're all exactly the same so it looks unified it looks beautiful like that how about that you're sending out red tomatoes yeah yeah that's what we do now what is dell's role in all this so dell's role has helped us grow what we do we started off with power scale and vxrail and stuff like that so everything's hosted on that and they have been a great partner at finding that solution to them i've been able to go to them and say hey i'm running into a storage problem i'm running into a compute problem they've been able to find a validated solution for us to use and to put out there and help us grow and then the next part that was really great that we've really now done is it's scalable as we're growing we've been able to community add more compute and more storage but not have to take things down to do it and that's what we really wanted to do yeah no i i think and i think what you're talking about there is really the one of the big issues that i was talking about earlier which is around complexity and cost right you know one of the answers to doing artificial intelligence in the enterprise is making sure that you can maintain and have an infrastructure that scales that's part of everything else and and to do that you've got to virtualize it and you know with power uh with a dell vxrail and power scale which it's all running vmware uh with with the uh with the containers and the vms on top of that actually managing you know and running those applications it takes a lot of the complexity of of worrying about where you're going to how you're going to manage that infrastructure and who's going to do it who's going to back it up how are you going to how you're going to you know keep costs down so it really really helps i think yeah yep and we just love it because we're able to take that solution make it better and make it do more and more every day and it's it's allowed our growers to see exponential time where they did it years ago it used to be overnight to get results sometimes from our system doing it now we're seeing it in real time and that's where i it really got to that point now where we're being reactive proactive to the to the plant the weather to stuff we know exactly what needs to happen before happens and that makes the plant grow more and that's what we're always aiming to do you know if you don't mind one of the things that i you were telling me about i think is really fascinating so is this idea that you know you need to have a data scientist you need a whole new staff to manage these applications these these technologies but you were talking about your growers are actually yeah they're actually data scientists that way right that's what we like to call them we call them grower scientists right now green sciences data scientists yeah because they've researched this data they know what the plant does and it's it's been a neat transition we talked about that how they went from being out in the greenhouse so much to being in front of the computer now but now with the help of ai they're more able to get back out into the greenhouse to now watch the plants see what's going on and be a part of the growth again and they said it's been great but they're the ones that are looking at these numbers every day every second if it's not remotely from home it's remote on the greenhouse they're launching everything because yeah think about they're watching 64 acres of land and making sure that does everything it needs to do so lisa this is a really good example of sort of distributed data at work right about this whole notion of data mesh where you have domain experts actually own the data you know they know they can bring context to the data it's not somebody who's just oh it's just data i don't really know what to do with it it's somebody who actually knows what it what it means that to me is a future use case that's going to explode yep it's like me i i look at their data and they always tease me because i'll look at it and i'll go yeah i have no idea but it's giving you numbers so are they right or not and it's a it's always a joke in the in the plant that i like ah you don't got question marks so it's working and then i'll go to them and say is this right and then they'll say yep we're on we're getting what we need i love the idea that you know we've we've heard of this term citizens citizen scientists or citizen data scientists and you have a grower data scientist yeah and i think that eliminates you talk again those problems like or challenges i mentioned earlier that kind of eliminates the complexity issue you know the uncertainty issue the fear of change when you've got your own uh teams who are who know what they need to do and they have the data to do it it just changes the game right yeah and the other two we found is i've always believed in it myself if you love what you do yeah you commit so much more to it and our growers they love what they do so their passion just exudes into the data and then it comes right back into the product well the technology is an enabler of their passion really i'm curious keith how the obviously the events of the last two years have been quite challenging how has ai been a facilitator of what seems like a competitive differentiation for your company uh it actually really accelerated it because we really had to invest in it that's when we started the the big journey to the vx rail the power protect data management we really had to invest in and then we heavily invested in the ai we've always had some lingerie in the background and it's always been there and we've been using it for years and years now but it really brought it right to the forefront though we have to do this better and we had to really push everything and as we grew it became more and more apparent that we were taking that road that investment was paying off for us now yeah how do i buy ai from you so you know it's interesting like i said we want to make it easy for for customers to implement an ai solution at dell and it's not so much that you go out and you buy an ai right or something like that what you're doing is is you're you're making your infrastructure ready for the applications that you need to run right and so at dell we have this uh these predefined uh architectures that we call validated designs they're validated uh to work in you know in a co in any a common environment we take the you know we take the guesswork out of uh how to put these systems together uh and in the case of artificial intelligence you know we we validate with our partners like uh uh vmware and like nvidia to make sure that the technologies work together so that they fit into the existing infrastructure they already have and uh you know in a way it's i think of it as virtualized ai but i think even more importantly it's it's ai for for any company it's not not for the not for the special scientists and you know not for the not for the uh the researcher at the university it's it's for you know it's for nature fresh farms with vxrail it's software defined you're able to bring in a gpu you've got the flexibility to do that for example yeah whereas with the traditional you know the old days you wouldn't be able to do that you'd be you'd have a lot of time on your hands and a lot of compute power you spent a lot of money doing what you need to do yeah oh yeah we'd be spending all the time working at it growing it and doing more and it just made our life easier not to manage the life the managed life cycle of the ai systems that we have is so much easier now because it's all predefined it's all it's all ready to go upgrade process all that is built into it yeah so life cycle is much easier from the i.t side so keith talk to talk to those folks in the audience who might have those those perceived challenges or limitations that jonathan was talking about because you're making it sound like this has been such an enabler of a business that's 23 years old we're taking growers who are experts at growing and they're playing and loving playing with data and ai how do you how do you advise folks to really eliminate some of those preconceived challenges that are out there i would say you have to sit there and just dive in you have to actually start to do it but you have to think about not where you the first two steps say where we want to be five steps from now and then say talk to a partner like dell with us and say this is where we want to get to this is and then figure out a way how to get there and committing to that path you can't get frustrated the first few times ai is very flustering sometimes the first few pass don't work and just saying going back to the drawing board each time we'll do it we've had a couple experiments where it didn't work and we didn't get the results we wanted and we had to just say let's change our thought process and how do we optimize this ai and then all of a sudden we started getting the right results but that it's it's like uh falling over the first time you fall over as a child it's gonna hurt but each time he gets a little less each time failure is progress yeah that's right that's right fail fast yeah failure can be a good f word yeah if you but you have to be open-minded yep oh yes every minute every minute you have to be open-minded and you have to you have to think outside the box too and that's the biggest part of things it's just not accepting things and just saying we have to do it but you have to have the culture that will embrace that and it sounds like the growers these are people that are expert and growing how it sounds like it wasn't an uphill battle to get them to come on board and become these citizen growers data scientists well you know it was funny because with the technology it kind of gave them that work-life balance that they didn't have before their life was inside the greenhouse because the plants grow 24 by 7. so now all of a sudden they just kept growing they could they could go home they kept doing their thing they could go home at five o'clock and because of the vdi solutions and stuff like that and the ai that's helping them grow they can kind of turn off and instead of having to come in sunday morning and that the the one joke we used to have is that on sundays if you're in church and there's clouds had come rolling out all the growers would stand up and leave because they had to go to their church they had to go back to their farm now the system does that automatically for them so they're able to get their work life home balance back so it was different for them it was a jump for them anybody that's not used to technology and jumping into it is hard but once they started to see the benefits and what more yield they can get and the home work life balance it was amazing there's no i can't underestimate the work-life balance enough i think it's challenge it's a very challenging thing for people in any industry to achieve we've we've seen that in the last two years with you know do i live at work do i work from home so achieving that is kudos to you and for del for enabling that because that's that's big that that affects everybody guys thank you so much for joining us talking about ai what you're doing at nature fresh the future what's possible yeah and how you buy ai from dell no i think it's great i think you know nature fresh farms is a great euro you've been a great like a great partner for sure but also this great kind of beacon to show people how it can be done and i think it's just a thank you very much we really enjoyed it excellent well thanks for thanks for bringing the beacon on the show we appreciate it we want to thank you for watching for our guests i'm lisa martin for dave vellante i'm lisa martin i should say you're watching thecube day three of our coverage live from the show floor of dell tech world 2022 stick around we'll be right back with our next guest after a short break [Music] you

(upbeat music) >> Hey, welcome back to Las Vegas. Lisa Martin here, covering Coupa Insp!re 2022. theCUBE is really happy to be here at this event. About 2,500 folks are here, which is great to see. I have two guests from Microsoft with me. Please, welcome Jonathan Allen, the director of global network modeling design and planning, and Cassie Wang, senior global network model and design engineer. Guys, thanks so much for joining me today. >> No problem. Thanks Lisa for having us. >> Thank you. >> So let's talk about what's going on at Microsoft, the Microsoft supply chain. Supply chain is a term that's on everyone's lips these days for some interesting reason, but talk to me a little bit about the Microsoft supply chain and how does it scale to meet the needs of business? >> Yeah, Lisa, it's really an interesting design at Microsoft. When you look at all the products we service, from Xbox consoles, controllers, Xbox games, Xbox Live cards, service devices for retail customers, for consumer customers and commercial customers. And then the way we go to market through distributors, retailers, and direct to consumer homes, we have to have a supply chain that actually executes across all the products and customer needs based on seasonality. When you think about our products, Xbox console heavy Christmas, heavy consumer, heavy retail commercial devices for service, heavy quarter ends, heavy periods of time back to school. So, we have to have a supply chain that effectively works across all of our products, all of our customers, and all the differences analogies that we have to manage. >> And do so globally? >> And do so globally. >> So talk to me about the transformation. That's a word that we talk a lot about digital transformation, right? >> Yes. >> Before COVID, now we've seen the acceleration of digital transformation during COVID, we've seen challenges with the supply chain. Talk to me about Microsoft supply chain journey from a digitalization perspective, what you guys have gone through. >> Yeah, absolutely. Data is the key. And I have a philosophy which is around managing a business by facts and figures. And so, when Cassie first came on about a year and a half ago, our focus was on digitizing our supply chain. So how do you take our physical supply chain, digitize it in a way that you have a digital mapping and a duplication of what's happening physically in a digital way across the supply chain. So about every single day, we're grabbing in about 500 gigabytes of data, that then allows us to understand the physical and the virtual world of our supply chain, to understand how it's moving, how it's executing and how it's delivering. As for example, we were able to, when the war began in Ukraine, to understand where our trains were, how they were moving, and if they were continuing to move versus stopping. On the second side, we're leveraging that data now to make decisions about where our supply chain is today, which is really focused in the changing environments that are real time occurring. That's driving opportunities, whether it's about reducing carbon, whether it's driving cost down or whether it's servicing the customers to make real time decisions, while at the same time planning for three to five years out based on our growth, our projections, and making sure we'll have the right infrastructure partner supply chain in place to service with those changes in growth. >> Basically you need a crystal ball? >> Basically. >> Essentially? >> Yes. >> And Cassie, it sounds like from what Jonathan just said, you joined the team during the pandemic? >> Yes. >> So, during a time of massive change? >> Fully remote, yeah. Talk to me a little bit about that and some of the opportunities that you saw in helping the supply chain modernization. >> Yeah, definitely. So when I joined Microsoft, it's great time. And it's all the risks and challenges and dynamic changing environment that's really involved. So we spent a long time, like from the time I joined Microsoft, we spent the time to set up this digital chain of our supply chain. So really to transform what is happening physically to how do we see it digitally. So just to bring the visibility of the supply chain. So the great thing is we are able to leverage the tool from Coupa, the digital transformation and also supply chain design optimization tool to help us really build the digital twin, and also the model for Microsoft device supply chain. >> Now, interesting comment. So when I met Casie, the first time I met her, was in person when I interviewed her. Second time I met her in person was here at Coupa, and I was afraid I wouldn't recognize her. (all laughing) >> Of course, challenges of last year. Talk to me about speaking of challenges, talk to me about some of the challenges that Microsoft saw and said, "We need a partner like Coupa to help us eliminate these challenges. We don't have time. Real time is no longer nice to have. We've got to be able to transform, so we have that visibility in real time." >> Absolutely. When you think about time, time and decisions, overnight, cities get locked down in China, cities get locked down in Europe. And if you wait days or wait hours, that could be the difference between product on a boat, product on a plane, or product not arriving to support your customer needs. >> Right. And then the question is knowing that with that real time, how are you making decisions real time to change, to alternate airports? Making changes on the products you're making to make sure that, I was making this but now I should make this, because I have a risk of getting product to show. >> And you've got to do all that with very limited amount of time. And of course, cause there's the consumer. I mean, we think about the Microsoft on the business side but the consumer side, you mentioned some of the consumer products you don't offend the Xbox, the service consumers. One of the things that was really in short supply during the pandemic and probably still is to some degree, is patience. >> Yes. >> The consumer experience is so critical for a brand. >> Correct. >> And as is the employee experience. >> Yes. >> Talk to me a little bit about, from a supply chain digitization perspective, what was some of the executive sponsorships? Who were some of those executive sponsors that were involved in going, "Yeah, we need to move in this direction with Coupa, and it's got to be now."? >> The real supporter behind that is, my manager, Jeff Davidson, and then his leader, which is Donna Wharton, where they are truly about what are we doing next? How are we going to leverage the tools and the capabilities that are provided by others that allow us to do our job? So let's be clear on, let's use those that are designed to do what they're supposed to do, and then build where we need to. And that was the big difference, the digitization of the data, create the data, create the information so that we could then leverage the tools to create the information, right? And that information is then about bringing the facts, the information and the data forward, to have very fact-based conversations, which is back to manage the business by facts and figures. >> Right. Well, Cassie, one of the things that we've also learned in the last couple years, is that every company is a data company. If they're not a data company they're probably not going to be around. I even think of my grocery store and all that data that they have on me to be able to surface up. What did I buy last time, and I want to buy that again? Talk to me a little bit about why was Coupa the right choice to help facilitate this data strategy so that the visibility and the supply chain and the ability to tweak things on demand is there? >> Yeah. So, the main stuff that we are leveraging from Coupa are the data group and also the supply chain group. So data group enable us to really, for the people who do not have a intensive data manipulation backgrounds, they can use data group very straightfowardly to work on the data so they can build, they can grab the data transactional level and aggregate to the leadership level to see data in different aspects, tell the trends to get the key information. So that's the power of getting the massive data on a level that's like everybody can say, "Oh, wow! This is what it means." And another is definitely leveraging the data to get into a model, which is what we just talked about, the digital twin of our physical supply chain. So, we are able to like make analysis based on very easy design, like sensitive analysis, what-if analysis, to test out what our future supply chain can be. And what is the cost benefits? What is all the impacts on the on the lead times? On the carbons? So, yeah. So that's the power of leveraging the data. >> Speaking of carbons, how is Microsoft working towards being carbon negative, zero waste? What's some of the things that are going on there from a corporate responsibility perspective? >> Yeah, that's a really important one. As known about two years ago, we came out with a pledge to be carbon neutral by 2030. >> 2030. >> And so, the company as a whole is doing massive initiatives from different groups, but specifically in supply chain, we're constantly focusing on cutting our carbon footprint, whether it's the way we're making the products and designing the products, whether it's the way that we're designing our warehouses. So for example, just recently, we launched a Carbon Neutral DC in Europe, which is all solar panel based. We're about to do that as well in one of our US operations. We're working on other things that allow us to think about alternative pallets that eliminate the weight of wood, to a much lighter pallet that has a huge carbon reduction when you think about shipping things via the air and the carbon impact there. So, everything that we work on is really around three things; service, cost and sustainability. And our biggest objective is really taking all three of those objectives and trying to bring them closer to each other so that the decisions aren't as large against each other when you make one versus the other. That's our objective. So, how do we continue to move that ball forward, challenge the paradigms of the old, that we're so accustomed to and really move forward to changing? >> How does Coupa help with that? >> Oh, I can't say that, yeah. >> Yeah, so one of the actual dimensions, Microsoft our goal is to achieve carbon neutral by 2030. So traditionally, the trade off might be between cost and service, right? >> Okay. And now, the carbon is the most important priority. So the trade off, the balance, are between cost, service, time and carbon. So one of the great thing that Coupa can help us is in the network modeling. There is actually objective for lowering the carbon emissions. So that can be the top priority that you wanted to solve through your network modeling like in parallel to cost, to service. So you can just like very straightforwardly put more weight into carbon when you're making your decisions, like that can be a higher penalty cost when you have more carbon emissions. It's like a very straightforward way to translate the carbon goal into some quantifiable goal into the modeling and data. >> Jonathan, I'm curious from a Microsoft strategic partnership perspective, how important is it from Microsoft to partner with companies that have that strong commitment to help facilitate being carbon neutral by 2030, having a strong ESG initiative? >> It's critical. Microsoft for the most part is an outsourced supply chain in which we measure partners across the network. We have our partners run our distribution and centers, we have outsource manufacturing, we have outsourced logistics. And it's important that we're working with them about what their plans are, because they're just simply an extension of the Microsoft supply chain. >> Right. >> Right. They're not not just companies we work with, they're companies we partner with, to think about how can we change the future? What are the alternatives that we can do? How do we think about alternative fuels? How do we think about alternative shipping ways? How do we think about creating density in the network? So one of the biggest things when you really think about optimization is really around creating deensity. How do I create more with less, and make sure I'm taking, for every dollar spent, for every shipment made, I maximize it to its fullest, and leave no waste behind it? That's the goal. And so, partners challenging us is probably the most important piece because they're on the front line. They actually see our shipments, they see our loads, they see the work we're doing and how it's translating to their environment. And it's important that they give us that hard feedback back that allows us know where we're not meeting the bar. >> Got it. Cassie, you guys are giving a presentation in about a couple of hours. Talk to me about some of the things that the audience, like if you had to summarize the top three takeaways that the audience is going to learn from the top, what would they be? >> I think the first is sustainability. So we want everybody to know that this is the key mission for Microsoft. That's one of the priorities for the next eight years for Microsoft to achieve. And the second is just how Coupa can help us achieve that goal. And how do we leverage the the applications, the tools, the cutting edge technologies for us to achieve a sweet balance between sustainability and technology supplychain? >> I think one of the greatest things about conferences like this, is that Coupa is great with that customer centricity, is it the opportunity to hear from the voice of the customer? What challenges you had? Why you chose Coupa? How you resolved them? And that crystal ball that you talked about in terms of where we're going from here. I think that there's so much value. I'm sure in what you're going to share today with the audience. Jonathan, last question for you, for other folks in any industry that are about to embark on, or are in the midst of a supply chain, digital transformation, what's your advice? What recommendations would you give? >> For me, it's really about two things. First and foremost is about creating data. Focus on data, not an answer, not a conversation. What is the information that you require? And then the second piece about that is then how do you make sure you stitch it together? And how you create, whether it's manufacturing data, whether it's purchase order data, whether it's sales order data, whether it's shipment data, whatever it is, making sure that you can stitch end-to-end together, because each individual decision by itself, may be right, but could be wrong, because ultimately, it's about the decision for the whole, not the decision for the one. And then making sure you focus on the cultural change, which is around, it's just not my area, it's just not my thing, it's about the end, it's about the planet, it's about Microsoft, it's about the customer, it's about the future, and making sure you're really really focused on making that change, right? Not my change. >> Right, and Rob Bernstein even alluded to that a little bit this morning in his keynote talking about one of the things that Coupa breaks is silos. >> Yes. >> Organizations that, cause to your point, something might be really good for sales or operations, but not good for marketing or logistics, for example, need to be able to have that visibility across, but also another thing that Coupa is famous for is collaboration. >> Correct. >> Being able to enable that collaboration across lines of business, across teams, across partners. >> Yep. And an important statement of that is, when you think about change, think of it like a stream, right? Streams, they create pathways with persistence. When you believe in something and you're truly behind it, just stay the path, right? There'll be a time and a place, cause sometimes the decisions just aren't now, but they will become. There's a lot of things that, for example, myself and Cassie are constantly working on, that might not be right now, but they will be right in the future. And it takes sometimes, just the right opportunity, the right situation, but the key is making ysure you understand those things so when those opportunities present themselves, you can just step in. >> Yep. Another thing we've learned, I think in the last two years, I'm losing count, is it's not a matter of if, but when. >> Correct. >> And you can apply that general statement to pretty much anything these days. >> Absolutely. >> Guys, thank you so much for joining me talking about Microsoft's transformation of the supply chain, the digital twin that you've created. Have a great time in your session. I'm sure folks are going to learn a lot from you. >> Thank you very much. >> Thank you so much. >> All right, my pleasure. For Jonathan Allen and Cassie Wang, I'm Lisa Martin. You're watching the the CUBE's coverage of Coupa Insp!re 2022 from Las Vegas. Stick around, be right back with my next guest. (upbeat msuic)

(upbeat music) >> Welcome to theCUBE's coverage of PagerDuty Summit. I'm your host, Natalie Erlich for theCUBE. We're now joined by our guest Jonathan Rende. He is the SVP and General Manager of Products at PagerDuty. Thank you very much for joining the program today. >> That's a pleasure to be here. Thanks for having me, Natalie. Well, Summit 2021, an exciting time for PagerDuty. What are you looking forward to most? >> Well, finally, I'm looking forward to at some point, hopefully, not having to wear my mask in public anymore. I know that's the right thing to do still, and I am doing that, but it seems like things are starting to get back to normal. And because of that, what we're finding is a lot of our customers and clients business practices, especially in certain industries like the hospitality and entertainment, they're coming back as well, and to pre-COVID levels and their same level of usage and everything obviously, that got a little bit dampened during the pandemic. So I'm just looking forward to businesses normal and probably the biggest is talking to my colleagues in three dimensions in person versus two dimensions on a zoom. >> Right. Right. And yeah, I mean, it seems like, unfortunately, not this time we get to see each other in person. But looks like customer service is a big focus at the Summit. Why is it so important right now for companies to provide a seamless customer and digital experience? >> Well, we've learned a lot in the last 12 to 15 months. And one of those is that our historical audiences, developers, ITOps folks who have been on the front lines. And for the, a big part they've been distributed already. Customer service teams have always been on the front lines whenever there's a customer experience problem. And they're no longer working in the office across cubes being able to communicate they're remote now as well. And so with a couple of really interesting things have happened. One with the rise of digital services, the use, the demand on them, heck my own parents are now ordering groceries online, which they never did before. And with the increase with many of our clients and customers, the customer success organizations have to deliver a whole new level of customer experience for that digital experience versus just the brick and mortar in on-premise type of experience. And it's created a whole new set of needs around collaboration, communication. And we've seen that customer service teams are a critical component working with development and IT part of kind of like a three-legged stool that has to work together really well for great customer experience now in the digital age. >> Well, you mentioned this big push for digital and especially in light of the pandemic and what other ways did the pandemic impact customer service? >> So first, like maybe building on what I was just saying, just the collaboration aspect. Most customer service teams have historically that I get an opportunity to work with, they have to work for better, for worse in reactive mode. Cases get opened up, something isn't working, a customer is unhappy, there's a customer satisfaction issue, and so they're pulled in. And those individuals, they're lacking all the contexts that they need, and oftentimes, they're in a world where they have to pull in other individuals. And I think gone are the days where they can pass that customer case off to just another individual and then another individual and another individual, that's incredibly frustrating from a customer business experience. And so this notion of eliminating hand-offs and empowering that individual to be able to reach out to the people that they need and handle that case kind of from beginning to end and communicate directly bidirectionally with engineering teams when they're fixing an issue with electronic shopping cart, digital shopping cart, that's critical. They need to have that flow of information because they're a member of the team so that they can proactively communicate with their clients and give them updates of what's happening. >> Well, last year you announced a customer service solution. What are you announcing this week? >> So a couple of big things, we've recently just made available kind of like a complete in context experience or PagerDuty for customer service app for Zendesk and upcoming with Salesforce. It's really all about an agent, not having to switch out of their help desk, their contact center environment. They can get all the information they need in their world without having to move to other applications. They can instantly know if there's a really important issue in the back office with the systems, with the digital services that they need to be aware of. So we have a whole new set of PagerDuty for customer service products that we've made available. And then also a couple of different options for our customers and how they can consume that. We have a professional version and a business version. And really the difference between the two is if you want your customer service agents to really have full case ownership, to be able to be empowered to do everything, pull in the folks that they want to, they can do that in the business version of our package. >> How and why should DevOps and customer service work together in your opinion? >> So historically, I've always felt that in many times engineering teams will identify because of monitoring and many other technologies that they're using that they'll understand, that there is something that could be customer impacting and they'll work that diligently. Unfortunately, it's been more of a, kind of a stakeholder relationship only with customer service. Yes, they need to know about it. But what we've really worked towards is making sure that customer service is not just the stakeholder, they're an active participant because issues can be identified from customers on the front end or proactively by items issues that are identified in the back office. So being able to be right in the center of the customer world is super, super critical. >> And when you look at the next year and even the next five years, what are you most excited about? >> I think it's really empowering helping our customers, our community, customer service agents on the frontline do more, have more power at their fingertips. I know over and over again, I think, greater value is delivered to customers through those individuals that are contacted not always in the best of times. And there's some amazing statistics out there sets that it takes 10 good experiences to make up for a bad experience if you're a customer. So there's a big impact to this or if there's a particular pricing or product issue that a customer service issue is way more important, way more impactful, will lead somebody to use an alternative service versus the product itself or the pricing of it. It's the service element that's most important. Given all of that, when somebody does in their time of need have a customer service issue, when they do have a positive experience, three quarters of the time, they're super open to sharing that with others. And so if I look at some of that, again, what I'm excited about looking forward is how can we empower those agents to be able from cradle to grave. Take a case that comes in proactively communicate with their customers to provide a great experience to address some of those statistics. And we're really focused on automating that process. It's another truism is that, well, every business wants their customers to exponentially grow. You can't grow your customer service organization exponentially. You can't hire an infinite number of bodies. And so technology plays a really important role in that. And having PagerDuty for customer service as an integrated part of your Salesforce or your Zendesk or your fresh desk implementation will help those teams scale a little quality of life for those agents is important. And we believe that we can really help in that area. Minimize stress disruptions and help them provide better service to their customers. >> Yeah. Well, we touched on a lot of areas in terms of customer service, but another key feature of your role at PagerDuty is in product. So if you could outline some of the key products at PagerDuty and perhaps some insight on what you have in the pipeline. >> Yeah. So outside of just customer service, one of the huge parts of our community are those in ITOps and DevOps. And one of the areas of responsibility I have working with the team that I'm super proud of is what we're doing with what was recently announced last September, our Rundeck acquisitions. So we're announcing something called Runbook actions as a part of the PagerDuty platform. Think of it as a very simple, safe level of automation that every DevOps team can use to better address issues and kind of eliminate a lot of the toil and manual activities when they get pulled into a major event. And so we're releasing this new add on product, very excited about it. It's the first introduction of our Rundeck technology, new as a part of the integrated within the PagerDuty platform. So the reception we've gotten so far in early days has been tremendous and people are really excited, again, to eliminate toil, eliminate a lot of manual activities, allow them to fix items faster when seconds really matter. >> Terrific. Well, really, really appreciate your insights, Jonathan Rende, SVP and General Manager of Products at PagerDuty. Thanks very much for your insights. >> Thank you, Natalie. >> Terrific. And that's all for this session of the PagerDuty Summit. I'm your host Natalie Erlich. Thank you for watching.

>> Narrator: From around the globe, it's The Cube, with digital coverage of PagerDuty summit 2020. Brought to you by PagerDuty. >> Welcome to the Cube's coverage of PagerDuty Summit 2020, the virtual edition. I'm Lisa Martin and I'm pleased to welcome back to the program Cube alumni, Jonathan Randy, the Senior Vice President of Product at PagerDuty. Jonathan, welcome back. >> Good to be here. Great to be here again, Lisa, thank you. >> Quite the week for you guys, just wrapping up the three day virtual event this year reaching thousands of folks. Lots of news coming out, as we even kind of talked about the other day announcements, you said this was the biggest product release in the company's history, which is amazing to achieve during a pandemic, but AIOps, integration with Microsoft Teams, customer service solution. And we've heard a lot about automation in the keynotes and of course, with respect to the acquisition of Rundeck. Give us a quick little 60 second kind of overview of some of the things that you announced this week at the summit. >> Oh, it's been busy, as you said, and it has been really the biggest set of investments that we've brought all together at one time in the history of the company and so kind of leading the list was everything we're doing around, the category of AIOps. And so there's been a focus on automation, there's been a focus on what we're doing around event intelligence, and many new enhancements and updates to that product that's a part of the PagerDuty platform. We've also applied machine learning to our analytics, which is great with a recommendation engine to help organizations mature and really understand where they are and then, as you mentioned, big announcements around communication and collaboration with zoom, and Microsoft Teams, and even a new product from PagerDuty built on our core platform called PagerDuty for customer service. So it's been incredibly busy. >> And I'm sure lots of great feedback from customers and partners across the globe. You know, one of the things that you and I have already talked about is in the last six months, this explosion and a number of incidents that your customers are having to deal with and how PagerDuty is helping them to respond to those a lot faster. We talked about automation a lot last week, but as we think about the folks on the digital front line, have to be empowered with the information should be able to respond immediately to a customer inquiry, or risk the customer churning, talk to me a little bit about how automation, is this really kind of the next essential for combating that digital stress that the frontline workers are facing? >> Yeah, so automation has always been important to PagerDuty, and there really a couple kinds of automation that are so important. The first of which, and this is what many people know PagerDuty for is what we always refer to as people orchestration, it is automation, but it's automating is really the identification of issues and then engaging responders, these frontline workers on the right issues at the right time to make the right decisions with the right information. And so that's been the type of automation PagerDuty has really been focused on and more recently, we've taken some baby steps in the area of machine automation. We've done some things with custom actions in our web hook technology that we've delivered, but really to address some of the issues that you're referring to for workers on the front lines. We've had integrations with Rundeck, runbook automation vendors before and we have several partners in this area that do what's referred to many times as machine learning, not people orchestration and automation but machine learning. And we really felt it was important to have a world class capability as a part of PagerDuty, because it's one thing to engage individuals. But then if they still have to undergo manual toil, manual work and resolving issues, and much of that can be automated with machine automation. It's just a perfect match and it should be something that I would expect if I was a customer of PagerDuty ultimately to have. >> So PagerDuty has been working with Rundeck for about a year now, so to talk to us about some of the things that you saw from the capabilities, compatibilities rather, perspective, that you guys thought this is going to be a phenomenal addition to what PagerDuty delivers and exceeding our customer expectations. >> Well, this acquisition and the coming together of Rundeck with PagerDuty, we're super excited about, it's the first really major acquisition that PagerDuty has done and it's an extension to PagerDuty in multiple ways and it's an extension to PagerDuty in the use cases. And that customers can use us, you know, with Rundeck and PagerDuty. It's an extension to, as I just mentioned, people orchestration automation with machine automation. It's an extension of value. There's no overlap anyway, anywhere. But it's also, there's a lot of synergies and the coming together of these two organizations in particular as you know working more closely with Rundeck now, is really about their culture. Their culture is very similar to PagerDuty. And more importantly, like, as I've gotten to know, many of their customers, many of their users and there are, we have some of the same customers in the enterprise and mid market, which is really exciting, is that, although many of them are in the ITOps area, and while we have customers in ITOps, as well as in development, they all refer to themselves, those customers have Rundeck today as DevOps. And so they're very much along the same philosophy, as, you know, empowering self service, being able to take action as somebody on the on the front lines, and being able to take that action, not just be notified of it, but complete that work. And so, that notion of, you know, ubiquitous use, self service, empowerment, that's very consistent in Rundeck's culture, and their customers as it is with PagerDuty and our customers and our culture. >> I know both companies are steeped in DevOps and digital transformation, but it's nice to hear about the cultural alignment, because it's a big thing. It's not just a big thing for the two companies coming together, but also for your customers to ensure not just a seamless transition, but they really get to unlock the value of what Rundeck is going to add to PagerDuty's technologies, right? >> Very much so, very much so. In talking to some of their customers, who are our customers as well, it's just been so clear that it's a very similar use in many ways, although it's a different product, meaning a small group will start to use Rundeck and then other teams in the organization see the value of that and it grows virally. PagerDuty works in much the same way. And their product can be used for a lot of different automation uses in an organization from automating a data processing ETL process to provisioning systems for internal development teams. But one use case that really brings us both together is the focus on the incident response process, the incident response lifecycle and that's where we really got excited. And I'm seeing this week that our customers, our mutual customers are excited. Also, this notion of being able to not only identify, but also engage the right teams, prevent issues from happening in the first place, and then automate the diagnosing and the resolving of these issues before then you learn from that. So it's better the next time. So those automation steps in there, the diagnosing, and the the resolution, it's such an important part of the incident process that our customers just need in these times when digital services are more important than ever. >> Right digital services are the new norm. So is Rundeck, sort of a piece that allows PagerDuty to automate 100% of the incident response lifecycle? >> Much more than ever before, yes. So again, I look at it as take people orchestration and automation, add machine automation, the ability to bring down and bring back up a service as a part of a Rundeck set of steps or jobs, like having that together in one solution really does automate all of the incident response and gives the ability to incident to automate more and more of that incident response process. You know, the other key thing too, I was thinking through the other, obviously, throughout this process, in the other day was the synergy between, not only our customers, but our communities. And I always think of communities as a little different than just customers and PagerDuty has a thriving, growing community around it, in addition to our paying customers. One of the things that's in common with Rundeck is they have the same thing. They are an open source product with an enterprise product on top and it's a open source community of 60,000 DevOps professionals that we're bringing together with the PagerDuty community. So very excited about that synergy as well. >> Tell me a little bit about some of the feedback that you've heard from that community as these announcements including Rundeck have been made and this real obvious pivot towards automation. What are some of the things that you've heard that pleased you? >> Yeah, a couple things. From the community, from the customers, from internal teams, both on the Rundeck side of the house and on the PagerDuty side of the house. Sometimes it's just when things are, it's a good match, you don't have to explain it that much. People just see the natural synergy in it, you don't have to spend a lot of time explaining why machine automation and runbook automation is such a natural hand-in glove fit with PagerDuty and what we do today. And I think that's a huge validation. And, that message has been very consistent in what I've heard back. Some other specifics that were exciting to hear is some of our existing customers today who attended summit, who obviously had no background as to the announcement we were going to make with with Rundeck, contacted the Rundeck leadership, who then forwarded that information to me saying how excited they were, as they were attending summit, sitting in the virtual audience during our keynote addresses, as they heard the coming together of Rundeck as a part of PagerDuty, and immediately sent notes to the leadership on Rundeck saying how excited they were about that and how they wanted to expand the use, which then got forwarded to myself which nothing can be better validation. Nothing's more exciting than to see the community really understand what we're doing and see the benefits of it. >> You're right. That's the most public objective validation that the brand, any brand could get. So what would be the next steps, for example, you know, we talked last week about a whole bunch of PagerDuty customers, 13,000 plus great brands, many types of brands, Zoom, Slack, AWS, they were on main stage with you and Jennifer and the team. But if we think about some of those existing customers, what would be the next step for them to start leveraging the value that Rundeck can deliver to their environment? >> So a couple things. First, there's so much that can be automated today, if you think of just like the two big departments that use Rundeck, and PagerDUty, and there are more frontline teams than just these two. But if you think of just Dev and development, and then ITOps as two organizations that are working more closely together than ever before. You know, the real opportunity is for them to really start to shorten the time it takes for them to do so many things in their world on via Rundeck, you know, Rundeck automation and going back to some of the comments, you know, questions you asked me earlier about where some of the synergies they've made it so easy, they being Rundeck, to automate to create what they call jobs, and then make those jobs, you know, everybody be able to run those in a standard way. And then from a compliance standpoint, get the reporting on that, that the use, I think will really not only grow within IT, but for the most part, a lot of the development community, the core DevOps teams out there that use PagerDuty on the dev side, I think that you know, run books have been largely a manual activity for them, manual steps that they do. If I had to guess, the majority of our, you know, partners, community, customers today, who use PagerDuty when they actually get pulled into a real event and they're walking through the steps that they need, whether it's pulling together all the diagnostics information, and then going out in action to solve a major incident, a major event, the majority of that is manual today. And so the fact that we're allowing the equivalent of a big red easy button for those individuals for those teams on the development side, who really have been doing this unassisted today, to automate more of what they're doing, to cut down on the time, to cut down on the toil, to reduce the time that digital services are out in their organization. I think that's a huge opportunity for the larger PagerDuty customer base. >> I was looking at the press release, and with respect to the Rundeck acquisition, and about Rundeck saying and customers have experienced up to 50% reduction in incident response time using Rundeck automated run books. So from a team productivity perspective, that's huge. >> Especially when, you know, minutes are millions of dollars. And we were talking about this the other day that so many casual services are now mission critical, they're critical path for all of us, we need them, both in our professional and in our personal lives. So given that, given what's riding on these services, and how PagerDuty has always been about, you know, behind all of those services, our people and those people have to respond in the most effective efficient way in those really critical important moments, that type of savings, you know, reducing the time that it takes by another 50% on top of that, hopefully our customers will see the value in that Just like we do today. >> Big reduction in digital strategy, which I think we could all use today. Let me ask you one last question. Since this was the fifth PagerDuty summit, but the first virtual, you got to interact, or rather had the chance to impact a lot more customers than our traditional in-person event. But what was your take on having this virtual experience? Did you feel that you were able to really engage those customers as much as you would like to in a digital world? >> I'm really glad you asked. So much of us put so much of our time and effort into this, and I know our customers depend on us to do that. That usually, when you meet in person, you know, as you say, this is our fifth PagerDuty summit, and the other four have all been live, but they've all been in person, that nothing does substitute for the interaction, the live interaction you get, whether it's delivering something on main stage, or interacting one on one, with customers and clients, nothing, I think is a substitute for that. We are where we are and I do believe we're making, you know, obviously the best of it. And it has been great, we've generated probably five times as much content in this event than we do for a normal in person event. So while the the interaction isn't quite what you would expect in a three dimensional versus a two dimensional world, and I think the positive is, there is more content, and all of that content is kind of imminently more shareable than ever before, I personally have gone in to look at some of the track sessions, more in, you know, via zoom than I have in the past when they were recorded, but you know, it was a live event because I was so busy with other things. So I think the downside is some of the real personal interaction, we can still have personal interaction, of course, but it's not quite the same, but the content, the material, and then the reuse of that over time. I see that as being positive. >> Absolutely, I couldn't agree more. Well, congratulations on a very successful event. I imagine you must need a good weekend rest after delivering the most product news and announcements in the history of the company, especially in the last six months. Jonathan, it's been great having you on the program. >> It's always a pleasure, Lisa, thank you so much for having us and I hope you get some rest this weekend too. >> Likewise, I'm looking forward to that. For Jonathan Randy, I'm Lisa Martin. You're watching The Cube. (lighthearted music)

>> Illustrator: From around the globe, it's the cube with digital coverage of PagerDuty summit 2020. Brought to you by pagerduty. >> Welcome to the cubes coverage of PagerDuty Summit 2020, the virtual edition. I'm Lisa Martin, and I'm pleased to welcome the Senior Vice President of Product for PagerDuty. Jonathan Rendy. Jonathan, welcome back to the cube. Thank you, Lisa. It's great to be here. So this is our virtual cube, virtual summit 2020. But one of the things that I know from talking with Jennifer yesterday 6is that this is the opportunity to reach way more people because there's, you know, no travel restrictions and budget and things like that. But one of the things that is quite impressive is that you're going to be in your keynote talking about a lot of changes and enhancements to the products the biggest release in pagerduty's History During COVID-19 really impressive. Talk to us about why this is such an exciting time. >> Well, it's it's exciting for a lot of reasons. And great to be here, although I'm getting so tired of working from home these days. But be that as it may, yeah, we we do have the biggest set of releases and investments and innovation that we're unleashing in the history of the company, which in these times is is no small feat. I want to thank all the teams have done a wonderful job. But we're using our summit event, as you know, to to talk about that to bring that out to discuss and we have some very high profile speakers coming. Joining us at the event. We have Andy Jassy, we have Eric Diwan, Stewart Butterfield and more. So it'll be a fantastic event, for executives and for practitioners alike. So sharing what we're doing new with all of this, these leaders joining us is going to be a great thing. >> One of the things that's become so critical in the last six months is digital services. And I think so many of us don't realize or don't think about the folks under, I don't want to say under the hood, but behind the scenes really, that are critical for you mentioned, the CEOs of AWS and zoom, and Slack, which are all essential. I mean, zoom is a household name, right? My mom even uses zoom, she's 75 that's pretty cool. But all of the criticality under the hood to ensure that these services continue because we're all now even more dependent on them than we ever have been before. >> Yeah, it's really interesting, I was thinking about this the other day, there were so many casual services that we all relied on, you know, pre March pre February, that now have become just mission critical and, and to everything that we do professionally and personally. And to your point, whether you're working out at home with, you know, your peloton, or whether you're in the two dimensional world with zoom all the time, we just expect all these services to be up and running and be available for us. And behind all those services that we expect to be there is a an amazing amount of complexity and dependencies. And behind all those complexity and dependencies our people and and that's a big part of what PagerDuty focuses on which is engaging people on the right issues at the right time. And of course, allowing them not just to be engaged but complete the work work, major issues, unexpected work, unplanned work, and complete all that in when moments and seconds and microseconds matters. So Pedro duty has a unique place in that whole ecosystem of what's considered crucial and critical now. >> We'll we've been hearing the term essential workers for since March right and thinking of them in a traditional sense of doctors and nurses and firemen and obviously grocery workers and, and deliver companies. But looking at it from pages through your lens, it's this the whole like digital frontline, the DevOps folks, the IT folks, the customer support folks who are really on the front lines of helping that brand be protected. Now it's, you know, the fact that everything is real time that now is now more important than ever is never been more important. So talk to us about sort of this switch to this digital default and what that means for operations. >> Yeah, as we were just saying, to your point, it's never been the services have never been more important and more essential to everything that we do. So it just makes perfect sense that all of the individuals who are responsible for building and delivering and supporting those services are essential. Now also and as a part of that we talk a lot about going from what everybody knows as DevOps to digital ops. And while it may sound like a marketing phrase, words matter, and it really means going from being responsive to being proactive and predictive. And that's so important for these individuals. To get ahead of this, we've seen super interesting data, when we look at our platform where there 