(upbeat music) >> Hello everyone, welcome to the special CUBE presentation of the AWS Partner Showcase season one, episode two. I'm John Furrier, your host of theCUBE. We've got two great guest here. Douglas Ko, Director of product marketing at Cohesity and Sabina Joseph General Manager of AWS, Amazon Web Services. Welcome to the show. >> Thank you for having us. >> Great to see you Sabina and Douglas. Great to see you, congratulations at Cohesity. Loved the shirt, got the colors wearing there on Cohesity, Always good I can't miss your booth at the shows, can't wait to get back in person, but thanks for coming in remotely. I got to say it's super excited to chat with you, appreciate it. >> Yeah, pleasure to be here. >> What are the trends you're seeing in the market when it comes to ransomware threats right now. You guys are in the middle of it right now more than ever. I was hearing more and more about security, cloud scale, cloud refactoring. You guys are in the middle of it. What's the latest trends in ransomware? >> Yeah, I have to say John, it's a pleasure to be here but on the other hand, when you asked me about ransomware, right? The data and the statistics are pretty sobering right now. If we look at what just happened in 2020 to 2021, we saw a tenfold increase in a ransomware attacks. We also saw the prediction of a ransomware attack happening every 11 seconds meaning by the time I finished this sentence there's going to be another company falling victim to ransomware. And it's also expected by 2031 that the global impact of ransomware across businesses will be over $260 billion, right? So, that's huge. And even at Cohesisity, right, what we saw, we did our own survey, and this one actually directly to end users and consumers. And what we found was over 70% of them would reconsider doing business with a company that paid a ransom. So all these things are pretty alarming and pretty big problems that we face today in our industry. >> Yeah, there's so many dimensions to it. I mean, you guys at Cohesity have been doing a while. It's being baked in from day one, security in the cloud and backup recovery, all that is kind of all in one thing now. So to protect against ransomware and other threats is huge Sabina, I got to ask you Amazon's view of ransomware is serious. You guys take it very seriously. What's the posture and specifically, what is AWS doing to protect customers from this threat? >> Yeah, so as Doug mentioned, right, there's no industry that's immune to ransomware attacks. And just as so we all level set, right? What it means is somebody taking control over and locking your data as an individual or as a company, and then demanding a ransom for it, right? According to the NIST, the National Institute of Standards and Technology cybersecurity framework, there are basically five main functions which are needed in order to plan and manage these kind of cybersecurity ransomware attacks. They go across identifying what do you need to protect, actually implementing the things that you need in order to protect yourself, detecting things if there is an attack that's going on, then also responding, how do you get out of this attack? And then bringing things, recovery, right? Bringing things back to where they were before the attack. As we all know, AWS takes security very seriously. We want to make sure that our customer's data is always protected. We have a number of native security solutions, but we are also looking to see how we can work with partners. And this is in fact when in the fall of 2019, the Cohesity CEO, Mohit Aron, myself and a couple of us, we met and we brainstorm, what could we do something that is differentiated in the market? When we built this data management as a service native solution on top of AWS, it's a first of a kind solution, John. It doesn't exist anywhere else in the market, even to even today. And we really focused on using the well architected review, the five pillars of security, reliability, operational excellence, performance, and cost optimization. And we built this differentiated solution together, and it was launched in April, 2020. And then of course from a customer viewpoint, they should use a comprehensive set of solutions. And going back to that security, that cyber security framework that I mentioned, the Cohesity data management as a service solution really falls into that recovery, that last area that I mentioned and solution actually provides, granular management of data, protection of data. Customers can spin up things very quickly and really scale their solution across the globe. And ensure that there is compliance, no matter how many times we do data changes, ads and so on across the world. >> Yeah, Sabina, that's a great point about that because a lot of the ransomware actually got bad actors, but also customers can misconfigure things. They don't follow the best practice. So having that native solutions are super important. So that's a great call out. Douglas, I got to go back to you because you're on the Cohesity side and a the partner of AWS. They have all these best practices that for the good actors, got to pay attention to the best practices and the bad actors also trying to get in creates a two, challenge an opportunity. So how do organizations protect their data against these attacks? And also how do they maintain their best practices? Because that's half the battle too, is the best practices to make sure you're following the guidelines on AWS side, as well as protecting the attacks. What's your thoughts? >> Yeah, absolutely. First and foremost, right? As an organization, you need to understand how ransomware operates and how it's evolved over the years. And when you first look at it, Sabina already mentioned it, they started with consumers, small businesses, attacking their data, right? And some of these, consumers or businesses didn't have any backup. So the first step is just to make sure your data is backed up, but then the criminals kind of went up market, right? They understood that big organizations had big pocket and purses. So they went after them and the larger organizations do have backup and recovery solutions in place. So the criminals knew that they had to go deeper, right? And what they did was they went after the backup systems themselves and went to attack, delete, tamper with those backup systems and make it difficult or impossible to recover. And that really highlighted some solutions is out there that had some vulnerabilities with their data immutability and capabilities around WORM. And those are areas we suggest customers look at, that have immutability and WORM. And more recently again, given the way attacks have happened now is really to add another layer of defense and protection. And that includes, traditionally what we used to call, the 3-2-1 rule. And that basically means, three copies of data on two different sets of media with one piece of that data offsite, right? And in today's world and the cloud, right? That's a great opportunity to kind of modernize your environment. I wish that was all that ransomware guys we're doing right now and the criminals were doing, but unfortunately that's not the case. And what we've seen is over the past two years specifically, we've seen a huge increase in what you would call data theft or data exfiltration. And that essentially is them taking that data, a specific sense of the data and they're threatening to expose it to the dark web or selling it to the highest bidder. So in this situation it's honestly very difficult to manage. And the biggest thing you could do is obviously harden your security systems, but also you need a good understanding about your data, right? Where all that sensitive information is, who has access to it and what are the potential risks of that data being exposed. So that takes another step in terms of leveraging a bunch of technologies to help with that problem set. >> What can businesses do from an architectural standpoint and platform standpoint that you guys see there's key guiding principles around how their mindset should be? What's the examples of other approaches- >> Yeah. >> Approach here? >> No, I think they are both us at Cohesity and I'll speak for Sabina, AWS, we believe in a platform approach. And the reason for that is this a very complicated problem and the more tools and more things you have in there, you add risk of complexity, even potential new attack surfaces that the criminals can go after. So we believe the architecture approach should kind of have some key elements. One is around data resiliency, right? And that again comes from things like data encryption, your own data is encrypted by your own keys, that the data is immutable and has that, right, want to read many or WORM capabilities, so the bad guys can't temper with your data, right? That's just step one. Step two is really understanding and having the right access controls within your environment, right? And that means having multi factor authentication, quorum, meaning having two keys for the closet before you can actually have access to it. But it's got to go beyond there as well too. We got to leverage some newer technologies like AI and machine learning. And that can help you with detection and analysis of both where all your sensitive information is, right? As well as understanding potential anomalies that could signify attack or threat in progress. So, those are all key elements. And the last one of course is I think it takes a village, right? To fight the ransomware war. So we know we can't do it alone so, that's why we partner with people like AWS. That's why we also partner with other people in the security space to ensure you really have a full ecosystem support to manage all those things around that framework. >> That's awesome. Before I get to Sabina, I want to get into the relationship real quick, but I want to come back and highlight what you said about the data management as a service. This is a joint collaboration. This is some of the innovation that Cohesity and AWS are bringing to the market to combat ransomware. Can you elaborate more on that piece 'cause this is important. It's a collaboration that we're going to gather. So it's a partner and you guys were going to take us through what that means for the customer and to you guys. I mean, that's a compelling offering. >> So when we start to work with partners, right? we want to make sure that we are solving a customer problem. That's the whole working backwards from a customer. We are adding something more that the customer could not do. That's why when either my team or me, we start to either work on a new partnership or a new solution, it's always focused on, okay, is this solution enabling our customer to do something that they couldn't do before? And this approach has really helped us, John, in enabling majority of the fortune 500 companies and 90% of the fortune 100 companies use partner solutions successfully. But it's not just focused on innovation and technology, it's also focused on the business side. How are we helping partners grow their business? And we've been scaling our field teams, our AWS sales teams globally. But what we realized is through partner feedback, in fact, that we were not doing a great job in helping our partners close those opportunities and also bring net new opportunities. So in our field, we actually introduced a new role called the ISV Success Manager, ISMs that are embedded in our field to help partners either close existing opportunities, but also bring net new opportunities to them. And then at re:Invent 2020, we also launched the ISB accelerate program, which enables our field teams, the AWS field teams to get incentive to work with our partners. Cohesity, of course, participates in all of these programs and has access to all of these resources. And they've done a great job in leveraging and bringing our field teams together, which has resulted in hundreds of wins for this data management as a service solution that was launched. >> So you're bringing customers to Cohesity. >> Absolutely. >> Okay, I got to get the side. So they're helping you, how's this relationship going? Could you talk about the relationship on the customer side? How's that going? Douglas, what's your take on that? >> Yeah, absolutely. I mean, it's going great. That's why we chose to partner with AWS and to be quite honest, as Sabina mentioned, we really only launched data management and service back in 2020, late 2020. And at that time we launched with just one service then, right, when we first launched with backup as a service. Now about 15 months later, right? We're on the brink of launching four services that are running on AWS cloud. So, without the level of support, both from a go to market standpoint that Sabina mentioned as well as the engineering and the available technology services that are on the AWS Cloud, right? There's no way we would've been able to spin up new services in such a short period of time. >> Is that Fort Knox and Data Govern, those are the services you're talking about Or is that- >> Yeah, so let me walk you through it. Yeah, so we have Cohesity DataProtect, which is our backup as a service solution. And that helps customers back their data to the cloud, on-prem, SaaS, cloud data like AWS, all in a single service and allows you to recover from ransomware, right? But a couple months ago we also announced a couple new services that you're alluding to John. And that is around Fort Knox and DataGovern. And basically Fort Knox, it is basically our SaaS solution for data isolation to a vaulted copy in the AWS cloud. And the goal of that is to really make it very simple for customers, not only to provide data immutability, but also that extra layer of protection by moving that data offsite and keeping it secure and vaulted away from cyber criminals and ransomware. And what we're doing is simplifying the whole process that normally is manual, right? You either do it manually with tapes or you'll manually replicate data to another data center or even to the cloud, but we're providing it as a service model, basically providing a modern 3-2-1 approach, right? For the cloud era. So, that's what's cool about Fort Knox, DataGovern, right? That's also a new service that we announced a few months ago and that really provides data governance and user behavior analytics services that leverages a lot that AI machine learning that everybody's so excited about. But really the application of that is to automate the discovery of sensitive data. So that could be your credit card numbers, healthcare records, a personal information of customers. So understanding where all that data is, is very important because that's the data that the criminals are going to go after and hold you host. So that's kind of step one. And then step two is again, leveraging machine learning, actually looking at how users are accessing and managing that data is also super important because that's going to help you identify potential anomalies, such as people sharing that data externally, which could be a threat. It could be in improper vault permissions, or other suspicious behaviors that could potentially signify data exfiltration or ransomware attack in progress. >> That's some great innovation. You got the data resiliency, of course, the control mechanism, but the AI piece machine learning is awesome. So congratulations on that innovation. Sabina, I'm listening to conversation and hear you talk. And it reminds me of our chat at re:Invent. And the whole theme of the conference was about the innovation and rapid innovations and how companies are refactoring with the cloud and this NextGen kind of journey. This is a fundamental pillar of AWS's rapid innovation concept with your partners. And I won't say it's new, but it's highly accelerated. How are you guys helping partners be with this rapid innovation, 'cause you're seeing benefits can come faster now, Agile is here. What are some of the programs that you're doing? How are you helping customers take advantage of the rapid innovation with the secret sauce of AWS? >> Yeah, so we have a number of leadership principles, John, and one of them, of course, is customer obsession. We are very focused on making sure we are developing things that our customers need. And we look for these very same qualities when we work with partners such as Cohesity. We want to make sure that it's a win-win approach for both sides because that's what will make the partnership durable over time. And this John, our leadership team at AWS, right from our CEO down believes that partners are critical to our success and as partners lean in, we lean in further. And that's why we signed the strategic collaboration agreement with Cohesity in April, 2020, where data management as a service solution was launch as part of that agreement. And for us, we've launched this solution now and as Doug said, what are the next things we could be doing, right? And just to go back a little bit when Cohesity was developing this solution with us, they used a number of our programs. Especially on the technical side, they used our SaaS factory program, which really helped them build this differentiated solution, especially focused around security compliance and cost optimizing the solution. Now that we've launched this solution, just like Doug mentioned, we are now focused on leveraging other services like security, AIML, and also our analytic services. And the reason for that is Cohesity, as we all know, protects, manages this data for the customer, but we want to make sure that the customer is extracting value from this data. That is why we continue to look, what can we do to continue to differentiate this solution in this market. >> That's awesome. You guys did a great job. I got to say, as it gets more scale, there's more needs for this rapid, I won't say prototyping, but rapid innovation and the Cohesity side does was you guys have been always on point on the back and recovery and now with security and the new modern application development, you guys are in the front row seats of all the action. So, I'll give you the final worry what's going on at Cohesity, give an update on what you guys are doing. What's it like over there these days? How's life give a quick plug for Cohesity. >> Yeah, Cohesity is doing great, right? We're always adding folks to the team, on our team, we have a few open racks open both on the marketing side, as well as the technology advocacy side. And of course, some of our other departments too, and engineering and sales and also our partner teams as well, working with AWS partners such as that. So, in our mind, the data delusion and growth is not going to slow down, right? So in this case, I think all tides raises all the boats here and we're glad to be innovative leader in this space and really looking to be really, the new wave of NextGen data management providers out there that leverages things like AI that leverages cybersecurity at the core and has an ecosystem of partners that we're working with, like AWS, that we're building out to help customers better manage their data. >> It's all great. Data is in the mid center of the value proposition. Sabina, great to see you again, thanks for sharing. And Douglas, great to see you too. Thanks for sharing this experience here in theCUBE. >> Thanks, John. >> Okay, this is theCUBE's AWS Partner Showcase special presentation, speeding innovation with AWS. I'm John Furrier your host of theCUBE. Thanks for watching. (upbeat music)

hey welcome to analytics unleashed i'm robert christensen your host today thank you for joining us today we have three quick wins that drive big gains in the enterprise workloads and today we have olaf with erickson we have john with orok and we have dragon with dxc welcome thank you for joining me gentlemen yeah good to be here thank you thank you good to have you hey olaf let's start off with you what big problems are you trying to solve today that are doing for those quick wins what are you trying to do today top top of mind yeah when we started looking into this microservices for our financial platform we immediately saw the challenges that we have and we wanted to have a strong partner and we have a good relationship with hp before so we turned to hp because we know that they have the technical support that we need the possibilities that we need in our platform to fulfill our requirements and also the reliability that we would need so tell me i think this is really important you guys are starting into a digital wallet space that correct yeah that's correct so we are in a financial platform so we are spanning across the world and delivering our financial services to our end customers well that's not classically what you hear about ericsson diving into what's really started you guys down that path and specifically these big wins around this digitization no what what we could see earlier was that we have a mobile networks right so we have a lot of a strong user base within them uh both kind of networks and in the where we started in the emerging markets uh you normally they have a lot of unbanked people and that people also were the ones that you want to target so be able to instead of going down and use your cash for example to buy your fruits or your electricity bill etc you could use your mobile wallet and and that's how it all started and now we're also turning into the emerged markets also like the western side part of worlds etc that's fantastic and i hey i want to talk to john here john's with o'rock and he's the one of those early adopters of those container platforms for the uh in the united states here the federal government tell us a little bit about that program and what's going on with that john yeah sure absolutely appreciate it yeah so with orock what we've done is we developed one of the first fedramp authorized container platforms that runs in our moderate and soon to be high cloud and what that does is building on the israel platform gave us the capability of offering customers both commercial as well as federal the capability and the flexibility of running their workloads in a you know as a service model where they can customize and typically what customers have to do is they have to either build it internally or if they go to the cloud they have to be able to take what resources are available then tweak to those designs to make what they need so in this architecture built on open source and with our own infrastructure we offer you know very low cost zero egress capability but the also the workload processing that they would need to run data analytics machine language and other types of high performance processing that typically they would need as we move forward in this computer age so john you you touched on a topic that's i think is really critical and you had mentioned open source why is open source a key aspect for this transformation that we're seeing coming up in like the next decade yeah sure yeah with open source we shifted early on to the company to move to open source only to offer the flexibility we didn't want to be set on one particular platform to operate within so we took and built the cloud infrastructure we went with open source as an open architecture that we can scale and grow within because of that we were one of the very first fedramp authorizations built on open source not on a specific platform and what we've seen from that is the increased performance capability that we would get as well as the flexibility to add additional components that typically you don't get on other platforms so it was a it was a good move we went with and one that the customer will definitely benefit from that that's that's huge actually because performance leads to better cost and better cost leads better performance around that i i'm just super super happy with all the advanced work that you always are doing there is fantastic and dragon so so you're in a space that i think is really interesting you're dealing with what everybody likes to talk about that's autonomous vehicles you're working with automobile manufacturers you're dealing with data at a scale that is unprecedented can you just open that door for us to talk to about these big big wins that you're trying to get over the line with these enterprises yeah absolutely and um thank you robert we approach uh leveraging esmeral from the data fabric angle we practically have a fully integrated the esmeral data fabric into our robotic drive solution rewarding drive solution is actually a game changer as you've mentioned in accelerating the development of autonomous driving vehicles it's a an end-to-end hyper-scale machine learning and ai platform as i mentioned based on the esmeralda data fabric which is used by the some of the largest manufacturers in the world for development of their autonomous driving algorithms and i think we all in technology i think and following up at the same type of news and research right across the globe in in this area so we're pretty proud that we're one of the leaders in actually providing uh hyperscale machine learning platforms for uh kind manufacturers some of them i cannot talk about but bmw is one of uh one of the current manufacturers that we provide uh these type of solutions and they have publicly spoken about their uh d3 platform uh data driven development platform uh just to give you an idea um of the scale as robert mentioned uh daily we collect over 1.5 petabytes of data of raw data did you say daily data daily the storage capacity is over 250 petabytes and growing uh there's over 100 000 cores and over 200 gpus in the in in the compute area um over 50 50 petabytes of data is delivered every two weeks into a hardware in loop right for testing and we have daily uh thousands of engineers and data scientists accessing the relevant data and developing machine learning models on the daily basis right part of it is the simulation right simulation cuts the cost as well as the uh time right for developing of the autonomous uh driving algorithms and uh the the simulations are taking probably 75 percent of the research uh that's being done on this platform that's amazing dragon i i i i the more i get involved with that and i've been part of these conversations with a number of the folks that are involved with it i i computer science me my geekiness my little propeller head starts coming out i might just blows my mind and i think so i'm going to pivot back over to olaf oh left so you're talking about something that is a global network of financial services okay correct and the flow of transactional typically non-relational transactional data flows to actual transactions going through you have issues of potential fraud you have issues a safety and you have multi-geographic regional problems with data and data privacy how are you guys addressing that today so so to answer that question today we have managed to solve that using the container platform to together with the data fabric but as you say we need to span across different regions we need to have the data as secure as possible because we have a lot of legal aspects to look into because if our data disappears but your money is also disappearing so it's a really important area for us with the security and the reliability of the platforms so so that's why we also went this way to make sure that we have this strong partner that could help us with this because just looking at where we are deployed in in more than 23 countries today and and we it's processing more than 900 million us dollars per day in our systems currently so it is a lot of money passing through and you need to take security in a it's as it's a very important point right it really is it really is and so uh john i mean you you uh obviously are dealing with you know a lot of folks that have three letters as acronyms around the government agencies and uh they range in various degrees of certa of security when you say fedramp i mean what could you just uh articulate why the esmerald platform was something that you selected to go to that fedrak compliant container platform because i think that's that that kind of speaks to the to the industrial strength of what we're talking about yeah it all comes down to being able to offer a product that's secure that the customers can trust and when we went with fedramp fedramp has very stringent security requirements that have monthly poems which are performance reviews and and updates that need to be done if not on a daily basis on a monthly basis so the customers there's a lot that goes on behind the scenes that they don't are able to articulate and what by selecting the hp esmerald platform for containers um one of the key strengths that we looked at was the esmo fabric and it's all about the data it's all about securing the data moving the data transferring the data and from a customer's perspective they want to be able to operate in an environment that they can trust no different than being able to turn on their lights or making sure there's water in their utilities you know containers with the israel platform built on orok's infrastructure gives that capability fedramp enables the security tied to the platform that we're able to follow so it's government uh guided which includes this and many and over hundreds of controls that typically you know the customers don't have time or the capability to address so our commercial customers benefit our federal customers you know that you discuss they're able to follow and check the box to meet those requirements and the container platform gives us a capability where now we're able to move files which we'll hear about through the optimal fabric and then we're able to run the workloads in the containers themselves and give isolation and the security element of fed wrapping esmeral gave us that capability in order to paint that environment fedramp authorized that the customers benefit from from security so they have confidence in running their workloads using their data and able to focus on their core job at hand and not worry about their infrastructure the fundamental requirement isn't it that that isolation between that compute and storage and going up a layer there in in a way that provides them a set of services that they can i wouldn't say set it and forget it but really had the confidence that what they're getting is the best performance for the dollars that they're spending uh john my hat's off to what the work that you all do in there thank you we appreciate it yeah yeah and dragon i want to i wanted to pivot a little bit here because you are primarily the the operator what i consider one of the largest data fabrics on the on the planet for that matter um and i just want to talk a little bit about the openness of our architecture right of all the multiple protocols that we support that allow for you know you know some people may have selected a different set of application deployment models and virtualization models that allow to plug into the data fabric you know it did can you talk a little bit about that yeah and i i think um in my mind right um to operate uh such a uh data fabric at scale right um there were three key elements that we were looking for right uh that we found in uh esmeralda fabric ring the first one was a speed cost and scalability right the second one was the globally distributed data lake or ability to distribute data globally and third was certainly the strength of our partnership with with hpe in this case right so if you look at the uh as well data fabric it's it's fast it's cost effective and it's certainly highly scalable because we as you just mentioned stretch the uh sort of the capabilities of the data fabric to hundreds of petabytes and over a million the data points if you will and it important what was important for us was that the esmeralda fabric actually eliminates the need for multiple vendor solutions which would be otherwise required right because it provides integrated file system database or or a data lake right and the data management on top of it right usually you would probably need to incorporate multiple tools right from different vendors and the file system itself it's it's so important right when you're working at scale like this right and honestly in our research maybe there are three file systems in the world that can support uh this kind of size of the auto data fabric the distributed data lake was also important to us and the reason for that is you can imagine that these large car manufacturers are testing and have testing vehicles all around the world right they're not just doing it locally around the uh their data their id centers right so uh collecting the data and this 1.5 petabytes example right uh for for bmw on a daily basis it's it's it's really challenging unless you have the ability to actually leverage the data in a distributed data like fashion right so data can basically reside in different data centers globally or even on-premise and in cloud environments which became uh very important later because a lot of this car manufacturers actually have oems right that would like to get either portions of the data or get access to the data in a in different environments not necessarily in their data center um and truly i think uh to build something at this scale right uh you you need a strong partner and we certainly had that in hpe and uh we got the comprehensive support right for uh for the software um but but more importantly i think uh partner that clearly understood uh criticality of the data fabric trend and the need for the vice fast response right to our clients and you know jointly i think we met all the challenges and it's so doing i think we made the esmo data fabric a much better and stronger product over the over the last few years that's fantastic thank you dragon appreciate it uh hey so if we're going to wrap up here any last words olaf do you want to share with us no looking forward now in from our perspective on helping out with the kobe 19 situation that we have uh enabling people to still be in the market without actually touching each other and and and leaving maybe for action market and being at home etc doing those transactions that's great thank you john in last comment yeah thanks yeah uh look for uh a joint offering announcement coming up between hpe and orok where we're going to be offering sandbox as a service where the data analytics and machine language where people can actually test drive the actual environment as a service and if they like it then they can move into a production-wise environment so stay tuned for that that's great john thank you for that and hey dragon last words yeah last words um we're pretty happy what we have done already for car manufacturers we're taking this solution right in terms of the uh distributed data-like capabilities as well as the uh hyperscale machine learning and ai platform to other industries and we hope to do it jointly with you well we hope that you do it with us as well so thank you very much everybody gentlemen thank you so much for joining us i appreciate it thank you very much thank you very much hey this is robert christensen with analytics unleashed i want to thank all of our guests here today and we'll catch you next time thank you for joining us bye [Music] [Music] [Music] easy [Music] you

>>From around the globe. It's the cube with digital coverage of an AI ops virtual forum brought to you by Broadcom. >>Welcome to the AI ops virtual forum. Finally, some Artan extended to be talking with rich lane now, senior analyst, serving infrastructure and operations professionals at Forrester. Rich. It's great to have you today. >>Thank you for having me. I think it's going to be a really fun conversation to have today. >>It is. We're going to be setting the stage for, with Richard, for the it operations challenges and the need for AI ops. That's kind of our objective here in the next 15 minutes. So rich talk to us about some of the problems that enterprise it operations are facing now in this year, that is 2020 that are going to be continuing into the next year. >>Yeah, I mean, I think we've been on this path for a while, but certainly the last eight months has, uh, has accelerated, uh, this problem and, and brought a lot of things to light that, that people were, you know, they were going through the day to day firefighting as their goal way of life. Uh, it's just not sustainable anymore. You a highly distributed environment or in the need for digital services. And, you know, one of them has been building for a while really is in the digital age, you know, we're providing so many, uh, uh, the, the interactions with customers online. Um, we've, we've added these layers of complexity, um, to applications, to infrastructure, you know, or we're in the, in the cloud or a hybrid or multi-cloud, or do you know you name it using cloud native technologies? We're using legacy stuff. We still have mainframe out there. >>Uh, you know, the, just the, the vast amount of things we have to keep track of now and process and look at the data and signals from, it's just, it's a really untenable for, for humans to do that in silos now, uh, in, in, you know, when you add to that, you know, when companies are so heavily invested in gone on the digital transformation path, and it's accelerated so much in the last, uh, year or so that, you know, we're getting so much of our business in revenue derived from these services that they become core to the business. They're not afterthoughts anymore. It's not just about having a website presence. It's, it's about deriving core business value from the services you're providing to your, through your customers. And a lot of cases, customers you're never going to meet or see at that. So it's even more important to be vigilant. >>And on top of the quality of that service that you're giving them. And then when you think about just the staffing issues we have, there's just not enough bodies to go around it in operations anymore. Um, you know, we're not going to be able to hire, you know, like we did 10 years ago, even. Uh, so that's where we need the systems to be able to bring those operational efficiencies to bear. When we say operational efficiencies, we don't mean, you know, uh, lessening head count because we can't do that. That'd be foolish. What we mean is getting the head count. We have back to burping on and higher level things, you know, working on, uh, technology refreshes and project work that that brings better digital services to customers and get them out of doing these sort of, uh, low, uh, complexity, high volume tasks that they're spending at least 20%, if not more on our third day, each day. So I think that the more we can bring intelligence to bear and automation to take those things out of their hands, the better off we are going forward. >>And I'm sure those workers are wanting to be able to have the time to deliver more value, more strategic value to the organization, to their role. And as you're saying, you know, was the demand for digital services is spiking. It's not going to go down and as consumers, if w if we have another option and we're not satisfied, we're going to go somewhere else. So, so it's really about not just surviving this time right now, it's about how do I become a business that's going to thrive going forward and exceeding expectations that are now just growing and growing. So let's talk about AI ops as a facilitator of collaboration, across business folks, it folks developers, operations, how can it facilitate collaboration, which is even more important these days? >>Yeah. So one of the great things about it is now, you know, years ago, have I gone years, as they say, uh, we would buy a tool to fit each situation. And, you know, someone that worked in network and others who will somebody worked in infrastructure from a, you know, Linux standpoint, have their tool, somebody who's from storage would have their tool. And what we found was we would have an incident, a very high impact incident occur. Everybody would get on the phone, 24 people all be looking at their siloed tool, they're siloed pieces of data. And then we'd still have to try to like link point a to B to C together, you know, just to institutional knowledge. And, uh, there was just ended up being a lot of gaps there because we couldn't understand that a certain thing happening over here was related to an advantage over here. >>Um, now when we bring all that data into one umbrella, one data Lake, whatever we want to call it, a lot of smart analytics to that data, uh, and normalize that data in a way we can contextualize it from, you know, point a to point B all the way through the application infrastructure stack. Now, the conversation changes now, the conversation changes to here is the problem, how are we going to fix it? And we're getting there immediately versus three, four or five hours of, uh, you know, hunting and pecking and looking at things and trying to try to extrapolate what we're seeing across disparate systems. Um, and that's really valuable. And in what that does is now we can change the conversation for measuring things. And in server up time and data center, performance metrics as to how are we performing as a business? How are we overall in, in real time, how are businesses being impacted by service disruption? >>We know how much money losing per minute hour, or what have you, uh, and what that translate lights into brand damage and things along those lines, that people are very interested in that. And, you know, what is the effect of making decisions either brief from a product change side? You know, if we're, we're, we're always changing the mobile apps and we're always changing the website, but do we understand what value that brings us or what negative impact that has? We can measure that now and also sales, marketing, um, they run a campaign here's your, you know, coupon for 12% off today only, uh, what does that drive to us with user engagement? We can measure that now in real time, we don't have to wait for those answers anymore. And I think, you know, having all those data and understanding the cause and effect of things increases, it enhances these feedback loops of we're making decisions as a business, as a whole to make, bring better value to our customers. >>You know, how does that tie into ops and dev initiatives? How does everything that we do if I make a change to the underlying architectures that help move the needle forward, does that hinder things, uh, all these things factor into it. In fact, there into the customer experience, which is what we're trying to do at the end of the day, w w whether operations people like it or not, we are all in the customer experience business now. And we have to realize that and work closer than ever with our business and dev partners to make sure we're delivering the highest level of customer experience we can. >>Uh, customer experience is absolutely critical for a number of reasons. I always kind of think it's inextricably linked with employee experience, but let's talk about long-term value because as organizations and every industry has pivoted multiple times this year and will probably continue to do so for the foreseeable future, for them to be able to get immediate value that let's, let's not just stop the bleeding, but let's allow them to get a competitive advantage and be really become resilient. What are some of the, uh, applications that AI ops can deliver with respect to long-term value for an organization? >>Yeah, and I think that it's, you know, you touched upon this a very important point that there is a set of short term goals you want to achieve, but they're really going to be looking towards 12, 18 months down the road. What is it going to have done for you? And I think this helps framing out for you what's most important because it'd be different for every enterprise. Um, and it also shows the ROI of doing this because there is some, you know, change is going to be involved with things you're gonna have to do. But when you look at the, the, the longer time horizon of what it brings to your business as a whole, uh it's to me, at least it all seems, it seems like a no brainer to not do it. Um, you know, thinking about the basic things, like, you know, faster remediation of, of, uh, client impacting incidents, or maybe, maybe even predictive of sort of detection of these incidents that will affect clients. >>So now you're getting, you know, at scale, you know, it's very hard to do when you have hundreds of thousands of optics of the management that relate to each other, but now you're having letting the machines and the intelligence layer find out where that problem is. You know, it's not the red thing, it's the yellow thing. Go look at that. Um, it's reducing the amount of finger pointing and what have you like resolved between teams now, everybody's looking at the same data, the same sort of, uh, symptoms and like, Oh yeah, okay. This is telling us, you know, here's the root cause you should investigate this huge, huge thing. Um, and, and it's something we never thought we'd get to where, uh, this, this is where we smart enough to tell us these things, but this, again, this is the power of having all the data under one umbrella >>And the smart analytics. >>Um, and I think really, you know, it's a boat. Uh, if you look at where infrastructure and operations people are today, and especially, you know, eight months, nine months, whatever it is into the pandemic, uh, a lot of them are getting really burnt out with doing the same repetitive tasks over and over again. Um, just trying to keep the lights on, you know, we need, we need to extract those things for those people, uh, just because it just makes no sense to do something over and over again, the same remediation step, just we should automate those things. So getting that sort of, uh, you know, drudgery off their hands, if you will, and, and get them into, into all their important things they should be doing, you know, they're really hard to solve problems. That's where the human shine, um, and that's where, you know, having a, you know, really high level engineers, that's what they should be doing, you know, and just being able to do things I >>Think in a much faster, >>In a more efficient manner, when you think about an incident occurring, right. In, in a level, one technician picks that up and he goes and triaged that maybe run some tests. He has a script, >>Uh, or she, uh, and, >>You know, uh, they open a ticket and they enrich the ticket. They call it some log files. They can look up for the servers on it. You're in an hour and a half into an incident before anyone's even looked at it. If we could automate all of that, >>Why wouldn't we, that makes it easier for everyone. Um, >>Yeah. And I really think that's where the future is, is, is, is bringing this intelligent automation to bear, to take, knock down all the little things that consume the really, the most amount of time. When you think about it, if you aggregate it over the course of a quarter or a year, a great deal of your time is spent just doing that minutiae again, why don't we automate that? And we should. So I really think that's, that's where you get to look long-term. I think also the sense of we're going to be able to measure everything in the sense of business KPIs versus just IT-centric KPIs. That's really where we going to get to in the digital age. And I think we waited too long to do that. I think our operations models were all voted. I think, uh, you know, a lot of, a lot of the KPIs we look at today are completely outmoded. They don't really change if you think about it. When we look at the monthly reports over the course of a year, uh, so let's do something different. And now having all this data and the smart analytics, we can do something different. Absolutely. I'm glad >>That you brought up kind of looking at the impact that AI ops can make on, on minutiae and burnout. That's a really huge problem that so many of us are facing in any industry. And we know that there's some amount of this that's going to continue for a while longer. So let's get our let's leverage intelligent automation to your point, because we can to be able to allow our people to not just be more efficient, but to be making a bigger impact. And there's that mental component there that I think is absolutely critical. I do want to ask you what are some of these? So for those folks going, all right, we've got to do this. It makes sense. We see some short-term things that we need. We need short-term value. We need long-term value as you've just walked us through. What are some of the obstacles that you'd say, Hey, be on the lookout for this to wipe it out of the way. >>Yeah. I, I think there's, you know, when you think about the obstacles, I think people don't think about what are big changes for their organization, right? You know, they're, they're going to change process. They're going to change the way teams interact. They're they're going to change a lot of things, but they're all for the better. So what we're traditionally really bad in infrastructure and operations is communication, marketing, a new initiative, right? We don't go out and get our peers agreement to it where the product owner is, you know, and say, okay, this is what it gets you. This is where it changes. People just hear I'm losing something, I'm losing control over something. You're going to get rid of the tools that I have, but I love I've spent years building out perfecting, um, and that's threatening to people and understandably so because people think if I start losing tools, I start losing head count. >>And then, whereas my department at that point, um, but that's not what this is all about. Uh, this, this isn't a replacement for people. This isn't a replacement for teams. This isn't augmentation. This is getting them back to doing the things they should be doing and less of the stuff they shouldn't be doing. And frankly, it's, it's about providing better services. So when in the end, it's counterintuitive to be against it because it's gonna make it operations look better. It's gonna make us show us that we are the thought leaders in delivering digital services that we can, um, constantly be perfecting the way we're doing it. And Oh, by the way, we can help the business be better. Also at the same time. Uh, I think some of the mistakes people really don't make, uh, really do make, uh, is not looking at their processes today, trying to figure out what they're gonna look like tomorrow when we bring in advanced automation and intelligence, uh, but also being prepared for what the future state is, you know, in talking to one company, they were like, yeah, we're so excited for this. >>Uh, we, we got rid of our old 15 year old laundering system and the same day we stepped a new system. Uh, one problem we had though, was we weren't ready for the amount of incidents that had generated on day one. And it wasn't because we did anything wrong or the system was wrong or what have you. It did the right thing actually, almost too. Well, what it did is it uncovered a lot of really small incidents through advanced correlations. We didn't know we had, so there were things lying out there that were always like, huh, that's weird. That system acts strange sometimes, but we can never pin it down. We found all of those things, which is good. It goes, but it kind of made us all kind of sit back and think, and then our readership are these guys doing their job. Right? >>And then we had to go through an evolution of, you know, just explaining we were 15 years behind from a visibility standpoint to our environment, but technologies that we deployed in applications had moved ahead and modernized. So this is like a cautionary tale of falling too far behind from a sort of a monitoring and intelligence and automation standpoint. Um, so I thought that was a really good story for something like, think about as Eagle would deploy these modern systems. But I think if he really, you know, the marketing to people, so they're not threatened, I think thinking about your process and then what's, what's your day one and then look like, and then what's your six and 12 months after that looks like, I think settling all that stuff upfront just sets you up for success. >>All right. Rich, take us home here. Let's summarize. How can clients build a business case for AI ops? What do you recommend? >>Yeah. You know, I actually get that question a lot. It's usually, uh, almost always the number one, uh, question in, in, um, you know, webinars like this and conversations that, that the audience puts in. So I wouldn't be surprised, but if that was true, uh, going forward from this one, um, yeah, people are like, you know, Hey, we're all in. We want to do this. We know this is the way forward, but the guy who writes the checks, the CIO, the VP of ops is like, you know, I I've signed lots of checks over the years for tools wise is different. Um, and when I guide people to do is to sit back and, and start doing some hard math, right. Uh, one of the things that resonates with the leadership is dollars and cents. It's not percentages. So saying, you know, it's, it brings us a 63% reduction and MTTR is not going to resonate. >>Uh, Oh, even though it's a really good number, you know, uh, I think what it is, you have to put it in terms of avoid, if we could avoid that 63%. Right. You know, um, what does that mean for our, our digital services as far as revenue, right. We know that every hour system down, I think, uh, you know, typically in the market, you see is about $500,000 an hour for enterprise. We'll add that up over the course of the year. What are you losing in revenue? Add to that brand damage loss of customers, you know, uh, Forrester puts out a really big, uh, casino, um, uh, customer experience index every year that measures that if you're delivering good Udall services, bad digital services, if you could raise that up, what does that return to you in revenue? And that's a key thing. And then you just look at the, the, uh, hours of lost productivity. >>I call it, I might call it something else, but I think it's a catchy name. Meaning if a core internal system is down say, and you know, you have a customer service desk of a thousand customer service people, and they can't do that look up or fix that problem for clients for an hour. How much money does that lose you? And you multiply it out. You know, average customer service desk person makes X amount an hour times this much time. This many times it happens. Then you start seeing the real, sort of a power of AI ops for this incident avoidance, or at least lowering the impact of these incidents. And people have put out in graphs and spreadsheets and all this, and then I'm doing some research around this actually to, to, to put out something that people can use to say, the project funds itself in six to 12 months, it's paid for itself. And then after that it's returning money to the business. Why would you not do that? And when you start framing the conversation, that way, the little light bulb turn on for the people that sign the checks. For sure. >>That's great advice for folks to be thinking about. I loved how you talked about the 63% reduction in something. I think that's great. What does it impact? How does it impact the revenue for the organization? If we're avoiding costs here, how do we drive up revenue? So having that laser focus on revenue is great advice for folks in any industry, looking to build a business case for AI ops. I think you set the stage for that rich beautifully, and you were right. This was a fun conversation. Thank you for your time. Thank you. And thanks for watching >>From around the globe with digital coverage. >>Welcome back to the Broadcom AI ops, virtual forum, Lisa Martin here talking with Eastman Nasir global product management at Verizon. We spent welcome back. >>Hi. Hello. Uh, what a pleasure. >>So 2020 the year of that needs no explanation, right? The year of massive challenges and wanting to get your take on the challenges that organizations are facing this year as the demand to deliver digital products and services has never been higher. >>Yeah. So I think this is something it's so close to all the far far, right? It's, uh, it's something that's impacted the whole world equally. And I think regardless of which industry you rent, you have been impacted by this in one form or the other, and the ICT industry, the information and communication technology industry, you know, Verizon being really massive player in that whole arena. It has just been sort of struck with this massive consummation we have talked about for a long time, we have talked about these remote surgery capabilities whereby you've got patients in Kenya who are being treated by an expert sitting in London or New York, and also this whole consciousness about, you know, our carbon footprint and being environmentally conscious. This pandemic has taught us all of that and brought us to the forefront of organization priorities, right? The demand. I think that's, that's a very natural consequence of everybody sitting at home. >>And the only thing that can keep things still going is this data communication, right? But I wouldn't just say that that is, what's kind of at the heart of all of this. Just imagine if we are to realize any of these targets of the world is what leadership is setting for themselves. Hey, we have to be carbon neutral by X year as a country, as a geography, et cetera, et cetera. You know, all of these things require you to have this remote working capabilities, this remote interaction, not just between humans, but machine to machine interactions. And this there's a unique value chain, which is now getting created that you've got people who are communicating with other people or communicating with other machines, but the communication is much more. I wouldn't even use the term real time because we've used real time for voice and video, et cetera. >>We're talking low latency, microsecond decision-making that can either cut somebody's, you know, um, our trees or that could actually go and remove the tumor, that kind of stuff. So that has become a reality. Everybody's asking for it, remote learning, being an extremely massive requirement where, you know, we've had to enable these, uh, these virtual classrooms ensuring the type of connectivity, ensuring the type of type of privacy, which is just so, so critical. You can't just have everybody in a go on the internet and access a data source. You have to be concerned about the integrity and security of that data as the foremost. So I think all of these things, yes, we have not been caught off guard. We were pretty forward-looking in our plans and our evolution, but yes, it's fast track the journey that we would probably believe we would have taken in three years. It has brought that down to two quarters where we've had to execute them. >>Right. Massive acceleration. All right. So you articulated the challenges really well. And a lot of the realities that many of our viewers are facing. Let's talk now about motivations, AI ops as a tool, as a catalyst for helping organizations overcome those challenges. >>So yeah. Now on that I said, you can imagine, you know, it requires microsecond decision-making which human being on this planet can do microsecond decision-making on complex network infrastructure, which is impacting end user applications, which have multitudes of effect. You know, in real life, I use the example of a remote surgeon. Just imagine that, you know, even because of you just use your signal on the quality of that communication for that microsecond, it could be the difference between killing somebody in saving somebody's life. And it's not predictable. We talk about autonomous vehicles. Uh, we talk about this transition to electric vehicles, smart motorways, et cetera, et cetera, in federal environment, how is all of that going to work? You have so many different components coming in. You don't just have a network and security anymore. You have software defined networking. That's coming, becoming a part of that. >>You have mobile edge computing that is rented for the technologies. 5g enables we're talking augmented reality. We're talking virtual reality. All of these things require that resources and why being carbon conscious. We told them we just want to build a billion data centers on this planet, right? We, we have to make sure that resources are given on demand and the best way of resources can be given on demand and could be most efficient is that the thing is being made at million microsecond and those resources are accordingly being distributed, right? If you're relying on people, sipping their coffees, having teas, talking to somebody else, you know, just being away on holiday. I don't think we're going to be able to handle that one that we have already stepped into. Verizon's 5g has already started businesses on that transformational journey where they're talking about end user experience personalization. >>You're going to have events where people are going to go, and it's going to be three-dimensional experiences that are purely customized for you. How, how does that all happen without this intelligence sitting there and a network with all of these multiple layers? So spectrum, it doesn't just need to be intuitive. Hey, this is my private IP traffic. This is public traffic. You know, it has to not be in two, or this is an application that I have to prioritize over another task to be intuitive to the criticality and the context of those transactions. Again, that's surgeons. So be it's much more important than postman setting and playing a video game. >>I'm glad that you think that that's excellent. Let's go into some specific use cases. What are some of the examples that you gave? Let's kind of dig deeper into some of the, what you think are the lowest hanging fruit for organizations kind of pan industry to go after. >>Excellent. Brian, and I think this, this like different ways to look at the lowest hanging fruit, like for somebody like revising who is a managed services provider, you know, very comprehensive medicines, but we obviously have food timing, much lower potentially for some of our customers who want to go on that journey. Right? So for them to just go and try and harness the power of the foods might be a bit higher hanging, but for somebody like us, the immediate ones would be to reduce the number of alarms that are being generated by these overlay services. You've got your basic network, then you've got your whole software defined networking on top of that, you have your hybrid clouds, you have your edge computing coming on top of that. You know? So all of that means if there's an outage on one device on the network, I want to make this very real for everybody, right? >>It's like device and network does not stop all of those multiple applications or monitoring tools from raising and raising thousands of alarm and everyone, one capacity. If people are attending to those thousands of alarms, it's like you having a police force and there's a burglary in one time and the alarm goes off and 50 bags. How, how are you kind of make the best use of your police force? You're going to go investigate 50 bags or do you want to investigate where the problem is? So it's as real as that, I think that's the first wins where people can save so much cost, which is coming from being wasted and resources running around, trying to figure stuff out immediately. I'm tied this with network and security network and security is something which has you did even the most, you know, I mean single screens in our engineering, well, we took it to have network experts, separate people, security experts, separate people to look for different things, but there are security events that can impact the performance of a network. >>And then just drop the case on the side of et cetera, which could be falsely attributed to the metric. And then if you've got multiple parties, which are then the chapter clear stakeholders, you can imagine the blame game that goes on finding fingers, taking names, not taking responsibility that don't has all this happened. This is the only way to bring it all together to say, okay, this is what takes priority. If there's an event that has happened, what is its correlation to the other downstream systems, devices, components, and these are applications. And then subsequently, you know, like isolating it to the right cost where you can most effectively resolve that problem. Thirdly, I would say on demand, virtualized resource, virtualized resources, the heart and soul, the spirit of status that you can have them on demand. So you can automate the allocation of these resources based on customer's consumption their peaks, their cramps, all of that comes in. >>You see, Hey, typically on a Wednesday, the traffic was up significantly for this particular application, you know, going to this particular data center, you could have this automated system, uh, which is just providing those resources, you know, on demand. And so it is to have a much better commercial engagement with customers and just a much better service assurance model. And then one more thing on top of that, which is very critical is that as I was saying, giving that intelligence to the networks to start having context of the criticality of a transaction, that doesn't make sense to them. You can't have that because for that, you need to have this, you know, monkey their data. You need to have multi-cam system, which are monitoring and controlling different aspects of your overall end user application value chain to be communicating with each other. And, you know, that's the only way to sort of achieve that goal. And that only happens with AI. It's not possible >>So it was when you clearly articulated some obvious, low hanging fruit and use cases that organizations can go after. Let's talk now about some of the considerations, you talked about the importance of a network and AI ops, the approach I assume, needs to be modular support needs to be heterogeneous. Talk to us about some of those key considerations that you would recommend. >>Absolutely. So again, basically starting with the network, because if there's, if the metrics sitting at the middle of all of this is not working, then things can communicate with each other, right? And the cloud doesn't work, nothing metal. That's the hardest part of this, but that's the frequency. When you talk about machine to machine communication or IOT, it's just the biggest transformation of the span of every company is going for IOT now to drive those costs, efficiencies, and had, something's got some experience, the integrity of the topic karma, right? The security, integrity of that. How do you maintain integrity of your data beyond just a secure network components? That is true, right? That's where you're getting to the whole arena blockchain technologies, where you have to use digital signatures or barcodes that machine then, and then an intelligence system is automatically able to validate and verify the integrity of the data and the commands that are being executed by those end-user told them what I need to tell them that. >>So it's IOT machines, right? That is paramount. And if anybody is not keeping that into their equation, that in its own self is any system that is therefore maintaining the integrity of your commands and your hold that sits on those, those machines. Right? Second, you have your network. You need to have any else platform, which is able to restless all the fast network information, et cetera. And coupled with that data integrity piece, because for the management, ultimately they need to have a coherent view of the analytics, et cetera, et cetera. They need to know where the problems are again, right? So let's say if there's a problem with the integrity of the commands that are being executed by the machine, that's a much bigger problem than not being able to communicate with that machine and the best thing, because you'd rather not talk to the machine or have to do anything if it's going to start doing wrong things. >>So I think that's where it is. It's very intuitive. It's not true. You have to have subsequently if you have some kind of faith and let me use that use case self autonomous vehicles. Again, I think we're going to see in the next five years, because he's smart with the rates, et cetera, it won't separate autonomous cars. It's much more efficient, it's much more space, et cetera, et cetera. So within that equation, you're going to have systems which will be specialists in looking at aspects and transactions related to those systems. For example, in autonomous moving vehicles, brakes are much more important than the Vipers, right? So this kind of intelligence, it will be multiple systems who have to sit, N nobody has to, one person has to go in one of these systems. I think these systems should be open source enough that they, if you were able to integrate them, right, if something's sitting in the cloud, you were able to integrate for that with obviously the regard of the security and integrity of your data that has to traverse from one system to the other extremely important. >>So I'm going to borrow that integrity theme for a second, as we go into our last question, and that is this kind of take a macro look at the overall business impact that AI ops can help customers make. I'm thinking of, you know, the integrity of teams aligning business in it, which we probably can't talk about enough. We're helping organizations really effectively measure KPIs that deliver that digital experience that all of us demanding consumers expect. What's the overall impact. What would you say in summary fashion? >>So I think the overall impact is a lot of costs. That's customized and businesses gives the time to the time of enterprises. Defense was inevitable. It's something that for the first time, it will come to life. And it's something that is going to, you know, start driving cost efficiencies and consciousness and awareness within their own business, which is obviously going to have, you know, it domino kind of an effect. So one example being that, you know, you have problem isolation. I talked about network security, this multi-layers architecture, which enables this new world of 5g, um, at the heart of all of it, it has to identify the problem to the source, right? Not be bogged down by 15 different things that are going wrong. What is causing those 15 things to go wrong, right? That speed to isolation in its own sense can make millions and millions of dollars to organizations after we organize it. Next one is obviously overall impacted customer experience. Uh, 5g was given out of your customers, expecting experiences from you, even if you're not expecting to deliver them in 2021, 2022, it would have customers asking for those experience or walking away, if you do not provide those experience. So it's almost like a business can do nothing every year. They don't have to reinvest if they just want to die on the line, businesses want remain relevant. >>Businesses want to adopt the latest and greatest in technology, which enables them to, you know, have that superiority and continue it. So from that perspective that continue it, he will read that they write intelligence systems that tank rationalizing information and making decisions supervised by people, of course were previously making some of those. >>That was a great summary because you're right, you know, with how demanding consumers are. We don't get what we want quickly. We churn, right? We go somewhere else and we could find somebody that can meet those expectations. So it has been thanks for doing a great job of clarifying the impact and the value that AI ops can bring to organizations that sounds really now is we're in this even higher demand for digital products and services, which is not going away. It's probably going to only increase it's table stakes for any organization. Thank you so much for joining me today and giving us your thoughts. >>Pleasure. Thank you. We'll be right back with our next segment. >>Digital applications and services are more critical to a positive customer and employee experience than ever before. But the underlying infrastructure that supports these apps and services has become increasingly complex and expanding use of multiple clouds, mobile and microservices, along with modern and legacy infrastructure can make it difficult to pinpoint the root cause when problems occur, it can be even more difficult to determine the business impact your problems that occur and resolve them efficiently. AI ops from Broadcom can help first by providing 360 degree visibility, whether you have hybrid cloud or a cloud native AI ops from Broadcom provides a clear line of sight, including apt to infrastructure and network visibility across hybrid environments. Second, the solution gives you actionable insights by correlating an aggregating data and applying AI and machine learning to identify root causes and even predict problems before users are impacted. Third AI ops from Broadcom provides intelligent automation that identifies potential solutions when problems occur applied to the best one and learns from the effectiveness to improve response in case the problem occurs. Again, finally, the solution enables organizations to achieve digit with jelly by providing feedback loops across development and operations to allow for continuous improvements and innovation through these four capabilities. AI ops from Broadcom can help you reduce service outages, boost, operational efficiency, and effectiveness and improve customer and employee experience. To learn more about AI ops from Broadcom, go to broadcom.com/ai ops from around the globe. >>It's the cube with digital coverage of AI ops virtual forum brought to you by Broadcom. >>Welcome back to the AI ops virtual forum, Lisa Martin here with Srinivasan, Roger Rajagopal, the head of product and strategy at Broadcom. Raj, welcome here, Lisa. I'm excited for our conversation. So I wanted to dive right into a term that we hear all the time, operational excellence, right? We hear it everywhere in marketing, et cetera, but why is it so important to organizations as they head into 2021? And tell us how AI ops as a platform can help. >>Yeah. Well, thank you. First off. I wanna, uh, I want to welcome our viewers back and, uh, I'm very excited to, uh, to share, um, uh, more info on this topic. You know, uh, here's what we believe as we work with large organizations, we see all our organizations are poised to get out of the, uh, the pandemic and look for a brood for their own business and helping customers get through this tough time. So fiscal year 2021, we believe is going to be a combination of, uh, you know, resiliency and agility at the, at the same time. So operational excellence is critical because the business has become more digital, right? There are going to be three things that are going to be more sticky. Uh, you know, remote work is going to be more sticky, um, cost savings and efficiency is going to be an imperative for organizations and the continued acceleration of digital transformation of enterprises at scale is going to be in reality. So when you put all these three things together as a, as a team that is, uh, you know, that's working behind the scenes to help the businesses succeed, operational excellence is going to be, make or break for organizations, >>Right with that said, if we kind of strip it down to the key capabilities, what are those key capabilities that companies need to be looking for in an AI ops solution? >>Yeah, you know, so first and foremost, AI ops means many things to many, many folks. So let's take a moment to simply define it. The way we define AI ops is it's a system of intelligence, human augmented system that brings together full visibility across app infra and network elements that brings together disparate data sources and provides actionable intelligence and uniquely offers intelligent automation. Now, the, the analogy many folks draw is the self-driving car. I mean, we are in the world of Teslas, uh, but you know, uh, but self-driving data center is it's too far away, right? Autonomous systems are still far away. However, uh, you know, application of AI ML techniques to help deal with volume velocity, veracity of information, uh, is, is critical. So that's how we look at AI ops and some of the key capabilities that we, uh, that we, uh, that we work with our customers to help them on our own for eight years. >>Right? First one is eyes and ears. What we call full stack observability. If you do not know what is happening in your systems, uh, you know, that that serve up your business services. It's going to be pretty hard to do anything, uh, in terms of responsiveness, right? So from stack observability, the second piece is what we call actionable insights. So when you have disparate data sources, tools, sprawls data coming at you from, uh, you know, uh, from a database systems, it systems customer management systems, ticketing systems. How do you find the needle from the haystack? And how do you respond rapidly from a myriad of problems as CEO of red? The third area is what we call intelligent automation. Well, identifying the problem to act on is important, and then acting on automating that and creating, uh, a recommendation system where, uh, you know, you can be proactive about it is even more important. And finally, all of this focuses on efficiency. What about effectiveness? Effectiveness comes when you create a feedback loop, when what happens in production is related to your support systems and your developers so that they can respond rapidly. So we call that continuous feedback. So these are the four key capabilities that, uh, you know, uh, you should look for in an AI ops system. And that's what we offer as well. >>Russia, there's four key capabilities that businesses need to be looking for. I'm wondering how those help to align business. And it it's, again like operational excellence. It's something that we talk about a lot is the alignment of business. And it a lot more challenging, easier said than done, right. But I want you to explain how can AI ops help with that alignment and align it outputs to business outcomes? >>Yeah. So, you know, one of the things, uh, I'm going to say something that is, uh, that is, uh, that is simple, but, but, but this harder, but alignment is not on systems alignment is with people, right? So when people align, when organizations align, when cultures align, uh, dramatic things can happen. So in the context of AI ops VC, when, when SRE is aligned with the DevOps engineers and information architects and, uh, uh, you know, it operators, uh, you know, they enable organizations to reduce the gap between intent and outcome or output and outcome that said, uh, you know, these personas need mechanisms to help them better align, right. Help them better visualize, see the, you know, what we call single source of truth, right? So there are four key things that I want to call out. When we work with large enterprises, we find that customer journey alignment with the, you know, what we call it systems is critical. >>So how do you understand your business imperatives and your customer journey goals, whether it is car to a purchase or whether it is, uh, you know, bill shock scenarios and Swan alignment on customer journey to your it systems is one area that you can reduce the gap. The second area is how do you create a scenario where your teams can find problems before your customers do right outage scenarios and so on. So that's the second area of alignment. The third area of alignment is how can you measure business impact driven services? Right? There are several services that an organization offers versus an it system. Some services are more critical to the business than others, and these change in a dynamic environment. So how do you, how do you understand that? How do you measure that and how, how do you find the gaps there? So that's the third area of alignment that we, that we help and last but not least there are, there are things like NPS scores and others that, that help us understand alignment, but those are more long-term. But in the, in the context of, uh, you know, operating digitally, uh, you want to use customer experience and business, uh, you know, a single business outcome, uh, as a, as a key alignment factor, and then work with your systems of engagement and systems of interaction, along with your key personas to create that alignment. It's a people process technology challenge. >>So, whereas one of the things that you said there is that it's imperative for the business to find a problem before a customer does, and you talked about outages there, that's always a goal for businesses, right. To prevent those outages, how can AI ops help with that? Yeah, >>So, you know, outages, uh, talk, you know, go to resiliency of a system, right? And they also go to, uh, uh, agility of the same system, you know, if you're a customer and if you're whipping up your mobile app and it takes more than three milliseconds, uh, you know, you're probably losing that customer, right. So outages mean different things, you know, and there's an interesting website called down detector.com that actually tracks all the old pages of publicly available services, whether it's your bank or your, uh, you know, tele telecom service or a mobile service and so on and so forth. In fact, the key question around outages for, from, uh, from, uh, you know, executives are the question of, are you ready? Right? Are you ready to respond to the needs of your customers and your business? Are you ready to rapidly resolve an issue that is impacting customer experience and therefore satisfaction? >>Are you creating a digital trust system where customers can be, you know, um, uh, you know, customers can feel that their information is secure when they transact with you, all of these, getting into the notion of resiliency and outages. Now, you know, one of the things that, uh, that I, I often, uh, you know, work with customers around, you know, would that be find as the radius of impact is important when you deal with outages? What I mean by that is problems occur, right? How do you respond? How quickly do you take two seconds, two minutes, 20 minutes, two hours, 20 hours, right? To resolve the problem that radius of impact is important. That's where, you know, you have to bring a gain people, process technology together to solve that. And the key thing is you need a system of intelligence that can aid your teams, you know, look at the same set of parameters so that you can respond faster. That's the key here. >>We look at digital transformation at scale. Raj, how does AI ops help influence that? >>You know, um, I'm going to take a slightly long-winded way to answer this question. See when it comes to digital transformation at scale, the focus on business purpose and business outcome becomes extremely critical. And then the alignment of that to your digital supply chain, right, are the, are the, are the key factors that differentiate winners in the, in their digital transformation game? Really, what we have seen, uh, with, with winners is they operate very differently. Like for example, uh, you know, Nike matures, its digital business outcomes by shoes per second, right? Uh, Apple by I-phones per minute, Tesla by model threes per month, are you getting this, getting it right? I mean, you want to have a clear business outcome, which is a measure of your business, uh, in effect, I mean, ENC, right? Which, which, uh, um, my daughter use and I use very well. >>Right. Uh, you know, uh, they measure by revenue per hour, right? I mean, so these are key measures. And when you have a key business outcome measure like that, you can everything else, because you know what these measures, uh, you know, uh, for a bank, it may be deposits per month, right now, when you move money from checking account to savings account, or when you do direct deposits, those are, you know, banks need liquidity and so on and so forth. But, you know, the, the key thing is that single business outcome has a Starburst effect inside the it organization that touches a single money moment from checking a call to savings account can touch about 75 disparate systems internally. Right? So those think about it, right? I mean, all, all we're doing is moving money from checking account a savings account. Now that goats into a it production system, there are several applications. >>There is a database, there is, there are infrastructures, there are load balancers that are webs. You know, you know, the web server components, which then touches your, your middleware component, which is a queuing system, right. Which then touches your transactional system. Uh, and, uh, you know, which may be on your main frames, what we call mobile to mainframe scenario, right? And we are not done yet. Then you have a security and regulatory compliance system that you have to touch a fraud prevention system that you have to touch, right? A state department regulation that you may have to meet and on and on and on, right? This is the chat that it operations teams face. And when you have millions of customers transacting, right, suddenly this challenge cannot be managed by human beings alone. So therefore you need a system of intelligence that augments human intelligence and acts as your, you know, your, your eyes and ears in a way to, to point pinpoint where problems are. >>Right. So digital transformation at scale really requires a very well thought out AI ops system, a platform, an open extensible platform that, uh, you know, uh, that is heterogeneous in nature because there's tools, products in organizations. There is a lot of databases in systems. There are millions of, uh, uh, you know, customers and hundreds of partners and vendors, you know, making up that digital supply chain. So, you know, AI ops is at the center of an enabling an organization achieve digital op you know, transformation at scale last but not least. You need continuous feedback loop. Continuous feedback loop is the ability for a production system to inform your dev ops teams, your finance teams, your customer experience teams, your cost modeling teams about what is going on so that they can so that they can reduce the intent, come gap. >>All of this need to come together, what we call BizOps. >>That was a great example of how you talked about the Starburst effect. I actually never thought about it in that way, when you give the banking example, but what you should is the magnitude of systems. The fact that people alone really need help with that, and why intelligent automation and AI ops can be transformative and enable that scale. Raj, it's always a pleasure to talk with you. Thanks for joining me today. And we'll be right back with our next segment. Welcome back to the AI ops virtual forum. We've heard from our guests about the value of AI ops and why and how organizations are adopting AI ops platforms. But now let's see AI ops inaction and get a practical view of AI ops to deep Dante. The head of AI ops at Broadcom is now going to take you through a quick demo. >>Hello. So they've gotta head off AI ops and automation here. What I'm going to do today is talk through some of the key capabilities and differentiators of Broadcom's CII ops solution in this solution, which can be delivered on cloud or on-prem. We bring a variety of metric alarm log and applauded data from multiple sources, EPM, NetApps, and infrastructure monitoring tools to provide a single point of observability and control. Let me start where our users mostly stock key enterprises like FSI, telcos retailers, et cetera, do not manage infrastructure or applications without having a business context. At the end of the day, they offer business services governed by SLS service level objectives and SLI service level indicators are service analytics, which can scale to a few thousand services, lets our customers create and monitor the services as per their preference. They can create a hierarchy of services based on their business practice. >>For example, here, the sub services are created based on functional subsistence for certain enterprises. It could be based on location. Users can import these services from their favorite CMDB. What's important to note that not all services are born equal. If you are a modern bank, you may want to prioritize tickets coming from digital banking, for example, and this application lets you rank them as per the KPI of your choice. We can source the availability, not merely from the state of the infrastructure, whether they're running or not. But from the SLS that represent the state of the application, when it comes to triaging issues related to the service, it is important to have a complete view of the topology. The typology can show both east-west elements from mobile to mainframe or not South elements in a network flow. This is particularly relevant for a large enterprise who could be running the systems of engagement on the cloud and system of records on mainframe inside the firewall here, you can see that the issue is related to the mainframe kick server. >>You can expand to see the actual alarm, which is sourced from the mainframe operational intelligence. Similarly, clicking on network will give the hub and spoke view of the network devices, the Cisco switches and routers. I can click on the effected router and see all the details Broadcom's solution stores, the ontological model of the typology in the form of a journal graph where one can not only view the current state of the typology, but the past as well, talking of underlying data sources, the solution uses best of the pre data stores for structured and unstructured data. We have not only leveraged the power of open source, but have actively contributed back to the community. One of the key innovations is evident in our dashboarding framework because we have enhanced the open source Grafana technology to support these diverse data sources here. You can see a single dashboard representing applications to infrastructure, to mainframe again, sourcing a variety of data from these sources. >>When we talk to customers, one of the biggest challenges that they face today is related to alarms because of a proliferation of tools. They are currently drowning in an ocean of hundreds and thousands of alarms. This increases the Elmont support cost to tens of dollars per ticket, and also affects LTO efficiency leading to an average of five to six hours of meantime to resolution here is where we have the state of the art innovation utilizing the power of machine learning and ontology to arrive at the root cause we not only clusterize alarms based on text, but employ the technique of 41st. We look at the topology then at the time window duplicate text based on NLP. And lastly learn from continuous training of the model to deduce what we call situations. This is an example of a situation. As you can see, we provide a time-based evidence of how things unfolded and arrive at a root cause. >>Lastly, the solution provides a three 60 degree closed loop remediation either through a ticketing system or by direct invocation of automation actions instead of firing hard-coded automation runbooks for certain conditions, the tool leverage is machine learning to rank automation actions based on past heuristics. That's why we call it intelligent automation to summarize AI ops from Broadcom helps you achieve operational excellence through full stack observability, coupled with AIML that applies across modern hybrid cloud environments, as well as legacy ones uniquely. It ties these insights with intelligent automation to improve customer experience. Thank you for watching from around the globe. It's the cube with digital coverage of AI ops virtual forum brought to you by Broadcom. >>Welcome to our final segment today. So we've discussed today. The value that AI ops will bring to organizations in 2021, we'll discuss that through three different perspectives. And so now we want to bring those perspectives together and see if we can get a consensus on where AI ops needs to go for folks to be successful with it in the future. So bringing back some folks Richland is back with us. Senior analysts, serving infrastructure and operations professionals at Forrester smartness here is also back in global product management at Verizon and Srinivasan, Reggie Gopaul head of product and strategy at Broadcom guys. Great to have you back. So let's jump in and rich, we're going to, we're going to start with you, but we are going to get all three of you, a chance to answer the questions. So we've talked about why organizations should adopt AI ops, but what happens if they choose not to what challenges would they face? Basically what's the cost of organizations doing nothing >>Good question, because I think in operations for a number of years, we've kind of stand stood, Pat, where we are, where we're afraid change things sometimes, or we just don't think about a tooling as often. The last thing to change because we're spending so much time doing project work and modernization and fighting fires on a daily basis. >>Problem is going to get worse. If we do nothing, >>You know, we're building new architectures like containers and microservices, which means more things to mind and keep running. Um, we're building highly distributed systems. We're moving more and more into this hybrid world, a multi-cloud world, uh, it's become over-complicate and I'll give a short anecdote. I think, eliminate this. Um, when I go to conferences and give speeches, it's all infrastructure operations people. And I say, you know, how many people have three X, five X, you know, uh, things to monitor them. They had, you know, three years ago, two years ago, and everyone's saying how many people have hired more staff in that time period, zero hands go up. That's the gap we have to fill. And we have to fill that through better automation, more intelligent systems. It's the only way we're going to be able to fill back out. >>What's your perspective, uh, if organizations choose not to adopt AI ops. Yeah. So I'll do that. Yeah. So I think it's, I would just relate it to a couple of things that probably everybody >>Tired off lately and everybody can relate to. And this would resonate that we have 5g, which is all set to transform the world. As we know it, I don't have a lot of communication with these smart cities, smart communities, IOT, which is going to make us pivotal to the success of businesses. And as you've seen with this call with, you know, transformation of the world, that there's a, there's a much bigger cost consciousness out there. People are trying to become much more, forward-looking much more sustainable. And I think at the heart of all of this, that the necessity that you have intelligent systems, which are bastardizing more than enough information that previously could've been overlooked because if you don't measure engagement, not going right. People not being on the same page of this using two examples or hundreds of things, you know, that play a part in things, but not coming together in the best possible way. So I think it has an absolute necessity to drive those cost efficiencies rather than, you know, left right and center laying off people who are like 10 Mattel to your business and have a great tribal knowledge of your business. So to speak, you can drive these efficiencies through automating a lot of those tasks that previously were being very manually intensive or resource intensive. And you could allocate those resources towards doing much better things, which let's be very honest going into 20, 21 after what we've seen with 2020, it's going to be mandate treat. >>And so Raj, I saw you shaking your head there when he was mom was sharing his thoughts. What are your thoughts about that sounds like you agree. Yeah. I mean, uh, you know, uh, to put things in perspective, right? I mean we're firmly in the digital economy, right? Digital economy, according to the Bureau of economic analysis is 9% of the U S GDP. Just, you know, think about it in, in, in, in, in the context of the GDP, right? It's only ranked lower, slightly lower than manufacturing, which is at 11.3% GDP and slightly about finance and insurance, which is about seven and a half percent GDP. So the digital economy is firmly in our lives, right. And as Huisman was talking about it, you know, software eats the world and digital, operational excellence is critical for customers, uh, to, uh, you know, to, uh, to drive profitability and growth, uh, in the digital economy. >>It's almost, you know, the key is digital at scale. So when, uh, when rich talks about some of the challenges and when Huseman highlights 5g as an example, those are the things that, that, that come to mind. So to me, what is the cost or perils of doing nothing? You know, uh, it's not an option. I think, you know, more often than not, uh, you know, C-level execs are asking head of it and they are key influencers, a single question, are you ready? Are you ready in the context of addressing spikes in networks because of the pandemic scenario, are you ready in the context of automating away toil? Are you ready to respond rapidly to the needs of the digital business? I think AI ops is critical. >>That's a great point. Roger, where does stick with you? So we got kind of consensus there, as you said, wrapping it up. This is basically a, not an option. This is a must to go forward for organizations to be successful. So let's talk about some quick wins, or as you talked about, you know, organizations and sea levels asking, are you ready? What are some quick wins that that organizations can achieve when they're adopting AI? >>You know, um, immediate value. I think I would start with a question. How often do your customers find problems in your digital experience before you do think about that? Right. You know, if you, if you, you know, there's an interesting web, uh, website, um, uh, you know, down detector.com, right? I think, uh, in, in Europe there is an equal amount of that as well. It ha you know, people post their digital services that are down, whether it's a bank that, uh, you know, customers are trying to move money from checking account, the savings account and the digital services are down and so on and so forth. So some and many times customers tend to find problems before it operations teams do. So a quick win is to be proactive and immediate value is visibility. If you do not know what is happening in your complex systems that make up your digital supply chain, it's going to be hard to be responsive. So I would start there >>Visibility this same question over to you from Verizon's perspective, quick wins. >>Yeah. So I think first of all, there's a need to ingest this multi-care spectrum data, which I don't think is humanly possible. You don't have people having expertise, you know, all the seven layers of the OSI model and then across network and security and at the application level. So I think you need systems which are now able to get that data. It shouldn't just be wasted reports that you're paying for on a monthly basis. It's about time that you started making the most of those in the form of identifying what are the efficiencies within your ecosystem. First of all, what are the things, you know, which could be better utilized subsequently you have the >>Opportunity to reduce the noise of a trouble tickets handling. It sounds pretty trivial, but >>An average you can imagine every trouble tickets has the cost in dollars, right? >>So, and there's so many tickets and there's art >>That get created on a network and across an end user application value, >>We're talking thousands, you know, across and end user >>Application value chain could be million in >>A year. So, and so many of those are not really, >>He, you know, a cause of concern because the problem is something. >>So I think that whole triage is an immediate cost saving and the bigger your network, the bigger >>There's a cost of things, whether you're a provider, whether you're, you know, the end customer at the end of the day, not having to deal with problems, which nobody can resolve, which are not meant to be dealt with. There's so many of those situations, right, where service has just been adopted, >>Which is just coordinate quality, et cetera, et cetera. So many reasons. So those are the, >>So there's some of the immediate cost saving them. They are really, really significant. >>Secondly, I would say Raj mentioned something about, you know, the user, >>Your application value chain, and an understanding of that, especially with this hybrid cloud environment, >>Et cetera, et cetera, right? The time it takes to identify a problem in an end user application value chain across the seven layers that I mentioned with the OSI reference model across network and security and the application environment. It's something that >>In its own self has massive cost to business, >>Right? That could be >>No sale transactions that could be obstructed because of this. There could be, and I'm going to use a really interesting example. >>We talk about IOT. The integrity of the IOT machine is exciting. >>Family is pivotal in this new world that we're stepping into. >>You could be running commands, >>Super efficient. He has, everything is being told to the machine really fast with sending yeah. >>Everything there. What if it's hacked? And if that's okay, >>Robotic arm starts to involve the things you don't want it to do. >>So there's so much of that. That becomes a part of this naturally. And I believe, yes, this is not just like from a cost >>standpoint, but anything going wrong with that code base, et cetera, et cetera. These are massive costs to the business in the form of the revenue. They have lost the perception in the market as a result, the fed, >>You know, all that stuff. So >>These are a couple of very immediate problems, but then you also have the whole player virtualized resources where you can automate the allocation, you know, the quantification of an orchestration of those virtualized resources, rather than a person having to, you know, see something and then say, Oh yeah, I need to increase capacity over here, because then it's going to have this particular application. You have systems doing this stuff and to, you know, Roger's point your customer should not be identifying your problems before you, because this digital is where it's all about perception. >>Absolutely. We definitely don't want the customers finding it before. So rich, let's wrap this particular question up with you from that senior analyst perspective, how can companies use make big impact quickly with AI ops? Yeah, >>Yeah, I think, you know, and it was been really summed up some really great use cases there. I think with the, uh, you know, one of the biggest struggles we've always had in operations is isn't, you know, the mean time to resolve. We're pretty good at resolving the things. We just have to find the thing we have to resolve. That's always been the problem and using these advanced analytics and machine learning algorithms now across all machine and application data, our tendency is humans is to look at the console and say, what's flashing red. That must be what we have to fix, but it could be something that's yellow, somewhere else, six services away. And we have made things so complicated. And I think this is what it was when I was saying that we can't get there anymore on our own. We need help to get there in all of this stuff that the outline. >>So, so well builds up to a higher level thing of what is the customer experience about what is the customer journey? And we've struggled for years in the digital world and measuring that a day-to-day thing. We know an online retail. If you're having a bad experience at one retailer, you just want your thing. You're going to go to another retailer, brand loyalty. Isn't one of like it, wasn't a brick and mortal world where you had a department store near you. So you were loyal to that because it was in your neighborhood, um, online that doesn't exist anymore. So we need to be able to understand the customer from that first moment, they touch a digital service all the way from their, their journey through that digital service, the lowest layer, whether it be a database or the network, what have you, and then back to them again, and we're not understanding, is that a good experience? >>We gave them. How does that compare to last week's experience? What should we be doing to improve that next week? Uh, and I think companies are starting and then the pandemic certainly, you know, push this timeline. If you listened to the, the, the CEO of Microsoft, he's like, you know, 10 years of digital transformation written down. And the first several months of this, um, in banks and in financial institutions, I talked to insurance companies, aren't slowing down. They're trying to speed up. In fact, what they've discovered is that they're, you know, obviously when we were on lockdown or what have you, they use of digital servers is spiked very high. What they've learned is they're never going to go back down. They're never going to return to pretend endemic levels. So now they're stuck with this new reality. Well, how do we service those customers and how do we make sure we keep them loyal to our brand? >>Uh, so, you know, they're looking for modernization opportunities. A lot of that that's things have been exposed. And I think Raj touched upon this very early in the conversation is visibility gaps. Now that we're on the outside, looking in at the data center, we know we architect things in a very way. Uh, we better ways of making these correlations across the Sparrow technologies to understand where the problems lies. We can give better services to our customers. And I think that's really what we're going to see a lot of the innovation and the people really clamoring for these new ways of doing things that starting, you know, now, I mean, I've seen it in customers, but I think really the push through the end of this year to next year when, you know, economy and things like that straightened out a little bit more, I think it really, people are gonna take a hard look of where they are and is, you know, AI ops the way forward for them. And I think they'll find it. The answer is yes, for sure. >>So we've, we've come to a consensus that, of what the parallels are of organizations, basically the cost of doing nothing. You guys have given some great advice on where some of those quick wins are. Let's talk about something Raj touched on earlier is organizations, are they really ready for truly automated AI? Raj, I want to start with you readiness factor. What are your thoughts? >>Uh, you know, uh, I think so, you know, we place our, her lives on automated systems all the time, right? In our, in our day-to-day lives, in the, in the digital world. I think, uh, you know, our, uh, at least the customers that I talk to our customers are, uh, are, uh, you know, uh, have a sophisticated systems. Like for example, advanced automation is a reality. If you look at social media, AI and ML and automation are used to automate away, uh, misinformation, right? If you look at financial institutions, AI and ML are used to automate away a fraud, right? So I want to ask our customers why can't we automate await oil in it, operation systems, right? And that's where our customers are. Then the, you know, uh, I'm a glass half full, uh, cleanup person, right? Uh, this pandemic has been harder on many of our customers, but I think what we have learned from our customers is they've Rose to the occasion. >>They've used digital as a key needs, right? At scale. That's what we see with, you know, when, when Huseman and his team talk about, uh, you know, network operational intelligence, right. That's what it means to us. So I think they are ready, the intersection of customer experience it and OT, operational technology is ripe for automation. Uh, and, uh, you know, I, I wanna, I wanna sort of give a shout out to three key personas in this mix. It's about people, right? One is the SRE persona, you know, site, reliability engineer. The other is the information security persona. And the third one is the it operator automation engineer persona. These folks in organizations are building a system of intelligence that can respond rapidly to the needs of their digital business. We at Broadcom, we are in the business of helping them construct a system of intelligence that will create a human augmented solution for them. Right. So when I see, when I interact with large enterprise customers, I think they, they, you know, they, they want to achieve what I would call advanced automation and AI ML solutions. And that's squarely, very I ops is, you know, is going as it, you know, when I talk to rich and what, everything that rich says, you know, that's where it's going and that's what we want to help our customers to. So, which about your perspective of organizations being ready for truly automated AI? >>I think, you know, the conversation has shifted a lot in the last, in, in pre pandemic. Uh, I'd say at the end of last year, we're, you know, two years ago, people I'd go to conferences and people come up and ask me like, this is all smoke and mirrors, right? These systems can't do this because it is such a leap forward for them, for where they are today. Right. We we've sort of, you know, in software and other systems, we iterate and we move forward slowly. So it's not a big shock. And this is for a lot of organizations that big, big leap forward where they're, they're running their operations teams today. Um, but now they've come around and say, you know what? We want to do this. We want all the automations. We want my staff not doing the low complexity, repetitive tasks over and over again. >>Um, you know, and we have a lot of those kinds of legacy systems. We're not going to rebuild. Um, but they need certain care and feeding. So why are we having operations? People do those tasks? Why aren't we automating those out? I think the other piece is, and I'll, I'll, I'll send this out to any of the operations teams that are thinking about going down this path is that you have to understand that the operations models that we're operating under in, in INO and have been for the last 25 years are super outdated and they're fundamentally broken for the digital age. We have to start thinking about different ways of doing things and how do we do that? Well, it's, it's people, organization, people are going to work together differently in an AI ops world, um, for the better. Um, but you know, there's going to be the, the age of the 40 person bridge call thing. >>Troubleshooting is going away. It's going to be three, four, five focused engineers that need to be there for that particular incident. Um, a lot of process mailer process we have in our level, one level, two engineering. What have you running of tickets, gathering of artifacts, uh, during an incident is going to be automated. That's a good thing. We should be doing those, those things by hand anymore. So I'd say that the, to people's like start thinking about what this means to your organization. Start thinking about the great things we can do by automating things away from people, having to do them over and over again. And what that means for them, getting them matched to what they want to be doing is high level engineering tasks. They want to be doing monitorization, working with new tools and technologies. Um, these are all good things that help the organization perform better as a whole great advice and great kind of some of the thoughts that you shared rich for what the audience needs to be on the lookout. For one, I want to go over to you, give me your thoughts on what the audience that should be on the lookout for, or put on your agendas in the next 12 months. >>So there's like a couple of ways to answer that question. One thing would be in the form of, you know, what are some of the things they have to be concerned about in terms of implementing this solution or harnessing its power. The other one could be, you know, what are the perhaps advantages they should look to see? So if I was to talk about the first one, let's say that, what are some of the things I have to watch out for like possible pitfalls that everybody has data, right? So yeah, there's one strategy we say, okay, you've got the data, let's see what we can do with them. But then there's the exact opposite side, which has to be considered when you're doing that analysis. What are the use cases that you're looking to drive? Right. But then use cases you have to understand, are you taking a reactive use case approach? >>Are you taking active use cases, right? Or, yeah, that's a very, very important concentration. Then you have to be very cognizant of where does this data that you have, where does it reside? What are the systems and where does it need to go to in order for this AI function to happen and subsequently if there needs to be any backward communication with all of that data in a process manner. So I think these are some of the very critical points because you can have an AI solution, which is sitting in a customer data center. It could be in a managed services provider data center, like, right, right. It could be in a cloud data center, like an AWS or something, or you could have hybrid views, et cetera, all of that stuff. So you have to be very mindful of where you're going to get the data from is going to go to what are the use cases you're trying to get out to do a bit of backward forward. >>Okay, we've got this data thing and I think it's a journey. Nobody can come in and say, Hey, you've built this fantastic thing. It's like Terminator two. I think it's a journey where we built starting with the network. My personal focus always comes down to the network and with 5g so much, so much more right with 5g, you're talking low latency communication. That's like the true power of 5g, right? It's low latency, it's ultra high bandwidth, but what's the point of that low latency. If then subsequently the actions that need to be taken to prevent any problems in application, IOT applications, remote surgeries, uh, self driving vehicles, et cetera, et cetera. What if that's where people are sitting and sipping their coffees and trying to take action that needs to be in low latency as well. Right? So these are, I think some of the fundamental things that you have to know your data, your use cases, that location, where it needs to be exchanged, what are the parameters around that for extending that data? >>And I think from that point at one word, it's all about realizing, you know, sense of business outcomes. Unless AI comes in as a digital labor that shows you, I have, I have reduced your this amount of time and that's a result of big problems or identified problems for anything. Or I have saved you this much resource in a month, in a year or whatever timeline that people want to see it. So I think those are some of the initial starting points, and then it all starts coming together. But the key is it's not one system that can do everything. You have to have a way where, you know, you can share data once you've caught all of that data into one system. Maybe you can send it to another system at make more, take more advantage, right? That system might be an AI and IOT system, which is just looking at all of your street and make it sure that Hey parents. So it's still off just to be more carbon neutral and all that great stuff, et cetera, et cetera, >>Stuff for the audience to can cigarette rush, take us time from here. What are some of the takeaways that you think the audience really needs to be laser focused on as we move forward into the next year? You know, one thing that, uh, I think a key takeaway is, um, uh, you know, as we embark on 2021, closing the gap between intent and outcome and outputs and outcome will become critical, is critical. Uh, you know, especially for, uh, you know, uh, digital transformation at scale for organizations context in the, you know, for customer experience becomes even more critical as who Swan Huseman was talking, uh, you know, being network network aware network availability is, is a necessary condition, but not sufficient condition anymore. Right? The what, what, what customers have to go towards is going from network availability to network agility with high security, uh, what we call app aware networks, right? How do you differentiate between a trade, a million dollar trade that's happening between, uh, you know, London and New York, uh, uh, versus a YouTube video training that an employee is going through? Worse is a YouTube video that millions of customers are, are >>Watching, right? Three different context, three different customer scenarios, right? That is going to be critical. And last but not least feedback loop, uh, you know, responsiveness is all about feedback loop. You cannot predict everything, but you can respond to things faster. I think these are sort of the three, three things that, uh, that, uh, you know, customers aren't going to have to have to really think about. And that's also where I believe AI ops, by the way, AI ops and I I'm. Yeah. You know, one of the points that was smart and shout out to what he was saying was heterogeneity is key, right? There is no homogeneous tool in the world that can solve problems. So you want an open extensible system of intelligence that, that can harness data from disparate data sources provide that visualization, the actionable insight and the human augmented recommendation systems that are so needed for, uh, you know, it operators to be successful. I think that's where it's going. >>Amazing. You guys just provided so much content context recommendations for the audience. I think we accomplished our goal on this. I'll call it power panel of not only getting to a consensus of what, where AI ops needs to go in the future, but great recommendations for what businesses in any industry need to be on the lookout for rich Huisman Raj, thank you for joining me today. We want to thank you for watching. This was such a rich session. You probably want to watch it again. Thanks for your time. Thanks so much for attending and participating in the AI OBS virtual forum. We really appreciate your time and we hope you really clearly understand the value that AI ops platforms can deliver to many types of organizations. I'm Lisa Martin, and I want to thank our speakers today for joining. We have rich lane from Forrester who's fund here from Verizon and Raj from Broadcom. Thanks everyone. Stay safe..

>> Narrator: From theCUBE Studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Welcome back to the Broadcom AIOps Virtual Forum. Lisa Martin here talking with Usman Nasir, Global Product Management at Verizon. Usman, welcome back. >> Hi Lisa, hello, what a pleasure to be back. >> Good to see you. So 2020, the year of that needs no explanation, right? The year of massive challenges, I wanting to get your take on the challenges that organizations are facing this year as the demand to deliver digital products and services has never been higher. >> Yeah, so Lisa I think this is something that's so close to all our hearts, right? It's something that's impacted the whole world equally. And I think regardless of which industry you're in, you have been impacted by this in one form or the other. And the ICT industry, the information and communication technology industry. You know Verizon being really massive player in that whole arena. It has just been sort of struck with this massive concentration that we have talked about for a long time, we have talked about these remote surgery capabilities whereby you've got patients in Kenya were being treated by experts sitting in London or New York, and also this whole consciousness about our carbon footprint and being environmentally conscious, this pandemic has taught us all of that and brought this to the forefront of organizational priorities, right? The demand, I think that's a very natural consequence of everybody sitting at home. And the only thing that can keep things still going is this data communication, right? But I wouldn't just say that that is what's kind of at the heart of all of this. Just imagine, if we are to realize any of these targets that the world is, well leadership is setting for themselves, hey, we have to be carbon neutral by X year as a country, as a geography, et cetera, et cetera. You know, all of these things require you to have this remote working capability. This remote interaction, not just between humans, but machine to machine interactions. And this is a unique value chain, which is now getting created, that you've got people who are communicating with other people or communicating with other machines, but the communication is much more, I wouldn't even use the term real-time because we've used real-time for voice and video, et cetera. We're talking low latency, microsecond decision-making that can either cut somebody's you know, arteries or that could actually go and remove the tumor, that kind of stuff. So that has become a reality, everybody's asking for it. Remote learning, being an extremely massive requirement where, you know, we've had to enable these virtual classrooms. Ensuring the type of connectivity, ensuring the type of privacy, which is just so critical. You can't just have everybody in a go on the internet and access a data source. You have to be concerned about the integrity and security of that data as the foremost. So I think all of these things, yes, we have not been caught off guard, we we're pretty forward-looking in our plans and our evolution, but yes, it has this fast track a journey that we would probably believe we would have taken in three years. It has brought that down to two quarters where we talked to execution. >> Right, massive acceleration. All right, so you articulated the challenges really well, and a lot of the realities that many of our viewers are facing. Let's talk now about motivations AIOPs, as a tool, as a catalyst, for helping organizations overcome those challenges. >> So yeah, now, all that I said, you can imagine, it requires microsecond decision-making. Which human being on this planet can do microsecond decision-making on complex network infrastructure which is impacting end user applications which have multitudes of effect? You know, in real life, I use the example of a remote surgeon. Just imagine that even because of you just lose your signal on the quality of that communication, for that microsecond it could be the difference between killing somebody and saving somebody's life. It is that critical. We talk about autonomous vehicles. We talk about this transition to electric vehicles, smart motorways, et cetera, et cetera, in federal environment, how is all of that going to work? You have so many different components coming in, you don't just have a network and security anymore. You have software defined networking that's becoming a part of it. You have mobile edge computing that is rented for the technologies 5G enables. We're talking augmented reality. We're talking virtual reality. All of these things require that resources and why being carbon conscious, we don't just want to build a billion data centers on this planet, right? We have to make sure that resources are given on demand. And the best way of resources can be given on demand and could be most efficient, is that the decision making is being made at million microsecond and those resources are accordingly being distributed, right? If you're bent relying on people, sipping their coffees, having teas, talking to somebody else, you know just being away on a holiday, I don't think we're going to be able to handle that one that we have already stepped into. Verizon's 5G has already started businesses on that transformational journey, where they're talking about end user experience personalization. You're going to have events where people are going to go and it's going to be three-dimensional experiences that are purely customized for you, how does that all happen without this intelligence sitting there? And a network with all of these multiple layers of spectrum, it doesn't just need to be intuitive, hey, this is my private IP traffic, this is public traffic, you know, it has to now be in to or this is an application that I have to prioritize over another, task to be intuitive to the criticality and the context of those transactions. Again, that's surgeons, surgery it's much more important than husband sitting and playing a video game. >> I'm glad that you think that, that's excellent. Let's go into some specific use cases. What are, some of the examples that you gave, what's kind of dig deeper into some of the what you think are the lowest hanging fruit for organizations kind of pan industry to go after here? >> Excellent, right? And I think this like different ways to look at the lowest hanging fruit. Like for somebody like Verizon, who is the managed services provider, you know very comprehensive medicines, but we obviously have food timing much lower than potentially for some of our customers who want to go on that journey, right? So for them to just go and try and harness the power of their health, foods might be a bit higher hanging. But for somebody like us, the immediate ones would be to reduce the number of alarms that are being generated by these overlay services. You've got your basic network, then you've got your whole software defined networking on top of that, you have your hybrid clouds, you have your edge computing coming on top of that. So all of that means if there's an outage on one device on the network, I want to make this very real for everybody, right? It's a lot device and network does not stop all of those multiple applications or monitoring tools from raising havoc and raising thousands of alarm in their one capacity. If people are attending to those thousands of alarms, it's like you having a police force and there's a burglary in one bag and the alarm goes off in 50 bags, (laughing) how are you going to make the best use of your police force? You're going to go investigate 50 bags, or do you want to investigate one, where the problem is? So it's as real as that, I think that's the first wins where people can save so much costs, which is coming from being wasted and resources running around trying to figure stuff out. Immediately, I'm tied this with network and security. Network and security is something which has eluded even the most you know, I mean amazing of brains in our engineering. Well, we typically have network experts, separate people, security experts, separate people, to look for different things, but there are security events that can impact the performance of a network and then use your application center et cetera. Which could be falsely attributed to the network. And then if you've got multiple parties, which are then the top to clear stakeholders, you can the blame game that goes on, pointing fingers, taking names, not taking responsibility. That is how it's all this happened. This is the only way to bring it all together to say okay, this is what takes priority, if there's an event that has happened, what is its correlation to the other downstream systems, devices, components and these are applications? And then subsequently, you know like isolating it to the right cost, where you can most effectively resolve that problem. Thirdly, I would say on demand virtualized resource. Virtualized resources, the heart and soul, the spirit of status that you can have them on demand. So, you can automate the allocation of these resources based on customer's consumption, their peaks, their trends, all of that comes in and you see, hey, typically on a Wednesday, the traffic was not significantly for this particular application. You know, going to this particular data center, you could have this automated AIOPs, which is just providing those resources on demand. And so if it's to have a much better commercial engagement with customers and just a much better service assurance model. And then one more thing on top of that, which is very critical, is that as I was saying giving that intelligence to the networks to start having context of the criticality of a transaction. That doesn't make sense to me, you can't have that. Because of that you need to have this multi layer data. You need to have multiple system which are monitoring and controlling different aspects of your overall end user application value chain to be communicating with each other, and that's the only way to sort of achieve that goal and that only happens with AIOPs It's not possible with that You can't prioritize transactions. >> So Usman you clearly articulated some obvious low-hanging fruit use cases that organizations can go after. Let's talk now about some of the considerations you've talked about the importance of the network and AIOPs, the approach, I assume it needs to be modular, support needs to be heterogeneous. Talk to us about some of those key considerations that you would recommend. >> Absolutely, so again, basically starting with the network because it says, if the network sitting at the middle of all of this is not working, then things can communicate with each other, right? And the cloud doesn't work nothing. None of this is at the heart of all of this. But then subsequently when you talk about machine to machine communication or IOT, which is just the biggest transformation of every company is going for IoT now to drive those costs, efficiencies enhancement and customer experience, the integrity of data accounts parameter, right? The security integrity of that. How do you maintain integrity of your data beyond just the secure network components that is traversing, right? That's where you're getting to the whole arena of blockchain technology, where you have to use digital signatures or barcodes that machine then and then an intelligent system is automatically able to validate and verify the integrity of the data and the commands that are being executed by those end-user terminal or any terminal by those IoT machines, right? That is paramount. And if anybody is not keeping that into their equation, that's in its own self is any add off system that is there for maintaining the integrity of your commands and your code that sits on those machines, right? Second, you have your network, you need to have any else platform which is able to rationalize all of that network information, et cetera. And a couple of that with that data integrity piece, because for the management ultimately, they need to have a coherent view of the analytics, et cetera, et cetera. They need to know where the problems are again, right? So, let's say if there's a problem with the integrity of the command that are being executed by the machine, that's a much bigger problem than not being able to communicate with that machine in the first place. Because you'd rather not talk to the machine or have it do anything if it's going to start doing wrong things. So, I think that's where it is, it's very intuitive. It's natural, you have to have it. Subsequently, if you have some kind of faith, and let me use that use case of autonomous vehicles again. I think if we're going to see in the next five years that these smart waterways, et cetera. They're all set for autonomous vehicles. It's much more efficient. It's much more space, et cetera, et cetera. So, within that equation, you're going to have systems which will be specialists in looking at aspects and transactions related to those systems. For example, an autonomous moving vehicles brakes are much more important than the wipers, right? So this kind of intelligence, there will be multiple systems to have to say and nobody has to, one person have to go and own these systems. I think these systems should be open source now that they are able to integrate them, right? If something's sitting in the cloud you were able to integrate that with obviously the regard of the security and integrity of your data that has to traverse from one system to the other, extremely important. >> So I'm going to borrow that integrity theme for a second as we go into our last question. And that is this kind of take a macro look at the overall business impact that AIOPs can help customers make. I'm thinking of, you know the integrity of teams aligning business and IT which we probably can't talk about enough. We're helping organizations really effectively measure KPIs that deliver that digital experience that all of us demanding consumers expect. What's the overall impact? What would you say in summarization? >> So I think that will run in fact is a lot of costs that customers and businesses gives me term to the term enterprises, defense was inevitable. This is something that for the first time will come to life. And it's something that is going to start driving cost efficiencies and consciousness and awareness within their own business which is obviously going to have the domino kind of an effect. So, one example being that you have problem isolation. I talked about network security, this multi-layers architecture which enables this new world of 5G. At the heart of all of it, it is to identify the problems to the source, right? Not be bogged down by 15 different things that are going wrong. What is causing those 15 things to go wrong, right? That speed to isolation in its own sense can make millions and millions of dollars to organizations as we organize. Next one is obviously overall impacted customer experience. A 5G world, you're going to have your customers expecting experiences from you, even if you're not expecting to deliver them in 2021, 2022. You would have customers asking for those experience or walking away, if you do not provide those experience. So, it's almost like a business can do nothing every year. They don't have to reinvest if they just want to die on the wine business, as one to remain relevant. Businesses want to adopt the latest and greatest in technology, which enables them to have the periodicity and continuity. So from that perspective, that continuity will read that they are intelligent system getting rationalizing information and making the scene. Supervised by people, of course, who were previously making some of those of you. >> That was a great summary because you're right, you know with how demanding consumers are, we don't get what we want quickly. We churn, right? We go somewhere else and we could find somebody that can meet those expectations. So, it has been thanks for doing a great job of clarifying the impact and the value that AIOPs can bring to organizations. That sounds really now as we're in this even higher demand for digital products and services, which is not going away it's probably going to only increase it's table stakes for any organization. Thank you so much for joining me today and giving us your thoughts. >> Pleasure, thank you. >> We'll be right back with our next segment. (upbeat music)

>> Announcer: Live from San Diego, California, it's theCUBE! Covering Cisco Live US 2019 Brought to you by Cisco and its ecosystems partners. >> Welcome back to theCUBE's coverage, day two, at Cisco Live. we are live in San Diego. I'm Lisa Martin, my co-host is Stu Miniman, and Stu and I are very pleased to welcome back to theCUBE, Mandy Whaley, senior director of the Developer Experience at DevNet, Mandy, welcome back. >> Thank you so much, happy to be here. >> Well thanks for having us at the DevNet Zone, The last two days this has been jammed packed, it's been tons of activity from the morning in 'til it shuts down, so you get a real sense of how strong this community is, and so something, yesterday, that Chuck Robbins kicked his keynote off with was 30th year of Cisco doing a partner, a customer event. >> Yes, it's incredible. >> So I thought, let's see what else is having a 30th year anniversary this year. And I discovered Bill and Ted's Excellent Adventure is 30 and I thought I want to talk to Mandy because how the DevNet experience has been Susie and Mandy's excellent adventure, look what you've built in five years! >> That is a really great analogy. (laughing) I really like that. No, it is really exciting to see where we are in this five year journey, and I was reminiscing with some of the team who is here in the very early days. Our second ever DevNet Express was here in San Diego, and we were in the same space, and I think we were maybe, 1/3 of this space was DevNet Zone, we had a classroom, and a few meeting spaces and some demos, but it was very vibrant and the community showed up then, but it's great to see five years later how we have workshops, and demos, and more interactive things, and what we've been able to build to really help enable the community, and then to see them just soaking it up, that's one of my favorite weeks of the year. >> Mandy, I really see the coming together of Cisco's traditional business, when I think about when I would write about Cisco, it's that army of CCIEs that are out there, whose jobs were relying on Cisco products and technology, and what you've built with the DevNet group, and how you have about 600,000 in this community and everything like that. Now, the certifications went through some major updates and there's some people who was like, oh my God, wait, it's not just the treadmill every year where I get my stamp, and keep my number. Bring us inside a little bit how that happened, and what the new career is and how certifications fit in to that. >> Absolutely, so this has been an exciting week for that reason as well, because we've been working, my team of developer advocates, and our DevNet experts have been working hand-in-hand with learning at Cisco, on this project around certifications, and it's so exciting to be able to finally tell people about it, and share it with the community and get the feedback. And what's really interesting about that program is we started from the beginning, really designing it with this idea of the IT team of the future, the infrastructure skills, the software skills coming together. Whether that's one person that learns both sides of it, or it's a team, that's combinations of those skills, that's really how the certifications are designed. So, there's abilities for someone to go very deep on the networking side, our CCIEs are incredible, and they have this incredible amount of knowledge, and that path is still the same, but there is also an addition of automation and software into that path, even in the very network focus certifications. Then we added the DevNet certifications, and these allow someone who's coming more from, I have a software background, but I am starting to automate infrastructure, I'm starting to span into the OPS world, I'm building on Cisco platforms, and allow those to connect together. And then there is this new concept of the specialist certification and that's where we really let people, kind of, choose and pick, kind of choose your own adventure, in terms of the certifications that you choose and the skills that you've build, so that you could start to take a security automation specialist with a DevNet professional developer and a data center certification, and really focus it on something like DevSecOps, or same kind of things for IoT, where you can put together wireless with IoT application development, and go towards roles like an IoT architect, or something like that. So, it's been an incredible project, my team has been very energized by the work with learning at Cisco on really taking the certifications and adding the software skills to it, and seeing how that's going to help enable this amazing community of people that's here at Cisco Live. >> This seems like this is a part of Cisco's transformation from purely a hardware network appliance vendor to a hardware plus software, subscription service at DevNet is part of that as an accelerate. >> Yeah, it definitely is and I think it really shows, with the certifications how Cisco is putting real effort into that, and how that is the direction that we're heading, and it gives a clear signal to people that we do need both sets of skills, and it gives you a pathway to get those skills, is the really important thing, because we heard requests from our community, We want a DevNet certification, We want a certification path for these software skills, and so, it's really in response to things that we've heard from our partners and our customers, they wanted these define paths to get there, and now we got this way to help them. >> All right so there was some other announcements this week, why don't you walk us through the rest of the news? >> Yeah, the other DevNet announcement that we're really talking with people a lot about here is the DevNet Automation Exchange. This is really focused around network automation and how DevNet and the DevNet community can help lead the way in network automation. And so the automation exchange is focused on tangible use cases, that we've heard from partners and customers some of them very simple, we have a walk, run, fly methodology that we're applying. So a lot of people when they start with network automation they come to us and say, "I don't know where to start. "I don't know where me, personally, with skills, "my organization does not know where to start." And so the walk phase is a lot about using automation to do read only kind of activities, get insights, get information, use it to help maybe do zero touch auditing or something like that. Things that are small projects people can pick up, and start building confidence around that work automation. The run phase is start taking action, you can start to implement policy, and start doing configuration through automation. And then the fly is really connecting all of that together, into a DevOps workflow, where maybe you're adding in a chatbot to communicate back to an Ops team, or you're noting that something drifted out of configuration and taking action to fix it. And so, the automation exchange is a place where we have 50 initial use cases, that we go through, we explain, and then we also give a code project, we actually give sample code, it's a repository on GitHub that matches to solving that use case. And so, automation exchange is curated by Cisco and created by our community. So people would be submitting them in, bringing their use cases in, bringing their code, we'll also be bringing use cases and code into it, and we really want it to be this vibrant place to move that conversation forward, and find out what are those walk, run, and fly use cases that people are really working on. >> With so much of networking changes today, being done manually, I think I saw a stat on the Cisco website, that upwards of 95% of all network changes are still done manually, and I think that's got to be a huge hit to OPEX. What are some, in this early history with network automation, what are some of the success stories that you guys are hearing with the impact that this walk, run, fly methodology or path is enabling businesses to achieve? >> Definitely, so yesterday in Chuck's keynote we heard him talk about the complexities kind of moving beyond human scale, and that's one of the things that automation really helps with, and that's where we hear some of the first real wins from our customers and partners around is we've been able to approach something we couldn't before because we've put things in place using automation, it helps us work more efficiently and scale further. So that's definitely a very common one. And then the other part of it is really, not necessarily just about speed or scale, but it's about reliability and reducing risk, and so doing things in an automated way, also can really help with that, and so it's really the combination of both of those where you get the biggest impact. >> Mandy, can you bring us inside a little bit the ecosystem because we heard on the main stage, lots of discussion of keynote, especially in this multi-cloud world that we live in, Cisco spanning across lots of environments here. From a DevNet standpoint we've talked to startups that are involved, as well as some of the big people, so give us the latest there, and what lessons learned from your team have you started to share with some of the other big companies that are looking to go down similar journeys? >> Yeah, I think that is one of the things that's very unique about the DevNet community is within the community we have technical stakeholders from small startups to really large partners or huge enterprises, and when we're all here in the DevNet Zone, we're all engineers, and we're all exchanging ideas kind of no matter what the scales. So it becomes this great mixing of shared experiences and ideas. And that is some of the most interesting conversations that I've actually heard this week, is people talking about how maybe they're using one Cisco platform in these two very different environments, and exchanging ideas about how they do that, or maybe how they're using a Cisco platform with an open source tool, and then people finding value, and thinking, "Oh, maybe I can do that in my environment." So that part of the ecosystem and community is very interesting and then, we're also helping partners find each other, so we do a lot of work around here's a partner in the Cisco ecosystem who goes and installs Meraki Networks, right? Here's a software partner who builds mapping technology on top of indoor WiFi networks, and getting those two together, because the software partner is not going to install the network, and the network person may not write that application in that way, and so bringing them together, we've had a lot of really good information coming back from the community around kind of finding each other, and being able to deliver those outcomes. >> There's so many impacts that DevNet has made, I'm certainly thinking of expansion of partnerships, and ecosystem, like wow, that you probably in the beginning didn't even realize were going to be some of the outcomes that you're seeing five years in. >> Yeah, it is exciting to be five years into it and certainly when I taught the first coding 101 for network engineers at Cisco Live five years ago in San Francisco I did not expect there to be DevNet certifications five years later, that is a really interesting path to think about how that evolves, and then certainly on the ecosystems side of the same thing. You know, we always knew that the APIs were going to become prevalent across all the Cisco platforms, and up and down the stack. And we always knew developers are this creative force and if you get those two things together, you can unlock a lot of interesting things, but it's been great to see it come into reality. >> So, Mandy, I had the opportunity to hear Fran, who is the chief people person at Cisco, talk to kickoff the event here, and they talked about the fact that 40% of the leadership team at Cisco has changed in the last 12 months, and they did that because something was right, it wasn't that there was problems, but Chuck Robbins has been here for four years the stocks been going gangbusters, but give us a little bit of insight, what does this transformation of DevNet which talk about 600,000 people in the giant community, but what does it mean inside? Fran talked about the people that are engaged are six times more engaged when they work, if they really like what they're doing, and we know kind of the quality of life benefits that happen if I, you know-- >> Definitely, yeah so, I think it's been very positive. I have super confidence in our leadership team right now, and the Cisco culture is one of the biggest things that I love about working at Cisco and I'm a mom of two boys, and I have flexibility to have this amazing job and career, and also be around with my boys, and that's a life goal and that's really meaningful to me. Within DevNet, working within the company to kind of drive some change, I think within this five years we have seen awareness of what developers need and want, and how to be developer friendly, like that has certainly been something we've been working internally to help lots of groups understand, and there's been a ton of progress around that. And then also just the attention from the product teams, and engineering teams, into the work they're putting into their APIs is just incredible, and I think that's the voice of the community coming back in and them seeing that the kind of innovation that it drives in our partner community, and all these people here learning about their platforms, I think that is the best kind of virtuous cycle that you can have. >> I can only imagine Cisco, history as it is, and as large as it is, that having a reputation being developer friendly is a massive competitive advantage. Especially for some probably larger enterprises that are still trying to make that pivot. You have so many demonstrable prove points of Cisco's developer friendliness, that I can only imagine that's probably contributing to all this great revenue numbers we're seeing. >> We do believe it is really important for Cisco's future, if we're going to be a software company, being developer friendly is certainly a very important part of that, and that was part of the original thought with DevNet starting five years ago. We always have more work to do, but it's great to see how far we've come. >> Definitely, well Mandy, congratulations on your excellent adventure, we're excited to see where it goes from here, we also appreciate being in the DevNet Zone, and getting to feel the buzz and the excitement, and I can just imagine how many partnerships are forming behind us, how many new products and services are going to be created, maybe new companies, it's very exciting. >> Mandy: Thank you, it's great to be here. >> We appreciate your time. For Stu Miniman, I am Lisa Martin. You're watching theCUBE live, from Cisco live. Thanks for watching. (upbeat music)

>> Live, from Miami Beach, Florida it's theCUBE covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami everybody, sunny Miami. Dave Vellante here with Peter Burris. You're watching theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, and there's a lot of noise here, and there's a lot of signal here. VeeamON 2019, this is theCUBE's third year doing Veeam's big customer show. We started doing NOLA, last year was Chicago, a very hip location here at the Fountainebleau Hotel. Carey Stanton is here. He is the Vice President of business development and corporate dev, corp-dev at Veeam and Jeff Kalat, a CUBE alum, >> Yep, you bet. >> long-time friend of theCUBE, senior director of strategic alliances at Hewlett-Packard Enterprise. Gentlemen, welcome to theCUBE, good to see you. >> Thanks for having us. >> You're very welcome. Carey let me start with you. Uh, I really want to talk about sports with you, but anyway, we won't. We'll hold that off. (laughter) >> (Carey) One day. >> Momentum. You're relatively new to Veeam. But you've been here now a couple years. Where's this momentum coming from, from your perspective, as a recent Veeam entrant. >> Yeah, no, the momentum's coming from across the board, but I think a big momentum is coming from new product innovation that we're doing with Office 365, and we're just driving up subscription business momentum that we have for the pent-up demand that we had for Euphor. But a big part is coming from our relationships like we have with HPE. We invested heavily a few years ago when we announced that joint reseller agreement. What we've done is not just continued to sell but add a plethora of new solutions to it Jeff's going to talk about what we're doing with GreenLake adding SimpliVity, adding the overall solutions that we have. But that's a team that started two years ago with two people that we now have over 20 people just working, dedicated with HPE on co-selling. And I'm happy to say that our business in first half, or I should say year-to-date is up 50% year over year on a global reseller business. >> Well Jeff, theCUBE as you know, has been documenting the ebbs and flows of HP and HPE over the last, better part of a decade. And when HP split in two, to HPE and HP Inc. One of the things that-- And then sold the software business, or a large portion of it. One of the things that went was data protection. >> (Jeff) You got it. >> (Dave) And that just opened up a whole new set of opportunities and Veeam was obviously one of those. And it's starting to pay dividends. >> You got it, yeah, to that point, that evolution through HPE.nex, we were able to focus on our core. And the benefit, the inherit benefit is that we can partner with the best of class in the marketplace. And Veeam is considered best of class. So when it comes to data availability, data protection, we're all in. And we're actually, as a company, we're actually doubling down now in our partnership with Veeam. We've actually taken them from, maybe a traditional storage alliance, and taken them to be one of our top global strategic alliances in the line of the Microsoft's, the Veeam, or as the SAP's. Because we see great momentum, we see great customer adoption and interest and we see great innovation at the product level, but also in the whole global market chain. >> Well talk a little more about that because it was, the move allowed you to form new partnerships that dramatically expanded your TAM but, I'm interested in the nature of the partnership. Is it, just go to market, is there engineering integration? Talk about that a little bit. >> Our first step when we came together and said okay let's take this to the next level, we realized we need to narrow our focus to the core customer values and we really settled on three core areas of this relationship. One is first, data protection for, around our intelligence storage, as you know, our storage portfolio 3 Par, Nimble, we've had a great relationship there, we continue to drive co-innovation at the road map level, but also drive go-to-market activities and marketing and we have feet on the street actively selling. So the first one's really expanding our work with storage. Now we're taking it, we're extending, if you will, through consumption based data management, using, well HPE has GreenLake, Greenlake we see 40% of customers by 2020 are going to be consuming their data center IT more in a consumption model. There are inherent benefits of that. What we now have offered and launched just recently Backup,is a service through our flex capacity coming out of GreenLake, providing customers the choice, if you will, to move from a, not from a capital expenditure, but, by the drink, if you will, consumption base. So that's the second core area. And the third core area is new for us, and that's around our HCI portfolio. As you know, we purchased SimpliVity. Well, SimpliVity has a lot of inherent backup, dedupe compression in line, but there actually are some Zivik use cases that we're deploying out there that show how Simplivity in a Veeam environment can actually, customers can see actually incremental values. So, those are the three key areas we're focused on as we up-level this whole relationship and partnership. >> (Dave) So Carey, please. >> I was just going to say if you think of, we talk a lot about we go after the technical decision maker in all these, hundreds of people here at the conference. And then going towards the executive, the enterprise. And it's through relationships with HPE on this, the flex capacity, being able to go to a customer and offer a true enterprise solution that they're looking for, everyone wants as a service. And so we've closed multiple deals this year thanks to having the Greenlake. So, our relationship with HPE continues to elevate and the enterprise is a result of the solutions that we're doing. Not just selling storage, but selling a complete solution. >> Rathmeyer was kind of tongue-in-cheek this morning at the analyst and media event. He was talking about how in 2013 he predicted that Veeam would be a billion dollar company by 2018. And he said he missed it by six months. One of the reasons was because you know, you got the subscription model. So that's, you know GreenLake obviously is part of that, maybe not the predominant part yet but I think you said you have 40% you're saying will consume, as a service by 2020. >> 2020, actually soon. >> (Dave) Okay so pretty substantial. >> Yeah. >> What's driving that? Is it just CFO's want to go to opex? Or is it-- >> I think it's a, there are many, the value you get without locking yourself into every three years needing to do a total forklift upgrade of your infrastructure, that's one thing. The second thing is moving it from a capital expenditure to an opex expediture. It can be planned, it can be budgeted as well. The third thing is the customer doesn't have to mess with all the technology, updating the firmware, the drivers and all that. We will do it on their behalf, right? We give them the economics of cloud on prem and that's the beauty of that. So we believe, and lock-step in alignment with Veeam, the world is hybrid in the future. So on prem is here to live forever, but increasingly we need to leverage the assets in the cloud and this is providing the ability of doing it in a consumption model. >> And it's not just the economics it's the experience as well. >> Oh totally, if you want to, if you live in a house and you're a home owner, and you want a new bathroom, you put in a bathroom. If you're a renter you end up in a long, laborious negotiation that you're going to lose. And the same kind of notion is here as people realize there's greater strategic opportunities and options from how to use their data differently. They want access to those options. And that's the basis of agility. The opex to capex is good but you've got to put it in business context. It's how you create additional options in your data oriented investments. So, as you guys are moving forward are you starting to have that conversation with customers? And relating data, data value, asset management, Backup, Restore, to this broader picture, this broader strategic union you're putting together? >> Yeah and that is a key imperative of how we get even stronger in traction is telling the bigger picture. And you look at the world of yesterday, where it's just backup and recovery, look at the advent of edge devices and the amount of data that's being put at the edge. Now look at AI and machine learning where, the data is inherently needed to project the changes and the needs that are in the future. So, I think these all tie in to the play and I believe at GreenLake our consumption model can provide great benefits, above and beyond the traditional backup and recovery. >> And I was just going to add to it, is that it also brings in our ecosystems, so the relationship, that tier one relationship we both have within Microsoft. So when you start looking at a solution that the business owner wants, they want to be able to say I need cloud, I need on prem, I need backup recovery, and so by going through GreenLake they can encompass, we have a broader ecosystem that we're able to bring in versus just single thread in these discussions where you're going in and selling a data protection story and leaving but you didn't solve that broader customer problem, and with GreenLake, they are solving that overall problem. >> Yeah, I'd just like to say nothing really happens until you make a sale. You talked about some of the growth earlier. But why Veeam? Obviously you're getting some traction in the market but there's a lot of players out there that you could partner with. And you do partner with others. But why Veeam? What makes Veeam so special? >> I think one, inherently we are lock-step in agreement of the over-arching strategy, we talked about hybrid, we talked about portfolio. Two is we've got the engagement at all levels of our organization, which all stems truly from having a unified roadmap. Innovation has to happen at the roadmap level and you need to be lock-step aligned through the value chain in the way you take it to market, the way you align your sellers, the way you deliver a value proposition that truly is valuable to our customers. It's proven from our IDC research that customers who are deploying and purchasing HPE and Veeam solutions are seeing a 250 plus percent ROI on that investment. So there's this huge customer benefit, and why not go bigger and go bigger and go bigger with them. >> (Dave) Same question to you Carey. So why HPEE, why is HPEE so special as a partner? >> I think HPE first and foremost, being that first partner that came to us to want to go all in, as Jeff was talking about, from day one, and top down. So we're not just working with a department of HPE we have it from Antonio, from Jim Jackson down the stack in the organization. We were aligned from day one. They lead with data protection, it's no longer, it's a a nice to have, it's a requirement in every one of their sales processes. We're their lead partner that they have in data protection. And what we'd been able to do and have that enterprise visibility by them assisting us on our journey. So, from across the board, whether it's through management, through technology, or just in true go-to-market, they're by far our number one partner that we have on our sell-with motion. >> So Jeff, I want to talk to the group about GreenLake. And Carey, I'd love to hear your thoughts on it as well. What are the challenges that go into a consumption-based model for a company that's traditionally sold products. As part of this overall move in all industries, all sectors, from a product to a services orientation. How do introduce metrics that are associated with the service? Because it used to be you just sold a product. And the metrics for storage are different from the metrics from backup, different from the metrics from compute. So as you've gone to GreenLake, because I love GreenLake, what kind of specialized, or specific types of things, how are you selling it to try to tie that service into the business outcomes that your customers are trying to see? >> Well clearly, I believe, some of our first wins, early wins we were able to monitor and metric the value the customers were getting, the service levels they've received and so we have a number of different methods of capturing the data, the empirical data, on the service levels and being able to use that to then, use that in the selling motion to be able to articulate the experience and the expectations that come with that. >> What are some of the harder problems that your customers are asking you to solve? And how are you approaching it together? >> Well I think that what we're talking about with GreenLake here is a real hard problem to solve, right? Consumpton based across geographic regions, across different technologies, on prem, off prem, hybrid. And we don't have another partner that we can go to market with when we hear this from the customer. So when we hear it, we know that we can lean in. And we truly are, to follow up from your question, is the fact is that HPEE is solving all this and then bringing us in as their number one partner, is the differentiator that we love. So solving those problems at an enterprise level, and at a commercial level and doing it with one partner is easy, right? We're shortening the sales cycle, increasing the value to the customer. >> Yeah, one thing I have to say and it's always, complexity is always a problem and an issue, right? So it will always be a problem and an issue and we will always be striving to improve and improve the complexity. But you know, Veeam, we're super simple, right? And we, especially when you look in our HCI portfolio and that's all about driving simplicity, if you will, in a way you can deploy IT, you can scale it. So I think complexity is, and will always be a problem. But it's a given too and it will always be there. And we will always be striving to make it even easier and easier for our joint customers. >> Well one of the challenges that you face, especially as you go to a sevices-only model, is how do you put a price on the outcomes that you're delivering as opposed to the price on the assets that the person is taking? So I think one of the biggest challenges, and it sounds like you guys are pretty close to getting this together, but it's part of a broader portfolio, is where does this, let's put it slightly differently. We've talked about this before in some of the other interviews. backup is moved from a have to have it, for maybe compliance or it just makes good sense to have it, to a strategic business capability for a company that's increasingly differentiating itself on it's data assets. That moves this conversation about, as a service, into a different group and a different, different level. And that's what I'm wondering. Those metrics have got to be a big part of the conversation. Because the entire organization is now recognizing backup is more than just a bolt-on. >> Yeah. One example, one of our close partners, we're here with them, Island. So, disaster recovery as a service, right? They standardize on Nimble and Veeam and together, that combination to them was good enough to build their business on. So there's inherent value and we expect to continue to grow and be able to expose that value. 'Cause we believe more and more customers, not just your pure enterprises but, from your mid-market all the way up, can be able to utilize and see that value and experience it. >> Just a point of clarification if I could on the HCI piece. Specifically around SimpliVity. So SimpliVity was known for it's backup use cases. >> (Jeff) Sure. Still is. >> So where does Veeam and SimpliVity fit, versus Simplivity solo. >> Yeah, yeah. Well first and foremost yes, Simplivity has inherent, great data availability features, inherent in it. That's core to it. But in reality, for customers, let's say a mixed environment, whether it be virtualized, non-vitrualized, there are inherent benefits to having Veeam in addition to SimpliVity. Another example would be customers who want to really have the access to be able to do specific file restores. So we see capabilities in running Veeam in parallel with SimpliVity. Actually I see a lot of customers that are deploying SimpliVity are also deploying Veeam and there, it's an additive value that they're seeing. And they're able to parse out features and functionality and be able to increase their level of value that couldn't be done, just purely from a Simplivity standpoint alone. >> All right Carey, we'll give you the final word. >> The final word is-- >> Bumper sticker on VeeamON. >> (laughing) >> Bumper stickers. >> I would say that, what we're doing here with HPEE, we would say we're in the first inning. What we're seeing on the innovations that we have coming out later this year with HPEE, coming into next year, and we're just thrilled to be having them a platinum sponsor of VeeamON and look forward to another successful year. >> Awesome. Guys thanks so much for coming on. I got to ask you, Boston-based person, Bruins fan? >> (Carey) Bruins, yes. >> You worried about Tuulka, at all, a 12 day layoff? >> (Carey) Nope. >> No problem. >> (Carey) Nope, Chara's going to be nice and rested and-- >> (Dave) Chara, more Chara or less Chara? >> I'm going to, yes well. I got to take more thanks. >> Okay, all right, good. We'll see, we'll see. Go Bruins. All right guys thanks so much for coming out and thank you for watching. Keep it right there we'll be back with our next guest shortly right after this break. You're watching theCUBE from VeeamON, 2019 from Miami. Be right back.

>> Live from Miami Beach, Florida, It's theCUBE covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami, everybody. This is Dave Vellante with Peter Burris. We're here at day one at VeeamON 2019. This is CUBE's 3rd year of doing VeeamON. We started in New Orleans, it was a great show. Last year was Chicago, and here, Miami at the Fontainbleau hotel. Marc Crespi is here, he's the vice president of sales engineering for the Americas at ExaGrid Systems Cube. Hello Marc, good to see you again. >> Good to see you. >> Thanks for coming on. So, give us the update. What's happening with ExaGrid? You guys got new headquarters in Marlborough. Marlborough's happening these days, right? We got the new shopping spa, and the mayor's going crazy, so give us the update on ExaGrid. >> Yes, so we just moved into a beautiful new headquarters in Marlborough and share it with some great other companies. The company continues to grow rapidly, double digit growth year over year, one of the few companies in this category that's growing that quickly. So everything's great. >> What's driving the growth? >> Well, customers are looking to fix the economics of backup. They've been spending too much money on it for a lot of years, so they look at products now, they want them to be simple, easy to use, and very cost-effective and we drive that trend very hard. >> Yeah I mean that doesn't really describe- what you just described, simple, easy to use, and cost-effective really doesn't describe backup for the past 20 years. So what are you doing specifically to make it simple, cost-effective, and easy to use? >> Well, first of all, by working with companies like Veeam. Veeam is a very easy-to-use product, it's very intuitive and then our product integrates very well with it so the products work together very well and makes just a very simple solution. >> What do you see as other big trends in backup? showed a slide today, 15 billion dollars. A big chunk of that, maybe close to half of it was backup and recovery, there's all kind of other stuff: data management, analytics, etc, etc, etc. What do you see, obviously cloud, you talked about the big superpowers, what are the big trends that are driving your business and more importantly, your customers transformation? >> Well, customers are looking to reduce the amount of data that they actually have to move. So, incremental technology's a really big- themes of pioneer in that, obviously doing incremental backups and that saves time and effort, saves space, along with data deduplication, it really makes for cost-effective storage solution. >> Talk a little bit more about why you're growing, how you sort of uniquely compete in the marketplace with some of the big whales. >> Sure, so our most unique feature is our architecture, and it has both technical aspects and economic aspects. Because we're a scale-out architecture, meaning that with every capacity increase of your data, we're not just adding storage, we're adding CompuPower network memory, etc. so that we keep the backup times very, very, very low. That also makes for a very cost-effective architecture because what we've done is you can scale out pretty much infinitely and we've also eliminated the concept of the end of a life of products. So we never force our customers into mandatory refreshes so their economics are very predictable over a long period of time. >> What do you see as the biggest use cases today that are driving your business? I mean, obviously, backup and recovery, I talked earlier about some of these emerging data management, cloud obviously, is this big, Edge, you seeing much going on there. What are some of those workloads and use cases that you see? >> I think probably one of the biggest use cases these days is what I would call instant recoveries, meaning that rather than doing a traditional restore, which could take a long number of minutes to hours. Customers will actually run production workloads off of the backup target as a way to get users back productive more quickly than would've been done in the past. >> Yeah, and that's key because you see in RPO and RTO's sort of companies putting more and more pressure on the IT groups to shrink those times, presuming you're seeing that in conjunction with digital, digital business, digital transformation. You talked about architecture before. What about your architecture and maybe with your partnership with Veeam allows customers to shrink those RPO and RTO times? >> I think the other aspect of our architecture that's very unique is what we called adaptive deduplication. One of the things we looked at when we architected the product was deduplication is obviously a very effective technology, but what are potential cons. Things that would make it less effective in backup. And one of the things we realized was if you put deduplication in the middle of the backup window and due to deduplication while the backups are running, then you could interfere with the speed of disk. So we do something called adaptive deduplication which means that we allow the object from the backup software to land and then we deduplicate and replicate them in parallel, but we make sure that we're not throttling the backups. So, we provide disk speeds even though we use deduplication. >> Okay. So, that's an example of one of the things you're doing to sort of improve it. How about Veeam integration? Is there anything specific there that you're doing that we should know about? >> Well, part of it is because of adaptive deduplication and because we maintain complete copies of backups. We uniquely support instant Veeam recovery like no other vendor can. Furthermore, we run what's called the Veeam data remover which is actually Veeam technology runs inside of our appliance and sets up a optimized communication protocol with the Veeam software that allows us to do a number of great things. >> Wait, double click on on that. So, is it an efficient protocol or is there other sort of accelerators that you've got in there? >> The protocol is optimized, and then we do some other acceleration around how you do synthetic folds and things of that sort that are unique to the data mover. >> And you have news with Veeam this week, do you not? >> Yes, we do. We're announcing something called ExaGrid backup with Veemam and what it is in a nutshell is the ability for a customer to purchase both technologies from their preferred reseller by just ordering one part number. So it dramatically simplifies the acquisition of the two technologies and allows customers to simplify the buying process. >> So Veeam, I know, is all channel sales. How about you guys? How do you go to market? >> We also are, yes. >> So, talk more about your go-to market. What do you have? Like, an overlay sales force that it helps facilitate? You got partners? Maybe you can talk more about your ecosystem. >> Well, we have a worldwide sales force and our sales people, the people that do the selling, work directly with our partners, so we don't have a specialized channel workforce, but we have a specialized channel strategy, and our entire sales team is very well trained on the channel, how to work with the channel, and make them happy and successful. >> So, backup for a long time time was kind of an afterthought. It was non-differentiated. You just did what you needed to make sure the devices could be recovered. >> Yeah, you bolted it on. >> You bolted it on. >> Right. >> Increasingly, it's becoming recognized as a central capability to any digital business, because if your data goes away or your data's no longer available, your digital business is gone. >> Right. >> That suggests we're going to get a greater degree of differentiation in the types of devices, in the types of systems, etc, that are going to become part of a backup solution. First of all, do you agree with that? And then secondly, go back to the use cases, where do you guys see yourselves fitting into that increasingly federated backup capability? >> Well, I certainly do agree with it. I mean, it's always been a necessity, but now even with things like Ransomware and the cryptoviruses, and things of that sort, it's even more important than it's ever been. It's no longer just data loss, etc. So, we fit into that trend and we'll continue to fit into that trend by continuing to drive the economics through the floor. Customers want that level of protection, it's a little bit like insurance. You need the protection, but you don't want to pay a dollar more than you have to, right? So you want to put it on an economic diet, and the way our technology evolves, we come out with denser, faster systems at a lower cost per terabyte just about every year. And we'll continue to do that. >> So do you anticipate then that there's going to be specialized use cases or are you just going after taking costs out of the equation? >> It's not so specialized because it's very horizontal. Everybody does it and everybody backs up all their data. So, we don't specialize in any one area of the data center like database or anything of that sort. We go wherever the customer needs us to go inside their data center. >> It's in the data center, sorry David, it's in the data center. >> In the data center, we also have a cloud offering, we have partners that will offer disaster recovery as a service, so they'll have data centers that manage on behalf of the customers, and we also have an offering that goes into Amazon web services. And, shortly, we'll be coming out with one for Azure. >> And that is what? A software based offering that uses the cloud as a target? >> Correct, it's a virtual appliance that you can replicate into the cloud. >> All right. We don't have much time left tonight, we have a really important topic to cover, which is, we talked about last year, but I want to bring it up again, which is sports. >> Yup. Why don't we talk Boston sports, we could talk about Warriors. I got a question for you, but- >> I'll watch >> I asked you last year, and I think it was May, we were in Chicago, I said "Would you have traded Tom Brady?" At a time when the sentiment was, he was done. And you said "No way, absolutely not." You, Peter McKay, and Patrick Osmond all said emphatically no, you made the right call. So good job. >> Thank you. >> Your thoughts? >> Would never trade him. He can play until he's 100 for all I care. As long as he keeps performing at such a high level, why would you lose him? >> And then, of course, the Red Sox, 108 wins, that was an amazing gift that they gave us. So, I don't know if you're a baseball fan. >> I am. >> All right, I got to ask you, Peter. Are the Warriors the greatest basketball team in the history of basketball? >> Well, let's see... >> Brendan says yes. >> They are the best basketball team at a time of the most competitive NBA. Some of the rules have changed, but the athletes are better, they're more conditioned, they are more knowledgeable by how to play this game, and they are the best team in basketball without Kevin Durant and without Boogie Cousins. >> Yeah. >> So ... hard to argue. >> They're sweeping Portland without Durant which is pretty amazing. So Brendan, for years, has been trying to tell me that. You know, Brendan is our local basketball genius so, I don't know. >> Now, would the Warriors have beaten say a Bill Russell Celtics team with the Celtics- Bill Russell Celtics team rules? Maybe not. >> Yeah, I don't know. I would say I'm starting to come around to Brendan's way of thinking. But, Marc, we'll give you the last word here. VeeamON 2019, great venue here in Miami, very hip, hip company, hip venue, ExaGrid growing, double digit growth rate, so congratulations on that. Your final thoughts? >> Just great to be here, I always like coming to Veeam events, they're always very well attended, I get to meet a lot of customers and really enjoy it. >> Marc Crespi, thanks very much for coming to theCUBE. It's great to see you again. >> Thank you. >> All right, keep it right there everybody. Peter and I will be back with our next guest right after this short break. This is VeeamON 2019 and you're watching theCUBE.

>> Live from Stanford University. It's the Cube covering global Women in Data Science conference brought to you by Silicon Angle media. >> Welcome back to the Cube. I'm Lisa Martin Live at the Stanford Ari Aga Alone, My Center for the Fourth Annual Women and Data Science Conference with twenty nineteen and were joined by a very special guest, Liza Donnelly, cartoonist for The New Yorker. But Liza, you are a visual journalists, visual journalism. You're here live, drawing a lot of the things that are going on. It would. You were just at the Oscars at the Grammys. Your work is so unique, so descriptive. Tell us a little bit our audience about what is visual journalism? >> Well, I suppose a lot of us define it different ways. But I did find it is somebody who I am, somebody who goes to events, either political or social, cultural and draw what I see. I'm not a court reporter. I'm I'm an Impressionist. I give people a feeling that they're they're with me from what? By what I draw what I see, how I draw it, and and it's I don't usually put any editorializing in those visual drawings, but my perspective is sort of a certain kind of approach. >> So you're bringing your viewers along this journey in almost real time. When people see people might be most failure with New Yorker your illustrations there. But folks that are watching the Woods event lie that engaging with that tell us a little bit about the importance of using the illustrations to bring them on this journey as if they were here. >> Well, you know, I send the drawings out immediately, do them on my iPad and I send them out on social media almost immediately, so as I do that so that people can see them immediately. So they feel like they're there, and it's a way to draw attention to whatever it is I'm drawing. Because on the Internet, there's so many words in so many photographs, people see a drawing by other stream that like, Wait, what's that? And I'm a thumb stopper, in other words, so it's. It gives people different perspective on what's going on. And I think that my background is a cartoonist for The New Yorker for forty years. Informs these drawings in an indirect background kind of way, because I have been watching culture have been watching politics for a very long time, so it gives me a, you know, a new attitude or a way to look at what's going on, >> right? And so you you call these illustrations, not cartoons. >> I do call the cartoons cartoons. Okay, we'll do the cartoons for the for >> The New Yorker and some other magazines, and those have a caption, and they often are supposed to be funny, or at least cultural commentary. I do political cartoons for medium, and those also have it have a point of view, are a caption. But the's this visual journalism like I'm doing here is more like reportage. It's more like this is what's happening here. You might be interested in seeing what people are talking about, what they're doing and I do behind the scenes to I don't just do like the Oscars. I'll do the stars if I could get them. And on the red crime on the red carpet, it's really cool. If I catch them, I'll draw them. And then But then I also do the people taking out the trash, the guy painting, you know, painting the sideboard or the counterman, things like that. So I try to give a sense of what it's like to be there. >> So you really kind of telling a story from different perspectives. Yes, right. Yeah. And so the role of I'd love to understand you mentioned being with the New Yorker for very long time and loved. You understand from your perspective, the evolution of cartoons and the impact they can make in in our society, in politics and economics. Tell us a little bit about some of the impacts that you've seen evolve over the last few decades. >> Well, I've written about >> that. I'm also a writer. I've written about that for a very sites. Did a commentary on op ed for The New York Times about the Charlie Hebdo's murders a couple years ago because we know cartoons can be very controversial. Yes and problematic Nick. And that's been true through the course of the history of our country, and I'm sure in England and other countries as well. But it's compounded. Now because of the Internet. I think cartoons could be misunderstood that could be used as weapons. People are gonna be talking about this next week at the South by Southwest. I'm talking about political cartoons and what what their impact has been in the past and how, >> how they, how they create an impact now >> and why that is, and how we could use it to the to our to good effect. You know, not a divisive tool, which I think is a problem that we're dealing with right now in our culture is everybody's so divided and so opinionated and so hateful towards each other. Can we use cartoons? Not to perpetuate that, but to make things better in some way. >> And that's kind of the theme of Wits, Women and Data Science Conference. You know, we're talking Teo and listening Teo at the live event here at Stanford and all of those around the world. It's really strong leaders and data sign. So we think of data science on DH, the technical skills. But data is generated. We generate tons of it as people, right with whatever we're buying, what we're watching on Netflix. But we're listening to on Spotify, etcetera. There's this data trail that we're all leaving, and we know you talked about using cartoons for good. Same conversations that we have on the data side, about being able to use data for good for cancer research, for example, rather than exposing and being malicious, that's interesting. Parallel that you've seen over the years that there is a lot of potential here. Tell me a little bit about the appetite in. Maybe we'll say the millennials and the younger generations for cartoons as a tool for positive the spread of positive social news and not fake news. >> Well, there. I know that >> there's more and more cartoons on the Internet now. A lot of Web comics and cartoonists are young. Cartoonists are using the Internet effectively, too. Put out their ideas. In fact, I when the Internet hit, I was mid career right, and it just took off and helped me become Mohr more well known just by leveraging the Internet. No, because I love it. You know, I love Communicate. It's >> actually it's really an extension >> of what I did as a child learning to draw, communicate with people. I was shy. I don't want to talk. The Internet is just a matter of for me. It's like a dialogue with people on DH. That's how I look at it, and I I think this new generation is really trying to find ways to use these tools in a good way. I think there's a whole new, you know, the kids in their >> twenties. I think they're trying >> to make a better world, are working on it, and that's exciting. >> You talk about communication and how you used your artistic skills from the time you were a child to communicate. Being shy. We also talk about communication in the context of events like the women, the data science, where it isn't just enough to be ableto understand and have the technical acumen to evaluate complex, messy data sets. But the communication piece kind of go back, Teo sort of basic human scaled, being able to communicate effectively. This is what I think the data say and why, and here's what we can do with it. So I think it's interesting that you're here at this event. That has a lot of parallels with communication with using a tool or information for the betterment off a little bit about how you got involved with women in data science. >> Well, I met Margot Garretson >> about five years ago, and through a mutual friend, we met in Iceland. All places >> like it's conference >> about women's rights. It was, it was the Icelandic women are so powerful anyway. We met there, really, to be good friends, and she invited me to come live, draw her new conference at the time. I think she had one year of it, and I thought, data science, OK, >> did you even know what >> that Wass? Yeah, kind of. But I didn't think I didn't see my connection. But I thought, Well, it's about women's rights and >> I'm a big part of my interest in what I want to do with my work is promote equal rights for women around the world. And so I thought, this this sounds terrific. Plus, it's global, and I do a lot of work globally to help them and help freedom of speech as well. So it seemed to be a great fit on DH and and it seems even more to be a good fit in that. It's a way to get the information out there in a visual way because people will hear that word data, and they like they probably just >> start. Yeah, zero because >> they see it connected with a cartoon or drawing it humanizes it for them a little bit. And if I could do that, that's great. And that's what's also fun is that I thought about this today was drawing the speakers, and I'm drawing one of the speakers. I forget her name right now, but I thought and I put it out on the Internet. There were no words on there, but it was just a woman speaker talking about really very technical data science. I put on the Internet with the caption on the tweet and I thought, People, it's it's it's just a constant reminder to people that women are doing this. And it's not a silly not like writing a long essay about why women should be in data signs and why they are and why they're important. But they're doing great things. But if you see it, it resonates a little bit more quickly and more forcefully. >> Absolutely. And it aligns with what we hear and say a lot of we can't be what we can't see. >> That's right. Yeah, that's a saying right where you said that. >> Yes. I'm not sure I'd love to take credit for it. Sure >> would be if she can see it, she could be it. That's another >> thing. That a young girl, she's my drawing of a professor talking on stage. Maybe she'll think about it. >> Absolutely. So in the last few seconds here, can you just give us a little bit of an idea of how you actually What What inspires you when you're seeing someone give a talk like you mentioned about maybe an esoteric or a very technical top? What do you normally look for? That's that Ah ha moment that you want to capture in ten minutes. >> Well, I try to capture that person's essence. I'm not a caricaturist. I don't pretend to be, but I draw >> a likeness of them, and they're the full body is the best body language. You know, they're just tick yah late ing. And then oftentimes I try to capture a sentence that they're saying that has has more universal appeal that somehow brings like a not like a layman into the subject A little bit. If I can find that sentence in what they're saying, I'll put that you have the speech balloon will be saying that. But I just try to capture the person best. I can >> do anything if you compare two wins. Twenty eighteen. Here we are a year later. Even more people here, the live event, even more people engaging and think Margo's that about twenty thousand live today. One hundred thousand over. I think the one hundred thirty plus regional with events, anything that you hear, see or feel that's even more exciting this year than last year. >> Um, well, I do. I do feel the >> the increase in numbers. I can feel it. There's there soon be more people here I don't true, but the senior more young people here, what else is it is it is a buzz. I think there's a >> There's an energy >> is an energy. Not that there wasn't there last. The last I've >> done three years now. It's been there, but there's a certain excitement right now. I think more women are stepping into this field of being recognized for doing so. >> And it's great that you're able Tio, reach, help wigs, reach an even bigger audience and tell this story with your illustrations in a more visual way, way also. Thank you so much, Liza, for taking some time. Must daughter by the Cuban talked to us. It's an honor to meet you And you. I love your drawings. >> Thank you so much. You >> want to thank you for watching the Cube? I'm Lisa Martin Live at the fourth annual Women and Data Science Conference at Stanford's took around. Be right back with my next guests.

live from Stanford University it's the cube covering global women and data science conference brought to you by Silicon angle media good morning and welcome to the cube I'm Lisa Martin and we are live at the global fourth annual women in data science conference at the Arriaga Alumni Center at Stanford I'm very pleased to be joined by one of the Wits ambassadors this year Regina cut of our math data science senior manager Accenture at Google and as I mentioned you are an ambassador for wits in Bangla Road the event is Saturday so Janelle welcome to the cube thank you pleasure it is - this is the fourth annual women in data science conference this year over 150 regional events of which you are hosting Bengaluru on Saturday March 9th 50-plus countries they're expecting a hundred thousand people to engage tell us a little bit about how you got to be involved in wins yeah so I care about data science but also what accurate representation of women in gender minority in the space and I think it's global initiative is doing amazing job in creating a significant impact globally and that kind of excited me to get involved with its initiative so you have which I can't believe you're an SME with ten plus years experience and data analytics focusing on marketing and customer analytics you've had senior analytics leadership positions at Accenture Hewlett Packard now Google tell me a little bit about before we get into some of the things that you're doing specifically the data--the on your experience as a female in technology the last ten plus years it's been exciting I started my career as an engineer I wanted to be a doctor fortunately unfortunately it couldn't happen and I ended up being an engineer and it has been an exciting ride since then I felt that had a passion for doing personal management and I posted management and specialization of operational research and project management and I started my career as a data scientist worked my way up through different leadership positions and currently leading a portfolio for Accenture at Google yeah in the read of science domain yeah it's exciting absolutely so one of the things that is happening this year wins 2019 the second annual data thon that's right really looking at predictive analytics challenge for social impact tell us a little bit about why Woods is doing this data thon and what you're doing in not respectively in Bengaluru okay so well you see data science in itself is a highly interdisciplinary domain and it requires people from different disciplines to come together look at the problem from different perspectives to be able to come up with the most amicable and optimal solution at any given point of time and Gareth on is one such avenue that fosters this collaboration and data thon is also an interesting Avenue because it helps young data science enthusiasts whom the require design skill sets and also helps the data science practitioners enhance and sustain their skill sets and that's the reason which Bangalore was keen on supporting what's global data thon initiative so this skill set so I'd like to kind of dig into that a bit because we're very familiar with those required data analytics skill sets from a subject matter expertise perspective but there's other skill sets that we talk about more and more with respect to data science and analytics and that's empathy it's communication negotiation can you talk to us a little bit about how some of those other skills help these data thon participants not just in the actual event but to further their careers absolutely so really into the real world so there are a lot of these challenges wherein you would require a domain expert you require someone who has a coding experience someone who has experience to handle multiple data sites programmatically and also you need someone who has a background of statistics and mathematics so you would need different people to come together I look at the problem and then be able to solve the challenges right so collaboration is extremely pivotal it's extremely important for us to put ourselves in other shoes and see a look at the problem and look at the problem from different perspective and collaboration or the key to be able to be successful in data science domain as such okay so let's get into the specifics about this year's data sets and the teams that were involved in the data thon all right so this year's marathon was focused on using satellite imagery to analyze the scenario of deforestation cost of oil palm plantations so what we did at which Bangalore is we conducted a community workshop because our research indicated that men dominated the Kegel leaderboard not just in Bangla but for India in general despite that region having amazing female leader scientists who are innovators in their space with multiple patents publications and innovations to the credit so we asked few questions to certain female data scientists to understand what could be the potential reason for their lower participation and the Kegel as a platform and their responses led us to these three reasons firstly they may not have the awareness about Kegel as a platform may be a little bit more about that platform so reviewers can understand that right so Kegel is a platform where in a lot of these data sets have been posted if anybody is interested to hold the required a design skill says they can definitely try explore build some codes and submit those schools and the teams that are submitting the codes which are very effective having greater accuracy he would get scored and the jiggle-ator build and you know that which is the most effective solution that can be implemented in the real world so we connected this data Sun workshop and one of the challenges that most of the female leader scientists face is having an environment to network collaborate and come up with a team to be able to attempt a specific data on challenge that is in hand so we connected data from workshop to help participants overcome this challenge and to encourage them to participate into its global hit a fun challenge so what we did as a part of this workshop was we give them on how to navigate Kegel as a platform and we connected an event specifically focused on networking so that participants could network form teams we also conducted a deep in-depth technical session focusing on deep neural nets and specifically on convolutional neural nets the understanding of which was pivotal to be able to solve this year's marathon challenge and the most interesting part of this telethon workshop was a mentorship guidance we were able to line up some amazing mentors and assign these minders to the concern or the interested participating teams and these matters work with respective teams for the next three weeks and for them terms with the required guidance coaching and mentorship held them for the VidCon showed me that's fantastic so over a three-week period how many participants did you have there 110 plus people for the key right yeah for the event and there are multiple teams that have formed and we assigned those mentors we identified seven different mentors and assigned these mentors to the interested participating teams we got a great response in terms of amazing turnout for the event new teams got formed new relationships got initiated new relationships new collaborations all right tell us about those achievements so they were there was one team from engineering branch or engineering division who were really near to the killer's platform they have their engineering exams coming up but despite that they learned a lot of these new concepts they form the team they work together as a team and we were able to submit the code on the Kegel leader board they were not the top scoring team but this entire experience of being able to collaborate look at the problem from different perspective and be able to submit the code despite one of these challenges and also navigate the platforming itself was a decent achievement from my perspective a huge achievement yeah so who you are at Stanford today you're gonna be flying back to go host the event there tell us about from your perspective if we look at the future line of sight for data science let's just take a peek at the momentum this that this Woods movement is generating this is our fourth year covering this fourth annual event fourth year on the cube and we see tremendous tremendous momentum mm-hmm with not just females participating and the woods leaders providing this sustained education throughout the year the podcast for example that they released a few months ago on Google Play on iTunes but also the number of participants worldwide as you look where we are today what in your perspective is the future for data science all right so data science is a domain is evolving at a lightning speed and may possibly hold the solution to almost all the challenges faced by humanity in the near future but to be able to come up with the most amicable and sustainable solution that's more relevant to the domain achieving diversity in this field is most and initiatives like wits help achieve that diversity and foster a real impact absolutely what's original thank you so much for joining me on the cube this morning live from wins 2019 we appreciate that wish you the best of luck kids a local event in Bengaluru over the weekend thank you it was a pleasure likewise thank you we want to thank you you're watching the cube live from Stanford University at the fourth annual woods conference I'm Lisa Martin stick around my next guest will join me in just a moment

>> Announcer: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018, brought to you by SnapLogic. >> Hey, welcome back, Jeff Frick here with theCUBE. We're at the Crossroads 101 and 92. You've probably been there. You're probably stuck in traffic. Look up, you'll see the sign SnapLogic. That's where we are. We're talking digital transformation. You've probably heard us talk about digital transformation on theCUBE, but not that many people or, excuse me, companies actually have an executive who's in charge of digital transformation. And that's not the case here at SnapLogic. And we're really excited to have our next guest. She's Diletta D'Onofrio, and she's the Head of Digital Transformation for SnapLogic. Welcome. >> Thank you, thank you for inviting me. >> Absolutely, so why does SnapLogic have a Head of Digital Transformation? I've never heard that for a company, and you're not really running digital transformation inside the company. You're helping your customers' digital transformation journey. >> Yeah absolutely, because integration is at the core of many transformations that we see led by our clients. And it's not about implementing a software for the most part. There's always the people processing technology. >> Jeff: Right, right. >> So what we are trying to do is to insert ourselves in the strategic discussion so that the implementation is more solid and secure. >> Right, right. >> And, so that's the intent of our practice. >> Right, and as you said, people process technology. We hear it all the time, and we hear a lot, too, of best practices in digital transformation is you have to make a commitment to that process change. You have to make a commitment to the people change. That's actually the hardest part. >> Diletta: Yeah. >> I think integration, usually, no one really wants to talk about integration up front because that's that hard little piece that we have to worry about down the road, but let's just not pretend that we have to do that. But as you said, that's a really important piece. It's tying all these systems together. So, you've been helping people with digital transformation here and in some of your prior jobs. So when you sit down with someone who's never heard that term, what do you tell them? What is digital transformation? >> So typically, we're pretty fortunate because I think especially in high tech, here in the valley, there are many clients that have a role which is equivalent to mine and is focused internally on digital transformation. So there either the head of digital transformation, the chief of digital officer. And what we typically do with them is to try to figure out what their plans are and participate to their journey by obviously helping from an integration perspective. >> Jeff: Right. >> Both on the application and data side. >> And where do there usually report up? It's always an interesting conversation because we go to chief data officer events. We go to chief analytics officer events. So you've got kind of these new evolving roles that are really built around data and enabling data and becoming a data driven enterprise. But does it report to the CIO? Does it report to the CTO? Does it report to up through the CEO? And then now you've got this role of people kind of heading up the digital transformation. Where do you see them reporting through? And what's kind of the most effective? Maybe that's a better question. What's the more effective place for them to report through? >> It's a little bit all over the map. There is not a standard. For example, a couple of clients, at Qualcomm, our equivalent in digital transformation is head of application, and he reports to the CIO. >> Jeff: Okay. >> So that's pretty traditional. Often the CIO is chartered with digital transformation for obvious reasons. He has the skillset, he has the team, he has the capability. But, I've seen cases where he or she reports to the CEO. >> Okay. >> Which is even more interesting I think because then it put an emphasis on the importance of the program and the importance of the targets associated with this program. So another client of ours airborne in Texas is actually the CMO and head of sales who reports to the CEO and is also in charge of digital transformation. And we are helping him with some cust-- >> It has the hat of also sales and marketing? >> Diletta: Absolutely, three jobs. >> So that's pretty interesting. Which is good cause those are the things that are kind of leading edge, front edge, to the client. As opposed to digital transformation just on your back-end processes. System integrators, in both those companies, you just listed as big companies. The system integrators have been building transformation businesses for a long, long time. How do they fit? How do you work with them? How does that kind of all come together around the project? >> Yep, so Qualcomm for example, you can see pretty much any single system integrator that you can imagine of. And they all have a portion of the transformation. >> Jeff: Right. >> None of them covers the entire scope. >> Jeff: Right. >> And the interesting portion as well is that because they are all competitors, often there is not a lot of collaboration. And then we are a little bit kind of agnostic, but obviously we have an interest in penetrating the account in terms of making the use of our technology. >> Right. >> So it's in our interest in what I'm trying to do, obviously I come from the system integrator world, so I do speak their language. And what we are trying to do is to work with them to make sure that we understand, were there use cases, were there business cases, and we kind of work together across different objective to enable the client to hopefully be digitally transformed. >> Right, so it's such a big word and the CEOs are talking to the boards about it and the public companies are talking to the analysts on the earnings call. We're going to digitally transform, and these are big organizations that are complex and have many, many pieces and parts. How do you get started? What are some best practices for people that have a board edict, or have a CEO edict? We need to digitally transform, I'm afraid of the competition, I don't even know who's coming. Where should people start, how do they slice and dice this thing so their not trying to eat the whole elephant in one bite? >> Yeah, the only cases that I've seen success on are the ones where, hopefully the leader has done that before. In some kind of shape or form. If it's a brand new chief digital officer, there are more challenges. But the most important thing is kind of keep the momentum. And you tend to keep the momentum through some sort of quick-wing. So if the scope is too large, and the roadmap is to fix over three or five years given the speed of change in technology is very difficult to achieve those goals. >> Jeff: Right. >> So it's much better to have a more agile mentality and maybe plan a year ahead. We did some very tangible, deliverable in the way and mobilize everyone around this. So that the momentum is kept and it's not just a nice word that a company has because they need to talk about the digital transformation. >> Right, and then what do you look at? You obviously have a specific point of view. You have your background and you've been a system integrator, and transformation leader. But in terms of coming from the SnapLogic point of view and integration, and that opportunity, What do you look for as opportunities for those early wins? Either based on prior experience or you just know there's some really inefficient ugly things that you can make big difference on, relatively easy. What do you look for as kind of those first wins in a digital transformation project? >> Yeah, ideally we love to be involved with everything to do with customer and sales and revenue. Because obviously those are the biggest paying point for the client. >> Jeff: Right. >> But often, you need to be flexible enough to understand what the priorities are. Currently I am involved in a much more traditional close activity accounting process. You will be thinking, okay, this may cost us, but actually fixing that problem first will create a lot of credibility within the company. So I think a company like ours has to be very flexible, need to listen to the client. >> Mh-hm. >> And be very flexible in terms of what priorities to start with first. >> Right. >> To prove the technology and then progress, maybe for higher value-- >> Right. >> activities. >> So I would hope it's 2018, that people understand that they're not setting forth on a five-year SAP, ERP implementation. Are we hopefully passed that, that this is not new information. That you need to take small bites, small victories, and move quickly. >> Yeah. >> Are we there? >> Yes but, still, I've seen a lot of strategy document and business plan that are two, three years of arisen and I think the arisen is way too long. But also at the same time, is this still teaching function? So you ask to picture a vision, at least directionally. >> Right. Right. >> So I think the vision has to be generic enough to then flex with the project and the activities within. >> Right. >> Two, three months. >> Right. >> Quarterly on most occasions. >> It's so funny that we continue to find these massive inefficiencies all over the place. You'd think that most of it had been wrung out by now. Between the European PA Limitations and all the business process reengineering, I guess was the old process >> Yes. >> before digital transformation. So I just wonder if you can share some stories from the field about some of these relatively short duration projects, and the yields that they are providing on this path to a more comprehensive digital transformation. >> Yeah so, the first example that comes to mind, again, going back to Qualcomm. When they talk about human capital management or engineering, what is interesting there is that you take the entire hire to retire. And it's pretty overwhelming. From the moment you hire an employee to the moment you obviously retire their function or their role, And what they did quite interestingly, was to come up with a few applications that will make the life of the employees and their manager easier. So we are biting the process by building application that for example, enable to facilitate the on-boarding or application that help HR with analytics and inquires. And gradually trying to automate the process which today even in a large company like a Fortune 100 company can be incredibly manual. >> Right. Right. >> And then another example that comes to mind to me is if you look at the entire holder to cash cycle of a company, from the moment the client to get in contact with the company through a website, to the moment they actually purchase the product. Again, there are many touch point and they're often disconnected. And a client of ours, Airborne, what we're doing with them is to just take one small bite which is figuring out from the time a client tried to configure a product on the website to the time they want to try the product. Our experience can be more automated. So that there is not a lot of interaction necessarily with customer services which has a limited bandwidth. But it's much more self-service. >> Jeff: Right. Right. >> And then gradually tackle the rest of the holder to cash cycle. >> So both of those examples are really about automating manual processes. >> Diletta: Yeah. >> As you just described them. So then what are the KPIs that you're using to measure success? Is it total time duration? Number of steps? Calls back to a person? What are some of the metrics of success? >> Yeah, so you see on the customers side it's kind of easy because you tend to very much require feedback from the customer. So if the customer satisfaction index goes up, or revenue goes up, or less return. So those KPIs we're kind of more familiar with. >> Okay. >> But when you look at the HR award, the human capital management award, there are so many ramifications of being able to serve your employees better. But much more intangible. Like for example, turnover. Well there is good turnover and bad turnover. So if you're serving your employees better with better hours, by which they can self-service some of their activities. Does it translate in less turnover? Maybe yes, or maybe actually that's translating more turnover because maybe the employees that sneak around are the ones that are more technology savvy, so. >> Right. >> Diletta: The human capital management side is harder in terms of defining KPIs. In it's much more early stage then anything to do with customer. And then there is the other universe associated with digitalizing product. Like for example, the world of IOT. That we are involved with, with a few clients. And that is a very measurable and tangible because you actually coming up with new product and what we're doing is facilitating the ability to access data. >> Jeff: Right. >> Which is a very tangible element of the product development lifecycle. >> So of all the transformation projects that you're involved in, how would you break them down in rough numbers of kind of cost savings on an existing process, which is through automation. Versus kind of forward facing customer facing, let's just call it warpped around a customer experience so ultimately you're getting higher customer satisfaction scores and revenue. Versus the third which you just touched on, which is so, so important. Which is converting from a product based company or some of these more tangible into more of a service recurring revenue. That's probably built around that product and the example that gets thrown around all the time is, when GE starts selling miles of propulsion versus selling engines. It's a very different kind of relationship. So in the things that you work on, how would you kind of break up the percentages in those three buckets? >> Yeah, so what we see still a lot, and what I would like to see less, is the first bucket. >> Jeff: Okay. >> Which is reducing cost so I will save more than 50%. >> Jeff: Okay. >> Which is around reduce cost, drive efficiency, better reporting, eliminating application, right? Because many client have too many application to preform some of these back office processes. >> Right. Right. >> And they're very much associated with cost exercise. >> Right. >> And so over 50%, for sure. >> Okay. And that's logical cause that's obviously an easy place to start. You're not changing the company per se. >> Yeah. >> You're looking for efficiencies. Alright so, Diletta, I'll give you the last word before we sign off. If you get called in to a new project, it's a CEO, they're stressed out, they know they have to do this. What do you tell them about digital transformation? How do you kind of help them break it down so it's not just this overwhelming, giant, goal on high? But actually something that they should get excited about, something they can have some success with and something that ultimately is going to be a really good thing. >> I think there is no one recipe. It's about figuring out where the company wants to go. What is the primary objective? Is it sales? Is it new market? Is it new product? And then kind of break it down in a tangible chunck and it kind of makes sense to them. But you got to go for the first priority item. This year I'm sure we'll be able to articulate very well. >> Yes, get that quick win. Well Diletta, thanks for spending a few minutes with us. And good luck on transforming everybody. (laughs) >> Thank you. >> Alright, she's Diletta, I'm Jeff. You're watching theCUBE, from SnapLogic headquarters in San Mateo, California. Thanks for watching. (bright music)

>> Announcer: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018, brought to you by SnapLogic. >> Hey, welcome back, Jeff Frick here with theCUBE. We're at the Crossroads 101 and 92. You've probably been there. You're probably stuck in traffic. Look up, you'll see the sign SnapLogic. That's where we are. We're talking digital transformation. You've probably heard us talk about digital transformation on theCUBE, but not that many people or, excuse me, companies actually have an executive who's in charge of digital transformation. And that's not the case here at SnapLogic. And we're really excited to have our next guest. She's Diletta D'Onofrio, and she's the Head of Digital Transformation for SnapLogic. Welcome. >> Thank you, thank you for inviting me. >> Absolutely, so why does SnapLogic have a Head of Digital Transformation? I've never heard that for a company, and you're not really running digital transformation inside the company. You're helping your customers' digital transformation journey. >> Yeah absolutely, because integration is at the core of many transformations that we see led by our clients. And it's not about implementing a software for the most part. There's always the people processing technology. >> Jeff: Right, right. >> So what we are trying to do is to insert ourselves in the strategic discussion so that the implementation is more solid and secure. >> Right, right. >> And, so that's the intent of our practice. >> Right, and as you said, people process technology. We hear it all the time, and we hear a lot, too, of best practices in digital transformation is you have to make a commitment to that process change. You have to make a commitment to the people change. That's actually the hardest part. >> Diletta: Yeah. >> I think integration, usually, no one really wants to talk about integration up front because that's that hard little piece that we have to worry about down the road, but let's just not pretend that we have to do that. But as you said, that's a really important piece. It's tying all these systems together. So, you've been helping people with digital transformation here and in some of your prior jobs. So when you sit down with someone who's never heard that term, what do you tell them? What is digital transformation? >> So typically, we're pretty fortunate because I think especially Nytec here in the valley, there are many clients that have a role which is equivalent to mine and is focused internally on digital transformation. So there either the head of digital transformation, the chief of digital officer. And what we typically do with them is to try to figure out what their plans are and participate to their journey by obviously helping from an integration perspective. >> Jeff: Right. >> Both on the application and data side. >> And where do there usually report at? It's always an interesting conversation because we go to chief data officer events. We go to chief analytics officer events. So you've got kind of these new evolving roles that are really built around data and enabling data and becoming a data driven enterprise. But does it report to the CIO? Does it report to the CTO? Does it report to up through the CEO? And then now you've got this role of people kind of heading up the digital transformation. Where do you see them reporting through? And what's kind of the most effective? Maybe that's a better question. What's the more effective place for them to report through? >> It's a little bit all over the map. There is not a standard. For example, a couple of clients, at Qualcomm, our equivalent in digital transformation is head of application, and he reports to the CIO. >> Jeff: Okay. >> So that's pretty traditional. Often the CIO is chartered with digital transformation for obvious reasons. He has the skillset, he has the team, he has the capability. But, I've seen cases where he or she reports to the CEO. >> Okay. >> Which is even more interesting I think because then it put an emphasis on the importance of the program and the importance of the targets associated with this program. So another client of ours airborne in Texas is actually the CMO and head of sales who reports to the CEO and is also in charge of digital transformation. And we are helping him with some cust-- >> It has the hat of also sales and marketing? >> Diletta: Absolutely, three jobs. >> So that's pretty interesting. Which is good cause those are the things that are kind of leading edge, front edge, to the client. As opposed to digital transformation just on your back-end processes. System integrators, in both those companies, you just listed as big companies. The system integrators have been building transformation businesses for a long, long time. How do they fit? How do you work with them? How does that kind of all come together around the project? >> Yep, so Qualcomm for example, you can see pretty much any single system integrator that you can imagine of. And they all have a portion of the transformation. >> Jeff: Right. >> None of them covers the entire scope. >> Jeff: Right. >> And the interesting portion as well is that because they are all competitors, often there is not a lot of collaboration. And then we are a little bit kind of agnostic, but obviously we have an interest in penetrating the account in terms of making the use of our technology. >> Right. >> So it's in our interest in what I'm trying to do, obviously I come from the system integrator ward so I do speak their language. And what we are trying to do is to work with them to make sure that we understand, were there use cases, were there business cases, and we kind of work together across different objective to enable the client to hopefully be digitally transformed. >> Right, so it's such a big word and the CEOs are talking to the boards about it and the public companies are talking to the analysts on the earnings call. We're going to digitally transform, and these are big organizations that are complex and have many, many pieces and parts. How do you get started? What are some best practices for people that have a board edict, or have a CEO edict? We need to digitally transform, I'm afraid of the competition, I don't even know who's coming. Where should people start, how do they slice and dice this thing so their not trying to eat the whole elephant in one bite? >> Yeah, the only cases that I've seen success on are the ones where, hopefully the leader has done that before. In some kind of shape or form. If it's a brand new chief digital officer, there are more challenges. But the most important thing is kind of keep the momentum. And you tend to keep the momentum through some sort of quick-wing. So if the scope is too large, and the roadmap is to fix over three or five years given the speed of change in technology is very difficult to achieve those goals. >> Jeff: Right. >> So it's much better to have a more agile mentality and maybe plan a year ahead. We did some very tangible, deliverable in the way and mobilize everyone around this. So that the momentum is kept and it's not just a nice word that a company has because they need to talk about the digital transformation. >> Right, and then what do you look at? You obviously have a specific point of view. You have your background and you've been a system integrator, and transformation leader. But in terms of coming from the SnapLogic point of view and integration, and that opportunity, What do you look for as opportunities for those early wins? Either based on prior experience or you just know there's some really inefficient ugly things that you can make big difference on, relatively easy. What do you look for as kind of those first wins in a digital transformation project? >> Yeah, ideally we love to be involved with everything to do with customer and sales and revenue. Because obviously those are the biggest paying point for the client. >> Jeff: Right. >> But often, you need to be flexible enough to understand what the priorities are. Currently I am involved in a much more traditional close activity accounting process. You will be thinking, okay, this may cost us, but actually fixing that problem first will create a lot of credibility within the company. So I think a company like ours has to be very flexible, need to listen to the client. >> Mh-hm. >> And be very flexible in terms of what priorities to start with first. >> Right. >> To prove the technology and then progress, maybe for higher value-- >> Right. >> activities. >> So I would hope it's 2018, that people understand that they're not setting forth on a five-year SAP, ERP implementation. Are we hopefully passed that, that this is not new information. That you need to take small bites, small victories, and move quickly. >> Yeah. >> Are we there? >> Yes but, still, I've seen a lot of strategy document and business plan that are two, three years of arisen and I think the arisen is way too long. But also at the same time, is this still teaching function? So you ask to picture a vision, at least directionally. >> Right. Right. >> So I think the vision has to be generic enough to then flex with the project and the activities within. >> Right. >> Two, three months. >> Right. >> Quarterly on most occasions. >> It's so funny that we continue to find these massive inefficiencies all over the place. You'd think that most of it had been wrung out by now. Between the European PA Limitations and all the business process reengineering, I guess was the old process >> Yes. >> before digital transformation. So I just wonder if you can share some stories from the field about some of these relatively short duration projects, and the yields that they are providing on this path to a more comprehensive digital transformation. >> Yeah so, the first example that comes to mind, again, going back to Qualcomm. When they talk about human capital management or engineering, what is interesting there is that you take the entire hire to retire. And it's pretty overwhelming. From the moment you hire an employee to the moment you obviously retire their function or their role, And what they did quite interestingly, was to come up with a few applications that will make the life of the employees and their manager easier. So we are biting the process by building application that for example, enable to facilitate the on-boarding or application that help HR with analytics and inquires. And gradually trying to automate the process which today even in a large company like a fortune 100 company can be incredibly manual. >> Right. Right. >> And then another example that comes to mind to me is if you look at the entire holder to cash cycle of a company, from the moment the client to get in contact with the company through a website, to the moment they actually purchase the product. Again, there are many touch point and they're often disconnected. And a client of ours, Airborne, what we're doing with them is to just take one small bite which is figuring out from the time a client tried to configure a product on the website to the time they want to try the product. Our experience can be more automated. So that there is not a lot of interaction necessarily with customer services which has a limited bandwidth. But it's much more self-service. >> Jeff: Right. Right. >> And then gradually tackle the rest of the holder to cash cycle. >> So both of those examples are really about automating manual processes. >> Diletta: Yeah. >> As you just described them. So then what are the KPIs that you're using to measure success? Is it total time duration? Number of steps? Calls back to a person? What are some of the metrics of success? >> Yeah, so you see on the customers side it's kind of easy because you tend to very much require feedback from the customer. So if the customer satisfaction index goes up, or revenue goes up, or less return. So those KPIs we're kind of more familiar with. >> Okay. >> But when you look at the HR award, the human capital management award, there are so many ramifications of being able to serve your employees better. But much more intangible. Like for example, turnover. Well there is good turnover and bad turnover. So if you're serving your employees better with better hours, by which they can self-service some of their activities. Does it translate in less turnover? Maybe yes, or maybe actually that's translating more turnover because maybe the employees that sneak around are the ones that are more technology savvy, so. >> Right. >> Diletta: The human capital management side is harder in terms of defining KPIs. In it's much more early stage then anything to do with customer. And then there is the other universe associated with digitalizing product. Like for example, the world of IOT. That we are involved with, with a few clients. And that is a very measurable and tangible because you actually coming up with new product and what we're doing is facilitating the ability to access data. >> Jeff: Right. >> Which is a very tangible element of the product development lifecycle. >> So of all the transformation projects that you're involved in, how would you break them down in rough numbers of kind of cost savings on an existing process, which is through automation. Versus kind of forward facing customer facing, let's just call it warpped around a customer experience so ultimately you're getting higher customer satisfaction scores and revenue. Versus the third which you just touched on, which is so, so important. Which is converting from a product based company or some of these more tangible into more of a service recurring revenue. That's probably built around that product and the example that gets thrown around all the time is, when GE starts selling miles of propulsion versus selling engines. It's a very different kind of relationship. So in the things that you work on, how would you kind of break up the percentages in those three buckets? >> Yeah, so what we see still a lot, and what I would like to see less, is the first bucket. >> Jeff: Okay. >> Which is reducing cost so I will save more than 50%. >> Jeff: Okay. >> Which is around reduce cost, drive efficiency, better reporting, eliminating application, right? Because many client have too many application to preform some of these back office processes. >> Right. Right. >> And they're very much associated with cost exercise. >> Right. >> And so over 50%, for sure. >> Okay. And that's logical cause that's obviously an easy place to start. You're not changing the company per se. >> Yeah. >> You're looking for efficiencies. Alright so, Diletta, I'll give you the last word before we sign off. If you get called in to a new project, it's a CEO, they're stressed out, they know they have to do this. What do you tell them about digital transformation? How do you kind of help them break it down so it's not just this overwhelming, giant, goal on high? But actually something that they should get excited about, something they can have some success with and something that ultimately is going to be a really good thing. >> I think there is no one recipe. It's about figuring out where the company wants to go. What is the primary objective? Is it sales? Is it new market? Is it new product? And then kind of break it down in a tangible chunck and it kind of makes sense to them. But you got to go for the first priority item. This year I'm sure we'll be able to articulate very well. >> Yes, get that quick win. Well Diletta, thanks for spending a few minutes with us. And good luck on transforming everybody. (laughs) >> Thank you. >> Alright, she's Diletta, I'm Jeff. You're watching theCUBE, from SnapLogic headquarters in San Mateo, California. Thanks for watching. (bright music)

live from Stanford University in Palo Alto California it's the cube covering women in data science conference 2018 brought to you by Stanford welcome to the cube we are alive at Stanford University I'm Lisa Martin and we are at the 3rd annual women in data science conference or woods whiz if you're not familiar is a one-day technical conference that has keynote speakers technical vision talks as well as a career panel and we are fortunate to have guests from all three today it's also an environment it's really a movement that's aimed at inspiring and educating data scientists globally and supporting women in the field this event is remarkable in its third year they are expecting to reach sit down for this 100,000 people today we were here at Stanford this is the main event in person but there's over 150 plus regional events around the globe in 50 plus countries and I think those numbers will shift up during the day and I'll be sure to brief you on that we're excited to be joined by one of the speakers featured on mainstage this morning not only a cube alum not returning to us but also the first ever female president of Harvey Mudd College dr. Maria Klawe a maria welcome back to the cube thank you it's great to be here it's so exciting to have you here I love you representing with your t-shirt there I mentioned you are the first-ever female president of Harvey Mudd you've been in this role for about 12 years and you've made some pretty remarkable changes there supporting women in technology you gave some stats this morning in your talk a few minutes ago share with us what you've done to improve the percentages of females in faculty positions as well as in this student body well the first thing I should say is as president I do nothing nothing it's like a good job the whole thing that makes it work at Harvey Mudd is we are community that's committed to diversity and inclusion and so everything we do we try to figure out ways that we will attract people who are underrepresented so that's women in areas like computer science and engineering physics it's people of color in all areas of science and engineering and it's also LGTB q+ i mean it's you know it's it's muslims it's it's just like all kinds of things and our whole goal is to show that it doesn't matter what race you are doesn't matter what gender or anything else if you bring hard work and persistence and curiosity you can succeed i love that especially the curiosity part one of the things that you mentioned this morning was that for people don't worry about the things that you you might think you're not good at i thought that was a very important message as well as something that I heard you say previously on the cube as well and that is the best time that you found to reach women young women and to get them interested in stem as even a field of study is the first semester in college and I should with you off camera that was when I found stem in biology tell me a little bit more about that and how what are some of the key elements that you find about that time in a university career that are so I guess right for inspire inspiration so I think the thing is that when you're starting in college if somebody can introduce you to something you find fun engaging and if you can really discover that you can solve major issues in the world by using these ideas these concepts the skills you're probably going to stay in that and graduate in that field whereas if somebody does that to when you're in middle school there's still lots of time to get put off and so our whole idea is that we emphasize creativity teamwork and problem-solving and we do that whether it's in math or an engineering or computer science or biology we just in all of our fields and when we get young women and young men excited about these possibilities they stick with it and I love that you mentioned the word fun and curiosity I can remember exactly where I was and bio 101 and I was suddenly I'd like to biology but never occurred to me that I would ever have the ability to study it and it was a teacher that showed me this is fun and also and I think you probably do this too showed that you believe in someone you've got talent here and I think that that inspiration coming from a mentor whether you know it's a mentor or not is a key element there that is one that I hope all of the the viewers today and the women that are participating in which have the chance to find so one of the things every single one of us can do in our lives is encourage others and you know it's amazing how much impact you can have I met somebody who's now a faculty person at Stanford she did her PhD in mechanical engineering her name is Allison Marsden I hadn't seen her for I don't know probably almost 12 years and she said she came up to me and she said I met you just as I was finishing my PhD and you gave me a much-needed pep talk and you know that is so easy to do believing in people encouraging them and it makes so much difference it does I love that so wins is as I mentioned in the third annual and the growth that they have seen is unbelievable I've not seen anything quite like it in in tech in terms of events it's aimed at inspiring not just women and data science but but data science in general what is it about wizz that attracted you and what are some of the key things that you shared this morning in your opening remarks well so the thing that attracts me about weeds is the following data science is growing exponentially in terms of the job opportunities in terms of the impact on the world and what I love about withes is that they had the insight this flash of genius I think that they would do a conference where all the speakers would be women and just that they would show that there are women all over the world who are contributing to data science who are loving it who are being successful and it's it's the crazy thing because in some ways it's really easy to do but nobody had done it right and it's so clear that there's a need for this when you think about all of the different locations around the world that are are doing a width version in Nigeria in Mumbai in London in you know just all across the world there are people doing this yeah so the things I shared are number one oh my goodness this is a great time to get into data science it's just there's so many opportunities in terms of career opportunities but there's so many opportunities to make a difference in the world and that's really important number two I shared that it's you never too old to learn math and CS and you know my example is my younger sister who's 63 and who's learning math and computer science at the northern Alberta Institute of Technology Nate all the other students are 18 to 24 she suffers from fibromyalgia she's walked with a walker she's quite disabled she's getting A's and a-pluses it's so cool and you know I think for every single person in the world there's an opportunity to learn something new and the most important thing is hard work and perseverance that it's so much more important than absolutely anything else I agree with that so much it's it's such an inspiring time but I think that you said there was clearly a demand for this what Wits has done in such a short time period demonstrates massive demand the stats that I was reading the last couple of days that show that women with stem degrees only 26% of them are actually working in STEM fields that's very low and and even can start from things like how how companies are recruiting talent and the messages that they're sending may be the right ones maybe not so much so I have a great example for you about companies recruiting talent so about three years ago I was no actually almost four years ago now I was talking in a conference called HR 50 and it's a conference that's aimed at the chief human resource officers of 50 multinationals and my talk I was talking for 25 minutes on how to recruit and retain women in tech careers and afterwards the chief HR officer from Accenture came up to me and she said you know we hire 17,000 software engineers a year Justin India 17,000 and she said we've been coming in at 30 percent female and I want to get that up to 45 she said you told me some really good things I could use she she said you told me how to change the way we advertise jobs change the way we interview for jobs four months later her name is Ellen Chowk Ellen comes up to me at another conference this has happens to be the most powerful women's summit that's run by Fortune magazine every year and she comes up and she says Maria I implemented different job descriptions we changed the way we interview and I also we started actually recruiting at Women's College engineering colleges in India as well as co-ed once she said we came in at 42% Wow from 30 to 42 just making those changes crying I went Ellen you owe me you're joining my more my board and she did right and you know they have Accenture has now set a goal of being at 50/50 in technical roles by 2025 Wow they even continued to come in all around the world they're coming in over 40% and then they've started really looking at how many women are being promoted to partners and they've moved that number up to 30% in the most recent year so you know it's a such a great example of a company that just decided we're gonna think about how we advertise we're going to think about how we interview we're gonna think about how we do promotions and we're going to make it equitable and from a marketing perspective those aren't massive massive changes so whether it expects quite simple exactly yeah these are so the thing I think about so when I look at what's happening at Harvey Mudd and how we've gotten more women into computer science engineering physics into every discipline it's really all about encouragement and support it's about believing in people it's about having faculty who when they start teaching a class the perhaps is technically very rigorous they might say this is a really challenging course every student in this course who works hard is going to succeed it's setting that expectation that everyone can succeed it's so important I think back to physics and college and how the baseline was probably 60% in terms of of grades scoring and you went in with intimidation I don't know if I can do this and it sounds like again a such a simple yet revolutionary approach that you're taking let's make things simple let's be supportive and encouraging yet hopefully these people will get enough confidence that they'll be able to sustain that even within themselves as they graduate and go into careers whether they stay in academia or go in industry and I know you've got great experiences in both I have I so I've been very lucky and I've been able to work both in academia and in industry I will say so I worked for IBM Research for eight years early in my career and you know I tribute a lot of my success as a leader since then to the kind of professional development that I got as a manager at IBM Research and you know what I think is that I there's not that much difference between creating a great learning environment and a great work environment and one of the interesting results that came out of a study at Google sometime in the last few months is they looked at what made senior engineering managers successful and the least important thing was their knowledge of engineering of course they all have good knowledge of engineering but it was empathy ability to mentor communication skills ability to encourage all of these kinds of things that we think of as quote unquote soft skills but to actually change the world and and on those sasuke's you know we hear a lot about the hard skills if we're thinking about data scientists from a role perspective statistical analysis etcetera but those soft skills empathy and also the ability to kind of bring in different perspectives for analyzing data can really have a major impact on every sector and socially in the world today and that's why we need women and people of color and people who are not well represented in these fields because data science is changing everything in the world absolutely is and if we want those changes to be for the better we really need diverse perspectives and experiences influencing things that get made because you know algorithms are not algorithms can be hostile and negative as well as positive and you know good for the world and you need people who actually will raise the questions about the ethics of algorithms and how it gets used there's a great book about how math can be used for the bad of humanity as well as the good of humanity and until we get enough people with different perspectives into these roles nobody's going to be asking those questions right right well I think with the momentum that we're feeling in this movement today and it sounds like what you're being able to influence greatly at Mudd for the last twelve years plus there is there are our foundations that are being put in place with not just on the education perspective but on the personal perspective and in inspiring the next generation giving them helping them I should say achieve the confidence that they need to sustain them throughout their career summary I thank you so much for finding the time to join us this morning on the cube it's great to have you back and we can't wait to talk to you next year and hear what great things do you influence and well next twelve months well it's wonderful to have a chance to talk with you as well thank you so much excellent you've been watching the cube we're live at Stanford University for the third annual women in data science wins conference join the conversation hashtag wins 2018 I'm Lisa Martin stick around I'll be right back with my next guest after a short break

>> Narrator: Live from Las Vegas it's The Cube, covering AWS Reinvent 2017 presented by AWS, Intel and our ecosystem of partners. >> John: And we are live here at Las Vegas, at the Sands Expo wrapping up our coverage here. Reinvent three days strong, inter-going with AWS and a number of great partners within their ecosystem. One of those is Fortinet and we're now joined by Matt Play who is the VP of Cloud Carrier and service providers there at Fortinet, thanks for joining us here Matt, good to see you, sir. >> Matt: It's a pleasure to be here. