>>Mm. >>Amdocs is a leader in providing software and services to some key industries, like telecommunications, media and financial services. In our next session, >>we >>welcome Cedric Jay Gould, who is the head of technical product at Amdocs. And we'll learn about Amdocs modernisation journey and how it added value for their end customers. Cedric. Welcome. >>Welcome. Good. >>Thank you. So describe your modern application, your portfolio, and you know what you're delivering for customers. >>So home dogs is B s s S s players who we are providing a food digital suite for customers. Uh, our customers are communication service providers, which are have to deploy a full digital sweets customer experience. Um, we're for the full os BSS, BSS tax. So, actually, Amdocs is one of the leader in this kind of digital transformation. >>So of course you talk about this as and BS. I mean, you're talking about some really hardened, uh, stacks, right? Uh, telco industry. Uh, say what you want about it, but, boy, the phone works when you dial it. So So you've got this sort of a decades old, you know, platform that you guys have been evolving over the over the years. described this modernisation journey and and the role that couch base played. What value does this offer This modernisation offer to your organisation. And where does Couch based fit? >>Yeah, exactly the same. So that so. Basically what, uh, all solution is You know, it's a broad for you of a large number of components which have to deal with funds, uh, experience of the user and from and then dealing all the, uh, activation of the services in the network in order to deliver a solution, Uh, your services, like mobile services or communication services to, uh, Susan users. So we have a full suites, which, uh, was previously based on, you know, on technology is based on the oracle with web logic and things like that. And what we did is that we do a modernisation of, uh, this something, like, six years ago. A bit more than six years ago. We start to modernisation and transformation of our product into a creative solution. Collaborative solutions. So, uh, and when we did that, we start with Coach base as a partner, uh, to provide the nominative database. So we are actually delivery. We have a guarantee of more than 8000 people developing this product. It's a product which is used by more than 300 customers. Uh, so So it's it's real product that needs to be very flexible. That needs to address many kind of use cases from, uh, Telco or customers, which RCs PS usually till 0 to 1 telco. So we what we wanted to build is a food creative solution that can work on any cloud, then can can skill very, very easily and can address multiple use cases. Okay, And that's why, Coach Base, when we selected Coach Basit, it matched a lot of requirements and criteria as we had. And when we decided to modernise our product, we decided to work with >>you. So you had a lot of experience and and legacy with Oracle and Web logic. I'm curious just to follow up. Why didn't you stay with Oracle? You mentioned? Gotta run any cloud. You gotta be flexible. But could you could you double click on what Couch based delivered from a requirement standpoint, that was such a good fit? >>Well, there's there's a good fit with technology that such as, uh, coach basis. First it's a noise school detonates, right? So it's in terms of performance for some of the youth case that we have. It's very important to have, you know, technology which are are done and optimised for the noise secure use cases. That's the first thing. The second thing as I mentioned the scalability, the fact that you can, almost indefinitely infinitely you can increase the size of your cluster. You can have more, uh, servers and and and And this will skill, you know, very rapidly. And also what we're very interesting to have from coach bases the ability to have something which can be replicated across multiple sites. So with visual technology from coach base, which enable to build, you know, very modern architecture with deployment on multiple agents to have disaster recovery, active, active sites, you know, things like that which are very becoming like the main requirement for more customers now. >>Okay, so I'm presuming there were parts of your application portfolio that you weren't gonna touch and throw away that you had to collect or connect the new with the old. That's always, you know, you know, a challenge. I'm wondering what advice you give to an organisation. That's kind of investing in a similar path, trying to deliver the best digital experiences to customers. You know what? What would you say are the modernisation you gotta have must have, whether it's architecture, internal culture, what are some of those items? >>So so that yes, you're right. I think the integration with the legacy systems is actually, you know, very, very important topic in all domain in the domain. But we we made a very, uh, will see drastic choice or brave choice choice. When, uh, 60 years from now, when we decided to reformat to re platforms are completely or portfolio. Okay, So we we changed more than 95% of our portfolio and 95% of the portfolio today, Arklow native. Which means that they can be deployed on any cloud that actually, they are fully scalable and and and still, we did this transformation. Now, when we do the digital transformation of the, uh, customer system, then we need to integrate with legacy systems, and we need to help our customers to migrate from the legacy systems to creative solutions and doing so, it's important to have in the database domain. It's very important to have a solution which is very flexible in terms of, uh, what kind of data I can manage. And I can, as I said, skill easily, for sure. But also, it's sexual. Okay, Because when you are moving the data from a legacy system or record based or whatever to, uh, another type of, uh, database, you want to be sure that you are you can do it securely, and you're you're not, uh, compromising in any sense, Uh, in terms of security scalability, uh, etcetera. Right. So So, um, in this case, I mean, I will say And then in this opportunities journey, uh, this was very, very, very, very important component in, uh, you know, in our strategy, for all the reasons I mentioned right, it's very coordinative. It's scalable, It's secure. Uh, it's another product, uh, grade. So? So that's that's why it really is. So there's there's a chest back to you. >>You know, this notion that 90 per you really re platform 90% of your portfolio and made a cloud native. That's that's a It's a brave move because a lot of companies do that that I've talked to. They will build an abstraction layer and microservices and make that piece cloud native and then have that kind of overlay. You decided not to do that. Why is that? Was that for performance reasons? You were worried about just bringing along technical debt. I mean, that really must have been an interesting discussion internally in your company. >>Yeah, it's true. I mean, the main motivation, the main driver was business flexibility. Because now we live in a world where our customers, what they need is to be able to test the new feature quickly. And they need to be able to scale the system in a matter of hours. Okay, so we are not in a domain anymore. Where you you when you have to upgrade something, you need to take a few days. It needs to be done in a very, very quickly. And the only way to achieve those, uh, requirements business requirements is to be creative. It's to build microservices and to really realise one of those per cent of, uh, micro services architecture because this is the only way you will have the business flexibility. You will be able to have a resilient architecture. Uh, you know, you can, uh you can deploy this with full high availability across multiple zones, multiple regions and feeling that so, uh, any modern architecture today that that is competing with us, Actually, a micro services based architecture. There is no other way to achieve, uh to to to meet the requirement of the market today, and especially when five g is coming, things will become much more complex. Will become much more, uh, distributed. Uh, you cannot work anymore with the model it architecture. And again, I think the database is nowhere different. Needs to follow the same kind of architecture needs to follow the same principles. So that's that's why am I mean another another point about Yeah, >>So if I If I summarised, it sounds like your top three requirements would be flexibility, which you're getting from the cloud native and microservices piece the scale and the security. Is that right? That I get that right? The three top >>That's right. And the resilience as well. I mean the fact that now you know, with micro services architecture, if one of the system is done, he knows how to self to restart it himself. Right itself. Sorry. So So that's this kind of architecture that we built. It's an architecture which can be resilient in a sense that it can sense itself, and it can ensure full availability. And if something is going down, is not working properly, then on some kind of mechanisms will happen in order to go back to a stable state. >>Yeah. So you've got that automation in there. So you don't doesn't require the labour that it might have 10 years ago. So you're obviously embracing cloud native microservices. So you're on that jury. I'm curious. What are you doing with that? You're you're freeing up. You guys used to bring in lab coats and dig in and figure out what's wrong or restart the system. Where are you in your journey, and how are you? Sort of reallocating those resources. And where do you see that going? >>Yeah, Okay, so that's that's a very good point. Because actually, we when we build this new system, which is unable to do, you know, to self heal himself, right? Uh, actually, the question was more about how we can improve the system, even know how we can be sure that, uh, you know, issues that we we any issues which we are we are facing will not happen again. Well, not actual again. Okay. And this is a, uh, principle. Okay, Practise that we have now people are walking on automation. They're building automation around all these recovery procedures about, uh, fixing. So they're not actually digging into the application now anymore into the system, they learn how the system is walking and buildings all the right automation task to ensure that the system is constantly, constantly resilient. Alright, so that's the necessary practises organisation is now built around. You know, this kind of this approach developed computer develops being fully a geologically having sa reorganisation SRE oriented organisation. And, uh and that's the only way you know you can reach very high, uh, in terms of availability. >>So the big problem that your traditional telco customers have is the amount of data that they're servicing going through the roof and the cost per bit is sinking like that. And you have all the over the top providers coming in creating these customer experiences with modern applications and they've owned the customer data. You mentioned five g. So I'm interested in what the future of modern apps looks like for Amdocs and your customers because five G gives your traditional telco customers the ability if they can have these flexible systems that you're providing to now have better relationships with customers and actually kind of reclaim, you know, some of that that value that they've lost to a lot of competitors, your thoughts on the future. >>So first, you know, technically speaking, we we we will have two challenges. One is about data, and other one is about distribution of the work. Okay, because when we are speaking about five g, we're speaking about the age. We're speaking about the fact that an application may be located very closely to the network because it needs to be to to achieve, you know, to to deliver a very short latency, and, uh and this application can move. Okay, so you you you you will have to be able to distribute completely your your solutions. Okay. And that's why we are working closely with, uh, club providers at the US as you Google and because we we need to be sure that the applications of the systems that we are building will be able to distribute the application as close as possible to the end users. Okay, so that's that's one of the key challenges. Which means that the application is to be very possible and he'd be very scalable, and then it needs to be able to move very quickly from one place to another. That's really what is what What, what? What is happening now and what will become, uh, with five G? The other challenge is behind the communication of all these components is really the data, because now we will capture more and more that are coming from the different systems. And I'm not speaking only about the consequence the customer that are who they are, what they what they like and what they want to do, etcetera. And speaking also about, uh, monitoring that of the systems. Okay, so we will generate a lot of information and this this information needs to be traded very quickly, needs to be stored in very large data lake, and we need to have extraction and manipulation of the data very, very quickly to to give the right information to the applications. Um, in this case, okay, it's very important to have application to have databases that can as I said, skill very quickly. But also we'll be able to have very ideal city note, you know, sense that they with a certain amount of memory or sentiment of storage, you can store a lot of data. And this is where we are always, you know, checking what is the best technologies. And so far, not coach bases, technologies that we're using for for stalking, storing all the data. Because because it's it's a ratio in terms of, uh, performance on the number of data you can store, Uh is very high. Okay, so that's that's another challenge that we're addressing. Of course, God is not the only solution, but it's another another one. >>Excellent. Okay, we're gonna leave it there. Cedric, Thanks so much. A great storey and really appreciate your insights. >>You're welcome. Thank you very much. >>Okay, that's it for today. I hope you've enjoyed the application. Modernisation summit made possible by Couch Base. We shared some fresh survey data and got the perspectives of three expert analysts. We got an outstanding roadmap from Ravi Meyer. Um, who's the CEO of Couch base? And of course, we got the customer angle from Cedric. So look, Maybe you're an organisation going through a modernisation initiative. And if you're thinking about what the future of applications looks like cheque out couch. Based on the road this summer, the application modernisation summit is hitting the road traversing North America and Europe. Find out where they will be where they will be near you by visiting couch based dot com slash roadshow. Ravi is gonna be there along with other thought leaders and peers who will be sharing learnings and best practises on how to modernise now and for the future. And you'll get a chance to interact with some of those piers, something that everyone I know is looking forward to. This is Day Volonte. Thanks for joining us today. And thanks for watching the Cube. Mhm. Yeah. Mm, yeah.

>>Welcome back to the cubes coverage of Couchbase connect online, where the theme of the event is, or is modernized now. Yes, let's talk about that. And with me is Ravi, who's the senior vice president of engineering and the CTO at Couchbase Ravi. Welcome. Great to see you. >>Thank you so much. I'm so glad to be here with you. >>I asked you what the new requirements are around modern applications. I've seen some, you know, some of your comments, you gotta be flexible, distributed, multimodal, mobile edge. It, that those are all the very cool sort of buzz words, smart applications. What does that all mean? And how do you put that into a product and make it real? >>Yeah, I think what has basically happened is that, uh, so far, uh, it's been a transition of sorts. And now we are come to a point where, uh, the tipping point and the tipping point has been, uh, uh, more because of COVID and there COVID has pushed us to a world where we are living, uh, in a sort of, uh, occasionally connected manner where our digital, uh, interactions, precede our physical interactions in one sense. So it's a world where we do a lot more stuff that's less than, uh, in a digital manner, as opposed to sort of making a more specific human contact that has really been the, uh, sort of accelerant to this modernized. Now, as a team in this process, what has happened is that so far all the databases and all the data infrastructure that we have built historically, are all very centralized. >>They're all sitting behind. Uh, they used to be in mainframes from where they came to like your own data centers, where we used to run hundreds of servers to where they're going now, which is the computing marvelous change to consumption-based computing, which is all cloud oriented now. And so, uh, but they are all centralized still. Uh, but where our engagement happens with the data is, uh, at the edge, uh, at your point of convenience at your point of consumption, not where the data is actually sitting. So this has led to, uh, you know, all those buzzwords, as you said, which is like, oh, well we need a distributed data infrastructure, where is the edge? Uh, but it just basically comes down to the fact that the data needs to be where you are engaging with it. And that means if you are doing it on your mobile phone, or if you are sitting, uh, doing something in your body or traveling, or whether you are in a subway, whether you're in a plane or a ship, wherever the data needs to come to you, uh, and be available as opposed to every time you going to the data, which is centrally sitting in some place. >>And that is the fundamental shift in terms of how the modern architecture needs to think, uh, when they, when it comes to digital transformation and, uh, transitioning their old applications to, uh, the, the modern infrastructure, because that's, what's going to define your customer experiences and your personalized experiences. Uh, otherwise people are basically waiting for that circle of death that we all know, uh, and blaming the networks and other pieces. The problem is actually, the data is not where you are engaging with. It has got to be fetched, you know, seven seas away. Um, and that is the problem that we are basically solving in this modern modernization of that data, data infrastructure. >>I love this conversation and I love the fact that there's a technical person that can kind of educate us on, on this, because date data by its very nature is distributed. It's always been distributed, but w w but distributed database has always been incredibly challenging, whether it was a global SIS Plex or an eventual consistency of getting recovery for a distributed architecture has been extremely difficult. You know, I hate that this is a terrible term, lots of ways to skin a cat, but, but you've been the visionary behind this notion of optionality, how to solve technical problems in different ways. So how do you solve that, that problem of, of, of, uh, of, uh, of a super rock solid database that can handle, you know, distributed data? Yes. >>So there are two issues that you're a little too over there with Forrest is the optionality piece of it, which is that same data that you have that requires different types of processing on it. It's almost like fractional distillation. It is, uh, like your crude flowing through the system. You start all over from petrol and you can end up with Vaseline and rayon on the other end, but the raw material, that's our data in one sense. So far, we never treated the data that way. That's part of the problem. It has always been very purpose built and cast first problem. And so you just basically have to recast it every time we want to look at the data. The first thing that we have done is make data that fluid. So when you're actually, uh, when you have the data, you can first look at it to perform. >>Let's say a simple operation that we call as a key value store operation. Given my ID, give him a password kind of scenarios, which is like, you know, there are customers of ours who have billions of user IDs in their management. So things get slower. How do you make it fast and easily available? Log-in should not take more than five minutes. Again, this is a, there's a class of problem that we solve that same data. Now, eventually, without you ever having to, uh, sort of do a casting it to a different database, you can now do a solid, uh, acquire. These are classic sequel queries, which is our next magic. We are a no SQL database, but we have a full functional sequel. The sequel has been the language that has talked to data for 40 odd years successfully. Every other database has come and try to implement their own QL query language, but they've all failed only sequel as which stood the test of time of 40 odd years. >>Why? Because there's a solid mathematics behind it. It's called a relational calculus. And what that helps you is, is, uh, basically, uh, look at the data and any common tutorial, uh, any, uh, any which way you look at the data. All it will come, uh, the data in a format that you can consume. That's the guarantee sort of gives you in one sense. And because of that, you can now do some really complex in the database signs, what we call us, predicate logic on top of that. And that gives you the ability to do the classic relational type queries, select star from where Canada stuff, because it's at an English level, it becomes easy to, so the same data, you didn't have to go move it to another database, do your, uh, sort of transformation of the data and all this stuff. Same day that you do this. >>Now, that's where the optionality comes in. Now you can do another piece of logic on top of this, which we call search. This is built on this concept of inverted index and TF IDF, the classic Google in a very simple terms, but Google tokenized search, you can do that in the same data without you ever having to move the data to a different format. And then on top of it, they can do what is known as a eventing or your own custom logic, which we all which we do on a, on programming language called Java script. And finally analytics and analytics is the ability to query the operational data in a different way. I'll talk budding. What was my sales of this widget year over year on December 1st week, that's a very complex question to ask, and it takes a lot of different types of processing. >>So these are different types of that's optionality with different types of processing on the same data without you having to go to five different systems without you having to recast the data in five different ways and find different application logic. So you put them in one place. Now is your second question. Now this has got to be distributed and made available in multiple cloud in your data center, all the way to the edge, which is the operational side of the, uh, the database management system. And that's where the distributed, uh, platform that we have built enables us to get it to where you need the data to be, you know, in a classic way, we call it CDN in the data as in like content delivery networks. So far do static, uh, uh, sort of moving of static content to the edges. Now we can actually dynamically move the data. Now imagine the richness of applications you can develop. >>The first part of the, the answer to my question, are you saying you could do this without skiing with a no schema on, right? And then you can apply those techniques. >>Uh, fantastic question. Yes. That's the brilliance of this database is that so far classically databases have always demanded that you first define a schema before you can write a single byte of data. Couchbase is one of the rare databases. I, for one don't know any other one, but there could be, let's give the benefit of doubt. It's a database which writes data first and then late binds to schema as we call it. It's a schema on read things. So because there is no schema, it is just a on document that is sitting inside. And Jason is the lingua franca of the web, as you very well know by now. So it just Jason that we manage, you can do key lookups of the Jason. You can do full credit capability, like a classic relational database. We even have cost-based optimizers and the other sophisticated pieces of technology behind it. >>You can do searching on it, using the, um, the full textual analysis pipeline. You can do ad hoc wedding on the analytic side, and you can write your own custom logic on it using our eventing capabilities. So that's, that's what it allows because we keep the data in the native form of Jason. It's not a data structure or a data schema imposed by a database. It is how the data is produced. And on top of it, we bring different types of logic, five different types of it's like the philosophy is bringing logic to data as opposed to moving data to logic. This is what we have been doing, uh, in the last 40 years because we developed various, uh, database systems and data processing systems of various points. In time in our history, we had key value stores. We had relational systems, we had search systems, we had analytical systems. >>We had queuing systems, all the systems, if you want to use any one of them, our answer has always been, just move the data to that system. Versus we are saying that do not move the data as we get bigger and bigger and data just moving this data is going to be a humongous problem. If you're going to be moving petabytes of data for this is not one to fly instead, bring the logic to the data. So you can now apply different types of logic to the data. I think that's what, in one sense, the optionality piece of this, >>As you know, there's plenty of schema-less data stores. They're just, they're called data swamps. I mean, that's what they, that's what they became, right? I mean, so this is some, some interesting magic that you're applying here. >>Yes. I mean, the one problem with the data swamps as you call them is that that was a little too open-ended because the data format itself could change. And then you do your, then everything became like a game data casting because it required you to have it in seven schema in one sense at the end of the day, for certain types of processing. So in that where a lot of gaps it's probably flooded, but it not really, uh, how do you say, um, keep to the promise that it actually meant to be? So that's why it was a swamp I need, because it was fundamentally not managing the data. The data was sitting in some file system, and then you are doing something, this is a classic database where the data is managed and you create indexes to manage it, and you create different types of indexes to manage it. You distribute the index, you distribute the data you have, um, like we were discussing, you have acid semantics on top of, and when you, when you put all these things together, uh, it's, it's, it's a tough proposition, but they have solved some really tough problems, which are good computer science stuff, computer science problems that we have to solve to bring this, to bring this, to bear, to bring this to the market. >>So you predicted the trend around multimodal and converged, uh, databases. Um, you kind of led Couchbase through that. I want to, I always ask this question because it's clearly a trend in the industry and it, it definitely makes sense from a simplification standpoint. And, and, and so that I don't have to keep switching databases or the flip side of that though, Ravi. And I wonder if you could give me your opinion on this is kind of the right tool for the right job. So I often say isn't that the Swiss army knife approach, we have a little teeny scissors and a knife. That's not that sharp. How do you respond to that? Uh, >>A great one. Um, my answer is always, I use another analogy to tackle that, but is that, have you ever accused a smartphone of being a Swiss army knife? No. No. Nobody does that because it's actually 40 functions in one is what a smartphone becomes. You never call your iPhone or your Android phone, a Swiss army knife, because here's the reason is that you can use that same device in the full capacity. That's what optionality is. It's not, I'm not, it's not like your good old one where there's a keyboard hiding half the screen, and you can do everything only through the keyboard without touching and stuff like that. That's not the whole devices available to you to do one type of processing when you want it. When you're done with that, it can do another completely different types of processing. Like as in a moment, it could be a Tom, Tom telling you all the directions, the next one, it's your PDA. >>Third one, it's a fantastic phone. Uh, four, it's a beautiful camera, which can do your f-stop management and give you a nice SLR quality picture. Right? So next moment is a video camera. People are shooting movies with this thing in Hollywood, these days for God's sake. So it gives you the full power of what you want to do when you want it. And now, if you just taught that iPhone is a great device or any smartphone is a great device, because you can do five things in one or 50 things in one, and at a certain level, they missed the point because what that device really enabled is not just these five things in one place. It becomes easy to consume and easy to operate. It actually started the app is the economy. That's the brilliance of bringing so many things in one place, because in the morning, you know, I get the alert saying that today you got to leave home at eight 15 for your nine o'clock meeting. >>And the next day it might actually say 8 45 is good enough because it knows where the phone is sitting. The geo position of it. It knows from my calendar where the meeting is actually happening. It can do a traffic calculation because it's got my map and all of the routes. And then it's gone there's notification system, which eventually pops up on my phone to say, Hey, you got to leave at this time. Now five different systems have to come together and they can because the data is in one place without that, you couldn't even do this simple function, uh, in a, in a sort of predictable manner in a, in a, in a manner that's useful to you. So I believe a database which gives you this optionality of doing multiple data processing on the same set of data allows you will allow you to build a class of products, which you are so far been able to struggling to build, because half the time you're running sideline to sideline, just, you know, um, integrating data from one system to the other. >>So I love the analogy with the smartphone. I w I want to, I want to continue it and double click on it. So I use this camera. I used to, you know, my kid had a game. I would bring the, the, the big camera, the 35 millimeter. So I don't use that anymore no way, but my wife does, she still uses the DSLR. So is, is there a similar analogy here? That those, and by the way, the camera, the camera shop in my town went out of business, you know? And so, so, but, but is there, is that a fair, where, in other words, those specialized databases, they say there still is a place for them, but they're getting >>Absolutely, absolutely great analogy and a great extension to the question. That's, that's the contrarian side of it in one sense is that, Hey, if everything can just be done in one, do you have a need for the other things? I mean, you gave a camera example where it is sort of, it's a, it's a slippery slope. Let me give you another one, which is actually less straight to the point better. I've been just because my, I, I listened to half of the music on the iPhone. Doesn't stop me from having my full digital receiver. And, you know, my Harman Kardon speakers at home because they haven't, they produce a kind of sounded immersive experience. This teeny little speaker has never in its lifetime intended to produce, right? It's the convenience. Yes. It's the convenience of convergence that I can put my earphones on and listen to all the great music. >>Yes, it's 90% there or 80% there. It depends on your audio file mess of your, uh, I mean, you don't experience the super specialized ones do not go away. You know, there are, there are places where, uh, the specialized use cases will demand a separate system to exist, but even there that has got to be very closed. Um, how do you say close, binding or late binding? I should be able to stream that song from my phone to that receiver so I can get it from those speakers. You can say that, oh, there's a digital divide between these two things done, and I can only play CDs on that one. That's not how it's going to work going forward. It's going to be, this is the connected world, right? As in, if I'm listening to the song in my car and then step off the car and walk into my living room, that's same songs should continue and play in my living room speakers. Then it's a world because it knows my preference and what I'm doing that all happened only because of this data flowing between all these systems. >>I love, I love that example too. When I was a kid, we used to go to Twitter, et cetera. And we'd to play around with, we take off the big four foot speakers. Those stores are out of business too. Absolutely. Um, now we just plug into Sonos. So that is the debate between relational and non-relational databases over Ravi. >>I believe so. Uh, because I think, uh, what had happened was the relational systems. Uh, I've been where the norm, they rule the roost, if you will, for the last 40 odd years, and then gain this no sequel movement, which was almost as though a rebellion from the relational world, we all inhibited, uh, uh, because we, it was very restrictive. It, it had the schema definition and the schema evolution as we call it, all those things, they were like, they required a committee, they required your DBA and your data architect. And you have to call them just to add one column and stuff like that. And the world had moved on. This was the world of blogs and tweets and, uh, you know, um, mashups and, um, uh, uh, a different generation of digital behavior, digital, native people now, um, who are operating in these and the, the applications, the, the consumer facing applications. >>We are living in this world. And yet the enterprise ones were still living in the, um, in the other, the other side of the divide. So all came this solution to say that we don't need SQL. Actually, the problem was never sequel. No sequel was, you know, best approximation, good marketing name, but from a technologist perspective, the problem was never the query language, no SQL was not the problem, the schema limitations, and the inability for these, the system to scale, the relational systems were built like, uh, airplanes, which is that if, uh, San Francisco Boston, there is a flight route, it's so popular that if you want to add 50 more seats to it, the only way you can do that is to go back to Boeing and ask them to get you a set in from 7 3 7 2 7 7 7, or whatever it is. And they'll stick you with a billion dollar bill on the alarm to somehow pay that by, you know, either flying more people or raising the rates or whatever you have to do. >>These are called vertically scaling systems. So relational systems are vertically scaling. They are expensive. Versus what we have done in this modern world, uh, is make the system how it is only scaling, which is more like the same thing. If it's a train that is going from San Francisco to Boston, you need 50 more people be my guests. I'll add one more coach to it, one more car to it. And the better part of the way we have done this year is that, and we have super specialized on that. This route actually requires three, three dining cars and only 10 sort of sleeper cars or whatever. Then just pick those and attach the next route. You can choose to have ID only one dining car. That's good enough. So the way you scale the plane is also can be customized based on the route along the route, more, more dining capabilities, shorter route, not an abandoned capability. >>You can attach the kind of coaches we call this multi-dimensional scaling. Not only do we scale horizontally, we can scale to different types of workloads by adding different types of coaches to it quite. So that's the beauty of this architecture. Now, why is that important? Is that where we land eventually is the ability to do operational and analytical in the same place. This is another thing which doesn't happen in the past, because you would say that I cannot run this analytical Barre because then my operational workload will suffer. Then my friend, then we'll slow down millions of customers that impacted that problem. We will solve the same data in which you can do analytical buddy, an operational query because they're separated by these cars, right? As in like we, we fence the, the, the resources, so that one doesn't impede the other. So you can, at the same time, have a microsecond 10 million ops per second, happening of a key value or equity. >>And then yet you can run this analytical body, which will take a couple of minutes to run one, not impeding the other. So that's in one sense, sort of the, part of the, um, uh, problems that we have solved here is that relational versus, uh, uh, the no SQL portion of it. These are the kinds of problems we have to solve. We solve those. And then we yet put back the same quality language on top. Y it's like Tesla in one sense, right underneath the surface is where all the stuff that had to be changed had to change, which is like the gasoline, uh, the internal combustion engine, uh, I think gas, uh, you says, these are the issues we really wanted to solve. Um, so solve that, change the engine out, you don't need to change the steering wheel or the gas pedal or the, you know, the battle shifters or whatever else you need, or that are for your shifters. >>Those need to remain in the same place. Otherwise people won't buy it. Otherwise it does not even look like a car to people. So, uh, even when you feed people the most advanced technology, it's got to be accessible to them in the manner that people can consume. Only in software, we forget this first design principle, and we go and say that, well, I got a car here, you got the blue harder to go fast and lean back for, for it to, you know, uh, to apply a break that's, that's how we seem to define, uh, design software. Instead, we should be designing them in a manner that it is easiest for our audience, which is developers to consume. And they've been using SQL for 40 years or 30 years. And so we give them the steering wheel on the, uh, and the gas bottle and the, um, and the gear shifter is by putting cul back on underneath the surface, we have completely solved, uh, the relational, uh, uh, limitations of schema, as well as scalability. >>So in, in, in that way, and by bringing back the classic acid capabilities, which is what relational systems, uh, we accounted on and being able to do that with the sequel programming language, we call it like multi-state SQL transaction. So to say, which is what a classic way all the enterprise software was built by putting that back. Now, I can say that that debate between relational and non-relational is over because this has truly extended the database to solve the problems that the relational systems had to grow up the salt in the modern times, but rather than get, um, sort of pedantic about whether it's, we have no SQL or sequel or new sequel, or, uh, you know, any of that sort of, uh, jargon, oriented debate, uh, this, these are the debates of computer science that they are actually, uh, and they were the solve and they have solved them with, uh, the latest release of $7, which we released a few months ago. >>Right, right. Last July, Ravi, we got to leave it there. I, I love the examples and the analogies. I can't wait to be face to face with you. I want to hang with you at the cocktail party because I've learned so much and really appreciate your time. Thanks for coming to the cube. >>Fantastic. Thanks for the time. And the Aboriginal Dan was, I mean, very insightful questions really appreciate it. Thank you. >>Okay. This is Dave Volante. We're covering Couchbase connect online, keep it right there for more great content on the cube.

>> Welcome back to the cubes coverage of Couchbase connect online, where the theme of the event is, is modernize now. Yes, let's talk about that. And with me is Ravi mayor him, who's the senior vice president of engineering and the CTO at Couchbase Ravi. Welcome. Great to see you. >> Thank you so much. I'm so glad to be here with you. >> I want to ask you what the new requirements are around modern applications. I've seen some of your comments, you got to be flexible, distributed, multimodal, mobile, edge. Those are all the very cool sort of buzz words, smart applications. What does that all mean? And how do you put that into a product and make it real? >> Yeah, I think what has basically happened is that so far it's been a transition of sorts. And now we are come to a point where that tipping point and that tipping point has been more because of COVID and there are COVID has pushed us to a world where we are living in a in a sort of occasionally connected manner where our digital interactions precede, our physical interactions in one sense. So it's a world where we do a lot more stuff that's less than in a digital manner, as opposed to sort of making a more specific human contact. That does really been the sort of accelerant to this modernize Now, as a team. In this process, what has happened is that so far all the databases and all the data infrastructure that we have built historically, are all very centralized. They're all sitting behind. They used to be in mainframes from where they came to like your own data centers, where we used to run hundreds of servers to where they're going now, which is the computing marvelous change to consumption-based computing, which is all cloud oriented now. And so, but they are all centralized still, but where our engagement happens with the data is at the edge at your point of convenience, at your point of consumption, not where the data is actually sitting. So this has led to, you know, all those buzzwords, as you said, which is like, oh, well we need a distributed data infrastructure, where is the edge? But it just basically comes down to the fact that the data needs to be there, if you are engaging with it. And that means if you are doing it on your mobile phone, or if you're sitting, but doing something in your while you're traveling, or whether you're in a subway, whether you're in a plane or a ship, wherever the data needs to come to you and be available, as opposed to every time you going to the data, which is centrally sitting in some place. And that is the fundamental shift in terms of how the modern architecture needs to think when they, when it comes to digital transformation and, transitioning their old applications to the, the modern infrastructure, because that's, what's going to define your customer experiences and your personalized experiences. Otherwise, people are basically waiting for that circle of death that we all know, and blaming the networks and other pieces. The problem was actually, the data is not where you are engaging with it. It's got to be fetched, you know, seven sea's away. And that is the problem that we are basically solving in this modern modernization of that data, data infrastructure. >> I love this conversation and I love the fact that there's a technical person that can kind of educate us on, on this because date data by its very nature is distributed. It's always been distributed, but with the distributed database has always been incredibly challenging, whether it was a global SIS Plex or an eventual consistency of getting recovery for a distributed architecture has been extremely difficult. You know, I hate that this is a terrible term, lots of ways to skin a cat, but, but you've been the visionary behind this notion of optionality, how to solve technical problems in different ways. So how do you solve that, that problem of, of, of, of, of a super rock solid database that can handle, you know, distributed data? >> Yes. So there are two issues that you alluded little too over there. The first is the optionality piece of it, which is that same data that you have that requires different types of processing on it. It's almost like fractional distillation. It is like your crude flowing through the system. You start all over from petrol and you can end up with Vaseline and rayon on the other end, but the raw material, that's our data. In one sense. So far, we never treated the data that way. That's part of the problem. It has always been very purpose built and cast first problem. And so you just basically have to recast it every time we want to look at the data. The first thing that we have done is make data that fluid. So when you're actually, when you have the data, you can first look at it to perform. Let's say a simple operation that we call as a key value store operation. Given my ID, give him a password kind of scenarios, which is like, you know, there are customers of ours who have billions of user IDs in their management. So things get slower. How do you make it fast and easily available? Log-in should not take more than five milliseconds, this is, this is a class of problem that we solve that same data. Now, eventually, without you ever having to sort of do a casting it to a different database, you can now do solid queries. Our classic SQL queries, which is our next magic. We are a no SQL database, but we have a full functional SQL. The SQL has been the language that has talked to data for 40 odd years successfully. Every other database has come and tried to implement their own QL query language, but they've all failed only SQL has stood the test of time of 40 odd years. Why? Because there's a solid mathematics behind it. It's called a relational calculus. And what that helps you is, is basically a look at the data and any common editorial, any, any which way you look at the data, all it will come, the data in a format that you can consume. That's the guarantee sort of gives you in one sense. And because of that, you can now do some really complex in the database signs, what we call us, predicate logic on top of that. And that gives you the ability to do the classic relational type queries select star from where, kind of stuff, because it's at an English level becomes easy to so the same day that you didn't have to go move it to another database, do your sort of transformation of the data and all the stuff, same day that you do this. Now that's where the optionality comes in. Now you can do another piece of logic on top of this, which we call search. This is built on this concept of inverted index and TF IDF, the classic Google in a very simple terms, what Google tokenized search, you can do that in the same data without you ever having to move the data to a different format. And then on top of it, they can do what is known as a eventing or your own custom logic, which we all which we do on a, on programming language called Java script. And finally analytics and analytics is the, your ability to query the operational data in a different way. And talk querying, what was my sales of this widget year over year on December 1st week, that's a very complex question to ask, and it takes a lot of different types of processing. So these are different types of that's optionality with different types of processing on the same data without you having to go to five different systems without you having to recast the data in five different ways and apply different application logic. So you put them in one place. Now is your second question. Now this has got to be distributed and made available in multiple cloud in your data center, all the way to the edge, which is the operational side of the, the database management system. And that's where the distributed platform that we have built enables us to get it to where you need the data to be, you know, in the classic way we call it CDN'ing the data as in like content delivery networks. So far do static, sort of moving of static content to the edges. Now we can actually dynamically move the data. Now imagine the richness of applications you can develop. >> And on the first part of, of the, the, the answer to my question, are you saying you could do this without scheme with a no schema on, right? And then you can apply those techniques. >> Fantastic question. Yes. That's the brilliance of this database is that so far classically databases have always demanded that you first define a schema before you can write a single byte of data. Couchbase is one of the rare databases. I, for one don't know any other one, but there could be, let's give the benefit of doubt. It's a database which writes data first and then late binds to schema as we call it. It's a schema on read thing. So, because there is no schema, it is just a Json document that is sitting inside. And Json is the lingua franca of the web, as you very well know by now. So it just Json that we manage, you can do key value look ups of the Json. You can do full credit capability, like a classic relational database. We even have cost-based optimizers and other sophisticated pieces of technology behind it. You can do searching on it, using the, the full textual analysis pipeline. You can do ad hoc webbing on the analytics side, and you can write your own custom logic on it using or inventing capabilities. So that's, that's what it allows because we keep the data in the native form of Json. It's not a data structure or a data schema imposed by a database. It is how the data is produced. And on top of it, bring, we bring different types of logic, five different types of it's like the philosophy is bringing logic to data as opposed to moving data to logic. This is what we have been doing in the last 40 years, because we developed various database systems and data processing systems at various points in time in our history, we had key value stores. We had relational systems, we had search systems, we had analytical systems. We had queuing systems, all these systems, if you want to use any one of them are answered. It always been, just move the data to that system. Versus we are saying that do not move the data as we get bigger and bigger and data just moving this data is going to be a humongous problem. If you're going to be moving petabytes of data for this, it's not going to fly instead, bring the logic to the data, right? So you can now apply different types of logic to the data. I think that's what, in one sense, the optionality piece of this. >> But as you know, there's plenty of schema-less data stores. They're just, they're called data swamps. I mean, that's what they, that's what they became, right? I mean, so this is some, some interesting magic that you're applying here. >> Yes. I mean, the one problem with the data swamps as you call them is that that was a little too open-ended because the data format itself could change. And then you do your, then everything became like a game data recasting because it required you to have it in seven schema in one sense at, at the end of the day, for certain types of processing. So in that where a lot of gaps it's probably related, but it not really, how do you say keep to the promise that it actually meant to be? So that's why it was a swamp I mean, because it was fundamentally not managing the data. The data was sitting in some file system, and then you are doing something, this is a classic database where the data is managed and you create indexes to manage it. And you create different types of indexes to manage it. You distribute the index, you distribute the data you have, like we were discussing, you have ACID semantics on top of, and when you, when you put all these things together, it's, it's, it's a tough proposition, but we have solved some really tough problems, which are good computer science stuff, computer science problems that we have to solve to bring this, to bring this, to bear, to bring this to the market. >> So you predicted the trend around multimodal and converged databases. You kind of led Couchbase through that. I, I want, I always ask this question because it's clearly a trend in the industry and it, and it definitely makes sense from a simplification standpoint. And, and, and so that I don't have to keep switching databases or the flip side of that though, Ravi. And I wonder if you could give me your opinion on this is kind of the right tool for the right job. So I often say isn't that the Swiss army knife approach, where you have have a little teeny scissors and a knife, that's not that sharp. How, how do you respond to that? >> A great one. My answer is always, I use another analogy to tackle that, and is that, have you ever accused a smartphone of being a Swiss army knife? - No. No. >> Nobody does. That because it actually 40 functions in one is what a smartphone becomes. You never call your iPhone or your Android phone, a Swiss army knife, because here's the reason is that you can use that same device in the full capacity. That's what optionality is. It's not, I'm not, it's not like your good old one where there's a keyboard hiding half the screen, and you can do everything only through the keyboard without touching and stuff like that. That's not the whole devices available to you to do one type of processing when you want it. When you're done with that, it can do another completely different types of processing. Right? As in a moment, it could be a TomTom, telling you all the directions, the next one, it's your PDA. Third one. It's a fantastic phone. Four. It's a beautiful camera which can do your f-stop management and give you a nice SLR quality picture. Right? So next moment, it's the video camera. People are shooting movies with this thing in Hollywood, these days for God's sake. So it gives you the full power of what you want to do when you want it. And now, if you just thought that iPhone is a great device or any smartphone is a great device, because you can do five things in one or 50 things in one, and at a certain level, he missed the point because what that device really enabled is not just these five things in one place. It becomes easy to consume and easy to operate. It actually started the app based economy. That's the brilliance of bringing so many things in one place, because in the morning, you know, I get an alert saying that today you got to leave home at >> 8: 15 for your nine o'clock meeting. And the next day it might actually say 8 45 is good enough because it knows where the phone is sitting. The geo position of it. It knows from my calendar where the meeting is actually happening. It can do a traffic calculation because it's got my map and all of the routes. And then it's got this notification system, which eventually pops up on my phone to say, Hey, you got to leave at this time. Now five different systems have to come together and they can because the data is in one place. Without that, you couldn't even do this simple function in a, in a sort of predictable manner in a, in a, in a manner that's useful to you. So I believe a database which gives you this optionality of doing multiple data processing on the same set of data allows you will allow you to build a class of products, which you are so far been able to struggling to build. Because half the time you're running sideline to sideline, just, you know, integrating data from one system to the other. >> So I love the analogy with the smartphone. I want to, I want to continue it and double click on it. So I use this camera. I used to, you know, my kid had a game. I would bring the, the, the big camera, the 35 millimeter. So I don't use that anymore no way, but my wife does, she still uses the DSLR. So is, is there a similar analogy here? That those, and by the way, the camera, the camera shop in my town went out of business, you know? So, so, but, but is there, is that a fair and where, in other words, those specialized databases, they say there still is a place for them, but they're getting. >> Absolutely, absolutely great analogy and a great extension to the question. That's like, that's the contrarian side of it in one sense is that, Hey, if everything can just be done in one, do you have a need for the other things? I mean, you gave a camera example where it is sort of, it's a, it's a slippery slope. Let me give you another one, which is actually less straight to the point better. I've been just because my, I, I listened to half of my music on the iPhone. Doesn't stop me from having my full digital receiver. And, you know, my Harman Kardon speakers at home because they, I mean, they produce a kind of sounded immersive experience. This teeny little speaker has never in its lifetime intended to produce, right? It's the convenience. Yes. It's the convenience of convergence that I can put my earphones on and listen to all the great music. Yes, it's 90% there or 80% there. It depends on your audio file-ness of your, I mean, your experience super specialized ones do not go away. You know, there are, there are places where the specialized use cases will demand a separate system to exist. But even there that has got to be very closed. How do you say close, binding or late binding? I should be able to stream that song from my phone to that receiver so I can get it from those speakers. You can say that all, there's a digital divide between these two things done, and I can only play CDs on that one. That's not how it's going to work going forward. It's going to be, this is the connected world, right? As in, if I'm listening to the song in my car and then step off the car, walk into my living room, that same songs should continue and play in my living room speakers. Then it's a connected world because it knows my preference and what I'm doing that all happened only because of this data flowing between all these systems. >> I love, I love that example too. When I was a kid, we used to go to Tweeter, et cetera. And we used to play around with three, take home, big four foot speakers. Those stores are out of business too. Absolutely. And now we just plug into Sonos. So that is the debate between relational and non-relational databases over Ravi? >> I believe so, because I think what had happened was relational systems. I've mean where the norm, they rule the roost, if you will, for the last 40 odd years and then gain this no SQL movement, which was almost as though a rebellion from the relational world, we all inhabited because we, it was very restrictive. It, it had the schema definition and the schema evolution as we call it, all those things, they were like, they required a committee. They required your DBA and your data architect. And you had to call them just to add one column and stuff like that. And the world had moved on. This was a world of blogs and tweets and, you know, mashups and a different generation of digital behavior, There are digital, native people now who are operating in these and the, the applications, the, the consumer facing applications. We are living in this world. And yet the enterprise ones were still living in the, in the other, the other side of the divide. So out came this solution to say that we don't need SQL. Actually the problem was never SQL. No SQL was, you know, best approximation, good marketing name, but from a technologist perspective, the problem was never the query language, no SQL was not the problem, the schema limitations and the inability for these, the system to scale, the relational systems were built like airplanes, which is that if a San Francisco, Boston, there is a flight route, it's so popular that if you want to add 50 more seats to it, the only way you can do that is to go back to Boeing and ask them to get you a set from 7 3 7 2 7 7 7, or whatever it is. And they'll stick you with a billion dollar bill on the allowance that you'll somehow pay that by, you know, either flying more people or raising the rates or whatever you have to do. These are all vertically scaling systems. So relational systems are vertically scaling. They are expensive. Versus what we have done in this modern world is make the system horizontally scaling, which is more like the same thing. If it's a train that is going from San Francisco to Boston, you need 50 more people be my guest. I'll add one more coach to it, one more car to it. And the better part of the way we have done this here is that, and we are super specialized on that. This route actually requires three, three dining cars and only 10 sort of sleeper cars or whatever. Then just pick those and attach the next route. You can choose to have, I need only one dining car. That's good enough. So the way you scale the plane is also can be customized based on the route along the route, more, more dining capabilities, shorter route, not an abandoned capability. You can attach the kind of coaches we call this multidimensional scaling. Not only do we scale horizontally, we can scale to different types of workloads by adding different types of coaches to it, right? So that's the beauty of this architecture. Now, why is that architecture important? Is that where we land eventually is the ability to do operational and analytical in the same place. This is another thing which doesn't happen in the past, because, you would say that I cannot run this analytical query because then my operational workload will suffer. Then my front end, then we'll slow down millions of customers that impacted that problem. They'll solve the same data once again, do analytical query, an operational query because they're separated by these cars, right? As in like we, we, we fence the, the, the resources so that one doesn't impede the other. So you can, at the same time, have a microsecond 10 million ops per second, happening of a key value or a query. And then yet you can run this analytical query, which will take a couple of minutes to them. One, not impeding the other. So that's in one sense, sort of the part of the problems that we have solved it here is that relational versus the no SQL portion of it. These are the kinds of problems we have to solve. We solve those. And then we yet put back the same query language on top. Why? It's like Tesla in one sense, right underneath the surface is where all the stuff that had to be changed had to change, which is like the gasoline, the internal combustion engine the gas, you says, these were the issues we really wanted to solve. So solve that, change the engine out, you don't need to change the steering wheel or the gas pedal or the, you know, the battle shifters or whatever else you need, over there your gear shifters. Those need to remain in the same place. Otherwise people won't buy it. Otherwise it does not even look like a car to people. So even when you feed people, the most advanced technology, it's got to be accessible to them in the manner that people can consume. Only in software, we forget this first design principle, and we go and say that, well, I got a car here, you got the blow harder to go fast. And they lean back for, for it to, you know, to apply a break that's, that's how we seem to define design software. Instead, we shouldn't be designing them in a manner that it is easiest for our audience, which is developers to consume. And they've been using SQL for 40 years or 30 years. And so we give them the steering wheel on the, and the gas pedal and the, and the gear shifters by putting SQL back on underneath the surface, we have completely solved the relational limitations of schema, as well as scalability. So in, in, in that way, and by bringing back the classic ACID capabilities, which is what relational systems we accounted on, and being able to do that with the SQL programming language, we call it like multi-statement SQL transaction. So to say, which is what a classic way all the enterprise software was built by putting that back. Now, I can say that that debate between relational and non-relational is over because this has truly extended the database to solve the problems that the relational systems had to grow up to solve in the modern times, rather than get sort of pedantic about whether it's we have no SQL or SQL or new SQL, or, you know, any of that sort of jargon oriented debate. This is, these are the debates of computer science that they are actually, and they were the solve, and they have solved them with the latest release of 7.0, which we released a few months ago. >> Right, right. Last July, Ravi, we got got to leave it there. I love the examples and the analogies. I can't wait to be face-to-face with you. I want to hang with you at the cocktail party because I've learned so much and really appreciate your time. Thanks for coming to the cube. >> Fantastic. Thanks for the time. And the opportunity I was, I mean, very insightful questions really appreciate it. - Thank you. >> Okay. This is Dave Volante. We're covering Couchbase connect online, keep it right there for more great content on the cube.

>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hello and welcome back to the Cube Coverage of eight of us reinvent 2020 Virtual. I'm John for your host of the Cube. Normally we're in person this year. It's a virtual event. It is reinvent and cube virtual here. We got great interview here. Segment with VM ware and A W s. Two great guests. Keep both Cube alumni. Marc Lemire, senior vice president, general manager, The Cloud Services Business Unit VM Ware and Dave Brown, Vice president Elastic Compute Cloud easy to from Amazon Web services Gentlemen, great to see you guys. Thanks for coming on. >>Great. Thank you. Good to be back. >>Thanks. Great to be back. >>So you know, Dave, we love having you on because ec2 obviously is the core building block of a device. Once the power engine, it's the core product. And Mark, we were just talking a few months ago at VM World of momentum you guys have had on the business front. It's even mawr accelerated with co vid on the pandemic. Give us the update The partnership three years ago when Pat and Andy in San Francisco announced the partnership has been nothing but performance. Business performance, technical integration. Ah, lots happened. What's the update here for reinvent? >>Yeah, I guess the first thing I would say is look, you know, the partnership has has never been stronger. You know, as you said, uh, we announced the partnership and delivered the initial service three years ago. And I think since then, both companies have really been focused on innovating rapidly on behalf of our customers bringing together the best of the VM, or portfolio, and the best of, you know, the entire AWS. A set of capabilities. And so we've been incredibly pleased to be able to deliver those that value to our joint customers. And we look forward to continue to work very closely together. You know, across all aspects of our two companies toe continue to deliver more and more value to our joint customers. >>Well, I want to congratulate you guys at VM where, you know, we've been following that story from day one. I let a lot of people skeptical on the partnership. We were pretty bullish on it. We saw the value. It's been just been great Synergy day. I want to get your thoughts because, you know, I've always been riffing about enabling technologies and and the way it works is enabling technologies. Allow your partners to make more money, too. Right? So you guys do that with the C two, and I know that for a fact because we're doing well with our virtual event cloud, but are easy to bills are up, but who cares? We're doing well. This is the trend you guys are enabling partners, and VM Ware in particular, has a lot of customers that are on AWS. What's your perspective on all this? >>You know the part. The part maker system is so important for us, right? And we get from our customers. We have many customers who, you know, use VM ware in their own environment. They've been using it for years and years, um, true for many other software applications as well and other technologies. Andi, when they moved to AWS there very often. When you use those tools on those services on AWS is well and so you know, we we partner with many, many, many, many companies, and so it's a high priority for us. The VM Ware partnership, I think, is being sort of role model for us in terms of, you know, sitting out outside Sana goal back in 2016. I think it waas and, you know, delivering on that. Then continue to innovate on features over the last three years listening to our customers, bringing larger customers on board, giving them more advanced networking features, improving. You know that the instance types of being whereas utilizing to deliver value to their customers and most recently, obviously, with Outpost AWS outposts and parking with VM ware on VM are enabled outposts and bringing that to our customers and their own data centers. So we see the whole partner ecosystem is critically important. Way were spent a lot of time with VM and other partners on something that our customers really value. >>Mark, I want to get your thoughts on this because I was just riffing with Day Volonte about this. Um, heightened awareness with that covert 19 in the pandemic has kind of created, which is an accelerant of the value. And one >>of the >>things that's a parent is when you have this software driven and software defined kind of environment, whether it's in space or on premise or in the cloud. Um, it's the software that's driving everything, but you have to kind of components. You have the how do you operate something, And then how does the software works? So you know, it's the hand in the glove operators and software in the cloud really is becoming kind of the key things. You guys have been very successful as a company with I t operations, and now you're moving into the cloud. Can you share your thoughts on how VM Ware cloud on AWS takes that next level for your customers? So I think that's a key point that needs to be called that. What's your What's your thoughts on that? >>Yeah, I think you hit the nail on the head, and I think, you know, look, every company is on a journey to transform the level of capability they're able to offer to their customers and their employees, right? And a big part of that is how do they modernize their application environment? How do they how do they deliver new applications and services? And so this has been underway for for a while now. But if if anything, I think Cove, it has only accelerated. Um, the need for customers to be able to continue to go down that path. And so, you know, between VM ware in AWS, um, you know, we're looking to provide those customers a platform that allows them to accelerate their path to application, modernization and new services and capabilities. And, um, you know, Dave talked about the ecosystem and the importance of the ecosystem that AWS and I think you know, together. What we've been able to do if you sort of think about it, is, you know, bringing together this rich set of VM Ware services and capabilities. Um, that we've talked about before, as well as new VM Ware capabilities, for example, the ability to enable kubernetes based applications and services on top of this Corby, um or platform with Tan Xue. Right. So customers can get access to all of that is they go down this modernization path. But, you know, right next door in the same ese is 375 native AWS services that they can use together in conjunction, uh, with that environment. And so if you think about accelerating that journey right Being ableto rapidly migrate those VM ware based workloads into the AWS cloud. When you're in the AWS cloud, be able to modernize that environment using the VM Ware Tansu capability, the native AWS services and then the infrastructure that needs to come together to make that possible, for example, the network connectivity that needs to be enabled, um, to take advantage of some of those services together. Um, you know, we're really we're trying to accelerate our delivery of those capabilities so that we can help our customers accelerate the delivery of that application value thio to their customers. >>David want to get your thoughts on the trends If you speak to the customers out there at VM Ware, customers that are on the cloud because you know the sphere, for instance, very popular on the Ws Cloud with VM Ware Cloud as well as these new modern application trends like Tan Xue, Project Monterey is coming around the corner that was announced that VM world what trends do you see from the two perspective that you could share to the VM ware eight of his customers? What's the key wave right now that they should be riding on. >>Yeah, I think a few things, you know, we definitely are seeing an acceleration in customers Looking Thio looking to utilize humor on AWS You know, there was a lot of interest early on, really, over the last year, I think we've seen 140% growth in the service, which has been incredibly exciting for both of us and really shows that we we're providing customers with the service that works. You know, I think one of the key things that Mark called out just talking previously was just how simple it is for customers to move. You know, often moving to the cloud gets muddled with modernization, and it takes a long time because customers to kind of think about how do they actually make this move? Or are they stuck within their own facility on data center or they need to modernize? We moved to a different hyper visor with PM on AWS. You literally get that same environment on AWS, and so whether it's a a migration because you want to move out of your on premise facility, whether it's a migration because you want to grow and expand your facility without needing to. You know, build more data centers yourself Whether you're looking to build a d. R site on AWS on whether you looking just, you know, maybe build a new applications tank that you wanna build in a modern way, you know, using PMR in Tanzania and all the AWS services, all of those a positive we're seeing from customers. Um, you know, I think I think as the customers grow, the demand for features on being were in AWS grows as well. And we put out a number of important features to support customers that really, really large scale. And that's something that's being exciting. It's just some of the scale that we're seeing from very, very large being, we customers moving over to AWS. And so I think you know a key messages. If you have a Vienna installation today and you're thinking about moving to the cloud, it's really a little that needs to stop you in starting to move. It is is very simple to set up, and very little you have to do to your application stack to actually move it over. >>Mark, that's a great point. I want to get your thoughts on that in reaction toe. What? Dave just said Because this is kind of what you guys had said many years ago and also a VM world when we were chatting, disrupting operations just to stand up the clubs shouldn't be in place. It should be easy on you. Heard what Dave said. It's like you got >>a >>lot of cultures that are operating large infrastructure and they want to move to the cloud. But they got a mandate toe make everything. Is a services more cloud native coming. So, yeah, you gotta check off the VM where boxes and keep things running. But you gotta add more modern tooling mawr application pressure there. So there's a lot of pressure from the business units and the business models to say We gotta take advantage of the modern applications. How do you How do you look at that? >>Yeah, yeah, I mean, I think Look, making this a simple is possible is obviously a really important aspect of what we're trying Thio enable for our customers. Also, I think the speed is important, right? How you know, how can we enable them? Thio accelerate their ability to move to the cloud, but then also accelerate their ability Thio, um, deliver new services and capabilities that will differentiate their business. And then how do we, uh, kind of take some of the heavy lifting off the customers plate in terms of what it actually takes to operate and run the infrastructure and do so in a highly available way that they could depend upon for their business? And of course, delivering that full capabilities of service is a big part of that. You know, one of my when my favorite customer examples eyes a company called Stage Coach, uh, European based transportation company. And they run a network of Busses and trains, etcetera, and they actually decided to use VM. Tosto run one of their most mission critical applications, which is involved with basically scheduling, scheduling those systems right in the people that they know, the bus drivers in the train conductors etcetera. And so if you think about that application right, its's a mission critical application for them. It's also one that they need to be able to iterate involved and improve very quickly, and they were able to take advantage of a number of fairly unique capabilities of the joint service we built together to make that possible. Um, you know, the first thing that they did is they took advantage of something called stretch clusters. The M we're cloud on AWS stretch clusters Where, uh, we basically take that VM Ware environment and we stretch it. We stretch the network across to aws availability zones in the same region, Onda. Then they could basically run their applications on top of that that environment. And this is a really powerful capability because it ensures the highest levels of s L. A. For that application for four nines. In this case, if anything happens, Thio fail in one of those, uh, Aziz, we can automatically fail over and restart the application in the second ese on DSO provides this high level of availability, but they're also able to take advantage of that without on day one. Talk about keeping it simple without on day one, requiring any changes to the application of myself because that application knew how to work in the sphere. And so you know that I work in the sphere in the cloud and it can fail over on the sphere in the cloud on dso they were able to get there quickly. They're able Thio enable that application and now they're taking the next step. Which is how do I enhance and make that application even better, you know, leveraging some of the VM or capabilities also looking to take advantage of some of the native AWS capabilities. So I think that sort of speed, um you know that simplicity that helps helps customers down that path to delivering more value to their employees and their customers. That and we're really excited that were ableto offer that your customers >>just love the philosophy that both companies work back from the customer customer driven kind of mentality certainly key here to this partnership, and you can see the performance. But I think one of the differentiations that I love is that join integration thing engineering that you guys were doing together. I think that's a super valuable, differentiated VM where Dave, this is a key part of the relationship. You know, when I talked to Pat Gelsinger and and again back three years ago and he had Raghu from VM, Ware was like, This is different engineering together. What's your perspective from the West side when someone says, Yeah. Is that Riel? You know, it is easy to really kind of tied in there and his Amazon really doing joint engineering. What do you say to that? >>Oh, absolutely. Yeah, it's very real. I mean, it's been an incredible, incredible journey together, Right? Right, Right from the start, we were trying to work out how to do this back in 2016. You know, we were using some very new technology back then that we hadn't honestly released yet. Uh, the nitrous system, right? We started working with family and the nitrous system back in late 2016, and we only launched our first nitrous system enabled instance that reinvent 2017. And so we were, you know, for a year having being a run on the nitrous system, internally making sure that, you know, we would support their application and that VM Ware ran well on BC around. Well, on aws on, that's been ongoing. And, you know, the other thing I really enjoy about the relationship is learning how to best support each other's customers on on AWS and being where, and Mark is talking about stretch clusters and are being whereas, you know, utilizing the availability zones. We've done other things in terms of optimizing placement with across, you know, physical reaction in data centers. You know, Mark and the team have put forward requirements around, you know, different instance types and how they should perform invest in the Beamer environment. We've taken that back into our instance type definition and what we've released there. So it happens in a very, very low level. And I think it's both teams working together frequently, lots of meetings and then, you know, pushing each other. You know, honestly. And I think for the best experience or at the end of the day, for our joint customers. So it's been a great relationship. >>It helps when both companies are very fluent technically and pushing the envelope with technology. Both cultures, I know personally, are very strong technically, but they also customer centric. Uhm, Mark, I gotta put you on the spot on this question because this comes up every year this year more than ever. Um, is the question around VM ware on A W S and VM ware in general, and it's more of a general industry theme. But I wanna ask you because I think it relates to the US Um vm ware cloud on aws. Um, the number one question we get is how can I automate my I t operations? Because it's kind of a no brainer. Now it's kind of the genes out of the bottle. That's a mandate. But it's not always easy. Easy as it sounds to dio, you still got a lot to dio. Automation gets you level set to take advantage of some of these higher level services, and all customers want to get there fast. Ai i o t a lot of goodness in the cloud that you kinda gotta get there through kinda automating the based up first. So how did how are your customers? How are you guys helping customers automate their infrastructure operations? >>Yeah, I mean, Askew articulated right? This is a huge demand. The requirement from our customer base, right? Uh, long gone are the days that you wanna manually go into a u I and click around here, click there to make things happen, right? And so, um, you know, obviously, in addition to the core benefit of hey, we're delivering this whole thing is a service, and you don't have to worry about the hardware, the software, the life cycle all of that, Um you know, at a higher level of the stack, we're doing a lot of work to basically expose a very rich set of AP eyes. We actually have enabled that through something called the VM, or Cloud Developer center, where you can go and customer could go and understand all of the a p i s that we make available to that they can use to build on top of to effectively automated orchestrate their entire VM or cloud on AWS based infrastructure. And so that's an area we've we've invested a lot in. And at the end of the day, you know we want Thio. Both enable our customers to take their existing automation tooling that they might have been using on their VM ware based environment in their own data center. Obviously, all of that should continue to work is they bring that into the emcee aws. Um but now, once we're in AWS and we're delivering, this is a service in AWS. There's actually a higher level of automation, um that we can enable, and so you know everything that you can do through the VM or cloud console. Um, you can do through a P. I s So we've exposed roughly a piece that allow you to add or remove instance capacity ap eyes that allow you to configure the network FBI's that allow you toe effectively. Um, automate all aspects of sort of how you want Thio configure and pull together that infrastructure. Onda. You know, as Dave said, a lot of this, you know, came from some of those early just customer discussions where that was a very, very clear expectations. So, you know, we've we've been working hard. Thio make that possible. >>So can customers integrate native Cloud native technologies from AWS into APS running on VM ware cloud on any of us? >>Yeah. I mean, I'll give you one example for so we you know, we've been able to support for cloud formation right on top of the M C. Mehta best. And so that's, you know, one way that you can leverage these 80 best tools on top of on top of the m. C at best. Um and you know, as we talked about before, uh, you know everything on the VM ware in the VM ware service. We're exposing through those AP eyes. And then, of course, everything it best does has been built that way from the start. And so customers can work. Um, you know, seamlessly across those two environments. >>Great stuff. Great update. Final question for both of you. Uh, Dave will start with you. What's the unique advantages? When you people watching? That's gonna say, OK, I get it. I see the momentum. I've now got a thing about post pandemic growth strategies. I gotta fund the projects, so I'm either gonna retool while I'm waiting for the world to open up. Two. I got a tail wind. This is good for my business. I'm gonna take advantage of this. How do they modernize our application? What? The unique things with VM Ware Cloud on AWS. What's unique? What would you say? I >>mean, I think the big thing for me eyes the consistency, um, the other way that were built This between the the sphere on prime environment and the the sphere that you get on aws with BMC on aws. Um you know, when I think about modernization and honestly, any project that I do, we do it Amazon I don't like projects that required enormous amount of planning and then tooling. And then, you know, you've this massive waterfall stock project before you do anything meaningful. And what's so great about what we built here is you can start that migration almost immediately, start bringing a few applications over. And when you do that, you can start saying, Okay, where do we want to make improvements? But just by moving over to aws NBN were on AWS, you start to reap the benefits of being in the child right from day one. Many of the things Mark called out about infrastructure management and that sort of thing. But then you get to modernize off to that as well. And so just the richness in terms of, you know, being where a tan xue and then the you know, I think it's more than 200 AWS services. Now you get to bring all that into your application stack, but at a time at a at a at a cadence or time that really matters to you. But you could get going immediately, and I think that's the thing that customers ready need to do if you find yourself in a situation you know, with just how much the world's changed in the last year. Looking Thio. Modernize your applications deck, Looking for the cost benefits. Looking to maybe get out of the data center. Um, it's a relatively easy both forward and just put in a couple of engineers a couple of technicians on to actually starting to do the process. I think you'll be very surprised at how much progress you can actually make in a short amount of time. >>Mark, you're in charge of the Cloud Services business unit at VM Ware CPM. Where cloud on AWS successful more to do a lot of action kubernetes cloud native automation and the list goes on and on. What are the most unique advantages that you guys have? What would you say? >>Yeah, I mean, I would maybe just build on Dave's comments a bit. I think you know, if you look at it through the customer lens three ability to reiterate and the ability to move quickly and not being forced into sort of a one size fits all model, right? And so there may be certain applications that they run into VM, and they want to run into VM forever. Great. We could enable that there might be other applications that they want to move from a VM into a container, remove into kubernetes and do that in a very seamless way. And we can enable that with, uh, with Tan Xue, right? By the way, they may wanna actually many applications. They're gonna require, uh, complex composite applications that have some aspects of it running in communities, other aspects running on VMS. You know, other aspects connecting to some native AWS services. And so, you know, we could enable those types of, you know, incremental value that's delivered very, very quickly that allows them at the end of the day to move, move fast on behalf of their own customers and deliver more about it to them. So I think this this sort of philosophy, right that Dave talked about I think is is one of the really important things we've tried to focus on, um, together. But, you know, on behalf of our joint customers and you know that that sort of capabilities just gets richer and richer. Overtime right. Both of us are continuing to innovate, and both of us will continue to think about how we bring those services together as we innovate in our respective areas and how they need to link together as part of this This intense solution. Um, so, uh, you know that I think that you're gonna see us continue to invest, continue to move quickly. Um, continue to respond to what our customers together are asking us. Thio enable for them. >>Well, really appreciate the insight. Thanks for coming on this cube virtual, um, segment. Um, virtualization has hit the cube where we have multiple virtual stages out there at reinvent on the site. Obviously, it's a virtual event over three weeks, so it's a little bit not four days or three days. It's three weeks. So, um, if you're watching this, check out the site. Tons of good V o D. The executive leaderships Check out the keynotes that air there. It's awesome. Big news. Of course. Check out the cube coverage, but I have one final final question is you guys are leaders in the industry and within your companies, and we're virtual this year. You gotta manage your teams. You still gotta go to work every day. You gotta operate your business is a swell as work with customers. What have you guys learned? And can you share any, um, advice or observations of how to be effective as a leader, a za manager, and as a customer interface point for your companies? >>Well, I I think, uh, let me go first, then Mark Mark and had some things, you know, I think we're moving to certainly in the last year, specifically with covert. You know, we've we've we've just passed out. I think we just passed out seven months off, being remote now on, obviously doing reinvent as well. Um, it zits certainly taken some adjusting. I think we've done relatively well, um, with, you know, going virtual. We were well prepared at Amazon to go virtual, but from a leadership point of view, you know, making sure that you have been some positives, right? So for one, I have I have teams all over the world, and, uh, being virtually actually helped a lot with that. You know, everybody is virtually all on the same stage. It's not like we have a group of us in Seattle and a few others scattered around the world. Everybody's on the same cold now. on that has the same you know, be able to listen to in the same way. But I better think a lot about sort of just my own time. Personally, in the time that my team spends, I think it's been very easy for us. Thio run a little too hot waken start a little too early and run a little too late in the evenings on DSO, making sure that we protect that time. And then, obviously, from a customer point of view, you know, we found that customers are very willing to engage virtually as well around the world s Oh, that's something we've been able to utilize very well to continue to have. You know what we call our executive briefing center and do those sorts of things customer meetings on in some ways. You know, without the plane trip on either side to the other side of the world, you're able to do more of those and stay even more in contact with your customers. So it's been it's been a lot of adjustment for us. I think we've done well. I think you know, a zay said. We've had a look at Are we keeping it balanced because I think it's very easy to get out of balance and just from a time point of view. But I think I'm sure it'll show. It'll change again as the world goes back to normal. But in many ways, I think we've learned a lot of valuable lessons that I hope in some cases don't go away. I think well will probably be more virtual going forward. So that's what a bit of from my side >>creating. Yeah. Confronting hot people run hard. You can, you know, miss misfire on that and burnout gonna stay, Stay tuned. Mark your thoughts. Is leader customers defeating employees? Customers? >>Yeah. I mean, in many ways, I would say similar experience. I think, uh, I mean, if you sort of think back, right, uh, it's in many ways amazing that within the course of literally a week, right, I think about some of the BMR experience we went from, uh, you know, 90 95% of our employees, at least in the US, working in an office right to immediately all working from home. And, uh, you know, I think having the technology is available to make that possible and really? For the most part, without skipping a beat. Um, it is pretty pretty amazing, right? Um and then, you know, I think from a productivity perspective, in many ways, you know, it z increased productivity. Right? Um, they have mentioned the ability engage customers much more easily you think about in the past, you would have taken a flight to Europe to maybe meet with, you know, 5 to 10 customers and spent an entire week. And now you can do that in, you know, in the morning, right? Um, and the way we sort of engaged our teams, I think in many ways, um, sort of online, uh, can create a very, very rich experience, right? In a way to bring people together across many locations in a much more seamless way than if maybe part of the team is there in the office. And some other part of the team is trying toe connect in through resume or something else. A little bit of a fragmented experience. But if everyone's on the same platform, regardless of where you are e think we've seen some benefits from that. >>It's interesting. You see virtualization. What that did to the servers created cloud, you know. Hey, Productivity. >>You also have to be careful. You don't run those servers too hot. You >>gotta have a cooling. You got the cooling Eso I You know, this is really an interesting, you know, social, uh, equation Global phenomenon of productivity Cloud. Combined with this notion of virtual changes, the workloads, the work flows, the workplace and the workforce, right, The future work. So I think, you know, we're watching this closely. I know you guys have both had great success from the pandemic with this new pressure on the cloud, because it's a new model, a new way to do things, So we'll keep watching it. Thanks for the insight. Thanks for coming on and and enjoy the rest of reinvent. >>Great. Thank >>you. Great to be here. >>Okay, this the cubes coverage. I'm John for your host of Cuban, remember? Go to the reinvent site. Three weeks of great virtual content over this month, Of course. Cube coverage for three weeks. Stay tuned off. All the analysis and a lot of great thought leadership in the industry commentary. Stay with us throughout the month. Thank you. Yeah,

>>live from Orlando, Florida It's the cue covering Microsoft Ignite Brought to you by Cohee City. >>Welcome back, everyone to the cubes. Live coverage of Microsoft ignite here in Orlando, Florida. I'm your host, Rebecca Night, along with my co host Stew Minimum. We are joined by David Noi. He is the VP of cloud at cohesively, which is where we are. We're in the Coe City boots. So I should say thank you for welcoming us. >>My pleasure they found over here. >>So you are pretty brand new to the company. Ah, long time Tech veteran but new newish to Cohee City. Talk a little bit about what made you want to make the leap to this company. >>Well, you know, as I was, it was it was time for me to move from. My prior company will go to the reasons they're but a CZ. I looked around and kind of see who were the real innovators, right? You were the ones who were disrupting because my successes in the past have all been around disruption. And when I really looked at what these guys were doing, you know, first, it's kinda hard to figure out that I was like, Oh my gosh, this is really something different, Like it's bringing kind of the cloud into the enterprise and using that model of simplification and then adding data service is and it is really groundbreaking. So I just like, and the other thing was, I'll just throw this point out there. I read a lot of the white papers of the technology, and I looked at it and having been, you know, Tech veteran for a while, it looked to me like a lot of people who have done this stuff before we got together and said, If I had to do it again and do it right, what were things I wouldn't d'oh! And one of the things I would do, right? Right, so that was just fascinating. >>So, David, I was reading a Q and A recently with Mohit, founder of Cohee City, and it really is about that data you mentioned. Data service is, Yeah, bring us inside a little bit way in the storage and I t industry get so bogged down in the speeds and feeds and how fast you can do things in the terabytes and petabytes and like here. But we're talking about some real business issues that the product is helping to solve. >>I totally agree. Look, I've been in the in the storage industry for a while now, and you know, multi petabytes of data. And the problem that you run into when you go and talk to people who use this stuff is like old cheese. I start to lose track of it. I don't know what to do with it. So the first thing is, how do you search it? Index it? That's, you know, so I can actually find out what I have. Then there's a question of being able to go in and crack the date open and provide all kinds of data. Service is from, you know, classifications. Thio. Uh oh. Is this Ah, threat or business? Have vulnerabilities in it. It's really a data management solution. Now, of course, we started with backup, right? But then we're very quickly moving into other. Service is back on target file an object. You'll see some more things coming out around testing dead. For example, if you have the world's data is one thing to just keep it and hold it. But then what do you do with it. How do you extract value out of it? Is you really gotta add data management Service is and people try to do it. But this hyper converge technology and this more of a cloud approach is really unique in the way that it actually goes about it. >>I speak a little bit of that. That that cloud approach? >>Yeah, So I mean, you know, But he comes from a cloud background, right? He wrote was big author of the Google foul system. The idea, basically is to say, Let's take a look at a global view of how data is kept. Let's basically be ableto actually abstract that with the management layer on top of that and then let's provide service is on top of that. Oh, by the way, people now have to make a decision between am I gonna keep in on premise or keep it in the cloud? And so the data service is how to extend not just to the on Prem, but actor actually spend Thio. Pod service is as well, which is kind of why I'm here. I think you know what we do with Azure is pretty fascinating in that data management space, too. So we'll be doing more data management. Is the service in the cloud as well? >>So let's get into that a little bit. And I'm sure a lot of announcements this week with your arc and another products and service is. But let's dig into how you're partnering and the kinds of innovative things that go he see a Microsoft are doing together >>what we do. A lot of things. First of all, we weave a very rapid cadence of engineering, engineering conversations. We do everything from archiving data and sending long term retention data into the cloud. But that's kind of like where people start right, which is just ship it all up there. You know, Harvard, it's held right. But then think about doing migrations. How do you take a workload and actually migrated from on Prem to the cloud hold? We could do wholesale migrations of peoples environments. You want to go completely cloud native, weaken, fail over and fill back if we want to as well so we can use the cloud is actually a D. R site. Now you startle it. Think about disaster. Recovery is a service. That's another service that you start to think about what? About backing up cloud native workloads? Well, you don't just want to back up your work Clothes that are in the on Prem data certainly want to back him up also in the cloud. And that includes even office 3 65 So you just look at all of what you know. That means that the ability then could practice that data open and then provide all these additional when I say service is I'm talking about classifications, threat analysis, being able to go in and identify vulnerabilities and things of that nature. That's just a huge, tremendous value on top of just a basic infrastructure capabilities. >>David, you've been in the industry. You've seen a lot of what goes on out there, help us understand really what differentiates Cohee City. Because a lot of traditional vendors out there that are all saying many of the same word I hear you're Clough defying enters even newer vendors. Then go he sitio out there >>totally get it. Look, I mean, here's here's kind of what I find really interesting and attractive about the product. I've been in the storage history for a long time, so many times, people ask me, Can I move my applications to the storage? Because moving the data to the application that's hard. But moving the application to the data Wow, that makes things a lot easier, right? And so that's one of the big things that actually we do that's different. It's the hyper converged platform. It's a scale out platform. It's one that really looks a lot more like some of the skill of platforms that we've done in the past. But it goes way beyond that. And then the ability. Then say, OK, let's abstract that a ways to make it as simple as possible so people don't have to worry about managing lots of different pools and lots of different products for, you know, a service one versus service to versus service three, then bringing applications to that data. That's what makes it really different. And I think if you look around here and you talk to other vendors, I mean don't provide a P eyes. That's one thing that's great and that's important. But it actually bring the applications to the data. That's you know, that's what all of the cloud guys dont look a Google Gmail on top. They put search on top. They put Google translate on top. Is all of these things are actually built on top of the data that they store >>such? Adela This morning in the Kino talked about that there's going to be 500 million knew at business applications built by 2023. How is cohesive? E position to, you know, both partner with Microsoft and everyone out there to be ready for that cloud native >>future. That's a great question. Look, we're not gonna put 500 million applications on the product, right? But we're gonna pick some key applications that are important in the top verticals, whether it's health care, financial service is public sector and so long life sciences, oil and gas. But in the same time, we will offer the AP eyes extensions to say anything about going into azure if we can export things is as your blobs, For example, Now we can start to tie a lot of the azure service's into our storage and make it look like it's actually native as your storage. Now we can put it on as your cold storage shed, a hot storage. We can decide how we want to tear things from a performance perspective, but we can really make it look like it's native. Then we can take advantage of not just our own service is, but the service is that the cloud provides is well on. That makes us extraordinarily powerful >>in terms of the differentiator of Cohee City from a service of standpoint. But what about from a cultural standpoint we had sought Nadella on? The main stage is turning. Talking a lot about trust and I'm curious is particularly as a newer entrants into this technology industry. How how do you develop that culture and then also that reputation. So >>here's one of the interesting things when when I joined the company and I've been around for a while and I've been in a couple of very large brand names, I started walking down the holes and I'm like, Oh, here, here. Oh, you're here. Wait, you're here. It's like an old star cast, and when you go into, you know, some of the customer base and it's like, Hey, we know each other for a long time. That relationship is just there. On top of that, I mean the product works, it's solid. People love it. It's easy to use, and it actually solves riel problems for them. On Dhe, you know, we innovate extraordinarily fast. So when customers find a problem, we're on such a fast release cadence. We can fix it for them in extraordinarily, uh, in times that I've never seen before. In fact, is a little bit scary how fast the engineering group works. It's probably faster than anything I've ever seen in the past. And I think that helps that build the customers trust because they see that if we recognize there's a problem, we're gonna be there to soldier for >>them. There's trust of the company when we talk about our data. There's also the security aspect. Yes, cohesive. He fit into the A story with Microsoft and beyond. >>The security part is extraordinarily important. So look, we've already, as I said, built kind of our app marketplace and we're bringing a lot of applications to do things like Ransomware detection, um, vulnerability detection day declassification. But Microsoft is also developing similar AP eyes, and you heard this morning that they're building capabilities for us to be able to go and interact with them and share information. So we find vulnerabilities because share it with Ambika. Share with us so we could shut them down. So way have the native capabilities built in. They have capabilities that they're building of their own. Imagine the power of it being able to tie those two together. I just think that that's extraordinarily powerful. >>What about Gross? This is a company that is growing like gangbusters. Can you give us a road map? What you can expect from Coach? >>Look, I've never seen growth like this. I mean, I joined specifically to look at a lot of the cloud, and the file on Object service is and, you know, obviously have a background in backup data protection as well. I haven't seen growth like this since my old days when I was a nice guy. Started in, like, Isil on back in the, you know, way, way old days, this is This is you know, I can't give you exact numbers, but I'll tell you, it's way in the triple digits. And I mean and it's extraordinarily fast to see from an an azure perspective. We're seeing, you know, close to triple digit growth as Well, so I love it. I mean, I'm just extraordinarily excited. All right, >>on the product side, Give us a little bit of a look forward as to what we should be expecting from cohesive. >>Absolutely so from a look forward perspective. As I said, we protect a lot of on premise workloads, and now and we protect, obviously, as your work clothes as well. So we protect observe e ems. But as we think about some of the azure native service is like sequel in other service is that air kind of built native within a azure. We'll extend our application to be able to actually do that as well will extend kind of the ease of use and the deployment models to make it easier for customers to go on, deploy and manage. It really seems like a seamless single pane of glass, right? So when you're looking at Cory City, you should think of it as even if it's in the cloud or if it's on premise. It looks the same to you, which is great. If I want to do search and index, I can do it across the cloud, and I can do it across the on Prem so that integration is really what ties it together makes it extraordinarily interesting. >>Finally, this is this is not your first ignite. I'm interested to hear your impressions of this conference, what you're hearing from customers. What your conversations that you're having. >>You know, it's a lot of fun. I've been walking around the partner booths over here to see, like, you know, who could we partner with? That's more of those data management service is because we don't think of ourselves again. You know, we started kind of in the backup space. We have an extraordinarily scalable storage infrastructure. I was blown away by the capabilities of the file. An object. I mean, I was as a foul guy for a long time. It was unbelievable. But when you start to add those data management capabilities on top of that so that people could either, you know, again, either your point, make sure that they can detect threats and vulnerabilities are you find what they're looking for or be able to run analytics, for example, right on the box. I mean, I've been asked to do that for so long, and it's finally happening. It's like It's a dream >>come true, Jerry. Now >>everything you ever wanted software defined bringing the applications to the data. It's just like, if I could ever say like, Hey, if I could take all of the things that I always wanted a previous companies that put him together it's cohesive. I'm looking around here and I'm seeing a lot of great technology that we can go and integrate with >>Great. Well, David, No, I Thank you so much for coming on the Cube. >>Thank you very much. I appreciate it. >>I'm Rebecca Knight, First Amendment. You are watching the Cube.

>> 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)

>> Live from the MIT campus in Cambridge, Massachusetts, it's theCUBE, covering the 12th Annual MIT Chief Data Officer and Information Quality Symposium. Brought to you by SiliconANGLE Media. >> Welcome back to theCUBE's coverage of MIT CDOIQ here in Cambridge, Massachusetts. I'm your host Rebecca Knight along with my cohost Peter Burris. We have two guests on this segment. We have Cortnie Abercrombie, she is the founder of the nonprofit AI Truth, and Carl Gerber, who is the managing partner at Global Data Analytics Leaders. Thanks so much for coming on theCUBE Cortnie and Carl. >> Thank you. >> Thank you. >> So I want to start by just having you introduce yourselves to our viewers, what you do. So tell us a little bit about AI Truth, Cortnie. >> So this was born out of a passion. As I, the last gig I had at IBM, everybody knows me for chief data officer and what I did with that, but the more recent role that I had was developing custom offerings for Fortune 500 in the AI solutions area, so as I would go meet and see different clients, and talk with them and start to look at different processes for how you implement AI solutions, it became very clear that not everybody is attuned, just because they're the ones funding the project or even initiating the purpose of the project, the business leaders don't necessarily know how these things work or run or what can go wrong with them. And on the flip side of that, we have very ambitious up-and-comer-type data scientists who are just trying to fulfill the mission, you know, the talent at hand, and they get really swept up in it. To the point where you can even see that data's getting bartered back and forth with any real governance over it or policies in place to say, "Hey, is that right? Should we have gotten that kind of information?" Which leads us into things like the creepy factor. Like, you know target (laughs) and some of these cases that are well-known. And so, as I saw some of these mistakes happening that were costing brand reputation, our return on investment, or possibly even creating opportunities for risk for the companies and for the business leaders, I felt like someone's got to take one for the team here and go out and start educating people on how this stuff actually works, what the issues can be and how to prevent those issues, and then also what do you do when things do go wrong, how do you fix it? So that's the mission of AI Truth and I have a book. Yes, power to the people, but you know really my main concern was concerned individuals, because I think we've all been affected when we've sent and email and all of a sudden we get a weird ad, and we're like, "Hey, what, they should not, is somebody reading my email?" You know, and we feel this, just, offense-- >> And the answer is yes. >> Yes, and they are, they are. So I mean, we, but we need to know because the only way we can empower ourselves to do something is to actually know how it works. So, that's what my missions is to try and do. So, for the concerned individuals out there, I am writing a book to kind of encapsulate all the experiences that I had so people know where to look and what they can actually do, because you'll be less fearful if you know, "Hey, I can download DuckDuckGo for my browser, or my search engine I mean, and Epic for my browser, and some private, you know, private offerings instead of the typical free offerings. There's not an answer for Facebook yet though. >> So, (laughs) we'll get there. Carl, tell us a little bit about Global Data Analytics Leaders. >> So, I launched Analytics Leaders and CDO Coach after a long career in corporate America. I started building an executive information system when I was in the military for a four-star commander, and I've really done a lot in data analytics throughout my career. Most recently, starting a CDO function at two large multinational companies in leading global transformation programs. And, what I've experienced is even though the industries may vary a little bit, the challenges are the same and the patterns of behavior are the same, both the good and bad behavior, bad habits around the data. And, through the course of my career, I've developed these frameworks and playbooks and just ways to get a repeatable outcome and bring these new technologies like machine learning to bear to really overcome the challenges that I've seen. And what I've seen is a lot of the current thinking is we're solving these data management problems manually. You know, we all hear the complaints about the people who are analysts and data scientists spending 70, 80% of their time being a data gatherer and not really generating insight from the data itself and making it actionable. Well, that's why we have computer systems, right? But that large-scale technology in automation hasn't really served us well, because we think in silos, right? We fund these projects based on departments and divisions. We acquire companies through mergers and acquisitions. And the CDO role has emerged because we need to think about this, all the data that an enterprise uses, horizontally. And with that, I bring a high degree of automation, things like machine learning, to solve those problems. So, I'm now bottling that and advising my clients. And at the same time, the CDO role is where the CIO role was 20 years ago. We're really in it's infancy, and so you see companies define it differently, have different expectations. People are filling the roles that may have not done this before, and so I provide the coaching services there. It's like a professional golfer who has a swing coach. So I come in and I help the data executives with upping their game. >> Well, it's interesting, I actually said the CIO role 40 years ago. But, here's why. If we look back in the 1970s, hardcore financial systems were made possible by the technology which allowed us to run businesses like a portfolio: Jack Welch, the GE model. That was not possible if you didn't have a common asset management system, if you didn't have a common cached management system, etc. And so, when we started creating those common systems, we needed someone that could describe how that shared asset was going to be used within the organization. And we went from the DP manager in HR, the DP manager within finance, to the CIO. And in many respects, we're doing the same thing, right? We're talking about data in a lot of different places and now the business is saying, "We can bring this data together in new and interesting ways into more a shared asset, and we need someone that can help administer that process, and you know, navigate between different groups and different needs and whatnot." Is that kind of what you guys are seeing? >> Oh yeah. >> Yeah. >> Well you know once I get to talking (laughs). For me, I can going right back to the newer technologies like AI and IOT that are coming from externally into your organization, and then also the fact that we're seeing bartering at an unprec... of data at an unprecedented level before. And yet, what the chief data officer role originally did was look at data internally, and structured data mostly. But now, we're asking them to step out of their comfort zone and start looking at all these unknown, niche data broker firms that may or may not be ethical in how they're... I mean, I... look I tell people, "If you hear the word scrape, you run." No scraping, we don't want scraped data, no, no, no (laugh). But I mean, but that's what we're talking about-- >> Well, what do you mean by scraped data, 'cause that's important? >> Well, this is a well-known data science practice. And it's not that... nobody's being malicious here, nobody's trying to have a malintent, but I think it's just data scientists are just scruffy, they roll up their sleeves and they get data however they can. And so, the practice emerged. Look, they're built off of open-source software and everything's free, right, for them, for the most part? So they just start reading in screens and things that are available that you could see, they can optical character read it in, or they can do it however without having to have a subscription to any of that data, without having to have permission to any of that data. It's, "I can see it, so it's mine." But you know, that doesn't work in candy stores. We can't just go, or jewelry stores in my case, I mean, you can't just say, "I like that diamond earring, or whatever, I'm just going to take it because I can see it." (laughs) So, I mean, yeah we got to... that's scraping though. >> And the implications of that are suddenly now you've got a great new business initiative and somebody finds out that you used their private data in that initiative, and now they've got a claim on that asset. >> Right. And this is where things start to get super hairy, and you just want to make sure that you're being on the up-and-up with your data practices and you data ethics, because, in my opinion, 90% of what's gone wrong in AI or the fear factor of AI is that your privacy's getting violated and then you're labeled with data that you may or may not know even exists half the time. I mean. >> So, what's the answer? I mean as you were talking about these data scientists are scrappy, scruffy, roll-up-your-sleeves kind of people, and they are coming up with new ideas, new innovations that sometimes are good-- >> Oh yes, they are. >> So what, so what is the answer? Is this this code of ethics? Is it a... sort of similar to a Hippocratic Oath? I mean how would you, what do you think? >> So, it's a multidimensional problem. Cortnie and I were talking earlier that you have to have more transparency into the models you're creating, and that means a significant validation process. And that's where the chief data officer partners with folks in risk and other areas and the data science team around getting more transparency and visibility into what's the data that's feeding into it? Is it really the authoritative data of the company? And as Cortnie points out, do we even have the rights to that data that's feeding our models? And so, by bringing that transparency and a little more validation before you actually start making key, bet-the-business decisions on the outcomes of these models, you need to look at how you're vetting them. >> And the vetting process is part technology, part culture, part process, it goes back to that people process technology trying. >> Yeah, absolutely, know where your data came from. Why are you doing this model? What are you doing to do with the outcomes? Are you actually going to do something with it or are you going to ignore it? Under what conditions will you empower a decision-maker to use the information that is the output of the model? A lot of these things, you have to think through when you want to operationalize it. It's not just, "I'm going to go get a bunch of data wherever I can, I put a model together. Here, don't you like the results?" >> But this is Silicon Valley way, right? An MVP for everything and you just let it run until... you can't. >> That's a great point Cortnie (laughs) I've always believed, and I want to test this with you, we talk about people process technology about information, we never talk about people process technology and information of information. There's a manner of respects what we're talking about is making explicit the information about... information, the metadata, and how we manage that and how we treat that, and how we defuse that, and how we turn that, the metadata itself, into models to try to govern and guide utilization of this. That's especially important in AI world, isn't it? >> I start with this. For me, it's simple, I mean, but everything he said was true. But, I try to keep it to this: it's about free will. If I said you can do that with my data, to me it's always my data. I don't care if it's on Facebook, I don't care where it is and I don't care if it's free or not, it's still my data. Even if it's X23andMe, or 23andMe, sorry, and they've taken the swab, or whether it's Facebook or I did a google search, I don't care, it's still my data. So if you ask me if it's okay to do a certain type of thing, then maybe I will consent to that. But I should at least be given an option. And no, be given the transparency. So it's all about free will. So in my mind, as long as you're always providing some sort of free will (laughs), the ability for me to having a decision to say, "Yes, I want to participate in that," or, "Yes, you can label me as whatever label I'm getting, Trump or a pro-Hillary or Obam-whatever, name whatever issue of the day is," then I'm okay with that as long as I get a choice. >> Let's go back to it, I want to build on that if I can, because, and then I want to ask you a question about it Carl, the issue of free will presupposes that both sides know exactly what's going into the data. So for example, if I have a medical procedure, I can sit down on that form and I can say, "Whatever happens is my responsibility." But if bad things happen because of malfeasance, guess what? That piece of paper's worthless and I can sue. Because the doctor and the medical provider is supposed to know more about what's going on than I do. >> Right. >> Does the same thing exist? You talked earlier about governance and some of the culture imperatives and transparency, doesn't that same thing exist? And I'm going to ask you a question: is that part of your nonprofit is to try to raise the bar for everybody? But doesn't that same notion exist, that at the end of the day, you don't... You do have information asymmetries, both sides don't know how the data's being used because of the nature of data? >> Right. That's why you're seeing the emergence of all these data privacy laws. And so what I'm advising executives and the board and my clients is we need to step back and think bigger about this. We need to think about as not just GDPR, the European scope, it's global data privacy. And if we look at the motivation, why are we doing this? Are we doing it just because we have to be regulatory-compliant 'cause there's a law in the books, or should we reframe it and say, "This is really about the user experience, the customer experience." This is a touchpoint that my customers have with my company. How transparent should I be with what data I have about you, how I'm using it, how I'm sharing it, and is there a way that I can turn this into a positive instead of it's just, "I'm doing this because I have to for regulatory-compliance." And so, I believe if you really examine the motivation and look at it from more of the carrot and less of the stick, you're going to find that you're more motivated to do it, you're going to be more transparent with your customers, and you're going to share, and you're ultimately going to protect that data more closely because you want to build that trust with your customers. And then lastly, let's face it, this is the data we want to analyze, right? This is the authenticated data we want to give to the data scientists, so I just flip that whole thing on its head. We do for these reasons and we increase the transparency and trust. >> So Cortnie, let me bring it back to you. >> Okay. >> That presupposes, again, an up-leveling of knowledge about data privacy not just for the executive but also for the consumer. How are you going to do that? >> Personally, I'm going to come back to free will again, and I'm also going to add: harm impacts. We need to start thinking impact assessments instead of governance, quite frankly. We need to start looking at if I, you know, start using a FICO score as a proxy for another piece of information, like a crime record in a certain district of whatever, as a way to understand how responsible you are and whether or not your car is going to get broken into, and now you have to pay more. Well, you're... if you always use a FICO score, for example, as a proxy for responsibility which, let's face it, once a data scientist latches onto something, they share it with everybody 'cause that's how they are, right? They love that and I love that about them, quite frankly. But, what I don't like is it propagates, and then before you know it, the people who are of lesser financial means, it's getting propagated because now they're going to be... Every AI pricing model is going to use FICO score as a-- >> And they're priced out of the market. >> And they're priced out of the market and how is that fair? And there's a whole group, I think you know about the Fairness Accountability Transparency group that, you know, kind of watch dogs this stuff. But I think business leaders as a whole don't really think through to that level like, "If I do this, then this this and this could incur--" >> So what would be the one thing you could say if, corporate America's listening. >> Let's do impact. Let's do impact assessments. If you're going to cost someone their livelihood, or you're going to cost them thousands of dollars, then let's put more scrutiny, let's put more government validation. To your point, let's put some... 'cause not everything needs the nth level. Like, if I present you with a blue sweater instead of a red sweater on google or whatever, (laughs) You know, that's not going to harm you. But it will harm you if I give you a teacher assessment that's based on something that you have no control over, and now you're fired because you've been laid off 'cause your rating was bad. >> This is a great conversation. Let me... Let me add something different, 'cause... Or say it a different way, and tell me if you agree. In many respects, it's: Does this practice increase inclusion or does this practice decrease inclusion? This is not some goofy, social thing, this is: Are you making your market bigger or are you making your market smaller? Because the last thing you want is that the participation by people ends with: You can't play because of some algorithmic response we had. So maybe the question of inclusion becomes a key issue. Would you agree with that? >> I do agree with it, and I still think there's levels even to inclusion. >> Of course. >> Like, you know, being a part of the blue sweater club versus the (laughs) versus, "I don't want to be a convict," you know, suddenly because of some record you found, or association with someone else. And let's just face it, a lot of these algorithmic models do do these kinds of things where they... They use n+1, you know, a lot... you know what I'm saying. And so you're associated naturally with the next person closest to you, and that's not always the right thing to do, right? So, in some ways, and so I'm positing just little bit of a new idea here, you're creating some policies, whether you're being, and we were just talking about this, but whether you're being implicit about them or explicit, more likely you're being implicit because you're just you're summarily deciding. Well, okay, I have just decided in the credit score example, that if you don't have a good credit threshold... But where in your policies and your corporate policy did it ever say that people of lesser financial means should be excluded from being able to have good car insurance for... 'cause now, the same goes with like Facebook. Some people feel like they're going to have to opt of of life, I mean, if they don't-- >> (laughs) Opt out of life. >> I mean like, seriously, when you think about grandparents who are excluded, you know, out in whatever Timbuktu place they live, and all their families are somewhere else, and the only way that they get to see is, you know, on Facebook. >> Go back to the issue you raised earlier about "Somebody read my email," I can tell you, as a person with a couple of more elderly grandparents, they inadvertently shared some information with me on Facebook about a health condition that they had. You know how grotesque the response of Facebook was to that? And, it affected me to because they had my name in it. They didn't know any better. >> Sometimes there's a stigma. Sometimes things become a stigma as well. There's an emotional response. When I put the article out about why I left IBM to start this new AI Truth nonprofit, the responses I got back that were so immediate were emotional responses about how this stuff affects people. That they're scared of what this means. Can people come after my kids or my grandkids? And if you think about how genetic information can get used, you're not just hosing yourself. I mean, breast cancer genes, I believe, aren't they, like... They run through families, so, I-- >> And they're pretty well-understood. >> If someone swabs my, and uses it and swaps it with other data, you know, people, all of a sudden, not just me is affected, but my whole entire lineage, I mean... It's hard to think of that, but... it's true (laughs). >> These are real life and death... these are-- >> Not just today, but for the future. And in many respects, it's that notion of inclusion... Going back to it, now I'm making something up, but not entirely, but going back to some of the stuff that you were talking about, Carl, the decisions we make about data today, we want to ensure that we know that there's value in the options for how we use that data in the future. So, the issue of inclusion is not just about people, but it's also about other activities, or other things that we might be able to do with data because of the nature of data. I think we always have to have an options approach to thinking about... as we make data decisions. Would you agree with that? Yes, because you know, data's not absolute. So, you can measure something and you can look at the data quality, you can look at the inputs to a model, whatever, but you still have to have that human element of, "Are you we doing the right thing?" You know, the data should guide us in our decisions, but I don't think it's ever an absolute. It's a range of options, and we chose this options for this reason. >> Right, so are we doing the right thing and do no harm too? Carl, Cortnie, we could talk all day, this has been a really fun conversation. >> Oh yeah, and we have. (laughter) >> But we're out of time. I'm Rebecca Knight for Peter Burris, we will have more from MIT CDOIQ in just a little bit. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. We go out to the events, and we extract the signal from the noise. We're here at Knowledge18, ServiceNow's big customer event. 18,000 ServiceNow practitioners and partners and constituents here. As I say, this is day three. This is our sixth year at Knowledge. Jeff Frick and I are co-hosting. When we started in 2013 early on, we saw this ecosystem grow, and one of the first CIOs we had on from the ServiceNow customer base was Link Alander, who is here. He's the Vice Chancellor of College Services at Lone Star College. Link, always a pleasure. Great to see you again. Thanks for coming back on. >> It's always great to get back and talk with you, see what's happening in the industry, and follow you. But, once again, great conference. >> It really is, I mean, wow. Last year was huge. The growth keeps coming. We said that Dan Rogers, the CMO, K18, 18,000. How ironic. >> Yeah, wow, let's see, your first was six years ago, right? >> Dave: Yep, it was 2013. So my first would have been New Orleans, which had been I think 2012, 2011. >> Right, right, the year before we met 'em. >> Three to four thousand in this conference. Actually, that might be the high count. >> Yeah, I mean, it's quite amazing. And the ecosystem has exploded. What's your take on how, not only ServiceNow and the ecosystem have grown, but how it's affected your business? >> Let's start with the, yeah, yeah, yeah. Let's start with the ecosystem part because, really, you've got so many more partners out there now. You've got so many more integration points. What was really exciting as we saw this morning with Pat, and some of the enhancements they're doing on the DevOps side, but also what we're going to see with the ability to integrate our cloud linkage, which is really the challenge for everybody as a practitioner today. How do you bring all these cloud services? I've got quite a few of them in my environment. How do I actually integrate those in with my ServiceNow, with my ERP, with all of the other instances? So, seeing what they're doing in that space is great. From the business standpoint, when we came onto ServiceNow, we came on like everybody else, a journey for IT service management. Can we improve our services? Can we help our customers out? In our case, that'd be our faculty and staff. What we didn't realize was the opportunity that came to us with the platform. And one of the first things we did when we brought the platform back to us was we built an app for students. We built a way to help students out with their student financial aid. Now I've got, I think we're roughly at about nine of our areas that are using Enterprise Service Management. I just came back from giving a presentation about legal, and what we've done in the legal space to where that's helped the organization to move forward faster. So that's really cool in what it does, but it also elevates the position of IT in the organization. It really does bring us forward. >> Yeah so, let's talk a little about Lone Star College, 'cause I love your model, you know, and we can both relate. Kids in college, and, you know, the cost of education, the ROI, which I think is a big focus of what you guys provide for your students, so how's that going? How's the model working? >> Well the model's working great. And you know, you hear the pressures out there, 'cause one of the first thing is, how do you help a student complete. So, we're really very focused on student completion, but then now, you've got another focus that, well, it's been there, but it's really getting stronger, on gainful employment. So not only that, how do you get a student in college, how do they complete on time, but then how do they come out and have a livable wage, an earnable wage? And so I'll give a plug on that always because that's what we're focused on. Whether you're just coming to us to transfer to another institution or whether you're coming in the workforce. And we have a very strong workforce development, and one of the things I got out of this conference that I've been working on for quite awhile was for us to become a ServiceNow train, to get that integrated into our curriculum. And I was really excited. We've talked to them before about this, and it's been a discussion, but now what we're looking at is a program that they put in France where they have a six week program that if people are going out of there, coming in, six weeks later, job retrained, 100% placement. A year later, they have 98% retention, and those 2% just went to another company. So I can't think of a better opportunity for us from our standpoints in our workforce development. And I'm really excited we're going to be starting to move that forward now. >> It's interesting to hear John Donahoe on Tuesday talk about their measurement of customer success. And we were asking him on theCUBE, well, your customers measure success in a lot of different ways, so how do you take that input? Your measurement of success is student success, as you just have indicated. >> Absolutely, absolutely. You know, my focus has always been is IT is just a support operation. We're not the mission of the college. And that's important. Because as long as we have that mindset, we realize that it's us helping the faculty to less stress on their life, or the staff, then we've improved their experience, which will improve the student experience. The same goes for the administrative systems. We want administrative systems to have a user interface that's intuitive to today's student. It wasn't designed by a person that was intuitive to today's student. So we have that challenge, and that's what I liked about the change this year and the user interface in ServiceNow and where they're going with UI and UX, and how much of an enhancement that makes for our customers. But it's also, that's the changes that are happening in industry right now. Coach K was at the CIO Decisions, and he was talking about he's headed to go through all this process, and 50 forward years of difference, and he's recruiting 18-year-olds, and he's sending emojis to them, his recruits. But like, yeah, because you have to relate to it. So, we started a process, and this is where coming to a conference like this helps me a lot, because it's like, yeah, I went down the right path. But my team came to me, and I've got a phenomenal team. They came to me and said, you know what, we really need to look at UI, UX, and design thinking. And I'm like, okay. Now let's discuss what we really want to do with this. One group was wanting design thinking to think about analytics. What does the customer need? How do they want to see this data come to them? And how can they make data-informed decisions? Well, we have then rolled that same design thinking into, how do we roll out the fluid technologies in our ERP? How do we become more of a user interface that today's student wants, to what we're trying to do next in mobile? >> That's a really interesting take, because we talk often about millennials entering the workforce, right? And consumerization of IT and expectations. But they're usually a pretty small and growing percentage of the workforce at a particular company. For you, it's like 90% of your customer base, right? And they're on the bleeding edge. They're coming in there 18, 17 years old. So you got to be way out front on this customer experience. So have you really taken that opportunity to redesign that UI, UX, and interface to the applications? That must be a giant priority. >> We've done a lot of incremental items, but really it's been a huge priority for us for the last, we have two really cool items coming down the path. One is the UI UX experience. How do we transform the student experience? The next is a process that our academic success side, the student services side have gone down, with guided pathways. Okay, you and I went to college. What did we do? We saw an advisor every single time we registered. Then we up to the thing, and we filled in a bubble sheet, right? >> Right, right. >> Well right now, the students are registering on a mobile phone while they're sitting down at a Starbucks. They're not seeing an advisor. We want them to see an advisor. So we push them those directions, but this guided pathway says, you know what, I want to do this degree. Then we just line out, here's the classes you're going to take, and whether we use program enrollment, whatever methodology, we can help guide them in their pathway to success and completion, which is a big difference. And that's what needs to happen today. >> Right, well it's interesting, I always like to talk about banking, right? 'Cause banking, you used to go see the banker, go into the teller, and, you know, deposit your check and get your cash. And now most people's experience with their bank is via electronic, whether it's online, on their phone, or their app. You have kind of the dichotomy, 'cause they still have their interaction with the teachers. So there's still a very people element, but I would imagine more and more and more of that administrative execution, as you just described, is now moving to the mobile platform. That's the way they interact with the administration of the school. >> Well, that's their expectation. So, that's what we have to deliver, and it's a challenge because we have resources, we have limitations in resources or capabilities, but it's really keeping that focus going to where you look at it. So as we're doing this UI UX right now, one of our major goals is going to be to bring students in the engagement as we go through the design process, and get their feedback. Not computer science people, not IT people. We want the normal student that's going to go register for a class. And since what you have is such a large transient population, you know, two years, they're in, they're done. 100,000 per semester. 160,000 unique each year. You've got to create that rich experience, but the engagement, the bonding to the institution. And I like the bank for an example because not too long ago I switched banks because I didn't like their app. >> Dave: Absolutely. >> And it's easy to do, it's real easy to do. >> Airlines, you appreciate the good apps. >> Link: Yeah, yeah, absolutely. >> How does ServiceNow contribute to that user experience, that, your customer experience? >> Well right now from the student side, they don't see much of ServiceNow. They can submit requests, and we can handle their incidents, and those types of items. They have certain things. We have the student financial aid. But it really is about the Enterprise Service Management philosophy. I think if you go back to one of theCUBEs, maybe two or three years ago, I said, "Who would have ever thought they would come to IT to talk about service delivery?" Okay? Now, everybody at Enterprise is like, okay, how do you do this? How do you not let things fall through the crack? So that the legal app was a great one, because that was a challenge that our general council or our COO had when he came in. Everything was falling through the crack. So they worked through their workflows. They built a process. And then they built, we built an app for them in ServiceNow that handles everything. Now when I'm in a cabinet meeting, I get to hear about how legal's doing so great. I'm like, what about me? I think we're still doing a good job. (laughing) >> Well, Link, I'm curious too on, kind of the big theme has always been at this show kind of low code, no code developing, right? Enable people that aren't native coders to build apps, to build workflows. How has that evolved over time within your organization? >> Well, we still want to make sure when we're putting out code. What it's enabled for us is, of course, our developers, it makes it easier to get to time to completion of a project. But we still want to make sure that whatever's built is production ready. You know, so we're not opening up the tool case to everybody. (laughing) But, sad to say, I actually still go in, and I'll build my dashboards, and I'll build my interaction, and I use my performance analytics, which does enable people. And we're seeing that in some of our heavier Enterprise Service Management side, but as far as letting them dive into the no code environment, I still have to put some protection on us. And like any organization, we always have to think of IT security. That's the other piece of it. What are they putting out there? What could be a violation of privacy? How do we handle that? >> Jeff: Right. >> So, we stay completely engaged, but the speed to deliver is what the change is. Our legal app was a three month development project. Three months to go from a, they had a separate system. And to go through the process, redesign it, build it, and put it in production. Three months. >> Three months? >> How many people, roughly? How many people did it take to get there? >> Well, we use a development partner that used three, and then I had two at the time on my own. I still have only three individuals that actually handle our, that are primary to ServiceNow in my organization, as large as our installation base is. >> Really? And that includes the permeation of ServiceNow into the rest of the organization, or? >> Link: Yes. >> Dave: Really? >> 'Cause I added, and before that, if it has been last year, it was one and a half. >> Dave: Wow. >> That's what I had then. And technically, I probably have only two and a half because one person has another job, which is running our call center. >> So what are you using now? You got obviously ITSM, what else is in there? >> ITSM, ITBM, we got a great presentation we gave earlier on project portfolio management, and what we've done with that. And where we're going next. Business operations. We're actually launching this summer, if everything goes right. This is more of an internal, us doing it, but what I've been doing is I've been taking our contract management piece, utilization, incidents request change, and project. Now I'm going to roll it in and then do analytics against it to come back with what is the total cost per service per month per individual. On every license contract I hold. >> It's funny, the contract management software licensing management piece is a huge untapped area that we hear over and over and over again. >> So, two years ago we talked a lot about security. I think ServiceNow just at that point had announced its intentions to get into that business. What do you make of their whole SecOps modules, and is it something you've looked at? State of security, any comments? >> Well this is one of those situations I think we're just a little bit too far ahead of them again. 'Cause we actually had built a modular ourself that handled what we needed. In my environment, I've got an ISO, but I also have the partners that support us. My SOC is operated by a third party. So they feed in the alerts. We ingest the alerts into the security module, and then we take action from there. So basically, they were about, a little bit behind us. And we had just looked at the model saying we need a better way to manage that event. >> So you got that covered. Yeah, I want to ask you, you know, a couple years ago we, when the big data meme was hitting, we were, of course, asking you all these data questions. Now the big theme is AI, and in some regards it's like, same wine, new bottle. But it's different. What's your thoughts on machine intelligence? Obviously ServiceNow talking about it a lot. How applicable is it to you? >> Okay, so. (laughing) >> You know why, that's good. I had to ask. >> Augmented intelligence. Let's just not make it artificial, okay? 'Cause I, when Fred had that conversation during the fireside and he said, you know, a computer takes 10,000 images to know what a cat is. And of course, the computer's a mundane object that can look at 10,000 images to determine that's a cat. You showed me the other ones earlier today, I about rolled over laughing. >> It's allowed on the blueberry, check it out. >> You know, augmented intelligence is going to be a driver. There's no question about it. What we saw on the interface about it abled to, as the machine learning goes through the process, it's picking up the information, and it's helping the agent to get to the resolution faster, that's great. Knowledge bases that are integrated in with that. Can you think about how much quicker it would be for somebody like myself who's going to go to a chatbot, and I'm going to run through a chatbot in automated intelligence and do that type of work. So that's going to make a significant difference. One of the areas we think they will be dramatic, for especially this generation, the millennials coming into the school, will be to put that augmented intelligence in, in that process. Because, trying to explain to a student, you know, yeah, you go to the registrar's office to take care of this, and you go to the bursar's office to take, they have no clue what those mean. Well, if we can take it to their language, but then also add in augmented intelligence to guide them through those navigation points. So augmented intelligence over the next years, it's taking that big data now, it's actually put into use, all that machine learning, and making something happen out of it. >> You know, digital is one of those things where I actually think the customers led the vendor community. So often in the IT business, and the technology business in general, a lot of vendor hype, whether it's hyper converged or software to fund, they kind of jam it down our throats, and then sort of get it adopted. I almost feel like, you've been doing digital for awhile now because your student force has sent you in that direction. And I feel like the vendor community is now catching up, but is that a right perception? I mean that, the digital is certainly real, and then you guys are leaning in in a big way. >> I think between the three of us we could probably come up with all the different hype words that have been used, and probably fill this room with every one of those words, right? But the reality is, as practitioners, you're looking at what is your customer base, what do you need to be able to deal with. So, we've been into digital transformation, absolutely. Is it a good definition? Was cloud a good definition? I mean, what am I really? It's either I'm going to use software as a surface, a platform as a sur, I have a gigantic private cloud. Okay, that's great. We're talking about high availability and scalability. But when you put all those in, we've been in a digital transformation everywhere. Your banks did it, that's why you have a bank app. Airplanes did it because, you know, what was that ticketing system they used to use? >> Dave: Yeah, Sabre. >> Sabre, that's what it was, oh yeah. It's probably still out there somewhere. But the reality is, is that, if you're not transforming digitally, you're going to get left behind. And even some big IT companies, and I'm sure we got a list of those bit IT companies also, that have fallen off the face of the earth, or are struggling to stay on because they didn't go through that digital transformation. They tried to do the same thing the same way and move forward. You can't do that. >> You know, you just reminded me. I just got a, hey, it's been awhile since I goofed on Nick Carr, but you remember, as a CIO, Does IT Matter? Right, in the early 2000s, that book. I mean, IT matters more than ever, right? I mean, Nick Carr obviously very accomplished, but missed it by a mile. >> Well, it's funny 'cause then IT was a support organization. Now that IT is an integrated piece in the way that everything just happens, right? It's not keeping the lights on and support so much anymore. >> I can't remember who brought that up in the keynote. Talking about the fact that, basically, we permeate the organization, okay? 'Cause there's not a function that they're doing that doesn't have some type of IT. And the question is are you sewing it together correctly. Because in the end, what are they going to want? Well, you want a seamless student experience. You want a seamless employee experience. Nobody's perfect, everything needs improvement. I'll always say that. But then at the same time is, you want that data to be all tied together so you can take advantage of big data. You can take advantage of machine learning. And then you can come back and report on it. You know, what we've done, so I guess three years ago is when I took over. I was put in charge of our analytics team. And our focus was unlocking the data so that people could have access and make decisions that are informed. You know, it's not data driven. We need to see the data, look at it, and come forward from there. So things like what ServiceNow did in performance analytics. Our general council highlighted the performance analytics as soon as we, we missed it, as he said. We put it in the first app, we didn't do it. We needed to add it. So we added it in. And he's like, wow, what I always thought was one thing. But now that I'm seeing the data, and I'm seeing the patterns, it's totally different. Because we have assumptions just 'cause we think we're busy. Performance analytics is letting him see exactly what's happening in his organization. >> Let me ask you a question. If somebody on your staff, let's say somebody that you mentored, came up to you and said, "Listen, Link, I really want to be a CIO. I mean, it's my aspiration. What advice would you give me?" >> Well, it's kind of hard when you ask this one, because I've mentored and then partnered, I wouldn't even call it mentored anymore, a great friend of mine, and he's now a CIO at Spellman in Georgia, yeah. In fact I was just chatting with him earlier because I saw something, I was like, hey, you need to check this out. It'll solve your problem. You know, it's a simple key fact. If you want to be in IT, you've got to be agile. You really have to be agile. You can't be rigid. You can't close those doors and keep your focus, and you have to constantly learn. If you don't just constantly learn, then you fall off. And that's something, when we talk about digital transformation and these companies that haven't made the transformation, that aren't here anymore, they stopped learning. They thought they had it. It's the companies that have actually continued to learn, or the CIOs or people coming up the ranks that look at it. And they look at things differently. It really is. The digital transformation is about keeping the CIO transformed, and every one of the staff. Had a discussion not too long ago with one CIO about how does he energize his staff. He's trying to do a transformation, but his staff is entrenched in the old way we did things. And, you know, sometimes you just have to shake things and get 'em excited about this piece of it. And a lot of times, if you're especially in a college, I have the luck of bringing a student in. What was your experience with that application? What did you think about it? They think it's the greatest thing they've ever created. But when you get it in front of a student, it can be something totally different. So, the biggest one right there, you got to have agility, you got to constantly learn, and you really, you know I might have a laser focus about things, I have a very agile planning model I use, but at the same time is I try to keep the door open to any possibilities. >> Well, Link, you're a great leader, and a friend of theCUBE. Can't thank you enough for making some time out of your busy schedule to come back on. Great to see you again. >> Jeff: Good seeing ya. >> It was great seeing you again, as always. As always. >> Alright, keep it right here, everybody. We'll be back with our next guest. We're live from Las Vegas, ServiceNow Knowledge18. You're watching theCUBE. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back everyone to theCUBE's live coverage of ServiceNow Knowledge18, I'm your host Rebecca Knight along with my cohost Dave Vellante. We're joined by Chris Bedi, he is the CIO of ServiceNow. Thanks so much for coming on the show Chris. >> Thanks for having me. >> So, we're hearing so much about improving employee experience and this is the goal, your goal, and also the collective goal of CIO, so can you tell us a little bit about why this, and how do you see your role in this? >> Yeah for sure, I mean if I rewind three or four years I don't think experience was really on anybody's agenda, or not high on the list. I think, you know, what we've come to realize or I've come to realize is that experience is critical to actually getting the right behavioral and economic outcomes. It is not optional anymore because with the amount of transformation that we're driving through technology it's changing processes, changing the way customers interact with us, suppliers interact with us, and that change needs to be easy. And not just easy for easy sake, but otherwise we don't get the business outcomes we are looking for. So, for me it's very purpose driven to say that for us to get those economic outcomes we have to focus on experience. >> I feel like the CIO role is evolving, and we've talked about this before, I'd love your thoughts on it. You know, it kind of used to be, alright we're going to keep the lights on, granted that's still part of the role but it's table stakes. >> It doesn't go away. (Rebecca laughs) But yes, still part of the role. >> You know, we can outsource our email, you know, what are we going to do with the cloud, okay. That's shifting, you know, with the digital economy, machine intelligence, the economy booming, this war on talent especially in Silicone Valley. Things are changing, how do you see the role changing and where do you see it evolving to? >> Well, I think the CIO role is changing. It's driven really by what's going on in every industry. If you think about it, everything, how fast your company operates, how efficient your processes are, how engaged your employees are via employee experiences, the mode in which you're able to interact with your customers, how digital your supply chain is, everything is powered by technology platforms and CIO's are the ones governing and managing and those technology platforms to deliver those outcomes, and I think it's only going to increase where technology has a bigger and bigger impact and I think that is really driving a shift in the CIO role where CIO's need to be front and center. There is no more, here's the business strategy, here's the technology strategy. They are one and the same thing and I think in our consumer lives we talk about the digital divides or the have's and have nots. I think the same thing is going to play out in enterprises where those enterprises that can figure out how to harness these newer technologies to drive meaningful business outcomes are going to start to separate themselves from the competition and that separation's only going to get bigger with time. So I think there's a tremendous amount of urgency on this topic as well. I was reading a recent article which talked about CEO's priorities for IT and saying favoring speed over cost, and I don't think that's because all of a sudden we're going to become frivolous with our spending. But I think again it just speaks to the urgency and the need for businesses to transform and it's now. >> It's not just harnessing the technologies, it's also harnessing the employee behaviors that need to change in order to create these cultural shifts that you're talking about, right, or? >> Yeah, for sure, and I would say and we had our CIO Decisions yesterday, one of the key topics was, you know, driving cultural transformation and I find that's a lot of what I'm doing and that involves a lot of selling, quite frankly. I mean, I don't have sales in my title, but by the very definition of it we're saying this technology has the promise to unlock a new business model, unlock a new process. Get to that next level of efficiency or productivity. But, you're selling a vision, right, and that means change, and people don't like change. As long as someone else is changing they're fine with it, once it's themselves, so we have to focus a lot and really double down on transformation efforts and play a key role in that, and to link it back to your first question, that transformation gets so much easier if we can deliver compelling experiences, right? So, it's all kind of tied together. >> Four years ago at K15, Frank Slootman sort of threw down the gauntlet to CIO's in the audience and said, you must become business leaders, if you don't become business leaders you'll be a dinosaur. How are you a business leader, and how are you becoming a business leader? >> I think it's really shaping IT's agenda based upon what's important to the organization. And, that's going to be different for different organizations but largely it's going to be things tied to customers, how productive and engaged are the employees, what can we do to drive margin, which is top and bottom line improvement in the economic model, and making sure that IT's goals and objectives are one and the same with the business goals and objectives. So, for example we do at ServiceNow in IT, we have a shared contract with every function. Marketing, sales, you know, professional services, that here's the business outcomes. On my dashboard, you'll seldom see a whole bunch of IT metrics, it's all about did we get to the business metric or not. Cuz if you're not measuring that then I'm not sure what you're measuring. >> Okay, so you, and I'm sure you have a lot of IT metrics, too, but you're able to then tie those IT metrics to business metrics >> Sure. >> And show how a change in one flows through the value to affect another. >> Yeah, I mean, where the role was, that doesn't go away and it's a critical part of the role and I don't want to undermine it which is, all the invisible things that just happen in corporations, you know, the utilities of, is the networking, and phones and all that, that has to be rock solid. That's table stakes, but yeah, for the next part of that, it's really driving those transformational business outcomes. >> So you're a big proponent and advocate of machine learning, how do you see machine learning transforming the modern work experience, the modern workplace and then the employee experience of the modern workplace? >> I think at a very high level, it's around speed and effectiveness of decision making. And, machine learning, I think has the promise or the opportunity for all of us to unlock that next wave of productivity. Just like in the late '90s we had ERP's and they drove a lot of automation, and supply chain and finance organizations around the world got better. They got faster, more efficient. I think machine learning can do that for the entire enterprise by leveraging platforms to help people make faster and better decisions. I know there's a lot written about replacing humans and things like that. I don't buy into that, I think it's just helping us be better and I think there's used cases all over the enterprise. The biggest barriers to machine learning in my mind typically come with talent. How do you do it, and the good news is here, I mean what we embedded with machine learning in the ServiceNow platform, you don't need an army of data scientists that are super hard to find, almost democratizing the ability to leverage machine learning. Second biggest one that when I talk to CIOs, it's lack of the right data, and they don't have the right data perhaps because they haven't yet digitized their processes, so that's a critical precursor. You got to digitize your processes to generate the right data to then feed the algorithms to get the outcome, but yeah machine learning I think is going to materially transform how we operate dramatically over the next three to five years. >> And, I mean, IT systems continue to get more complex. They in many cases becoming more of a black box. I wonder if I could get your thoughts on this. I mean, I remember reading Michael Lewis's book, Flash Boys, and he talked a lot about the flash crash, and nobody could explain it. They chalk it up to a computer glitch, and his premise was a computer glitch is computers are so complex we can't explain them anymore. >> Yeah. >> AI, machine learning, machine intelligence, going to make that even more complex and more of a black box. Is that a problem for us mortals? >> I think it's a problem, (laughs) for us mortals, but I think it's a problem and I'll tie it back to the transformation in human behavior. We're, I'll call it prototyping and rolling out and leveraging machine learning in our own enterprise, and one of the things we've observed is that us humans, us mortals as you call us, we need to know why, so if a machiner is making an algorithmic based recommendation or a decision we need to know why. And, our employees had a hard time accepting the ML based recommendation without knowing the why. So, we had to go back and rework that, and say how do we surface the why in the context of the recommendation and that got people over the hump. So I think it is a super important point where, as these algorithms get more and more sophisticated, our human brains, the way we interpret it, is we still need the why. >> Yeah, so you're trying to white box that, is what you're saying, which again is not easy. I often use the example of, a computer can tell me if I'm looking at a dog, or I joke Silicone Valley if you watch Silicone Valley >> Yeah yeah yeah, >> Hot dog or not hot dog. >> Hot dog, exactly. >> But, try to explain how you know it's a dog, it's hard >> It is challenging. >> To do that. >> Right. >> Especially if you think about data scientists, they are incredibly cerebral and way smarter than me and, they often have a hard time simplifying it enough where its consumable if you will. So, it is a challenge and I think, you know, it's something that'll evolve as we start to use more of it cause we'll just have to figure it out as an industry. >> I want to ask you about, one of the things that we're hearing so much about this conference is the neat things that you're doing around eradicating employee pain points and taking care of all those onerous, annoying, tedious tasks that we have to do, the filling out of paperwork and all of that sort of thing. What are sort of the next things you're thinking about, the other parts of the work day that are annoying for all of us when you sort of think ahead to the product lineup? >> I think, one of the things we do is figure out where you are and you know, digital transformation, right, is great, but it has so many different meanings depending on your company or your industry. So what we did internally is we actually gave definition and an answer to the question of how digital are you? So we take every process and a collection of processes to a department and bubble it up and so on forth, and we rate every process on how fast it is, how intelligent is, which is a measure of machine learning, and what's the experience we're delivering. And taking those three measures, we're able to come up with a score and more than anything it gave us a common language around the enterprise to say, how do we move this from a score of 50 to 70, how do we move this from a 60 to a 90, and which processes are most important to move first, second and third, right, and without that it gets really hard because digital transformation can just feel like this abstract concept and as business leaders, we do better when we have measurement. And once we have a number and a target and a goal, it's easier to get people aligned to that. So, that's been helpful for us as well on a change management aspect. >> So true. Coach K, you guys always have great outside guests come in and speak at your CIO Decisions Conference, I mean Robert Gates is one that, you know, I mean as much as you've accomplished in your life you haven't accomplished nearly as much as that guy. >> Yeah. >> Very humbling. Coach K was your, one of your guests this week, you host that event. >> I do. >> Share with us some of the, some of the learnings from Coach K. >> We had Coach K, Duke's basketball coach, I would argue best coach, best basketball coach >> I'm a Tarheel. >> Sorry, Tarheel here. >> Yeah exactly, Dean Smith. >> We had a couple in the audience- >> He said he's no Dean Smith the other day, (Rebecca laughs) well you know I don't know. >> And I am a college hoops junkie so for me, it was a massive treat. I just wanted to talk to him about so many games and things like that. But he, he really gave a great talk about just how to be a better leader, how to constantly be learning and applying yourself. I mean he's 71 years old and how he needs, he talked about how he had to reinvent himself at least ten times, he's been coaching for 42 years. To meet the players where they are, and changing himself. And every season, the day after the season ends, having a meeting with his managers saying, what do we need to change? And it could be they just won the national championship. So, never resting on his laurels, constantly learning, and he had really interesting anecdotes about when he coached the U.S. Olympic team, and the difference of 18-year-olds right out of high school versus these are the superstars of the NBA, massive egos, and one of the interesting things, he said so many interesting things I could keep going on but just, you know, he said don't leave your ego at the door. Bring your ego, cause that what makes you great. I need you to have that ego Kobe when you're taking that last second shot cause that's what makes you, you. But, also what he spent a lot of time is getting them aligned on values. Here's the core values that which we are going to operate as a team and that are going to allow us to be successful. And I think that leadership lesson applies to any team. He applied it in a very difficult environment while millions of people are watching but, and he talked about how he took that collection of individuals and made them a unit, and that was super powerful. >> Yeah, he coached the first dream team which was Magic, >> Yeah I think he's coached four or five, and >> and I think Byrd might have been hurt but he played, >> yeah. And how he would just >> and Jordan I mean that, try and bring that eclectic mix together. >> And then to hear, have someone be so, you know, I've done all these things, and then be articulate enough to be able to say, and this is what I did >> Yeah and just super humble >> this is how I brought out the best in people. >> Super humble and just, again, constant learning right, I mean John our CEO talks about be a learning animal. I think Coach K embodied that in spades. >> West Point grad too, right, with a lot of discipline >> Yeah. >> That's right, yeah, yeah. >> in his background and >> for sure, >> and it's really inspirational. >> And then he talked about that, that's where he learned a lot of his leadership lessons. >> Really, yeah? >> At West Point. >> Well, Chris it's been so fun talking to you we could, maybe we should get Coach K on with you. A little like, Mike Krzyzewski, yeah >> That would be a treat for me, you and me could talk about Duke Tarheels. >> Yeah, well okay, alright, if you insist. >> We could bring John Wooden into the greatest coaches ever conversation in fairness >> We could, we could. >> to the wizard of Westwood I mean. >> Cool, well thank you. >> Chris, thanks again for coming on. I'm Rebecca Knight for Dave Vellante. We will have more from theCUBE's live coverage of ServiceNow Knowledge '18 coming up just after this. (techno music)

>> Commentator: Live from Stanford University it's theCUBE covering the Women in Data Science Conference 2017. (jazzy music) >> Hi, welcome back to theCUBE. I'm Lisa Martin live at Stanford University at the second annual Women in Data Science WiDS tech conference. We are here with Ann Rosenberg from SAP. She's the VP head of Global SAP Alliances and SAP Next-Gen. Ann, welcome to the program. >> Thank you so much. >> So SAP is a sponsor of WiDS. Talk to us a little bit about that, and why is it so important for SAP to be involved in this great womens organization. >> So first of all, in my role as working with SAP's relationship to academia and also building up innovation network we see that data science is a very, very key skill set, and we also would like to see many more women get involved into this. Actually (mumbling) right now as we speak we are at the same time in 20 different countries around the world, 24 events we have. So we are both in Berlin, we are in New York, we are all over the world. So it's very important. I call it kind of a movement what we are doing here. It's important that all over the world that we inspire women to go into data science and into tech in general. So it is important thing for SAP. First of all, we need a lot of data science interested people. You also need our entire SAP ecosystem to go out to universities and be able to recruit a data science student both from a diversity perspective, whatever you are a female or a man of course. >> Absolutely, you're right. This is a very inspiring event. It's something that you can really actually feel. You're hearing a lot of applause from the speakers. When you're looking enabling even SAP people to go out and educate and recruit data scientists, what are some of the key skills that you're looking for as the next generation of data scientists? >> This is an interesting thing because you can say that you need like a very strong technical skill set, but we see more and more, and I saw that after I moved to Silicon Valley for two years that also the whole thing about design thinking, the combination of design thinking and data science is becoming something which is extremely important, but also the whole topic about empathy and also, so when you build solution you need to have this whole purpose driven in mindset. So I think what we're seeing more and more is that it's great to be a great data science, but it takes more than that. And that's what I see Stanford and Berkeley are doing a lot, that they're kind of mixing up kind of like the classes. And so you can be a strong data science, but at the same time you also have the whole design thinking background. That's some of the things that we look for at SAP. >> And that's great. We're hearing more and more of that, other skills, critical thinking, being able to not only analyze and interpret the information, but apply it and explain it in a way that really reflects the value. So I know that you have a career, you've been in industry, but you've also been a lecturer. Is this career that you're doing now, this job in alliances and next-gen for SAP sort of a match made in heaven in terms of your background? >> I actually love that question, probably the best question I ever got because it is definitely my dream job. When I was teaching in Copenhagen for some years ago I saw the mind of young people. I saw the thesis, the best of master thesis. I saw what they were able to do, and I'm an old management consultant, and I kept on thinking that the quality of work, the quality of ideas and ideations that the students come with were something that the industry could benefit so much from. So I always wanted to do this matchmaking between the industries and the mind of young people. And it's actually right now I see that it's started kind of, what I at least saw for the last two years that the industries that go to academia, go to universities to educate or to students to work on new ideas. And of course in Silicon Valley this has been going on for some time now, but we see all over the world. And the network that I'm responsible for at SAP, we work in more than 106 countries around the world, with 3,100 universities. And what I really want to do now, I call it the Silicon Valleys of the world where you are mapping the industries with academia with the accelerators and start ups. It's just an incredible innovation network, and this is what I see is just so much growing right now. So it's a great opportunity for academia, but equally also for the industry. >> I love that. Something that caught my eye, I was doing some research, and April 2016 SAP announced a collaboration with the White House's Computer Science for All Initiative. Tell us about that. >> I mean the whole DNA of SAP is in education. And therefore we do support a number of entity around the world. Whatever we talk about building up a skill set within data science, building skill set in design thinking, or in any kind of development skills is really, really important for us. So we do a lot of work together with the governments around the world. Whatever you talk about the host communication, for example, we have programs called Young Thinkers, Beatick, where you go out to high schools or you go into academia, to universities. So when this institute came up, we of course went in and said we want to support this. So if I look at United States, so we have a huge amount of universities part of the network that I'm driving with my team. So we have data curriculums, education material, we have train to train our faculties, boot camps. We do hackathons, coach games. We do around 1,200 to 1,600 hackathon coach games per year around the world. We engage with the industries out to the universities. So therefore it was a perfect match for us to kind of support this institute. >> Fantastic. Are there any things that SAP does as we look at the conference where we are, this Women in Data Science, are there things that you're doing specifically to help SAP, maybe even universities bring in more females into the programs, whether it's a university program or into SAP? >> Yeah, so for SAP in our whole recruiting process we definitely are looking into that. There is a great mix between female and male people who get hired into the company, but we also, it all start with that you actually inspire young women to go into a data science education or into a development education. So my team, we actually go in before SAP recruiting get involved where we, that's why we build up the strong relationships with universities where we inspire young women, like we do at this event here to why should they go in and have a career like this. So therefore you can see there's a lot of pre=work we need to be done for us to be able to go in and go into the recruiting process afterwards. So SAP do a lot of course in the United States, but all over the world to inspire young women to go into tech. And SAP does what we see today all over the world we have huge amount of female from SAP, female speakers at all our events who stand as role models to show that they are women, they are working for SAP, and are very, very strong female speakers and are female role models for all young women to get involved. So we do a lot of stuff to show that to the next generation of data science of whatever it is in tech. >> Yeah, and I can imagine that that's quite symbiotic. It's probably a really nice thing for that female speaker to be able to have the opportunity to share what she's doing, what she's working on, but also probably nice for her to have the opportunity to be a mentor and to help influence someone else's career. So you mentioned accelerators a minute ago, and I wanted to understand a little bit more about SAP Next-Gen Consulting, this collaboration of SAP with accelerators or start ups. How are you partnering to help accelerate innovation, and who is geared towards? Is it geared more towards student? Or is SAP also helping current business leaders to evolve and really drive digital transformation within their companies? >> So the big (mumbling) I'm working on right now too is as mentioned you said SAP Next-Gen is called SAP Next-Gen Innovation With Purpose. So it's linked to the 17 U.N. global goals. We've seen from now in Silicon Valley when you innovate you actually make innovation web purposes included. And that's why we kind of agreed on in SAP why don't we make an innovation network where the main focus is that all the innovation we get out of this is purpose driven linked to the 17 global goals. Like the event here is the goal number five, gender equality. In that network we actually do the matchmaking between academia. We look at all the disrupted new technologies, experience the technologies like machine learning like what's being discussed a lot here, block chain IOT. And then we look at the industry out there because the industries, they need all the new ideas and how to work with all the new opportunities that technology can provide, but then we also look into accelerator start ups. The huge amount, and often when you're in Silicon Valley you kind of think this is the world of the start ups of the world. So when you travel around the world, that's we we looked into a lot the last two years. We call the Silicon Valleys of the world, any big city around the world, or even smaller cities, they have tech hub. So you have Ferline Valley, you have Silicon Roundabout in London, you have Silicon Alley in New York, and that is where there is a huge amount of gravity of start ups and accelerators. And when you begin to link them together with the university network of the world and together with the industry network of the world, you suddenly realize that there is an incredible activity of creativity and ideations and start ups, and you can begin to group that into industries. And that give industries the opportunity not only to develop solution inside the company, but kind of like go in and tap into that incredible innovation network. So we work a lot with seeding in start up, early start ups into corporates, and also crowd source out to academia and the mind of young people all Next-Gen Consulting project where you similar work with students at universities on projects. It could be big data science project. It could be new applications. So I see like as the next generation type of consultancy and research what is happening in that whole network. But that is really what SAP Next-Gen is, but it is linked to the 17 U.N. global goals. It is innovation with purpose, which I'm really happy to see because I think when you build innovation, you really think about in the bigger, the whole (mumbling) thing that we know from singularity. You should think about a bigger purpose of what you're doing. >> Right, right. It sounds like though that this Next-Gen Consulting is built on a foundation of collaboration and sharing. >> It is, it is, and we have three Next-Gen lab types we set up. In this year we built, last year, we are a new year now, we built 20 Next-Gen labs at university campuses and at SAP locations. And here in the new year more labs is being set up. We are opening up a big lab in New York. We just recently opened up one in Valdov at SAP's headquarter. We have one here in Silicon Valley, and then we have a number of universities around the world where SAP's customers go in and work with academia, with educators and students because what do you do today if you're in industry? You need to find students who are strong in machine learning and all the new technologies, right? So there's a huge need for in industry now to engage with academia, an incredible opportunity for both sides. >> Right, and one last question. Who are you, in the spirit of collaboration, who do you collaborate back with at SAP corporate? Who are all the beneficiaries or the influencers of Next-Gen Consulting? >> So I collaborate, inside SAP I collaborate, SAP have a number of, we have ICN, Innovation Center Network. We have our start up focus program. We have a number of innovation, the labs, a number of basically do all our software developments, so they're heavily involved. We have our whole go to market organization with all our SAP customers and industry, I call them clubs. And then externally is of course academia, universities, and then it is the start up communities, accelerators and of course, the industry. So it is really like a matchmaking. That's like, when people ask me what do you do, and I'm a matchmaker. That's really what I am. (Lisa laughs) >> I like that, a matchmaker of technology and people all over. So you're on the planning committee for WiDS. Wrapping things up here, what does this event mean to you in terms of what you've heard today? And what are you excited about for next year's event? >> So for me, one year ago when I heard about this year I kind of said this is important, this is very important. And it's not just an event, it's a movement. And so that was where I went in and said you know, we want to be part of this, but it must be more than just an event here. It's staying for the need to be much more than that. And this is where we all teamed up, all the sponsors together with ISMIE, and we said okay, let us crowd source it out, let us live stream it out much more than ever. And this is also what the assignment is now, that we to so many locations. This is just the beginning. Next year is going to be even bigger, and it's not like that we will wait to next year. We this week announced the SAP Next-Gen global challenges linked to the 17 U.N. global goals. So we are inspiring everybody to go in and work on those global challenges, and one of them is goal number five, which is linked to this event here. So for us and for me this is just the beginning, and next year is going to be even bigger. But we are going to do so many event and activity up to next year. My team in APJ, because of the Chinese New Year, have already been planned coming up here. >> Lisa: Fantastic. >> And we have been doing pre-event, (mumbling) events. So again, it is a movement, and it's going to be big. That's for sure. >> I completely can feel that within you. And you're going to be driving this momentum to make the movement even louder, ever more visible next year. >> Ann: Yeah. >> Well Ann, thank you so much for joining us on The Cube. We're happy to have you. >> Thank you so much for the opportunity. >> And we thank you for watching The Cube. I am Lisa Martin. We are live at Stanford University at the second annual Women in Data Science Conference. Stick around, we'll be right back. (jazzy music)

but cute at servicenow knowledge 14 is sponsored by service now here are your hosts Dave vellante and Jeff trick we're back welcome everybody Alan line wind is here he's the vice president and chief technology officer of the cloud platform and infrastructure components of service now all the stuff that you don't see it's sort of behind the curtains all the magic and the secret sauce Alan welcome to the cube thank you very much for everything so what's the what's going on what's new in the in the cloud platform you guys obviously started this before cloud was sort of even referred to yes cloud you know I mean I mean Fred talks about his vision and sore clouds in there but you know really cloud started mid-2000s 2006 and then really started taking off so the latter part of the decade you guys kind of maybe not predated but so the same time you know so what's how was the platform evolved I mean the platform is really evolved during people like to talk about cloud when I think about cloud that's a little bit beyond water vapor so what we end it's been a hard time doing the very early to make silicon and make aluminum actually perform something for our customers the cloud platform has really evolved into being a platform that allows people to develop applications that are either both for IT or for the entire enterprise that's really what we're sort of here to talk about from service now is perspective in this whole show is what we've done on the platform is beyond IT and it can power services for the whole enterprise so we've scaled our cloud significantly we're in eight different regions across the planet 16 different data center locations and we're continuing to grow globally on our cloud right now so these data center locations that you used to you're building out data centers you we're actually using wholesale and retail space so we're using our data center partners and we're building out large cases of infrastructure that we own and operate on our own okay so so just make sure I understand so you're not building mega data centers yeah that's not your strategy that's right can you talk about why that's not strategy yeah I mean we're not building on mega datacenters like maybe they hear from facebook and google or other folks we're actually using our data center partners to build the infrastructure sort of meet our customer needs we don't necessarily host people or do sort of infrastructure services like those guys do we end up doing is we're in a building very specific cloud platforms in restructure for the enterprise it just turns out a footprint for that just isn't as big as other folks and we scale it as we need to do and there's confusion also about and I wonder if you could help us clear it up you're sort of your approach to multi-tenancy let's chat all right so you don't have a multi-tenancy that's remodel you've got more of a hybrid model can you talk about that a little bit and what the advantages are yeah absolutely there's folks that have a multi-tenant model what that really means is that multiple customers data is interlaced and and are intersected with in the same data structures within the same data sounds scary it is and can do that scary but we've actually ended up doing is segmenting both the application logic into virtual machines per customer and then actually dividing up the database itself on a per customer basis or every one of our customers has their own unique database process unique to them their own tables their own data they're on isolation and they have application luggages that's unique to them as well that's very different from multi-tenancy where you have a large database and a large piece of infrastructure that a lot of people share one of the biggest advantages for that for our customers is really about availability if I'm a big huge multi-tenant architecture I need to take all hundreds and hundreds of customers in this pod and move them somewhere else because of a failure that's a scary operation but we actually have the ability to do is move individual customers around our cloud and provide a very high available solution for them because of the fact in the way we've architected so if I'm a customer and and you're on a sales call and you tell me that I'm I good I want that right I'm like totally cool with that I'll tell you something right now if ok now if i'ma we're not quite big enough yet although there's some new products are coming up appeal to us but now if I'm let's say I'm an investor I might say well jeez aren't I going to get better leverage if I go multi-tenancy think Amazon and some of you know larger players also that response to that yeah I mean that's sort of an interesting distinction when people think about multi-tenancy their verses single term see what we call it what you actually find is that they think that the multi-tenancy allows you to scale the hardware better but the truth is what we've done when we actually called multi-instance is a hardware can be shared but the actual customer deployment the Java Virtual Machine the database for that customer is laid down on that shared harders we're actually getting good economics at the hardware and we're giving customers isolation they want we think it's very unique in industry loss is just really exciting things well we heard actually was interesting at oracle openworld which was here i want to say two years ago yeah so it was 2012 maybe was even 2011 was 2011 Ellison really railed on multi-tenancy yeah he railed on work day he railed on on on salesforce and said multi-tenancy is a bad thing you don't want to do it in the application now I think I know 12c changes that I'm not sure I know he did a flip flop Larry does that a lot but um but but your your your your dogma if you will is not going to flip flop rights right you guys got you you can see this am I correct well let me ask you does the scale you know to you know huge Heights that Frank's lubin once they hit yeah I mean we have 11,000 12,000 customer instances in the clouds individual instantiations but let me give you a quick fact here for knowledge we spun out 23,000 additional instances so we have the ability to scale this model in a very dynamic way and a very well orchestrated way we think it really helps our customers one of these I like to say about multi-tenancy is I get why it's good for the cloud provider I get why the folks that build multi-tenancy build it because you're right it you both at once you carve it up or bunch of pieces for a customer customers data is interlaced okay I'm not sure why I want that as a customer customer wants out isolation that's what we provide well giving both leverage of hardware and isolation of data yeah because again a conceptual you can see how there might be some some margin advantages but then then the big question to me a security sure know what kind of what kind of security nuance wants not the right word does it ease the security requirements does it make your security cleaner you know easier to scale replicate etc you talked about that a little yeah I mean it clearly makes our application logic easier because they viewed portion of the application is talking to that individual database instance for that individual customer but our security focus is really focused on protecting those instances from the various threats so we're always looking at threats on the Internet we're always adding our perimeter firewalls we're already doing our third party audits we're doing a penetration test so just like any other cloud provider we're continually updating our security model and making sure we're advancing and trying to stay one step ahead of bad guys but because we have customer data that is segmented and isolated it does make our security model easier and more straightforward for the customer by using a lot of open source in the back end yeah we do do a bunch of my soup of open source for the databases of course right we do a bunch of apology on the front end using Mongo right we are using Mongo to help us get our document store for a larger customers that's right what kind of effect if any did heartbleed have on you guys yeah we looked at heart bleed and we we looked at the effect of it we didn't really see much in effect we weren't using systems are affected by that yeah awesome so Alan we've been covering a lot of data center stuff absolutely and there's a lot of interesting innovation that's happening in the infrastructure we're cooling and our and segmentation and all kinds of interesting things where's the line of innovation in the data center between your stuff and the infrastructure provided that you're working with yeah so we spend a lot of time actually focused on the actual sort of server platform storage platform communication between the web servers in the network we don't spend a lot of time on maybe hot aisle containment or cold out containment worried about you know efficiency of the building or air flow through the building we spend a lot of time sort of utilizing the best practices there so we go look for our data center providers that are really driving that peewee number down to the level 10 level but we're not architecting the building we'll look for those providers and then we'll deploy our equipment in a way that takes advantage of that you know we're following and using some of the practices from local compute we're looking at the next generation networking hardware and networking software that's out there and we're really sort of leveraging everything that they're building on the data center itself and then I know there's a lot of data data regulations that are driving kind of the location of your data centers or where he says you have 16 that's right they're basically at eight locations double located that's where if I recall a country's yeah yep so there's still some some open area that you need to penetrate based on customer and demand that you haven't gone yet or where the next one's going to be yeah we're going to build with the customers ask us to build we built into Switzerland and Geneva and Zurich because of that we built in a Canada for data sovereignty issues we're building into Brazil we're building in Asia right now Hong Kong and Singapore so we're going to kind of go over the customer demand takes us oh it's a big question on on Germany and this came up actually we're at the AWS reinvent we did the age of aw our summit and Amazon doesn't have a data center in Germany sure don't have a data we do not turn out right but of course everybody knows german law but everybody knows but but the the sort of urban legend is German losses you got a store data in Germany when we asked amazon this they said well we have a location in ireland that's part of the EU is that a similar response that you guys track we have amsterdam and london and we serve the EU countries ramps down so if I'm a German customer I would store my data there yeah right I mean that would be the default I mean we actually might have a German customer that want to be in the US but we actually had our customers pick which region of the world that want to be deployed in and we deploy on their behalf in there that's a prerequisite of going through the process right you use wage in a store your data that's right and then that's a sales guys figure that out so I so I asked actually i'll ask you as well the Amazon perspective has that ever been tested you know in the court of law do we actually know that this stands up cuz you always hear so much from the the anti amazon crowd oh well you can't choose where your data is stored that's not true certainly not true with you that's right and Germany Brazil very strict they actually have a location in Brazil but but so are you comfortable that it's consider compliant with German law and in this instance do you have those conversations or customers I mean obviously you do business in Germany yeah i mean i'll say my last name is Austrian German but I'm not well-versed in German like everything people tell me I know we can deploy and it's always a good answer without a lawyer okay I am NOT a liar but it's not stopping sales right not something i mean i've seen this again there's so much chatter and noise out there yeah but none of those misperceptions people like to throw that thought out there they like to say you can't do business I haven't had that objection I'm sure we may run into it but right now it's not top of mind good it was interesting it at a pro Conal i would actually had a lawyer on Richard on every often on the Cuban he said you know there's even different data laws in Massachusetts from Connecticut you know Mike well where is the data I mean especially the cloud and is distributed you're talking about across state borders and it hasn't really been challenged and it apparently it hasn't yet or it's going to get really nasty because cloud just by its very nature stuffs distributed that's right it's replicated it's all over the place so it's everywhere from so everybody uses Germany but he was talking about the difference between two borders border states so it could be interesting at some point in time should we talked earlier about my sequel was really was surely the the data platform that you started that's right and then Mongo came in recently didn't it within a year or two we end up doing is we we deploy the master database so the reads and writes in my sequel we also have capabilities in the platform that when we start to scale the hardware we can add what's called we replicas so we can add sort of versions of my sequel that can take transactions that are read-only and then for people that have large document stores you're doing attachments are doing forums are doing images things are really document-based we can actually deploy Mongo and then we can use Mongo for that particular type of transaction in that system as well so that's what you use in long ago that's okay that wasn't clear to me and that's relatively new initiative is it not yeah came out in Calgary which was last year was that release right okay member i'm talking about it last year i think it at no 13 that's right okay so what's what's next for you guys you know behind the curtain which I it's not really behind the curtain many customers would say if I'm hurting right now that's it but you guys didn't you know it's not like is this is a mean well I guess it is party in marketing but you know you don't be talking about products you're talking about value but it's great we have an opportunity to speak to guys like you actually you know running the factory right yeah so what's next what's what a customer is asking for what are the innovations that you guys are working on yeah i think what customers are really asking for is for us to take the cloud platform in the infrastructure and really to evolve it to be that hardened highly available persistent you know people want to talk about the cloud being like electricity being always on we obviously strive for that but like any other business we we have issues you know hardware does go break and we does booming overnight we have to make sure we perfect it we're constantly tuning that we're focused very much on availability you'll see something tomorrow we're actually going to show customers their individual availability as opposed to this sort of larger distributed availability if you will talk about we're also looking into more automation so that way things that generally break that we now have humans intervene with we want to have that automation kick off automatically and then have people automatically have have the machines do that automatically instead of the humans and we're spending a lot of time just really focused on keeping the cloud alive keeping the cloud available and making sure it is kind of behind the curtain yeah invisible is always good right you know I asked Fred this morning and I'll ask you cuz I didn't fully grasp the answer and I want to want to get pressing at this fred was maybe a little over my head or was i don't know maybe I just didn't get it but so the question I had is so you're not really like the mega data center right we talked about earlier you're not like Amazon or Facebook or Google but you know you're growing you could you're getting to a scale that's quite large and you can you can see you know the future you could be very very large today you've got you know n number of applications it's not overwhelming and the question I ask for fred was working a sort of architecture question in database than the database world you've got transactions you're locking on the database the record that's one one application says I got it and then releases it then the next one has it as you grow out the applications my question the fred was does that become problematic do you get no queuing problems performance issues scale issues and he said his answer if I could summarize and I hope I get this right was especially we're not a heavy locking environment and so on number two there's a lot of other things that go on engagements that go on outside of that lock so you didn't see it as a challenge because of the nature of the applications and and I guess the architecture itself but as you grow to massive scale does that potentially become a problem have you architected around that do you have to architect around that or am I just not understanding it yeah i mean i think if we were multi-tenant where we had thousands of customers sharing a single database doing with those locking issues and the similar issues we'd have that issue but fortunately because every customer gets their own version of their own unique database they're just worried about the applications that they're running so what we end up doing is going to monitoring the hardware and monitoring the databases for transaction rates per customer and as this transaction rates per customer as they add applications as they add users as they're adding joins and lists and building forms and creating services like Fred talked about this morning we can actually find out if their database is starting to see issues and if their particular database to start to see issues we can then go to point B but because we can go deploy things like Mongo on a customer by customer basis so we don't have this Gale issue per se we have the monitor the individual customer transaction rate issue and make sure we're always automating and always upgrading the infrastructure to match yeah ok so you've obviously thought about this problem and the customer has to be quite large to even encounter the problem that's right and then you've got methods techniques approaches even I don't even call it brute force approaches we can we can solve it more silica there are cases where the bigger box wins right yeah Moore's Law wins you can you can add more metal to the clouds so and you can make a bigger so the point of all the reason I'm asking all these questions is not just for sort of you know academic or theoretical cures is there is this a potential constraint to your growth down the road and I'm hearing no it's not yeah we don't see it as a constraint some of our biggest customers are running very very large transaction rates regular scale both the core metal to actually drive those transactions as well as tune the system and tune the way the database behaves that way those interactions you're talking about those locks those joins or select statements can actually be handle by the system in a very efficient manner and what do you make of all this you know it's sort of started at at vmworld a year or so ago with the whole software-defined meme and the acquisition of nice Sarah software-defined networking now they're talking about software-defined storage you certainly see that from the hyperscale guys what do you make of that is that is that how does that affect your world well you're talking to guy that actually worked on a software-defined networking company I founded a company called viata in my path to know Coach brocade actually bought right so I believe in the sufferer Defined Networking I believe that software and algorithms running the metal makes a lot of sense our automation our workflow orchestration tools we have on the platform are what we use to bend our metal in the way we like for our customers and I think really putting logic into the software and learning a software actually change the infrastructure is the way for the future and so thinking about your storage and your network and yours your compute infrastructure you're sort of buying off the shelf that's right standard servers are you buying from ODMs or a combination we do we'd a little both we actually look at our servers on an annual basis we evaluate both ODMs that are in white boxes as well as your typical OEMs and then we're looking to understand the transaction rates and the performance of those particular pieces of hardware we do a price performance evaluation and we sort of upgrade and continue to migrate the farm forward and how about the storage and you buying big giant containers or not as big sands we're not so its commodity storage it's chemist or horizontally scaled across the service we don't believe in centralized storage model no fiber channel no InfiniBand no fiber to know and your stack is your stack our stack is on you've written your own stack to do replication and data migration and run app shots the replication side is actually using my sequel binlog replication okay the backup itself is actually using some open source tools as well as some technologies you stuck on top of it we actually call it sm vault for servers no vault and we've actually developed both a hybrid of open source and our own technologies to make that work do you use tape we do not use tape no tape no euro tape yeah i think frankly i'm not surprised Frank salute with the kind of it yeah and what about the networking what's the strategy there yeah from the networking point of view we use commodity here as well from you know the big two vendors out there cisco and juniper we're continually looking to upgrade we're continually looking to drive layer through technologies down close to the user and have a very reliable very done system let me give you an example in every data center cage location we have at least three tier one providers we have a fully read on the network all the way from the internet through the firewalls through the little answers all the way down to the servers in the rack and we just believe a high-availability enterprise-grade top the bottom and and what about this notion of converged infrastructure you're seeing that a lot is that's something that you're you're looking at you're staying away from you're adopting or we actually think it makes a lot of sense you know I'm not going to tell you we're doing it right now because it's it's pretty bleeding edge and we want to be highly available for the enterprise but this idea of a converged network and systems infrastructure that works together with automation again it's just part of our platform part of our DNA so kind of a single throat to choke and yeah reduce passed me at Pat patch management just a block of infrastructure that that's sensible for you absolutely i mean from our point of view the ServiceNow cloud platform would be that orchestration and automation this is like filled day for me being able to ask of a practitioner that's that's actually building out a big animatic cloud you know sounds awesome and okay well let's see so we hit on s the end we are you here on all the pieces here i guess i think i'm out i think i think i'm thinking about anytime you want yeah that's fantastic i really appreciate the insights you know cuz you know a lot of the lot of the cloud suppliers don't like to talk about you know the internal plumbing but i think it's important you know your customers want to know i mean at the end of the day you don't build a great you know multi-billion dollar business without understanding how infrastructure works in the architecture of the infrastructure I'm a really strong believer that our applications are driving Enterprise forward and I'd have a hard time talking to the cios I talked to you on a regular basis without convincing them but the infrastructure they are relying on for those applications is as solid as it gets do you see the need I do have another one so do you set the need you know remember the early days we all lose I all thought okay here's here comes you know guys like Amazon its commodity infrastructure software lead that's going to lead into the enterprise you're starting to see that happen now but now Amazon's kind of done a one-eighty that's right they're going highly customized infrastructure there's they won't show us their servers but they'll show us so you know no some odm server that's super dense and they say we blow that away because they control their data centers do you see that type of customization requirement for your servers and for your free for your networking we spend time looking at that as well I won't say perhaps we do it quite in-depth as Amazon don't run quite the same size farm they do but we do look at you know the motherboards and the PCI cards and this the the flash disk that's in there the SSD we spend time understand the bios we spend the time understanding how many ports were going to connect to the top Iraq switch we spend time specking all that I mean we're full heart and enterprise platform and our customers depend on us to do that so we have to we have to do that diligence are you using fun all right we still got time are you using flash how are you using it yeah we are using flash we find that the flash arrays we use fusion-io and for those s SD cards we put them into our higher-end database servers from moving actually off spinning media onto flash for the entire farm and one of the way we use it is it helps us get I ops out of the database servers and it actually helps in replication because the way replication works is I'm operating data center a I do my transaction in that database I write it out to the flash because the database is in memory I send it over the parasite the parasites gotta read it off disc and rerun that transaction and keep that replication in sync so that I oh actually does help us keep replication going so using percona my sequel or no no okay so do you raising are on my signal okay do you do atomic rights with fusion we are doing some rights for fusion yes yeah okay so you're essentially bypassing the scuzzy stack and writing directly to we have ability to do that with a new fusion on your driver so I'm not sure they're widely deployed it does it have potential absolutely not it's an amazing performance you can go straight from memory straight to SSD just like you're acting a ram chip why wouldn't we want to not only am I limiting the spinning disk I'm eliminating the overhead of the the storage protocol we'd love to be able to do that yes okay that's understanding the life of the flash / David's lawyers article that we covered the other day because I written specifically for flash as opposed to written for disk how about object stores that's something that you you know we generally don't have a ton of object stores that we do but when we do their document types are attachments to an incident their graphics on a particular application they're part of a workflow that pops up or resent something to the customer and if that is sort of documents become heavy transactional types for reads in the database put those on Mongo okay so and you're doing sort of a combination of block and file or it's all blocked it's all block all block okay well file except I guess what you doing in manga course violence or quasi object that's right awesome I'm having a field day I really appreciate all the insights you know it's this is good i'm actually any the second watch this several times i mean i mean the truth is for us it's all about like i said it's all about talking about folks about infrastructure we think the infrastructure is the core foundation for everything we do in the enterprise apps the apps are really what our customers are about letting them be creators and letting them do our applications but let's face it you know we build the cloud and the club's got to be solid to run those apps my last question so you we've been talking about all these cool innovations when do you see these or do you see these seeping into the the enterprise on-premise do you see that as a sort of viable approach for CIOs or or in your view are they just going to sort of outsourced it mostly to the cloud over the next decade I'm pretty clearly biased at the moment but you know I over your application driven we're talking about infrastructure fair enough from the side I mean I think the things that we're doing in the cloud and the infrastructure are sort of leading-edge I do you think the enterprises are going to adopt that but I'll be honest you there are certain enterprises are ahead of us right there are certain folks that are thinking one or two steps ahead of us because rat just a bigger scale than we are almost though yeah not most but there are some we've learned from them in their banks and yeah i'm thinking the big banks the big big financial institutions we spend time with them learning what they're doing inside so we can actually make the cloud better and they're sharing with you okay absolutely because they're trying to learn too yeah they're ready one happens to somebody that's running on bailing wire right yeah that's amazing innovations actually going on in financial services and it's like the the downturn ever happened yeah well thanks very much for five years all right great stuff keep it right there buddy Jeff Rick and I'll be right back we're live from 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