13,000 customers of how life has changed for all of those customers and those half a million users of our platform today, pre COVID. And now that we're in the middle of this with, again, reflecting how important services are the increased use of those, and then the rise in issues. And what's the great news is that individuals and companies using the platform are actually getting better at addressing them than they were pre COVID. So with the bad news, there's, there's good news, too. >> I agree, there are always silver linings, I was looking at my notes here. And one of the things when PagerDuty evaluated your platform, and as we mentioned over 13,000 customers, during COVID, seeing an increase in traffic and demand for digital services, more than a 38% increase in incidence compared to the prior period. But you also talked about how the big impact that pager duty is helping your customers make and resolving those incidents faster. And I guess maybe sorting through the noise, and a better more automated way. >> Exactly. And a lot of it has to do with what we've been doing. And then another piece is our new releases. And so again, we've looked at our data to your point. And we've seen this over a third rise, in the number of issues, that organizations are running into across the board. And with our new releases, we're able to reduce interruptions by over 65%. So it's great news that again, with with the rising use and the rise in interruptions and people having to context switch from what they're doing to you know, firefight and jump in the middle one and collaborate across organizations that there's light on the horizon, the light at the end of the tunnel, I should say, and then things are going to get better. And our new releases are going to help in a big way. >> Okay, I'm assuming you have a crystal ball, which is great. So I'm going to be looking for some more predictions, but talking to your customers. And you know, I can imagine now there's more noise. You mentioned this switch from DevOps to digital ops and this now this digital default that I know, Jennifer has talked about, and it's this probably going to be one of the things that that shapes the winners and the losers of tomorrow in every industry. But tell me a little bit about how you're helping how you're using, you know, the traditional buzzwords, AI, machine learning, and putting them really effectively to work so that it's now not just a buzzword that companies in any industry should be thinking about, but it's actually machine learning is going to be critical to sorting through this increased volume of data and helping resolve incidents faster to not just, you know, prevent customer churn, but also to make sure that your folks on the digital front lines aren't burned out. >> Well, with the transition that we were talking about before, you know, everybody realizes that they have to be all in now, there's no, we're migrating to the cloud. And there's reasons for that, moving from on prem systems to to the public cloud, in many ways, we've seen that massively accelerate. And with that comes and how the systems are, have to be built and managed and delivered there, you see this increasing complexity. And going back to what we were talking before, individuals are behind all of that complexity. And so it's so important that in our new releases, we really up the bar, we've really raised the game, so to speak on what we're doing to take advantage of our data that we capture. And also this increase in information that's coming in, we refer to it a lot of times as telemetry when you, you know, start to refactor and rebuild your systems in the public cloud, and you have all those dependencies and you have more information, more data flowing to you, which can translate to more interruptions. And very easy, It's very easy for organizations and teams to get overwhelmed by that. And so our new releases, focus on making sense of that we talked about the reduction in interruptions and the reduction in noise. But we've also focused equally, on helping folks with context with information when something goes south, when something is different than what a team expected. How do you fix that once you engage the right people, they're so big part of our releases also been about applying machine learning to add context to speed up fixing and resolving and finding the root cause of these issues in a big way. And we do that through a number of different ways in our in our products, in our PagerDuty platform, event intelligence, and also our analytics, again, to draw these relationships around service dependencies and our analytics, we've included a recommendation engine. So now we can show organizations and teams predict. If you make these changes, you will see these improvements. And this will be your returns and using our data combined with the data that's coming in, That's a big part of what the PagerDuty platform is all about. >> well that analytics piece is, critical as as the machine learning because the volumes of data are getting bigger and bigger and bigger such that it can't be can't depend on just humans. There's something that I'm curious about, too, is with the rise in incidents, how can PagerDuty help customers kind of sort through the noise and maybe Park things that might be able to be resolved on their own without having to escalate? >> It's a great question. And we do it through a couple of ways. One, we've applied machine learning so many times when, when interruptions when issues alerts come in, and they can look different, but they're all related to the same thing. So we're applying machine learning to better group and intelligently organize and group all of those informations into the singular incidents that really matter that you really need to pull teams together on which is important. The next thing we're doing is we're using machine learning to say, Hmm, okay, it looks like these, these issues, these incidents are happening on different services that teams own. And what we're also using the machine learning to do now is to show the dependencies between those services. So we often see situations where you can have a couple of teams in your organization, working on issues that are delivered to them, not knowing that they're related. And in some ways they can be working against each other. So having information to know that one issue is upstream. And the other issue is downstream allows one team to step forward and the other team to step back. And we're using our machine learning for that, to give that additional context and help pinpoint where the issues are. So it's the most effective use of these teams when they come in, Nothing's more frustrating by the way than being interrupted, whether it's the middle of the day or the middle of the night, only to find out that either you're being unproductive or you didn't need to be there in the first place. >> Oh, absolutely, yes. And I'm seeing some stats that people are the folks on the digital front lines are working an average of 10 hours more a week. And so many more of those interruptions are happening and when you'd like to be off on the weekends and the middle of the night. But one of the things that that you took context, absolutely critical, but also collaboration, different teams that need to be to your point, are we working on the same thing, and we don't know, the collaboration now that work is distributed is even more critical than ever? What are some of the things that you're hearing from customers about what PagerDuty is doing to facilitate that collaboration so that things just run much more smoothly, and the demanding consumer on the other end is satisfied? >> Well, to your point, one of the most critical things, since we're talking about not just a technology issue, we're talking about a people issue is communication, and collaborating. And that is so important, not only in general, but in these moments that matter. And so one of the things we've done in the new platform is we're introducing industry firsts, video war rooms, with our partners and customers zoom, as well as Microsoft Teams. And so we're also updating our slack integrations as well. But as we live in this two dimensional world, those responders, those teams that have to come together to fix issues with the single click of a button, now they can participate in those issues, in a video sense, in a video war room, but not just engage in that way. We've also added the ability to manage the issue through zoom through Microsoft Teams as a part of PagerDuty. So individual don't need to context switch from one product to another, they can do everything they need to do from from that world. So a big part of that collaboration and communication is all about the in the moment, you know, teams working together in those forums. But there's another side of communication collaboration in these major events. That's critical as well. And that has to do with what I always think of as the ripple effect. There's there are the teams working the issues. And then there are all the teams adjacent to that, whether they're business stakeholders, whether they're customer service teams, that also need to take action. They may not be fixing the issue, but they have to engage and they have worked to do they have actions they need to take equally, that are different. And so for those other organizations, it's we've increased the scalability of our stakeholder notification into the 10s of thousands. So those folks can keep in touch in tight alignment to what's happening to an issue being fixed, which, again, in today's world, this effect, affects everyone in an organization, not just the teams tasked with addressing the problems. >> Right. And of course, the demanding consumer on the other end isn't considering the fact that the customer support person that they're talking to might not have access to everything they need. And it's critical. It's business critical for any type of organization to understand that, even their customer support folks, and I shouldn't say even those guys and girls are on the digital front lines. And brand reputation hangs on the data that they have the context that they have, and their ability to resolve a customer issue because we were more demanding as consumers before COVID. And now I think even more than other because we're dependent on it. We're dependent on zoom, or dependent on Slack, we're dependent on Amazon and AWS, and so many other digital services. And we don't get what we want as consumers, right, we're going to go I'm going to go find someone else who's going to be able to respond to this in in one second, because I'm only going to give it a half a second. So last question, Jonathan for you so much announced this PagerDuty Summit 2020, unique in that way unique in the virtual asset. But what are some of the things that you see on the horizon, say, the next six months, because I'm pretty sure you have a crystal ball, let's open that up. >> Well, I see a couple of things. And while I never said that I'm Nostradamus, I see a couple of things. And one is that there is a material, seismic shift towards full service ownership. and so teams, and this was happening before as a part of DevOps. But when I was talking previously about moving to digital Ops, we're seeing large organizations have major initiatives around this notion of the frontline teams have to be empowered to work directly on these issues. And we always call that this phrase, full service ownership, which means you build it, you ship it, you own it. And that's both for development and IT organizations. And I think you brought up a really interesting point before, in this trend that I see happening and only accelerating, it's happening because people want to innovate faster. And those individuals, those teams, whether you're, again, in Dev, it Ops, or even in customer service, it's important that you're empowered to do this to help in that innovation. So I see that as the first seismic shift. And actually, as a part of that. The other big part of our announcements is where we're at summit, announcing PagerDuty for customer service. It's a curated product, just for customer service teams, because they're part of that big triangle with Dev and IT teams that they need to be in the loop, they need to be empowered with the same types of tools, they need to be able to act as a, essentially an incident commander, they have cases that come in, and they need to be able to engage the right individuals to provide that customer service to what you were saying before. And they need to have a direct link to everything that's happening in Dev and it so they can be proactive and get ahead of customer cases also. So again, to your question of, like, what do I see? I think that shift is brought on by people being all in, you know, with with their, their cloud migrations and refactoring. And then full service ownership being something that empowering individuals on the front lines, democratizing, you know, decision making and empowering those teams. I see that as the biggest shift happening overall. >> Excellent, Jonathan, thanks for sharing what you are unpacking at summit 20 and the opportunities that had a lot of silver linings. We appreciate your time. >> Thank you, Lisa. It's been a pleasure being here. >> For Jonathan Randy. I'm Lisa Martin. You're watching the cube (upbeat music)

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Welcome back everybody. Jeffrey here with the cube. We're at RSA 2020, downtown San Francisco and Moscone center, 40,000 professionals in the security industries, the biggest security event in the world. I'm pretty sure, certainly the biggest one in the U S we're excited to have somebody who's been running around taking care of these problems and talking to customers for a very long time. It's got a great longterm perspective. We're happy to have him. Jonathan, new wind, the VP global field say-so team for fortunate. Jonathan, great to see you. So you said you've been coming to this show for a long, long time. Love to get kind of your impressions that the human element is the theme. Yeah, well, sheer, you know, I, I think, uh, it's changing. It's uh, the attendance is broken out by very senior people who've been here for, you know, multiple events and then a whole new slew of people are coming into the industry, right. >>And there's a lot of excitement. It's, um, there's a little bit less of a buzz. It just seems it's a little bit less people here this year because of the virus scare. Um, but overall I think that the themes are pretty consistent, which is kind of tragic that the themes are consistent year after year because this suggests that not a lot has changed despite the $130 billion and it works with purity span. You know, absolutely complexity. Uh, everyone is telling me about how to solve complexity, how to do more with less, uh, how to do more with less and fewer people and how to get their arms around this vast volume of data that's being generated. And there's a lot of talk about automation and AI, uh, but much more practical, less buzzwords and more practical solutions. And yet still tons of new vendors, right? Tons of new opportunities. >>You know, I don't know what the final count is on the vendor side, but it's a really large number and you go off into the corners to the EDBD little, little, a little mini boost is still a time of innovation. So I think that people trying to move the ball. So I think when the first show first started, there were less than a less than 500 vendors, I think in the industry back in 2007 I think today we're North of of 5,000 and it's probably 8,000 or about 5,000 vendors in the immediate vicinity here. But just go around the corner and there are dozens of others having their own events and the neighboring hotels and restaurants. It's astounding the number of different point products are still coming into the industry and, and, and that really suggests that we haven't gotten our arms around integrating all of this technology. >>And it's just another level of complexity. So what do you tell your friends on the buy side, right? Who know you and say, say Jonathan, I'm going, I'm going to RSA. How in the heck am I supposed to navigate not only the show specifically, but kind of this vendor landscape and then make sense of it all? I'm telling him to look for vendors that are partners that have a longterm perspective and that do the integration for you. You know, one of the things coming from an operational background, as I talked to other CSOs, like our job is to operate technology. It really isn't about integrating technology. It really isn't about OAA and product. I want to focus my budget and my resources on operating technologies and manage risk. So I look for partners and mentors like, like Fordanet that has a fabric with 258 plus different products and vendors that are already integrated out of the box. >>I'm looking for someone that solves complexity rather than a specific problem or specific threat vector. And I'm really looking for some of that helps me understand and manage risk because that's the object of the exercise in cybersecurity today. It's not about compliance, it's about compliance, it's about security, it's about resilience, but a reasonable level of care in managing risk. Right. And yeah, it's, it's a great topic cause I was thinking that kind of in terms of insurance. Yeah. In terms of, you know, how much do you spend and you can't insure everything to 100% right. So it's going to be some number less than that. Everybody else needs a piece of the pie. But how do you make those kinds of trade offs, investment versus risk? Because you can't absolutely protect everything. It makes no sense. So I think that value of it comes back to the CSO and his or her team. >>It's a very human decision. Uh, there is no prescriptive definition of what reasonable care is. You know, outside of one statement by Kamala Harrison, she was the state's attorney in California here, which is the CIS 20 is the minimum level of reasonable care. And so now we have to understand how do we define what is reasonable, what is the risk appetite or tolerance for a company? And once you identify those things, what are the controls and mitigation measures that you're gonna have in place to mitigate those risks? And then what's left is residual risk. And that's a hard decision. How much will you absorb? How much will you transfer, uh, and how much will you just tolerate? Um, but it's really no longer just about compliance, uh, and it's no longer just about having a security or continuity or resilience about all of those things. At a reasonable level. >>Right. It's interesting as pulling up Winnie Naylor from, from Cisco gave one of the early ketos and she talked about, you know, really this security profession, embracing those pesky people that keep clicking on links because really they're the people that can, that have the data around the specific, um, applications and specific assets that the company has to kinda have that informed decision as to what is it worth to protect and do we need to protect it? Do we need to protect them more? Can we let this thing go a little bit? Yeah. I think the human element is the hardest part, you know, in mind at this conference and its theme, that human element. The hardest part about this job is that it's not just mechanical issues on routing issues and networking issues, but it's about dealing with all types of humans, innocent humans that do strange and bad things unknowingly. >>And then malicious people who do very bad things that by design. And so the research suggests that no matter what we do in security awareness training, some 4% of our employee base will continually fail security awareness tests. Well, we fished actively. And so one of the things that we need to do is use automation and intelligence so that you could comb through all of that data and make a better informed decision about what risks you're going to mitigate, right? And for this 4% that are habitually abusing the system and can't be retrained while you can isolate them, right, and make sure that they're, they're separated and they're not able to, uh, to do things that may harm the organization. Right. The other human element is the people on the security teams, right. And it's a tough resource. There aren't enough of them. And, and, and historically, they'd been the ones that, that integration point between all these different systems and it's a highly stressful job. >>You know, there was a Forbes article that said 17% of all CSOs are functional alcoholics. I mean, I mean, and they met as a 17 for 17%. One of every six CSOs medicates himself or herself with alcohol. And medicate is a very specific term of art. It doesn't mean recreational drinking means you are a functional alcoholic and that tells you about the level of stress and complexity. You know, in this job, our research suggests that the average CSO lifespan is somewhere on the low end of about 12 months on the high end, somewhere about 24. You know, in their role or in their profession, their role and their current job, their current gig, they're not lasting more than than two years. Uh, the sheer complexity and stress of the job and you know, and, and those, of course, 24 months, three of those months are just orientation cause that gives you an idea. >>It's a level of stress and complexity that the average CSO is going to face here. Right. So really begs for a lot more automation, a lot more automation on the defense side. It does, it, it makes for a lot more automation. And how do you help those teams cope with a massive levels of complexity and data that's coming out of these digitized and digitally transformed enterprises, right? And when you think about each person's going to generate three to five terabytes of data per person per day, uh, and that computing is going to change in the next three to five years. Right now 85% of computing and data generated comes from traditional it functions as you move into 5g and edge based computing, the vast majority of data generating computing will be done on the edge. So the level of complexity, the number of technologies and devices that we're going to have to monitor is only going to expand, right? >>Right, right. And the speed of those transactions and the speed of the potential harm. So marry that against the research data says that 99% of the attacks could have been mitigated through simple intermediate controls and that the patches, the signatures were readily available. And so the thing to contemplate as we go into this heightened level of complexity and expansion of our computing environment is we're missing the basics today, right? Right. If 99% of the successful attacks are based upon exploits that are known that the signatures are available in the patches available for then a year, what are we going to do when everything else becomes even more complex, more sophisticated. Yeah. That's funny. That was part of, of of raw heats keynote, uh, to kick off the whole thing is he said, you know, we as security professionals like to focus on the complex, we like to focus on the, the ornate and the, and the super sophisticated attacks on the reality is the vast majority and we're just coming right in the normal side door that they've been coming in all along. >>And one thing I decided during my time at the Verizon data breach investigations report was a 77% of all the breaches were not identified by the security team. They were identified by law enforcement. And so 77, 77% of the case. So let's, so let's say you've got a CIS admin that that goes out and accesses financial information before the earnings call and does insider trading. And it's the sec that calls the FBI. And then it's the FBI that calls you and said, by the way, your CIS admin is going to be charged with insider trading. And that's how they know that there's been a compromise out. And in many cases, what does that tell you? Despite $130 billion of network security spend this year alone, that's seven out of 10 data breaches will be identified by law enforcement and not the security team. Yeah. So that tells you that not the security law enforcement team, either it's the FBI or the sec hires the cl service and it just says that security is so complex that until we find ways like the FORNAS security fabric to automate and to manage complexity in an integrated way, you know, that's the, that's the leading edge indicator that I look for is that at what point do security teams identify more data breaches then law enforcement and the victims and they're way behind at this point? >>I think so, unfortunately. Yes. That's crazy. So, um, but there's a lot more AI now that you guys can use to write on the good guys side. But how does that really square the circle when you're saying so many of it just comes through the simple approaches because of lack of visibility. Uh, SOC teams are overwhelmed by the volume of data. And so the way to address the volume and variety and velocity of data is to use artificial intelligence to use a machine to make human decisions and behavior at machine speed. And so when we launched our 40 AI product offering and the virtual security analysts, you know, the research that we did suggest that is he pivoted a five SOC analysts. And so that's one way of helping SOC teams that are overwhelmed by the volume of data that are understaffed, to use artificial intelligence to distill out from all of that, that data, that useful patterns, and to marry that with our Florida guard intelligence, say, okay, this is the techniques, tactics and procedures most likely associated with this threat vector right now, escalate that to a human to make a decision on whether you want to mitigate that. >>And once you decide to mitigate that, use the automated and integrated capabilities of the fabric to make an efficient and effective, uh, mitigation, uh, of that incident. Right? Yeah. Yeah. That's interesting. You bring up the sec case. We had a conversation earlier today where we were talking about deep fakes. Yeah. If somebody had the use case that, you know, what, if you just had a pretty straight forward, deep fake of some executive from some companies saying something to move the market and you drop that into the, uh, into the social stream three minutes before the close on a Friday, you get a play off the off the margin leverage. Nobody gets to really investigate the thing until the four minutes are over. Markets are closed, right? You get a significant financials damage in a situation like that, not even really directly impacting the company system. Right. >>So you're, you're hitting on the fact that we are more interconnected than ever and that the traditional compensating controls that we would have used to mitigate that type of risk is not, not as effective. And so, you know, that's going to be a challenge moving forward. Everything is going to be more interconnected, accelerated and decisions will be driven by data. So it's all of those things will drive complexity. So maybe next year when we talk again, we'll see it and see that. But I'm a little, one of the reasons I'm, you know, I have a credit freeze personally is that I'm aware of things like, like deep fakes, uh, impersonations moving my identities. So having a credit freeze allows, allows me to know that no one can leverage my credit even if they have my data. Right. Interesting. So thanks. Question. We sit down here a year from now, uh, without the benefit of 20, 20 hindsight. >>Yeah. You know, what do you think the themes are going to be? What, what do you see as kind of this kind of short term move in the market based on some of these factors that you've identified? I think, uh, more automation, more uh, artificial intelligence ways of automating the traditional process was insecurity. The secondarily, I think there's going to be the rising awareness of edge based computing and smart systems, autonomous level five vehicles that are networked and rather than a sensory based awareness, smart homes, smart industrial applications, uh, that computing will be done on the edge increasingly and those industrial applications, that 85% of the data computer will be done there. And that increasingly the cloud will become a repository for, for, uh, for storage and correlation. But the actual computing and actuation will be done on the edge. And so as 5g takes hold, you're going to see tremendous transformations in our society and our economy and how we conduct commerce, how we communicate. >>Uh, and that leads some more complexity. That's why, that's why I'm so focused on helping organizations getting security right now before that next onslaught of complexity hits us. It's coming. It is the five G IOT thing is, is just around the corner. The look at the telcos, there is a very specific reason why they're investing literally hundreds of billions of dollars into five G and the tremendous societal and economic changes that that will bring in infrastructure, communications and security will have to stay pace with that. One of the things that we're going to see moving forward is that the digital infrastructure is only successful only as successful as a security is. And I think we'll, we should see a breakdown in the traditional operational silos in network operations and security operations as Michelle Dennett. He said earlier on the air, if you cannot protect, you should not connect. But unfortunately people are still connecting before they're ready to. Absolutely. Well, hopefully there'll be a little bit more circumspect going forward. We'll try Jonathan, thanks for, uh, for taking a few minutes and sharing your perspective. Really appreciate it. Always a fun time. Alright, Jonathan, I'm Jeff. You're watching the cube where at RSA 2020 from downtown San Francisco. Thanks for watching. We'll see you next time.

>> Announcer: From San Francisco, it's the Cube, covering PagerDuty Summit 2019. Brought to you by PagerDuty. >> Hey, welcome back everybody, Jeff Frick here with the Cube. We're at PagerDuty Summit in downtown San Francisco. It's about a thousand people, fourth year of the show, third year of the Cube this year, happy to be back. Ironically, (laughs) a couple weeks ago we were at Sumo Logic Illuminate down the road by the airport, and we're excited to have somebody from Sumo here to talk about how do these platforms work together. So, returning again is Jonathan Rende SVP products at PagerDuty and joining us is Bruno Kurtic. He is the founding VP of product strategy for Sumo Logic. Bruno great to see you, Jonathan welcome back. >> Thanks, for having us. >> All right so Bruno we were just at your show, now you got to take a little bit easier, probably quite not as many responsibilities. We'll talk a little bit about your relationship between the two companies cause from the outside looking in, looks like there's some redundancies, it looks like two platforms, it looks like where's my single pane of glass but in fact there's a real synergistic opportunity to work together. >> Good question, so they are two platforms but it's entirely synergistic. You know between the two technologies, PagerDuty and Sumo Logics, we sort of helped our customers who run mission critical products and services that serve their customers in fact, number one, get information from their systems and applications to understand what's happening in them and then leverage our two platforms to resolve those issues, make sure those applications are running, that their customers are happy, that they're delivering the services that they are there to deliver to them. >> And I know Jon you got a long list of great companies that you guys work for and you said it's a really key part of the company strategy. >> Yeah the ecosystem that we work with with one of our favorite partners, Sumo Logic, we use Sumo, we're a big customer of Sumo Logic as well and it's really important all of the telemetry, all the machine information that's coming in. Again the part that we play as in that is how do we orchestrate people to get work done when things go south? And how do we get the right people on and give them some information about what they're doing to help triage what they're doing. >> Right. >> So the two work together really, really well. >> So what are the themes at both keynotes? Ramin's keynote as well as Jennifer's is data. And the fact that you guys both have a giant proprietary data set about machine activity and people activity from running these businesses. I was teasing on Twitter an overnight sensation ten years in the making that you can leverage to deliver more value. So, as we look forward, data's been important but, right, now all the hot topic is machine learning and artificial intelligence. How are you now taking this next gen technology and applying it to these giant datasets to offer kind of proprietary insight to your customers. I'll start with you, Bruno. >> Sure, so there's a massive amount of data, right? It's growing at a rate of Moore's Law so there's more data than any human could cope with. And so our task at Sumo's is figuring out what is that data trying to communicate to you? So we spend a lot of effort on machine learning, pattern detection, advanced analytics, to help our customers sort through that massive amount of data to understand whether their services are available, whether they're performing, whether they're secure, whether they are compliant, and we boil that up into a set of insights that we then feed downstream or upstream in this case to PagerDuty to help those people who are responsible for those services do the work to make sure they're restored and working well. >> And I guess to compliment what Bruno is saying, one of the things that we're doing is we're also ingesting a lot data, a lot of machine data from monitoring products and from service desk products, other kind of sources of data because that also informs who needs to get engaged when a system goes down? And then what do they need to do in order to fix it? And so it's all context it's all data and how we can help narrow that down. We had a really interesting statistic this was earlier this year where we were looking at per responder how is this growth of interruptions and alerts, how is that trending? And now compared to just a couple of years ago it's about three times the amount of noise that's coming at them now per responder than three years ago. So, clearly the people on the end of this are getting overwhelmed if we don't do something intelligently (laughs) to make sense of it for them. >> Right. That's interesting cause it's really a lot false positives, (stammers) I don't know if that's the right characterization but certainly too much to prioritize and an overwhelming amount of data for a person to try to filter, so you're really trying to add that intelligence on the front end so hopefully the right problems are getting surfaced and not just this broad (laughs) base of false positives, or minor positives maybe. >> Yeah, it's funny you say false positives because one of the concepts that we have is there are you know, alerts and incidents that need to be managed, but then there are un-actionable alerts and incidents. Things that really shouldn't be bothering you. So you have to walk that fine line between what do you act on that you should take action on and what are the things you shouldn't take action on and kind of ignore? And so we use machine learning to do a lot of that work and filter out the bad noise and bring the important information in. >> Yeah, I wonder if you have any thoughts, Bruno, on how much of that filtration needs to happen (laughs) to kind of quiet down this tsunami that's coming over the transom. >> Well on our terms it's, you know, every one of our customers send us billions of records per day, literally billions. >> Jeff: Billions of records per day? >> Billions of records and so figuring out what matters amongst those billions of records is a hard job. There's a lot of false positives, false negatives that need to be sorted through, before it even gets handed up to the upstream technologies like PagerDuty, right? So, we spend a lot of time doing outlier detection, doing predictive analytics, doing sort of pattern detection, machine learning type of techniques to make sure that the stuff that gets bubbled up has as few false positives and as few false negatives as possible so that the insights that intelligent actions that need to be taken are most appropriate and can be prioritized and handled by a small team of people who own those actions. >> Right, it's funny you say billions and billions. I have a digitalization challenge, I keep throwing out to people and there's yet to be, I've yet to get a great response which has shown me a billion, a billion piece dataset in a visualization that I as a person can look at and comprehend what the heck is going on. Beyond something as simple as you know, half of them on this side and half of them on this side. I mean we're not wired for that way. We're not wired to be able to take in billions of data points. It's just not, it's just not going to happen. >> Just for that context we actually, we analyze a quadrillion records a day. So talk about billions and then you know many more orders of magnitude than that, it's, those are numbers that are hard to comprehend, right? We don't think in those numbers, right? It's really hard to humans to grasp. >> So, so how do we keep up? I mean, how do we keep up? I mean it's kind of a bigger problem, but you know as much as anybody kind of exponential growth of this data. We're barely getting into IOT and industrial IOT and sensors on everything at the house and on our clothes and our shoes. You scared about keeping up? Can we keep up? What do you, you know, kind of, how do you see this crazy trajectory on the data? We have to kind of gate it somehow? >> So from my perspective there is no sense in being scared of it, right? A digital business generates data, we all got data that can't run. So the task is to capture it, analyze it, to understand it and serve up intelligence from it, right? So our task is to keep pace with that growth and build resilient scalable systems with the analytics that are required to understand it, right and so you know we can't shy away from it, so whether we like it or not. >> Here it comes (laughs). >> It's not an easy task but we can't walk away. >> Right right, and then the other just crazy increasing complexity. No, thank you. (laughing) Is on your guy's side, really is the variety. I mean we used to talk about the old big data big three you know variety, and veracity and velocity. You know the interconnectivity of all these systems is also the thing that's growing so exponentially and so when something does break the ability to find what broke amongst this huge potential is really a hard and growing problem. >> Yeah, it is and that's why it's sitting in the middle of an ecosystem of a lot of different products that will give and send off to telemetry that we have to look at. It is really important. You know, it's almost as if the information that we're always looking for on the PagerDuty platform, it has to be items that really are actionable by a person which, you know, if you look at the information that is flowing into Sumo Logic, it's even in some ways very broad. And so it's a wider funnel, we have a narrower funnel of kind of information but they're both very complimentary at each other cause one is that humans need to act on in the moments and the other one is how do I analyze in a broader sense? >> Right. >> Even a bigger range of information so both are so critical as a part of that whole ecosystem. As I was saying, we personally use Sumo Logic as a big part of how do we actually triage actual incidents? We built tons of libraries in the Sumo Logic product so we can make sense of even a broader set of information flowing in from all of our logs in some of those critical moments. So yeah, it's great synergy. >> Good, good, well I'm glad you guys are working on this big data problem cause it's a big hairy one. >> Jon: And it just keeps getting bigger. >> And the customers only benefit right? >> Yeah. >> Well Bruno, Jonathan, thanks again for taking a few minutes. Congratulation on the collaboration. It looks like it's working pretty well. (mumbling in agreement) He's Bruno, he's Jonathan, I'm Jeff and you're watching the Cube. We're at PagerDuty Summit downtown San Francisco. Thanks for watching, we'll see you next time. (rhythmic synth music)

>>from San Francisco. It's the Q covering pager duty. Summit 2019. Brought to you by pager Duty. >>Hey, welcome back. You're ready, Jeff? Rick here with the Cube. We're downtown San Francisco at the historic Western St Francis. A pager. Duty summit. It's the fourth year pager duty Summit, 30 year for the Q. Being here, I think they've about outgrown the venue. So he looked forward to seeing where we go next year. But we're excited to have somebody is at a very busy day. A lot of product announcements leading a lot of this effort. He's Jonathan. Randy, this s V P. Of product for pager duty. Jonathan, great to see you. Thanks for having me. So, congratulations. A lot of Ah lot of product announcements today. >>This is our biggest unveiling of the year. >>What s so I don't want you to pick your favorite baby, but what are some of the highlights? That goddess here today? >>Yes, a couple of big things today and tomorrow, not just today. >>Uh, >>first, we're really focused on applying. It is the buzzword of the sense of the new Millennium machine learning, but we're applying it across our entire portfolio, and we're doing it in a good way, not in a creepy way. We're doing in a good way to help organizations make sense of all the data they're getting. Tell him what's happening and, more importantly, what they could do to get better. And so that's something that we call our intelligence Dashboards is part of our analytics products. That's one big one, right? Right. And as you probably know, being here, pager duty is all about helping teams to be more effective in the moments that matter. And one of the other big announcements we have is intelligent triage. And so what is it way See with There's a lot of great companies here, partners that we're working with and whenever they're working, major issues within their companies were seconds, matter or even microseconds. They could lose millions of dollars that work in real time. They'll find out that there's multiple teams working on the same problems on Lee for one team to find out that somebody's undoing some of things that they're doing. So we focused in a huge way on building context, the visibility so that the teams in see what other issues air related That's what we call intelligent triage. So nobody needs to do double work, >>right? It's funny on the on the A I right in machine learning because they are the hot, hot, hot buzzword. But what I don't think are the hot buzzards, which is where all the excitement is happening, is it's the applied A I it's not Aye aye, for a eyes sake. Or were great. Aye aye company with an aye aye widget that we want to sell you. It's really leveraging a I within your core application space, your core domain expertise to make your abs do better things. And that's really what you guys have embraced. >>Absolutely. It's way have to be so empathetic to our users. Are users carry an unbelievable burden. They are on the front lines when things go down. They have, you know, minutes, seconds to make right decisions, and there's a lot of responsibility with that. So we're using a I in applied way to help them make sense of being overloaded with information, focus them in on the things that can make the biggest positive impact right, So it is applied a I in its purest form and >>the other part I found interesting is really anak knowledge mint that it's not just the people that have to fix the problem that needs to know about the problem, but there's a much larger kind of ecosystem that ecosystem around. That problem, whether it's sales reps executive for certain, is a whole bunch of people that should know, need to know, have value, to know beyond just the really smart person that I've now put on fixing the >>problem. You're bringing up a great point, which is a lot of people know page of duty because of how we help technical teams, developers and office people fix these incidents. When they happen right when a site goes down or when something search isn't working correctly but getting work done. We're taking that in its broadest context. It's beyond technical responders. First we have to service them. They're our core audience. They're why we're here today. But that unit of work getting work done goes beyond them as you're saying. It goes to what we call business responders who I could be working in a customer service team and while that incident is happening, I need that information so that I can ready my communication in case somebody calls up the sports desk and opens up a ticket. I need to know what to tell him right when it's gonna be fixed and how we're addressing their problems. Or I could be the CFO, a stakeholder and just want to know what's the real revenue impact of this outage of this time? So whether I'm taking action or I just need to know these air people outside of the sphere of the technical team and their business responders and stakeholders and we're automating the flow of information all of them so that they don't interrupt the poor responders team so they can focus on their work, >>right? Yeah. Another concept that kind of clarified today is all of your guys partnerships. You know, you've listened on your integration page on the Web site. It's clear. Well, data dog sales for Zenda Sumo AWS service now last CNN, IBM Blue mix. I mean, it's they can't go through the whole list. It's a huge list, but I think confusion in the market or maybe clarification is helpful is, you know, kind of where to those systems play versus your system when that Everyone wants to be a system of record, right? Everybody wants to be the database that has all the all the information. And yet you figured out a way to take your capabilities and augment all these other platforms and really puts you in a nice play across a really wide range of a problem. Sets. >>Yeah, it's it's so core to who we are way like to think of our pager duty platform. I always refer to it as it's a central nervous system, and what does that really mean? We always say it's a central nervous system and pager duty is about people. So all of those vendors, all of those companies, they're all valued partners. Many of them are customers of pager duty as well. They use us to keep their service is up on the monitoring world. But what pager duty is always focused on is ensuring that people two people collaboration to get real work done based on the information coming from those folks. So a lot of those vendors out there they play such an invaluable part of the ecosystem. They let us know they provide all the telemetry in the information in the data way, make sense of it and then engage people Finish that work. So in a way, you know that central nervous system is taking all these impulses just like a really central nervous system. And we're engaging the right people to help them effectively get the right right, and we couldn't do it without them. So the famous 350 plus way couldn't do what we do without them, and they're all here today. You >>didn't think I was going to read the whole hunt 350 >>Hope. That would be a long way >>Hades in desk on. And I know that was part of the new customer service and has been getting, you know, kind of your value kind of closer to the actual customer transaction. It's always in support of the customer transactions. The website's down transaction close, but this actually has taken it to the next level toe. Have a direct contact to the person who's actually engaged with the client to give them or inside is what's going on as being resolved in these type thing with a two way communication pattern. >>Yeah, it's something I'm personally really excited about. Where customer of zendesk as well. So we use end us and they use pager duty. So we get a lot of feedback on what's working, what's not working, which informed us and what we were doing. But there's two big problems in the industry that I've seen over, you know, two plus decades, which is customer service and support teams. They're dealing also on the front lines. Having them communicate and get information from development teams isn't always easy. And so both of us are really interested in kind of breaking down the walls between those organizations. But doing so in a way that's not interrupting those teams when they're doing their work that they have, right, so one, that's what we wanted to accomplish. How can we share information seamlessly automatically? So both teams are in sync, but they're not pestering each other and then to that work that's being done on the development side, when something does go wrong in a devil apps world, now, the customer support agents, the service agents they can get ahead of those cases that are being opened up, so they're not in the dark. They're not being flooded by tons of cases being opened up and they don't know what to say. They ready their communications and push it out because they're insane. >>It's really you think pager duty and notifications were surrounded by all these dashboards and computer stuff, but you made a really instant comment. It's all about the people you guys commissioned. A study called I'm gonna read an unplanned work, the human impact of an always on world and really going after unplanned work. Now it's funny, because everyone always talks about unplanned maintenance and on scheduled maintenance and the impacts on aircraft and the impacts on power generation and aircraft. This is the first time I've ever heard anyone couch it as as unplanned, which is completely disruptive fours on people and their lives, not to mention their service workers. And, according to the study, 2/3 of her pissed off and not too happy the way things are going at work anyway, with what kind of was zenith of that. And that's a really great way to reframe this problem into something much more human. >>The genesis of this all came from the concept that a CZ you'll read a lot we say we're always on. Let's keep it that way. Let's help help everyone. Keep it that way. It's a mantra with pager duty, and it comes from again when I say Genesis, it comes from even within our platform way. Don't have me Windows. We are on 24 7 360 days a year way have to be up when other service's aren't because of that. Whenever we work with organizations or vendors that that we pay for. And they say we have a maintenance window like a maintenance window my partner in crime runs engineering team are meant for. He always says maintenance Windows air for cars, not SAS software like there are no maintenance windows. And what that means as a first step is, if that's the case, there's no maintenance windows you're always on. Then you have to answer this question of how much time are you really spending unplanned work interruptions, right? So we really started taking not the heart. We really started trying to figure out what is the percentage everybody's trying to innovate more. That's planned war, right? Is it? 10% is a 20%. Is it 50%? The best organizations we see our 20 to 25% is unplanned work. We'll >>need 25% for the best organization. >>Yeah, so means not. So best organizations are very different, right? And so way feel that we uniquely can help organizations get way better at cutting down that time so that they can innovate more, Right? They're not firefighting. They're actually innovating and growing their business right. That's a big part of how we help people in these organizations do their job better. >>God, that's before you get in contact. Switching and pressure and disruption and >>way found some amazing statistics in my prior life. Iran Engineering. And it was at a sauce company. And what I found was whenever customers, whenever my top engineers would be put on Call Way, didn't have pager duty at the time, and they would be on call and interrupted on consecutive nights in the middle of the night. First, I would typically hear about when somebody was burned out is when I would see a resignation letter on my desk or somebody way no, after two or three or four successive interruptions in someone's personal life that goes on where they feel they're not being productive. One, they aren't productive at work either, to they're a huge retention risk. So way have that kind of data. We can look at it, and we can help management and organizations help them. And their teams take better care of their teams so that, you know, they're they're being more humane, humane knots, not human off pain, All right. And how you deal with those most expensive precious resource is in your company, which are your people is really important >>when they walk out the door every night, you know? So you gotta take care of him. So they come back the next day. It is? Yes. All right, Jonathan, last question is you as we wait, we're not quite done with some yet, but as we come to the closest on her arm really busy year. The AIPO. You guys have done amazing things, but you kind of flipped the calendar. Look forward. What are some of your kind of priorities as we as >>we move forward? Yeah. So it's been a crazy year. A lot of change and a couple things going forward. One were big partners with Amazon in a W S S O were attending reinvent. That's a big event for the company, but also at this event. As I mentioned before, it's probably our biggest unveiling of new innovations and products for our entire 12,000 plus customers. So for us, it may seem like it's an end. It's really just the beginning, because all of these products and intelligent triage business response, intelligent dashboards, these products that are apart, his capabilities that are part of our analytics and events intelligence on the pager duty, platform way have to keep evolving This we have to keep kind of moving forward because the world is always on and we've got to keep it that way. >>What? Andre just had a great line in his keynote about being scared is the generator of wisdom. But here it is, right here. Fear is the beginning of wisdom. Not necessarily fear, but fear getting caught. Keep moving that we have ahead of the pack. All right, Jonathan, Thanks for taking a few minutes and congratulations. I'm sure tough getting all those new babies out this week, but what a great what a great job. Thank you so much. All right. Pleasure. He's Jonathan. I'm Jeff. You're watching the cube. Where? Pager duty Summit in San Francisco. Thanks for watching. We'll see you next time.

>> Live from Orlando, Florida It's the Cube covering Enterprise Connect twenty nineteen brought to you by five nine. >> Hello from Orlando and Lisa Martin with Student A Man. We are in the five nine booth at Enterprise Connect. Twenty nineteen. We're excited to welcome back to the cube of one of our alumni, Jonathan Rosenberg, CTO and Head of a Eye of five nine. Jonathan. Thanks so much for joining Stew and me on the program on Day one of this big event. >> My absolute pleasure. I'm super excited to be here and super excited talk about my favorite topic, so love to be >> so. This event is has been around for a long time. Twenty eight twenty nine years evolving from PBX to voice con enterprise Connect. You've been to this event about the last ten years or so, least your perspective, and I know you're new at five a. M. But your perspective on the evolution of not just the contact center but customer experience and really thiss changing landscape of how enterprises and people want to communicate with each other. >> Yeah, well, I mean, it's been funny to sort of watch this through this technology. Evolution that manifested the show and in the market for a long time was about hardware by big, bulky iron and we used to have the petting, the hardware, petting zoos, we call it. You have racks of equipment. You could go look at this >> blinky lights and >> cables, you know. And then it moved to software on. We saw that here and now we're deep into the software is a service, as cloud based delivery models and actually a bunch of ways were coming to the tail end of that into this aye aye era. And that's what's all the hotness, and you see tons of that. Almost everyone's put some kind of a eye logo, our branding on their stuff, and there's there is some real meat to it, but but that sort of this interesting evolution and on its in its infancy in the Contact Center. And that's what's sort of exciting about it. >> So let's dig into that a little bit, because a CZ Lisa mentioned you've worked for a couple of the other companies that have big boost here at the show. We've talked about intelligence back in the call center days. Oh, yeah, but, you know, tell us what's different about the Aye aye data. The center of everything is something that way. Definitely believe in something that we hear all over the industry in the cloud shows an A I and everything. Why is this so exciting? What really brought you five nine and gets you've got a storied career? You know what? Why here? Why now? >> What is the technology is finally ready. I mean, technologies like speech recognition. And we've been the industry has been working on that for decades. And it was only in the last five years or so with the sort of creation of practical deep learning that the tech finally got good enough. And and that was because of new algorithms, New date, you know, massive data sets, great hardware that all made it possible. And so that sort of opened up the avenues. And that's why we're seeing products like Alexa and Cirie take off. Is the tech is finally gotten good enough. But what hasn't happened? Yes, it hasn't shown up in the workplace, and that's sort of what's really exciting to me is to take these technologies that have become so pervasive in the consumer world and use them to really re imagine how a lot of these enterprise products work. That's why I came to five nine came to find time to do that. To do that for five nine to do that for the industry. >> So you had a session this morning. Five surprising reasons why a business should move their contact center to the cloud. And we know cost is not the number one. Talk to us about some of those key imperatives that an enterprise in any industry really needs to be able to take advantage of by moving to cloud >> right, so a cost was a unsurprising reasons. So what I did in my session was I said, all right. Five. Unsurprising. Here's ten. Here's ten obvious reasons. So I went through those and cost is one of them. But I know what's surprising. There's a couple of the big ones. Story, really is that if you go to a truce as player, they have lots of customers, and they can actually aggregate data software capabilities across those customers and do things that are impossible on premise. So the two of them, for example, are better reliability. Often people like what you know. I want to go to the cloud. I'm worried about reliability. Well, if you dig into it. You can see that once the technology is matured, the reliability can be much better than it is on premise. Because of the complexity that you could build. Same with security, often viewed is wait. It's more secure in promise. Actually, if you look at what you can do in the cloud, you can spend a lot more money on security and advertise that cost over multiple customers. And then, of course, there's a I, and that's about getting access to training data, but not just training data from one company, but using it across multiple companies to make the I work better for everybody. So those were three the big ones. >> So when you talk about that kind of learning, how do you make sure that there's proper firewalls is, you know, is five nine going to be able to say, Okay, we can take care of everything. But wait, I don't know what my competitors on this I don't want them getting advantage based on you know what my company have. How do you balance? You know, there's the security issues. There's, you know, personal information issues, and they're, you know, competitive dynamics, which you know, is a talking point in the cloud. These absolutely. I mean, >> so that's a That's a paramount consideration to design of this whole thing. So it starts with a basic level of like, opted, like we're just, you know, we can't do this, and we can't use your data to train a model that shared unless you want it. And generally it's a given get like, Oh, you want access to the shared model, then you you provide training data for it. If you don't, you can use a custom one, but it won't be as accurate. But then you don't show your day. That's your choice. So give the customer the option and give them something in return for their data. And, of course, there's other parts of it, like, Well, you know, almost all the time, people aren't actually like looking at your data, its dues to train. These model's ideally without human in the loop having to do that. And so there's other privacy considerations baked in that it's that makes it feel that gives a customer comfort that they're they're able to do this >> without trust is critical, right? We talk about it stew and ideo and the Cuban every show. But that's really essential because, as we know is consumers, we're more and more and more empowered. These days, there were transacting something through chatter, video or Alexa or we're checking on. The status of a mortgage is something We have so much information. They also are very demanding. You want to have this conversation with a business regardless of the channel, and I want them to know what I'm what my issue is so that it can be addressed and resolved quickly. But I also want to make sure that what you're doing is not, you know, in the issue of privacy that we've all faced recently that it's done in a way where this business can actually foster a trusting relationship with me is like, >> Yeah, so the trust goes on many levels, one of which the most important to us is our customers have to trust us, and that's the only thing that gives trust his time. You know, you have to be invested for a long time, and so we've really focused on building this longtime customer trust with our reliability, with our high touch with our customers, and that gets us That's really just what gives us permission to even start to do these things. The other thing to to touch on what you said is that end users contact the contact center. That's one of the areas were actually there is already in the user expectation that my call is being recorded, that what I say can be used for training purposes. So one of the reasons I got into Contact Center was that the privacy issues are much more readily addressed in the contacts and space and other areas where you might be interested to apply this type of technology. I mean, we're talking about having a eyes that are listening in on calls and analyzing what you say. If I were to do that for a regular phone call between me and my friend like people be totally spooked like there's no expectation that that happens. There is an expectation on the contact center, so that's a great place to build and grow these technologies. >> Yeah, I love that because, right, those of us that have, you know, personal assistant at home there's almost an expectation that they're living listening in a little bit. Everybody's had the weight I was talking about that with someone not even on the phone, and all of a sudden I'm getting ads for that. That's not right. So question I have for you, you hired your first data scientist in the group. And one of things we look at is we now have this, you know, great access to data. One of the biggest challenges is okay, I can get the answers if I know the right questions to ask, What are some of the early areas that you're poking at? Any early use cases that you can share as to, you know, where we where we cease? Um, how did you >> do that? One of the first things we're looking at is what I'm calling cross customer analytics. So analytics is old news. Everyone's had that for a while. But what the cloud does is it gives a provider like us date across multiple customers. Now what we can't do is share one customer state is with another. That's a total nut. It's not what I'm talking about. But aggregates are interesting. So, for example, would be intrigued to know this is my first call resolution rate. How does that compare to similarly sized contact centers in my geography right, And that's something where we can produce an aggregate that has total anonymous ation. So no privacy issues, and it gives a customer this piece of insight that they have never, ever had before. Never, and the only way you could do it with enough privacy. Seven of data to produce a useful AGR ee it, and therefore it can only be done at the larger cloud contact centers and thus five nine, as one of the market leaders were wear having enough data to produce this kind of information. So this was an immediate, frankly fairly low hanging piece of fruit. We've started to dive into no product announcements. It's just just looking at data to see what comes out and see if there's interesting meet there. But it's a kind of insights. I'm really excited about >> it. I love that because people are always like, Oh, wait, I need to measure it. But sometimes numbers alone don't tell me anything. You gotta put that into context for me, right? What are my peers? What? One of my industry. You know, what other stuff do I have there? Otherwise, you know, numbers are just numbers. >> Numbers are just numbers. You don't really know how you're doing. You're like a little island, like, you know, your contact center is doing, but is that good? You have no idea. And we'LL be able to unlock that overtime. So very excited about that. >> Yeah. Sorry, Stuart, You guys have about five billion recorded customer conversations, so you can I can think of the massive amount of competitive advantage that's in there. But you also brought out something that I hadn't considered before. And that is whether I'm, you know, interacting with the business because I haven't issue to resolve with my Internet or something. And you're right. We do have this expectation that the call's going to be recorded, but I never think about it is this is actually something it's gonna help me down the line or the fifty other people that aren't calling in. So I thought your comment on privacy being kind of more advanced in the context of her was was point. It was very interesting and not something that I was aware. >> Yeah, it >> has to be right >> exactly. There's there's an expectation that this is what this conversation is about and and there's lots of tools in place for dealing with today. Already with credit card numbers and phone numbers, which do get communicated between a user and the comics in URGENT there's lots of you know, tak and precedent about how to read, act and extract and again all in the contacts and are nowhere else really does that technology exists. So >> yeah, so Jonathan, take us inside the life of the agent, so we know when we're from call centre to Contact Center. It really brought in the role a little bit when I've got a eye in there is their new skill sets. We need tohave. You know, we always talk about, you know, if if you're doing the same thing you were doing five years ago, chances are you might need to be looking for a new job, because by so fast, so in the context center, you know what, What? What is the life of the agent likely to go through over the next couple of years? >> So this is an interesting debate in the lemon, the industry, and there's sort of two thought camps in this one thought camp is the role of A I is to replace the agent. And this, frankly, is fairly traditional thinking. We use terms like Deflection, right, like we want to deflect the call from an agent means we don't want you to connect to a human being or containment, right? How successful were we keeping the call in the I. V. R. And a customer never got to an agent like these air industry terms, and they were. And people view a I is like helping those things. There's a different camp of which you can tell I'm sort of in, which is like, No, no, no, that's sort of the traditional way of thinking about it. And of course, we're gonna have voice spots and I V R is. But really, the question is, how do we deliver the best customer experience possible? That should actually be the guide post, and what's funny is in this industry we know what the best customer experiences. It's that you pick up the phone, you call the comic center. You didn't wait one second. You went right to an agent. They were an expert. They knew exactly what to do. They fixed their problem in twenty seconds, you were done. That's the best experience. The problem is, is no one can afford to deliver that experience today. Well, that's where technology could help. So for me, the central question is, how do we use a >> eye >> to label us to make it cost effective to deliver that experience all the time and that does have an impact on the agents. And it's going to be through assistance technologies that allow the agents to be guided in their interactions and allowing them to be experts quicker and to learn from the best experts in the contact center and change the way they think about training and access to data knowledge. It's going to be a pretty profound change, but it never takes the human out of the loop people. When you pick up the phone to call that Connick Center, it's because you actually want to talk to a person and that human touch, that empathy that you know, someone just tow, you know, vent at a little bit that matters, and we're nowhere anywhere near having an A. I provide that if ever so that's what's going to change >> humans and machines or Jonathan, Thank you so much for stopping by. The Cuban wedding was with me about what's happening at five nine. Contact Centerist Service and the tremendous advantage that data could bring two organizations. >> My pleasure. Thank >> you. Thank you for watching the Cube. I'm Lisa Martin was stewed Minutemen on the program Today Live from Orlando at Enterprise Connect twenty nineteen stew and I will be right back after a short break.

(upbeat funky music) >> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a Cube conversation. >> Hello everyone welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier. Co-host of the Cube. We got two special expert guests here talking multi-cloud, Jonathan King, Vice President of Strategy, Data Center, and Cloud for WWT. And Fabio Gori, Senior Director Cloud Solution and Marketing at Cisco. Multi-cloud is the topic. Guys are in the throes of it. Jonathan, you're in the front wave of a massive shift. Cisco powers networks for all companies these days, so guys multi-cloud is a reality. It's here. I want to get your thoughts on that, have a conversation. Thanks for joining us. >> Great, glad to be here. >> So multi-cloud is not really been debated. I mean people generally now step back and say multi-cloud is a reality. It's here, people have multiple clouds. Should only have data center on premise. But this idea of multi-cloud and hybrid cloud are somewhat getting mixed up, but multi-cloud is certainly more realistic in the reality sense than anything else. What's your take on multi-cloud, Jonathan? >> So I think we're at a point where there's a growing acceptance of multi-cloud as the architecture of the future. And when you arrive at that point it also means that multi-cloud is the architecture for today. Because if you see your competitors, you see new entrants in your space, moving in a rapid digital pace to meet their business needs, and you're not on the same kind of architecture. The same footing. Then you're going to be left behind. So, used to debate private cloud, hybrid cloud, multi-cloud. The way we see it is that we're in this multi-cloud world. And multi-cloud embraces an end-to-end imperative. How am I getting my apps and my development teams building those apps closer to my business and meeting my needs more rapidly? And then how am I connecting my entire business, my data, my network, all of it, to meet that needs. So multi-cloud architecture's really an imperative. It doesn't mean it's the only thing. There's other elements in terms of having a clear digital strategy. Thinking about how you're going to modernize your infrastructure. Of course, thinking about how you're transforming your security. All four of those elements really comprise a enterprise architecture. Multi-cloud being a core part of it. >> Fabio, Cisco, you guys have seen the waves of innovation, internet, connecting companies together through networking etc. Multi-cloud's a big part of your focus. Certainly at Cisco Live we covered that. What's the definition of multi-cloud now, because I've heard, it's been debunked, but I've heard people say, oh multi-cloud's an application workload moving across multiple clouds. Some say, no, it just means I have two clouds. So what is the definition? Baseline us here. >> So it's interesting because you can go Wikipedia and actually read the definition of multi-cloud, but what I'm really interested in is exactly what Jonathan was saying a moment ago. This is one of those rare cases where what you hear architecture is actually a technology architecture and the business architecture really coincide. People want to use innovation wherever it comes from. And because you can't allow yourself to be just restricted your choice, people want to have choice. Multiple choices. And that's why we're seeing adoption of multiple cloud services. Multiple SaaS solutioning for structure service solutions and the likes. So this is really what multi-cloud means. You're satisfying a business need. And while cloud computing was born, as we know, around 10 years ago, and it probably started with a kind of cost connotation, the speed and agility that you can get out of it now overwhelm the other parameters. And people are ready to spend anything it takes to become faster than their competitor, because that ultimately will really determines your destiny in the marketplace. >> And I want to drill into the tech side and have some specific pointed questions I'd love to ask you. Jonathan, first, talk about the relationship that WWT, World Wide Technology, has with Cisco, and your credibility in multi-cloud. You guys have a unique view First of all you work with Cisco, you guys partner together. A big part of your business. But you guys are in the middle of a lot of the action. Talk about the company. What kind of deals you guys are doing? What visibility do you guys have? Is it a landscape? Give an example of some of the work that you guys do, and then talk about the relationship with Cisco. >> Yeah so, the Cisco is a very strategic partner of ours. They have been for a long time. And we have the benefit of being at scale with Cisco. For repeatable waves of technology roll outs. In repeatable domains of technologies. So, customers come to us and look for our help as a trusted advisor to help them with their architectural decisions. And to help them often with knowledge gaps. So, architecture is a challenge. Especially when you're dealing with rapid change. So you have a pace of change externally. You cover this space. I mean every day, right? We were sitting here there's some kind of new thing going on. And, that change, I mean even companies who know what they're doing, and have deep benches of talent, have architectural challenges. But you take it to an enterprise or a government agency. How are they going to keep up? Well that's really our job and the value we bring is. We are constantly watching, talking to partners, talking to customers. And there's almost no one we're that as closely with as we are with Cisco, in terms of how we're watching trends, looking what's happening. And from a multi-cloud standpoint, in answer to your question there, it's a bit of a thought experiment. So if you define multi-cloud as really just, oh it's just between Amazon, Azure, Google. Multi-cloud is just multi public cloud. We do not see it that way, our clients don't see it that way. Our clients see it as a bigger domain. That multi-cloud includes how you're connecting to SaaS. How you're, there's multiple public clouds, a bigger definition there. But then it's also the edge, the cloud edge, the different edges that are out there are are being deployed in a cloud architecture. Your core data center has a private cloud. All of that we see as multi-cloud. And when you define it that way, you start to look at it. Companies are saying who do I turn to to help me with a multi-cloud architecture? Do I turn to someone that was born in the cloud. Who just really knows AWS. They know it really well. But that's what they know. Or a similar consulting company who's over here. The credibility that we have, we have those capabilities. But we also have depth and breadth, and history, and knowledge, and contracts and relationships. An incredible ecosystem. And important with Cisco, it's not just a one-way relationship. We have an ecosystem around us, collectively, that Cisco benefits because we have that ecosystem. And that's really what companies look for. It puts us in a very unique position because we see this AND world. It's not an OR world. And I think even the investments and movements that the public clouds have made recently. The hybrid offerings that they're bringing, and where Kubernetes is going to enable portability. All these things really are about a multi-cloud world, and we're just excited about where we are. >> It's interesting, there's the first wave, Amazon, I call it the Amazon wave because they really did take out the beach. And then public cloud. It kind of showed the way, the economics and the value creation piece. And you mentioned a few things that point at this next wave. That next big wave I see it is about people and technology. This holistic view around multiple architectures is a systems concept so it's not unproven. And Fabio we've seen this movie before in systems. Operating systems. You need networking. You got to connect things together. So this next wave of thinking about workloads and applications in context to an architecture see to the next narrative that people are starting to talk about. Versus. >> Absolutely >> Public cloud, because the people equation, who's going to run it, who's going to service it, who's the coders, what tools and APIs do I use. People behave in certain ways, and they like their favorite cloud, so it's a whole different ball game. You're thoughts. What's driving all this? >> I would say, look, we could talk about this forever. But I think we're seeing a pretty dramatic shift into an architectural model, right? I mean, if you remember a few years ago, we had networking specialists in the data center, storage specialists and compu-specialists, well guess what, people moved to full-stack type of expertise, right? And now we even have systems that are completely converged. Or hybrid converged. Well, we're seeing the same movie in the cloud. Where we're seeing the rise of cloud architectures, enterprise architectures, which become really determinable of the business. And these people, especially in the companies that are ahead of the game, in terms of cloud adoption and expertise. These guys are issuing the new guidance and guardrails for the entire organization in terms of what governance role you need to take, right? And the other groups actually execute this kind of strategy. This is, some people say this is finally SOA coming alive. The SOA, Service Oriented Architecture. That's exactly what it is without probably some of the kind of propriety underpinnings, or driven by certain market players in the past. This is a true, so if you think about microservices in containers, that's exactly what it is. And also we're seeing a lot of companies that are starting getting even organized by microservices. Which is the ultimate demonstration that the technology architecture and the business architecture are really converged. It's a fairly complicated concept, but in the end it's about really connecting the business to the underlying technology. >> And it's a shift that's happening in front of our eyes. And we're covering a lot of the news. Some notable news that we've been covering lately, the Department of Defense JEDI contract. That's in the public sector and military. CNCF, Amazon re:Invent. Google Nexus coming out. You're starting to see the formation where it's not about the cloud vendor or the cloud supplier anymore, as much as it is about the workload. So, there's been a debate of sole sourcing the cloud, that's certainly, we're seeing that on the DOD side 'cause it's more a military procurement thing. But that's not the right answer anymore, we're seeing that whole, spread the multi-vendor love around. It's not so much like it used to be. It's different now, there's new architecture. So, Jonathan, I want to go back to your multi-cloud architecture because I think the strategic question that I'd like to get to is. It might not be a bad thing to pick a cloud, a sole cloud for workload. But that's not meaning you're going to not use other clouds. This is a whole different thinking. So I can pick Amazon for this workload or pick Azure for that workload and Google for that workload. And holistically connect them all together. Seamlessly, this is not a bad thing. Your thoughts. >> There's a somewhat of a paradox when you talk about multi-cloud architecture and then you talk about moments in time where it makes architectural sense to pick one cloud, right? That particular decision there's issues around people and training and technology, and time to market, and API coverage. So there's all these things that you're trying to get a job done or a mission done and the amount of time that you have to achieve that job or that mission. What path am I going to choose? What engine am I going to put on the plane to get me there? Now that doesn't mean that that's the only engine you're going to put on your fleet. It just means that particular plane is going to have that kind of engine. And then the next time, you got another engine, you got a different kind of plane. You're thinking about how you're doing these things in waves and modules, and you're trying to build your aggregate velocity, 'cause really if you strip it all down. You know earlier we were talking about multi-cloud and people and talent, we're in a distributed computing land rush. And businesses of all sizes, government agencies, companies are trying to figure out how do we, you know. Electricity came along, now cloud has come along, right over the horizon cognification's coming along. How am I as an enterprise getting digitally ready, and getting on a footing to be able to do what I need to do in that domain? And really, it's about velocity and movement, so. Now that means that, that's why architecture is so important, because you have to make, you want a, people talk about one-way doors and two-way doors. So you want stop and think about, am I going through a one-way door or am I going through a two-way door? Meaning, do I have a way to come back? Is this a decision that I'm going to live with? If so how long? Is this a decision I can go through and I can come back? These kinds of approaches let you look across it. So an example would be networking. So networking is a foundation to every multi-cloud strategy. So you have to think, today my network in many enterprises is still a campus branch architecture. Well traffic patterns have changed. Even if you've just done nothing your customers have moved. Like all of a sudden, you know we talk to customers. We work with retailers, we work with all kinds of people, and it is like Global Climate Change. It's like global network change. The scale at which the clouds have arrived have changed the network patterns. So, if you start to look at it, you're saying, well what is a multi-cloud networking strategy? How do I need to rethink, well, guess what, the campus, my headquarters, is no longer the hub it used to be. The hub is now at the cloud edge, where all the other clouds are geographically aggregated. I need to move my network closer to that location. So we do a lot of work with Equinix in that context, right? So they have and have built a business around >> Sort of re-architecture's happening, and it's being driven by value creation, value shifting. >> Yes. >> Moving everything around. >> And that's where from a cloud networking standpoint, you look at that's a discussion where Cisco's so uniquely situated, because they are the networking company. They've been through the generations and they've been through different changes of generations. You know Wi-Fi, didn't used to be Wi-Fi. Now it is, right, it's here. And now we're in this next paradigm, where cloud networking didn't used to be here. Now it is, so. >> What's the new thought process for cloud networking. Because it makes a lot of sense, you have to connect clouds, obviously networking latency, SLAs around moving things around from point a to point b, storing stuff as well. Fabio, what's the equation look like? What's changed? Where do your customers go in this new architecture? >> Well, just building on top of what Jonathan was saying before, first of all the way we architect the networks, enterprise networks were networks in the past. Of course this is coming to an end. We need to rethink them, right? The fact that users now are going to use an enormous amount of software as a service applications that don't sit in your data center, means that constricting all the software in a single place doesn't make any more sense. But there's not just the traffic element. Think about all the intrusion detection and prevention, firewalling capabilities. Because you're moving away from that model, you need to start visualizing also those security functions and distributing them all the way to the edge of the network. In some cases, you need to have them in the cloud as well. We believe that the best way is a fully distributed model. Where you have a choice. Whether you keep it in your data center, or you put into the cloud, or even the to edge of the network. Again, you got to be ready for any kind of scenario. It's interesting how, you know, we're going to distributed computing as you said. But everything else is getting distributed as well. >> Oh yeah. >> Your entire infrastructure needs to follow your application and data. Wherever they go. And that's actually something unprecedented that we're seeing right now. >> And you brought up cloud architecture earlier, Jonathan. You mentioned it briefly. And this comes back to some of that this nuanced point around cloud architecture. The procurement standards aren't driving what you buy, its architectural workload dynamics are now telling procurement how we're buying. So the world shifting from, oh, I'm going to buy these servers. I'm going to buy this gear, the approved vendors. When you think about architecture the way you pointed it out, it's a completely different decision making process. So what's happening is old ways of procuring and buying and consuming technology are now shifting to. Still not going to stand up a cloud with a credit card if I'm doing dev ops, but now you start thinking holistically. The decision making on what that will look like has changed. This is probably impacting the cultural people side as well. What's your thoughts on this dynamic between cloud selection, security, architecture, and procurement? >> The example I normally give is, it's changing but it's also evolving, right? Because you're dealing with patterns that are there, and they're not going to go away, right? Money still has to be paid. Processes have to be followed and respected. The examples that I give would be, I've run large clouds in my past. Different platforms. And one thing you always watch out for when you're running a cloud is capacity. How much money do I have in the bank, so to speak, right? Am I going to have a run on the bank? So if you're running that cloud, either, and this is true if you're a service provider or you have your own private cloud. You're very concerned about you don't want to run out of capacity. Because bad things happen. Even unrecoverable bad things happen. Well in the public cloud, hey, I'm free and clear, I no longer have a capacity management team, I don't need to worry about them anymore. No, no, no no. 'Cause, you know, we just saw some press recently of a company that had a big overage. In cloud, what used to be capacity management is now cost optimization. 'Cause if you don't have it, you're going to have a similarly bad outcome. It's those kinds of things, right? How do you go, and it's those things, right? >> Once a benefit, now it's a challenge. So this could back down to the billion dollar question on the table in the industry is, how do I manage all this? I know how to connect it. Cisco could help me there. I understand multi-cloud, I totally buy into the architecture. I think this is clearly the direction. The management piece is kind of a fuzzy area. Can you guys help unpack cloud management? What are the table stakes? How should people be thinking about it? Because you mentioned security and intrusion detection. Not just moving packets around. We were talking before you came on about Kubernetes. There's all new sets of services moving up the stack, inside this dynamic. How do I manage it all? What single pane of glass is going to do it for me? >> Well, yeah, it's interesting you mentioned there. We've talked a lot about almost like an East West type shift you can think of where, multi-cloud is this thing that goes this way. Well, there's an equally crazy paradigm that's happening in a very fast period of time where it's almost like a North South North shift. Which is, Kubernetes, containers, service meshes. These architectures that are abstracting and lifting everything up. And in some ways, coming underneath as well, at the same time. Because now you've got a return of bare metal. You have these concepts architecturally where the VM is here to stay, it ain't going anywhere. It's still, the tooling around is insanely valuable. But you have now another benefit layer at a container orchestration layer, where there's portability, speed. There's all these benefits that come. And you just look at the stats of how fast containers are growing as a share. You're approaching a billion containers out there right now. And therein lies the challenge. Is that it'd be enough of a difficulty if you were saying I need to go from managing my private cloud, the stuff I have at a cloud edge, edge location, and the stuff I have in multiple public clouds. That's not all we're saying. We're saying also, you have a new tooling and a new set, and it's all software defined, and there's security, network, there's data. It just it's -- >> Complex. >> Exploding, it's complex. So the area that we're working on and want to hear more from Fabio is were innovating with Cisco on, we have great offerings and capabilities around cross cloud and VM orchestration. We're also looking now at that Kubernetes layer. >> Absolutely. >> What's real on that, the complexity he just pointed out is an opportunity at the same time because it just validates the shift that's going on. >> Absolutely. >> Management is an opportunity. >> Jonathan almost went through the entire set of needs. And what you take away from this is that fundamentally you have to instrument this incredibly distributed environment multiple sources and sourcing of this. In fact I love the analogy that you did with the planes, because there's a lot of kind of similarities to a supply chain management kind of business model, right? Where you want to supply different services. But a bottom line is that you're now moving away from what you have. It's a journey. And so this instrumentation, whether it's networking, security, analytics, management, these are actually the four pillars of our company multi-cloud strategy. They need to work across the old and the new. You can't afford to build another silo and maybe leveraging a bunch of open stores like-- >> So a data plane strategy is critical. >> It's, yeah, and it has to-- >> Across the hybrid and multi-cloud. >> East West, North South, and across the old and the new. It sounds very complex, but in reality the-- >> But you could build a taxonomy around this. And we've seen some research come out certainly from Wikiban and others. If it fits into the architecture that seems to be the question. So Jonathan, where does that fit in to the multi-cloud architecture in your opinion? >> So we, there's, you get into different terminology. We think about every company needs a cloud services strategy. So there's a taxonomy of services that we've developed. Where companies have to think about their application services strategy. Their operation strategy, governance strategy, foundation strategy. And this is, it's sort of coming what I teased upon earlier about moving from capacity planning when you own the cloud to cost optimization when you're running the cloud, right? It's the same, but different. And a lot of that difference gets down to services. I am going from a model of running my own product in an information technology modality to now I'm consuming services. So, I used to architect, and design, and build. Now I have to architect and really understand those differences. And so that's our cloud services strategy portfolio. And what we often see is we also have a dev ops portfolio. And we short-hand it, you could call it cloud native, right? Where we're looking at solutions around infrastructures code, around CICD pipelines, around cloud foundation capabilities that connect back-- >> Are they best practices or actually implementation? >> So both, we have content and workshops that we've developed, and then we have. Helping clients on projects very actively. And, you know, that's where it gets back to that architectural gap and knowledge gap. Is companies are looking for, hey, what's the pattern, what are the best practices. And then they don't expect, 'cause there's so many elements that change for a given company. And that change in the market, that there's a shelf-life to this. And it's like fresh produce. >> I love your example of engine in a plane. Do you have it for a single plane or fleet of planes? Does your company have two three big planes. It depends really, I mean, beauty's in the eye of the beholder, here, right? How you build and architect cloud, there's no boilerplate. It really is comes down to figuring it out. >> Where you are. >> So, with that, I want to go to my final point I want to dig into on the people side. So technology shift, business shift, check. You guys did a great job there. Great insight. Comes up every time I have to go to a Cube event and talk about cloud, is the cultural people skills gap problem. One, our company doesn't have the culture and/or we don't have the skill and we don't have the people to run it. So, automation certainly can help there but at the end of the day, if you don't have the people to do this. How do you solve the people problem? How are you guys helping companies? What is some of the state-of-the-art techniques? What's out there? >> So, I'll say a little. I appreciate Fabio's perspective, too. I think for us, really, you know, the old saying, culture eats strategy for breakfast. Culture's more important than ever. Because really, you're now moving to a mode where siloed organizations implementing siloed technology is enormously challenging. You have to move, and that's where dev ops and other patterns come in, where the people who build the app are doing the operations. Storage and networking and compute and apps and the business, they're all talking to each other. So culture really is foundational so that a culture where you're not making boundaries more rigid, you have to get to a point, and there's different ways to do this. I already recommend if people haven't already read the Phoenix Project. Hard to believe but it's an excellent book. And it's a fictional work about tech. It's like a novel about tech. >> I haven't read it yet, I'm going to get that. >> It's awesome. And it really gets you in the mindset of an organization going through change with the net. And it really, I mean I'm a geek, so I like it, but I've had other non-Geeks read it and they like it. But that's the key, it's a-- >> So you really got to set the table and invest in culture, making sure it's >> Culture's foundational. >> appropriately aligned. >> Culture's foundational. And then there's other best practices that always apply, right? So, what is your business vision? What is your mission? What are your values? What are the objectives you're trying to achieve in this space and time relationship? How are you prioritizing? These are all things because then if you have the right build around all that. Then what you drive to is an outcome at a certain point of time. And time's critical. We're in a market that's competing on time. So if you are not hyper aware of time. And what you're doing in a set point of time. And the trade-offs in making changes if your assumptions are wrong. These are all things that are foundational. >> Fabio, I want to get your thoughts. Chuck Robbins talks about solving the tech problems just because a tech company can solve tech problems all day long. He's also behind the people skillset. I've heard him publicly talk about it. But you guys at Cisco have actually had a great transformation with the DevNet Create community, where you harness the culture, and everyone's engaged around cloud, cloud native, and you have a kind of cloud DNA developing out of the core network. Your thoughts and Cisco's view on culture and people solving the problem. Because we need an army of cloud architects out there. There's not enough people. >> So that's true, but we carry an enormous responsibility in the marketplace as a vendor. We have to make things simple, right? There's still, you know, most of the IT infrastructure's still very complex to program and automate and the likes. That's why we're putting an enormous amount of RnD efforts, right? DevNet is like the tip of the spear. It's showing fundamentally our very loyal CCIEs and everybody else there's a better way to do things, right? Where you can actually really automate things together. You can get access to the APIs and simplify your life. You can simplify your life and the life of the business 'cause you can get faster. So making things simple, automating them, I don't know, if you think about, for instance, our cloud management orchestration philosophy. With the cloud center, we have a patent where we can actually model the application at once. And deploying it to wherever you want. We can deploy that application on-prem, on a VM, or like viralize kind of infrastructure. You can put it into AWS, you can put it into Azure, whatever you want. Kubernetes is kind of target on-prem. That is simplicity, right? We have to drive simplicity. And for me, it's all about automation, and sometimes you hear things like, in 10-base architecture and infrastructure all of that means simplicity and security. And that's the complexity of the whole thing for us is trading off, of course some of the complexity, richness, and flexibility. But it's got to be simple. If we don't make it simple, we are actually failing our goals. And that's where we're putting an enormous amount of RnD effort. >> And Jonathan, you guys at WWT have a unique aperture, view of the marketplace. You see a lot of the landscape, knowing what you guys do. Every vendor says they it, but you're really customer focused, so you're in you're digging in with the customers, it's a real value added service. I got to ask you the question with multi-cloud it sounds easy just to connect them all, right? It's like a subnet plug it in the coax, put a hub there. Put some adapter cards on a PC. The old days of connecting things. It just metaphorically seems easy What's the opportunity for connecting multi-cloud? So, as people realize when they wake up tomorrow or today. And they go, hey, you know what, I got lot of multi-cloud around. How do I connect them together? What's the opportunity, what's the opportunity for Cisco. 'Cause that seems to be the first order of business. I can connect things together in the architecture. And then what happens next? What's the opportunity to connect these clouds. >> The opportunity is gigantic. If you look at just the growth of the public clouds themselves. The CAGRs that they're representing. They're growing the rate their growing on very big numbers already. And it often gets overlooked, but Gartner will tell you also that the co-location, that cloud edge space, is also growing at a good CAGR. So you have just more and more going there. All of that needs to be connected. All of it needs to be protected. So networking is not just networking. Networking is security. A critical pillar of any security practice is really understanding and knowing in-depth your network. The introspection of it all. And at the same time, we're moving from a physical world. And we've moved and virtualized, but now the virtualization of the network now with SD-WAN coming, you're moving to a programmable model, where everything needs to be programmed. So it's not humans. So it's almost like every arc. Just in terms of the amount of data, the amount of traffic, that's all growing. Now, it's not just humans, it's machines doing things. And then also it's not just physical connections. It's software. So it's a three dimensional plot and it's growing on every axis. >> It just not in every device, it's software as a device. Software device connections. Service connections. What's Cisco's opportunity? How positioned are they that can do this? Because there's a lot of conversation around edge. Now you just mentioned a few of them, 5G. What's Cisco's opportunity in all this? >> Well I mean I think Cisco's shown recently and then through generations that they have a unique ability to lead and move with the market. And they're demonstrating that now. So, I think the importance of where the network sits, and not just the network, but again there's an adjacency of security. There's an adjacency of orchestration and management. Their global presence, their global operation. The sophistication of their channel business. All those things put them in a really strong place, we feel. >> You mentioned SD-WAN in a previous comment around talking about edge and stuff. If you think about Office 365, when companies roll that out. That basically takes SD-WAN from a little niche industry to all the internet. SD-WAN is basically the internet now. Your old grandfather's SD-WAN was over here, now everything's SD-WAN. That's basically the internet. So talk about the SD-WAN impact in this because with edge, that's super important too. Your thoughts. >> Well, it was back when we were talking about that traffic patterns are changing. So you're moving to no longer really this campus branch closed network. There's still an important need for that, of course. But now you're doing your business where your customers are. On their phone, in their car. Which means you're having to traverse and work and scale in a very different way. It's part where you have to put the network. And then, it's how you have to run and connect the network in your retail store or in these other things. Part of it is doing what we've always done in a better way. And then probably every day, more of it is about doing things in a new way that you couldn't do in the past to achieve a new business objective. >> Well Jonathan, thanks for coming on theCUBE conversation. I'd love to have you back on. Great insight. We could also do remotes. So when you go back to the home branch in St. Louis we can bring you in. >> Tells you Silicon Valley and St. Louis, man. Silicon angle, Silicon Valley, St. Louis. >> Let's do it. And I'll say congratulations on your success with Cisco. Fabio, it's been great to see you. Final word, Fabio, just bring it all together. Multi-cloud, it's here, kind of that's the reality. >> Yeah, I want to go back really to where we started the conversation, right? We can't forget the multicloud is still like a mean to and end. The end is, companies want to become and need to become innovative and fast. And that's actually why all this interest in multicloud. It's a business engine. That's why we're all so excited. Because it's a business issue. It's not so much a brand new technology that probably in two years is going to be out of fashion. My personal prediction, we're going to be talking about multicloud for several years. On the contrary of other trends. >> And just to real quickly bring in what we talked about before we came on camera. This is a CEO issue of companies, not CIO. >> Absolutely. >> This is showing the culture and the urgency, really, in all this. >> That's right. >> Absolutely. Guys, thanks so much for coming on. Great insight. Multi-cloud conversation, fantastic. Jonathan King, Vice President of Strategy, Data Center, and Cloud for WWT. Also Fabio Gori, friend of theCUBE, Senior Director Cloud Solution and Marketing at Cisco. Thanks for coming on. This theCUBE conversation. I'm John Furrier, thanks for watching. (upbeat funky music)

>> From Gillette Stadium in Foxboro, Massachusetts, if the queue recovering Vita Winter warmer, twenty nineteen Brought to you by Silicon Angle media. >> Hi. I'm stupid men. And this is the cubes coverage of V tug Winter warmer. Twenty nineteen here. A Gillette Stadium, home of the New England Patriots. Happy to welcome to the program. A community member, Someone I've known for many years at this point. Jonathan Frappe here. Who's with V Brown bag? Thanks so much for joining us from >> Thanks for having me. >> All right, so, you know, I watched this event, and when it started, it was, you know, originally the V mug for New England. And then it became vey tug And one, there's some of the politics stuff which we don't need to go into, but part of it was virtual ization and cloud. And what's the interaction there and what will users have to do? Different. And part of that is jobs. And one of the reasons I really wanted to bring you on is, you know, you started out heavy in that virtual ization base and you've been going through those machinations. So maybe just give our audience a little bit about, you know, your background, some of the things skill sets. You've got lots of acronyms on your on your you know, resume as it is for certification. You've done. So let's start there. >> Sure. So my background. I started this help desk. I did Windows two thousand Active Directory, administration and Exchange Administration all on site and moved into Mohr server administration. And when the empire started to become a thing, I was like, Wow, this is This is a game changer and I need to sort of shift my skill set. I understand the applications of music. I've been supporting him. But virtualization is going to change change That so started to shift there and saw a similar thing with Public Cloud and automation a cz, That same sort of next step beyond infrastructure management. >> All right. And you've had a bunch of certification. The real off a few. You know what? Where are you today? What? What have you added gives a little bit of a timeline. >> My first certification was a plus which come to you seemingly has come around and joined the ranks of posting toe linked in for everybody. So a plus was my first one. EMC PM, CSC on Windows two thousand. Took a little bit of a break in back into it. Bcp five era so four, five years ago. Cem Cem. Other of'em were Certs NSX Cloud see Emma and most recently, the solution's architect associate for a Ws. >> OK, great, in when you look at the kind of virtual ization and cloud, it's not like you thirst, which one day and said, Okay, I no longer need the VM were stuff. I'm going to do the cloud tell us a little bit about you know what led you to start doing the cloud and you know how you you know how your roles that you've had and you know the skill set that you want to have for your career. You know how you look at those. >> So for me, it is about being able to support what my business is doing. And sometimes the right answer's going to be VM, where sometimes it's going to be physical. Sometimes it's going to be containers or public cloud, or, you know, new fancy buzzwords like server lists. And I've always in my career tried to support what where, what application we're delivering to get the business, the information they need. So for me to do that properly, I need to be well versed across all of that infrastructure so that when when it's time to deliver something in public cloud or time to deliver something in the container, I'm ready to go when you do that. >> Yeah. What? What? What's the push and pull for some of the training bin? Is this something that you've seen? You said, like Veum, where you saw it, like, Oh, my gosh, I need to hop on that. You know, I remember back to those early days I remember engineers I worked with that were just like, this thing is amazing. That was like preview motion, even. Yeah, but you know, just what? That that impact we've seen over the last, you know, ten to fifteen years of that growth has there been times where the business is coming said, Hey, can you go learn this? Kaixian orders have been you driving most about yourself. Uh, >> it's it's been both. There are times when the business has come and said, Hey, we would really like to take advantage of virtual ization or public cloud. And it from a technology perspective, there may have been other factors that would impact the ability to do that. So that's why for me. I tried to sort of stay ahead of it when, you know virtual ization was taking off and everything I had was on physical servers. I knew I needed to have the VM where peace in my pocket so that when the business was ready and when other things like compliance, we're ready for it. We could move forward and sort of advanced that same thing with Public Cloud. Now that that's Mohr prevalent and sort of accepted in the industry a lot more cos they're moving in that direction. >> Yeah, and you know, what tips would you give your Pierre if they're a virtual ization person? You know, how are the waters in the cloud world is there are a lot of similarities. Is it? You know, do I have to go relearn and, oh, my gosh, I need to go learn coding for two years before I understand how to do any of this stuff. >> I think it's helpful. Tto learn some level of coding, but do it in an environment that you're comfortable in today. So if you're of'em were admin today, you know there's power, see Ally and be realized orchestrator and and even if you're on via Mars Cloud platform there's there's some basic power shell on bass scripting you could do in the cloud Automation. Get comfortable with the environment, you know. And then as that comfort grows when you move Oh, look, there's power shell commandments for a ws. If that's the route, you go so oh, already understand the format and how I how I glue those things together so you could get comfortable in the environment you're in today and sort of get ready for whatever that next step is. >> Yeah, I've always found I find it interesting. Look at these ecosystems and see where the overlaps and where two things come together. You know, I actually worked with Lennox for about twenty years. So I you know, back when I worked at Emcee the storage company and I supported the Lenox Group and Lennox was kind of this side thing. And then you kind of saw that grow over time and Lennox and virtual ization. We're kind of parallel, but didn't overlap is much. And then when we get to the cloud, it feels like everybody ended up in that space and there were certain skill sets that clinics people had that made it easy to do cloud in certain things that the fertilization people had that made it easy do there. But we're kind of all swimming in the same pools. We see that now in the, you know, core bernetti space. Now I see people I know from all of those communities on, but it's kind of interesting. Curious if you have anything you've seen in kind of the different domains and overlapping careers. >> Yes, you. For me. I think what's help is focusing on how the applications the business uses consumed, what some of the trends are around, how you know whether finance or marketing teams are interacting with those applications. If I know how the application works and what I need to do something to support it, the concepts aren't going to be vastly different. If I know how Exchange's install their sequel servers install, there's some custom application is insult. I could do that across the VM, where environment native US environment and should it supported into Docker by leveraging Cooper Netease. >> All right, so you've mentioned about the time the application, can you? How has it changed your relationship with kind of the application owners as you go from, you know, physical, virtual, the cloud. >> I don't think it should change much. The problem probably the biggest shift that you have is that at some point now, things are out of your control. So when I've got a server sitting in my data center that I can walk down the hallway to if something's not working, I have access to it. If there's an application down in the public cloud, or there's an A Ws outage or any public cloud provider outage, I have to wait. And that sort of I think the thing that I've seen business struggle with the most like, well, it's down, go fix it. It's like, I can't get to it right now, and I'm probably not driving to Virginia, Oregon to go reboot that server for Amazon. >> Whoever absolutely big shift we've seen right is, you know a lot of what I is. It I am managing is now things that aren't in my environment. You know, there was my data centers. My might have had hosted data centers where I'd call somebody up, you know, you know, tell the Rex paper person to reboot the servers or it's right, it's in the public cloud. In which case it's like, OK, what tools. What can I trouble shoot myself? Or is there some, you know, out of that I'm not aware of, you know, is affecting me. Yeah, >> it's Ah, it's a good shift to have for a infrastructure person because we're really getting to the point now. I think the tails, the scales have tipped to focusing more on delivering business value versus delivering infrastructure. The CFO doesn't necessarily think or care that spinning up a new V m faster is cool. They care about getting their application to their team so that they could do their work. So I think taking, you know, going to public cloud or going to other platforms where that's removed it sort of forces you to move to supporting supporting those business applications. >> So I'm curious it every time we have one of these generational shift time. Time is like, Oh, my gosh, I'm going to be out of a job on the server ID men Virtualization is going to get rid of me. I'm a virtual ization Had been cloud's going to get rid of me. This whole server listing will probably just get rid of all the infrastructure people I've read article yesterday was called the Creeping Apocalypse a CZ what they called it. But, you know, you know what you saying is there general fear in your peers or, you know, do you just, you know, dive in and understand it and learn it? If you could stay, you know, up with or a little bit ahead of the curve, you know you're going to keep employed. >> I would say that there's a mix there. Some people, even just a few months ago, some some folks I talked to and they were just sort of breaking into automation and like how they can automate deploying their applications in their legitimate concern, was I won't have a job anymore and sort of the way I looked at that was my job's going to change. I don't spend my entire day administering Windows two thousand active directory boxes any more. So I need Yes, I need to shift that and start thinking about what's next. If I can automate the routine task, you know, deploying an application, patching and application, bringing things up and down when there's some sort of failure than I, uh, I'm going to naturally grow my career in that way by getting rid of the boring stuff. >> Yeah, and I've been here in this argument against automation for decades now, and the question I always put two people is like, Look, if I could give you an extra hour a day or an extra day a week, do you have other projects that you could be doing or things that the business is asking for? That would be better. And I've yet to find somebody that didn't say, Yeah, of course, on DH. What are the things that you're doing that it would be nice to get rid of, You know, other people is like I love the serenity of racking and stacking cabling stuff. And nothing gets people more excited than beautiful cables in Iraq. I thought yesterday I saw people like going off about here's this data center with these beautiful, you know, rack, you know? So with the cable ties and everything, but I'm like, really, you know, there's more value you can add absolutely out there. So >> automate yourself into your next job. It is sort of the way I think I like to think about it. It's not a meeting, >> so let's you know, just look forward a little bit, you know? There's all these waves, you know, Cloud been a decade data was talking to keep downs in this morning on the Cube on we said, you know, when he talks to users, it's their data that super important applications absolutely is what drives, uh, you know, my infrastructure, but it's the data that's the super important piece. So you know, whether it be, you know, you're a I or, you know, you figure various buzz word of the day I ot You know, data is in the center. So what do you looking forward to is? Are there new search or new training that that are exciting? You are areas that you think you're Pierre should be poking out to help try to stay ahead of the curve. >> Yeah, and back to my earlier point about leveraging the thing you know today and how to sort of grow your career. And that next skill set is how I can look at data and make. I understand what's going on around that. So maybe maybe today that's taking some stats from any SX. I hosted an application and correlating that data together on help. You underst Yes. And you know what that means for the applicator action before or use their calls in. And that's going to help you grow into sort of this new realm of like, machine learning and big data. And in analytics, which I think is really the next thing that we're going to need to start doing as Mohr and more of that infrastructure shifted away into surveillance platforms and things that were not worried about How can I understand? How can I take that data? Transform it, use it, correlated together to, you know, help make decisions. >> Alright, on final thing, give us update on our friends at V Brown bag. So, you know, we talked Well, I always say, you know, when we go to V m world, it's like we're there. I'm trying to help kind of balance between the business and the technology. You want to go a little deeper and really geek out and understand some of these things. That's where you know the V brown bag. You know, people are going to be able to dig in with the community in the ecosystem. There was the V and V brown bag for virtual ization. But he brown bags doing much more than just traditional virtualization today. You know what? What? What's on the docket? >> Eso upcoming This year, we're gonna have some episodes around Python so helping add men's get to know Python start to get comfortable with it, Which would be a great language to a automate things that maybe you're doing today in your application, but also to be able to take data and and use Python, too. Manage that data extract value out of that data so that you can help make decisions. So look for the throughout this year and, you know, learn new things. >> All right, Jonathan, from pure pleasure to talk with you on camera after talking to off camera for many years. Thanks so much for joining us. All right. And we appreciate you joining us at this virtual ization and cloud user event. Ve tug Winter warmer. Twenty nineteen on student a minute. Thanks for watching the cue

>> Hello, and welcome to the special. Keep conversation here in Palo Alto, California John Furrier, Co-Host of the Cube. We're here with Jonathan Rosenberg, CTO chief technology officer and head of AI for Five9. Jonathan. Great. Great to see you. Thanks for coming in. >> Thanks. My pleasure to be here. >> So you've had a stellar career? Certainly. Technical career going way back to Lucent Technologies. Now here at Five9, Cisco along the way. You've been a really technical guru. You've seen the movie before. This's happening. Every wave of innovation, multiple ways you've been on. Now you're on the next wave, which is cloud AI, CTO Five9. Rapidly growing company. Yes, it is. What attracted you to five? >> Yeah, Great question. There's actually a lot of things that brought me to Five9. I think probably the most important thing is that I've got this belief, and I'm very motivated for myself. A least to do technology and innovate and create new things. And this belief that were on the cusp of the next generation of technology in the collaboration industry. And that next generation is going to be powered by artificial intelligence, and one of the ways I sort of talked about this is that if you look at the entire history of collaboration, up til now meetings, telephony, messaging was to figure out, a way to get the bits of data from one person to another person fast enough to have a conversation. That's it. You know, once we got the audio connected, we just moved the audio packets in the video packets and messaging from one place to another. And we didn't actually analyze any of that because we couldn't. We didn't have the technology to do that. But now, with the arrival of artificial intelligence and particular speech recognition, natural language processing, we can apply those technologies to that content and take all this dark data that's been basically thrown away the instant it was received, to process it and do things. And that is going to completely transform every field of collaboration, from meetings to messaging, to telephony. And I believe that so strongly, that is, That's great. That's going to be my next job. I wanna work on that. And it's going to start in the Contact Center because a contact center is the ideal place to do that. It's the tip of the spear for AI in collaboration, >> and it's in a really great area. Disruptive innovation are absolutely so Take us through the impact was one of things I have observed in this industry is you have You know, I don't want to say mainframe clients served to go back to date myself, but there was that wave of client server computer >> mainframes. Cool again. We just called clout. Now, hey, is >> exactly. So you have these structural industry waves take us through the waves of how we got here and what's different now? And why can't the old guard or the older incumbents surviving if you're not out in front that next wave your driftwood. So what? What's What's his ways mean? Why is this important? What has to change to be successful? >> Exactly. So there's been this this whole like you said these waves. So the first wave of telecommunications was like hardware: circuit switching, big iron switches, sitting in telco data centers, you know, And then that era transitioned to software and that was with the arrival voiceover IP and technologies like SIP, and that made it more less expensive. And anyone could do it, and it transformed the industry. The next wave, the third wave were still like halfway through and in some areas, actually, just beginning contact, center was early here, the third wave is cloud, right is now we're moving that software to a totally new delivery vehicle that allows us to deliver innovation and speed. And that wave has now enabled us to start the next wave, which is on ly in its infancy, which is AI right, and the application of machine learning techniques to automate all kinds of aspects of how people communicate in collaborate. >> I think cloud is a great example of Seen a. I, which had been a concept around when I was in computer science. Back in the eighties, there was a guy you know theory, and it's the science of it is not so much change, but computing's available. The data to be analysed for the first time is available. Yeah, you mentioned analyzing the bits writings. There's now a key part. What does it actually mean? Teo. Someone who's has a contact center has a large enterprise. Says, you know what? I got to modernize. How does A I fit them? What is actually going on, >> right? Great question. So a I actually consult lots different problem at the end of the day again, Hey, eyes like this, Let's. It's the biggest buzz word right on. It's in my title. So, like I'm a little guilty, right? >> We'll get a pay raise for, But >> what? It comes down to this, really this Korean machine learning, which is really like a fancy new algorithmic technique for taking a bunch of data and sort of making a decision based on it. So And it turns out, as we've learned that if you have enough data and you can have enough computing and we optimize the algorithms, you could do some amazing things, right? And it's been applied to areas like speech recognition and image recognition and all these kind of things. Self driving cars that are all about decision process is, Do I go left? I go right? Is this Bob? Is this Alice? Did the users say and or did they say or write those air all decision process? Is that these tools economy? What does it mean? The Contact Center? It means everything in the context. And if you look at the conduct center. It's all about decision. Process is, you know, where should this call get routed? What's the right agent to handle the call right now? When the agent gets the call, what kind of things should they be saying? What I do with the call after the call is done, How should the agent use their time? All those things are decision processes and their key to the contact center. So so, aye, aye. And Emily going to transform every aspect of it and, most importantly, analyzing what the person is saying connecting with the customer, allowing the age to >> be more. You know, I think this is really one of the most cutting edge areas of the business. And the technology and throw in CEO was talking about an emotional cognitive recognition around. Yeah, connecting with customers and data certainly is going to be a part of that. But as machine learning continues to get it, Sea legs. Yeah, you seeing kind of two schools of thought? I call it the Berklee School. Hard core mathematics. Throw math at it. And then you've got this other side of a machine learning which is much more learning. Yeah, it's less math. More about adaptive and self learning. One's deterministic one's non deterministic is starting to see these use cases where Yeah, there's a deterministic outcome, right throw machine learning at a great exactly helped humans come curate, create knowledge, create value that you've got a new emerging use case of non deterministic, like machine learning environments where I could be driving my test Look down the road or my company's run the Contact Center. I gotto understand what's gonna happen before it happens. Right? Talkabout this. What's your thoughts on this is This isn't really new, pioneering area. What's your view on >> this? Yeah, so I think it actually straight sort of a key point. I wantto narrow enough from what she said, which is that a lot of these problems still, it's about the combination of man and machine, right? It's that there's things that you know are going to be hard for the machine to predict. So the human in their usage of the product, teaches the machine, and the machine, as it observes, helped the human achieved mastery. And that human part, by the way, is even more important in the conduct centre than anywhere else. At the end of the day, your customer and you call up, you're reaching for human connection. You're calling this. You want to talk, you've got a problem. You need someone to not just give you the answers, but empathize with youto understand you. Right? And if you go back to anything about the best experience you've ever had when you called up for support or get a question answered. He was like it was someone who understood you who's friendly, polite, empathetic, funny. And they knew exactly what they were doing, right? And they solve it for you. So the way I think about that, is that actually the future of the context. Dinner is a combination of human and machine, and the human delivers the heart, and the machine delivers the master. >> And I just noticed your I'm looking at Twitter, right? And you just tweeted this forty minutes to go the future of Contact Center. Nice. A combination of human and machine human delivers heart. The machines lose mastery. I think this is so important because unpacking that words like trust come out True relationship. So you asked about my experiences is when I've gotten what I needed, You know, all ledger, the outcome I wanted. Plus I felt good about right. I trusted it. I trusted the truth. It was. And he's seeing that in media today with fake news. You're seeing it with Digital has kind of almost created, anonymous, non trustworthy its data. There's been no real human. Yeah, packaging. So I think you're I'm hearing you You're on the side of humans and machines, not just machines being the silver bullet. >> Absolutely, absolutely. And again, it goes back to sort of the history of the contact centre has been this desire to, like, just make it cheaper, right? But as the world is changing, and as customer experience is more important than ever before and is now, technology is enabling us to allow agents and human beings to be more effective through this. The symbiotic relationship that we're going to form with each other, like we can actually deliver amazing customer experiences. And that's what really matters. And that idea of trust I want to come back to that word that's like super Central to this entire thing. You know, you have that as a user, you have to trust the brand you have to trust the information you're getting from the agent. You have to trust the product that you're calling them talking about, and that's central to everything that we need to do. In fact, it's a It's a fundamental aspect of our entire business. In fact, if you again think about it for a moment here, we're going to customers who are looking to buy a context, and we're saying, Trust us, we're going to put it in the cloud, We're going to run it, We're going to operate it for you and we're going to deliver a great, highly reliable experience that takes trust to sew one of things that back to your early early question. Why did come two, five, nine? One of the things it has done is build this amazing trust with its customers to its huge, amazing reliability. Up time, a great human process of how we go in work with our customers. It's about building trust in every single >> way. So I want to put in the spot because I know you've seen many ways of innovation. You've seen a lot of different times, but now it's more accelerated. Got cloud computing at a much more accelerated innovation cycle. So as users expect interact with certain kind of environment. Roman talked about this in his interview. CEO Control. So you just want to be served on the channels that they want to be served in. So having a system that they have to go to to get support, They wanted where they are. And so how is the future of the customer interaction? Whether it's support our engagement is going to take place in context to nonlinear discovery, progression, meaning or digging a service themselves in the organic digital space. I honestly want to go to a site per se. How do you see the future evolving around this notion of organic discovery? Talking to their friends, finding things out? Does that impact how Five9 sees the future? >> Yeah, absolutely. And I think it gets back to sort of an old idea of Omni channel. I mean, this is something that the context people been talking about for, like forever, like the last ten years, right? And and its original meeting was just this idea. Oh, you know, you can talk to us via chat, or you can send us an e mail or you can send us a text or you could call us right and we'll work with you on any of those, like you said. Actually, what's more interesting is as customers and users moved between those things, and it actually switches from reactive to proactive right where we actually treat those channels as well. Depending on what the situation is, we're going to gather information from all these different data sources, and then we're going toe, find the right way to reach out to you and allow you to reach out to us in the most official. >> So you see a real change in user expectation experience with relative rule contact? >> Yeah, I mean, I mean, the one thing that technology is delivered is a change in user expectations on how things work. And if you look at the way we as human beings communicate with each other, it's dramatically different today than it was really just just a few years ago. >> So, Johnny, let's look under the hood now in terms of the customer environment, because certainly I've seen Legacy after Legacy sisters being deployed. It's almost like cyber security kind of matches the same kind of trend that in your world, which is throw money at something and build it out. So there's a lot of sprawl of solutions out there and trying to solve these problems. How does the customer deal with that? And they're going forward there on this new wave. They want to be modernized, but they got legacy. They had legacy process, legacy, culture. What's the key technical architecture, How you see them deploying this? What's the steps of the patient and her opinion? >> It will surprise you not one drop when I say it's go to the cloud, all right, and there are real reasons for it and by the way, this is going to be going to be talking about this at Enterprise Connect. So, So tune in Enterprise Connect. I'm going to be talking about this. Um, there's a ton of reasons, five huge ones, actually, about why people need to get to the cloud. And one of them is actually one of the ones we've been talking about here, which is a lot of this. Modernization is rooted in artificial intelligence. It turns out you just cannot do artificial intelligence on promise you cannot. So the traditional gear, which used to be installed and operated by legacy vendors like a VIA, you know, they go in, and Genesis, they go in the install a thing and it works just for one customer at a time. The oly way artificial intelligence works is when it gathers data across multiple customers. So multi tendency and artificial intelligence go hand in hand. And so if you want to take any benefit from the stuff that we've been talking about this conversation, the first step is you gotta take your context int the cloud just to begin building and adding your data on the set and then leverage the technologies and they come out >> So data is the central equation And in all this because good data feed's good machine learning good machine learning feeds Great a. I So data is the heart of this, yes. So data making data in the cloud addressable seems to be a key. Thought Your reaction and what are you guys doing with? >> Absolutely, absolutely. And this is, by the way, another reason why I joined five nine, that I've been speculating here. I said, All right, if Date if ya if the future is about a I miss, I said, That's what I want to do in collaboration. You need data to do that. You actually have to work for a company that has a lot of data. So market leadership matters. And if you go look at the contact center and you go look at all the industry and analyst reports like it made it pretty obvious, like who to go to there is like the leader in cloud Conduct. Sonar with with tons of agents and tons of data is Five9 and ah, and so that's That's why you're so building the data aggregating data. That's one of the first things I'm working on here is how do we increase and utilize the data that we've been gathering for years. >> And and a lot of that we've had this conscious with many customs before about Silas Silas. Kill innovation When it comes to data address ability, your thoughts on that and what customs Khun due to start thinking about breaking down those silent >> exactly so In fact, Silas have been a big part of the history of especially on premise systems. Once in fact, Afghan one silo for inbound contacts and are different for outbound. Different departments, by the way, also had their own different comic centers. And then you had other tools that on the other data, if you don't like a separate tool over there for serum and a different tool over there for WFOR debut Fam and something else for Q M. And all these things were like barely integrated together in the cloud that becomes much more natural. Spring these technologies together and the data can begin to flow from the systems in and out of each other. And that means that we have a much greater access to data and correlated data across these different things that allows us to automate all over the place. So it's this positive reinforcement sile cycle that you only get one year when you've gone to the club. >> The question I want to ask you, it's more customers on pretend I'm a customer for second. I won't ask you, Jonathan, what's the core innovation for me to think about and bring to my organization? If I want to go down the modern monitors you. How do you answer that question? What is the core innovation? Stretch it. I should have Marcy moving through the cloud is one beyond that is itjust cloud. Then what else? What, Juanito? Be preaching internally and organizing my culture >> around. Yeah, great questions. So, I mean, I think the cloud is sort of the enabler of many of these different pieces of innovation. Right? So velocity and speed is one of them. And then setting up and adjusting these things used to be super super hard. Ah, you wanted to add agents seats? Oh, my gosh, enough to go binding hardware and racket stack boxes and whatever. So even simple things like reactive nous, right? That's something that's important to talk about is that many of our customers and our businesses are highly seasonal. Right? We've seen like someone showed me a graph. This was like, Oh, my gosh, it was It was a company that was doing ah, telethon. And they said, Here's how many agents they have over this year. It was like two agents, and then it shut up. It's like five hundred agents of phones. Two days exactly. Drop back down. And I'm like, if you think about a business like that, you could never even do that. And so the so cloud is nice, but the way you talk about it, and as an I t buyer of these technologies, you talk your business owners about reacted nous speed, velocity, right? That's what matters to a business and then customer experience. >> You're one of the things that just to kind of end of second, I want to get your thoughts on. I'm gonna bring kind of industry trend. That's I think, might be a way to kind of talk about some of these core problems on data. Most mainstream people look at Facebook and saying, Well, what a debacle. They used my data. These men against me. I'm not in control of my data. You're seeing that weaponization people saying elections were rigged. So weaponizing data for bad is this content, and this context ends right? An infrastructure that's right, >> that's right. >> But there's also the other side, which is, you actually make it for good. So you started thinking about this people starting to realize Wow, I should be thinking about my data and the infrastructure that I have to create a better outcome. That's right, Your thoughts on that as people start to think about II in terms of the business context, right? How did they get to that moment where they can saying, I don't want anyone weaponizing did against me. I want to use it for good. How did the head of the company comes back to >> trust, by the way, right? Is that you know, on and to some degree that's an uphill battle due to some of these debacles that you just talked about. But Contact Center is a different beast of the whole thing. And interestingly, it's an area where there's already been an assumption by users that when they interact with the contact center, that data is sort of used to improve the experience. I mean, every contacts and the first thing I say, by the way, this call may be recorded for training. Um, honoring purses, Captain, that they are right. It's it's already opt in. There's an assumption that that's exactly how that is being used. So it's This is another reason. By the way, what's a contact center is? It was the tip of the spear because it was a place where there was already permission, where the data is exactly the kind of stuff that had already been subject to analysis and Attock customer expectation that that's actually what was happening. The expectation was there they building action, that data what was missing. So now we're filling in the ability to action on that All that data with artificial intelligence >> and final question. What's your vision going forward? A CTO and aye, aye. What's the vision of Five9? What do what do you see? The twenty miles stair for Five9 within consciousness. We just talked about >> it. So? So it's It's about revolution. I'll be honest. Right on. I tell people like, I'm not like an incremental, steady Eddie CTo like I do things because I want to make big changes. And I believe that the context and R is on the cusp of a massive change. And my boss, Rohan said this and this has been actually central to how I'm thinking about this. The Contact Center in the next five years will be totally different than the twenty five years before that. It's a technologist. I say. Wow, five years like that's not very long in terms of softer development. That's what we were going pretty much rewrite our entire stack over the next five years. And show. What should that start to look like? So for me, it's about how do we completely reimagine every single aspect of the context center to revolutionize the experience by merging together, human and machine and totally new >> and the innovation strategies cloud in a cloud and and and data great job and great to have you on pleasure. Great, great conversation. Quick plug for you guys. Going to be a enterprise, connect to Cuba. Lbi. They're covering the event as well. What you going to talk about that? What? Some of the interactions? What will be the hallway conversations? What's your objective? What's your focus >> exactly? So so I'm going to be having my own session. We're going to be talking about the five reasons that you may not think about to goto context on the cloud. I've hinted already. A James of them. I think we're too well. That's you can you know, A. I is clearly central and I'm going to start to talk about the other four. >> Great, great conversation. A lot of change. Massive change happening. Great innovation Stretch. Great mission here at Five9. Great, great mission around. Changing and reimagine. More change the next five years in the past twenty five years. Again cloud computing eyes doing it will be winners. Will be losers will be following it here on the Cube. Jonathan Rosenberg, CTO ahead of AI at Five9. I'm John Furrier with the Cube. Thanks for watching.

>> Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their Ecosystem partners. >> Oh welcome back, to theCUBE. Continuing coverage here from AWS re:Invent, as we start to wind down our coverage here on the second day. We'll be here tomorrow as well, live on theCUBE, bringing you interviews from Hall D at the Sands Expo. Along with Justin Warren, I'm John Walls, and we're joined by Jonathan Ballon, who's the Vice President of the internet of things at Intel. Jonathan, thank you for being with us today. Good to see you, >> Thanks for having me guys. >> All right, interesting announcement today, and last year it was all about DeepLens. This year it's about DeepRacer. Tell us about that. >> What we're really trying to do is make AI accessible to developers and democratize various AI tools. Last year it was about computer vision. The DeepLens camera was a way for developers to very inexpensively get a hold of a camera, the first camera that was a deep-learning enabled, cloud connected camera, so that they could start experimenting and see what they could do with that type of device. This year we took the camera and we put it in a car, and we thought what could they do if we add mobility to the equation, and specifically, wanted to introduce a relatively obscure form of AI called reinforcement learning. Historically this has been an area of AI that hasn't really been accessible to most developers, because they haven't had the compute resources at their disposal, or the scale to do it. And so now, what we've done is we've built a car, and a set of tools that help the car run. >> And it's a little miniature car, right? I mean it's a scale. >> It's 1/118th scale, it's an RC car. It's four-wheel drive, four-wheel steering. It's got GPS, it's got two batteries. One that runs the car itself, one that runs the compute platform and the camera. It's got expansion capabilities. We've got plans for next year of how we can turbo-charge the car. >> I love it. >> Right now it's baby steps, so to speak, and basically giving the developer the chance to write a reinforcement learning model, an algorithm that helps them to determine what is the optimum way that this car can move around a track, but you're not telling the car what the optimum way is, you're letting the car figure it out on their own. And that's really the key to reinforcement learning is you don't need a large dataset to begin with, it's pre-trained. You're actually letting, in this case, a device figure it out for themselves, and this becomes very powerful as a tool, when you think about it being applied to various industries, or various use-cases, where we don't know the answer today, but we can allow vast amounts of computing resources to run a reinforcement model over and over, perhaps millions of times, until they find the optimum solution. >> So how do you, I mean that's a lot of input right? That's a lot, that's a crazy number of variables. So, how do you do that? So, how do you, like in this case, provide a car with all the multiple variables that will come into play. How fast it goes, and which direction it goes, and all that, and on different axes and all those things, to make these own determinations, and how will that then translate to a real specific case in the workplace? >> Well, I mean the obvious parallel is of course autonomous driving. AWS had Formula One on stage today during Andy Jassy's keynote, that's also an Intel customer, and what Formula One does is they have the fastest cars in the world, and they have over 120 sensors on that car that are bringing in over a million pieces of data per second. Being able to process that vast amount of data that quickly, which includes a variety of data, like it's not just, it's also audio data, it's visual data, and being able to use that to inform decisions in close to real time, requires very powerful compute resources, and those resources exist both in the cloud as well as close to the source of the data itself at the edge, in the physical environment. >> So, tell us a bit about the software that's involved here, 'cause people think of Intel, you know that some people don't know about the software heritage that Intel has. It's not just about, the Intel inside isn't just the hardware chips that's there, there's a lot of software that goes into this. So, what's the Intel angle here on the software that powers this kind of distributed learning. >> Absolutely, software is a very important part of any AI architecture, and for us we've a tremendous amount of investment. It's almost perhaps, equal investment in software as we do in hardware. In the case of what we announced today with DeepRacer and AWS, there's some toolkits that allow developers to better harness the compute resources on the car itself. Two things specifically, one is we have a tool called, RL Coach or Reinforcement Learning Coach, that is integrated into SageMaker, AWS' machine learning toolkit, that allows them to access better performance in the cloud of that data that's coming into the, off their model and into their cloud. And then we also have a toolkit called OpenVINO. It's not about drinking wine. >> Oh darn. >> Alright. >> Open means it's an opensource contribution that we made to the industry. Vino, V-I-N-O is Visual Inference and Neural Network Optimization, and this is a powerful tool, because so much of AI is about harnessing compute resources efficiently, and as more and more of the data that we bring into our compute environments is actually taking place in the physical world, it's really important to be able to do that in a cost-effective and power-efficient way. OpenVINO allows developers to actually isolate individual cores or an integrated GPU on a CPU without knowing anything about hardware architecture, and it allows them then to apply different applications, or different algorithms, or inference workloads very efficiently onto that compute architecture, but it's abstracted away from any knowledge of that. So, it's really designed for an application developer, who maybe is working with a data scientist that's built a neural network in a framework like TensorFlow, or Onyx, or Pytorch, any tool that they're already comfortable with, abstract away from the silicon and optimize their model onto this hardware platform, so it performs at orders of magnitude better performance then what you would get from a more traditional GPU approach. >> Yeah, and that kind of decision making about understanding chip architectures to be able to optimize how that works, that's some deep magic really. The amount of understanding that you would need to have to do that as a human is enormous, but as a developer, I don't know anything about chip architectures, so it sounds like the, and it's a thing that we've been hearing over the last couple of days, is these tools allow developers to have essentially superpowers, so you become an augmented intelligence yourself. Rather than just giving everything to an artificial intelligence, these tools actually augment the human intelligence and allow you to do things that you wouldn't otherwise be able to do. >> And that's I think the key to getting mass market adoption of some of these AI implementations. So, for the last four or five years since ImageNet solved the image recognition problem, and now we have greater accuracy from computer models then we do from our own human eyes, really AI was limited to academia, or large IT tech companies, or proof-of-concepts. It didn't really scale into these production environments, but what we've seen over the couple of years is really a democratization of AI by companies like AWS and Intel that are making tools available to developers, so they don't need to know how to code in Python to optimize a compute module, or they don't need to, in many cases, understand the fundamental underlying architectures. They can focus on whatever business problem they're tryin' to solve, or whatever AI use-case it is that they're working on. >> I know you talked about DeepLens last year, and now we've got DeepRacer this year, and you've got the contest going on throughout this coming year with DeepRacer, and we're going to have a big race at the AWS re:Invent 2019. So what's next? I mean, or what are you thinking about conceptually to, I guess build on what you've already started there? >> Well, I can't reveal what next years, >> Well that I understand >> Project will be. >> But generally speaking. >> But what I can tell you, what I can tell you is what's available today in these DeepRacer cars is a level playing field. Everyone's getting the same car and they have essentially the same tool sets, but I've got a couple of pro-tips for your viewers if they want to win some of these AWS Summits that are going to be around the world in 2019. Two pro-tips, one is they can leverage the OpenVINO toolkit to get much higher inference performance from what's already on that car. So, I encourage them to work with OpenVINO. It's integrated into SageMaker, so that they have easy access to it if they're an AWS developer, but also we're going to allow an expansion of, almost an accelerator of the car itself, by being able to plug in an Intel Neural Compute Stick. We just released the second version of this stick. It's a USB form factor. It's got a Movidius Myriad X Vision processing unit inside. This years version is eight times more powerful than last years version, and when they plug it into the car, all of that inference workload, all of those images, and information that's coming off those sensors will be put onto the VPU, allowing all the CPU, and GPU resources to be used for other activities. It's going to allow that car to go at turbo speed. >> To really cook. >> Yeah. (laughing) >> Alright, so now you know, you have no excuse, right? I mean Jonathan has shared the secret sauce, although I still think when you said OpenVINO you got Justin really excited. >> It is vino time. >> It is five o'clock actually. >> Alright, thank you for being with us. >> Thanks for having me guys. >> And good luck with DeepRacer for the coming year. >> Thank you. >> It looks like a really, really fun project. We're back with more, here at AWS re:Invent on theCUBE, live in Las Vegas. (rhythmic digital music)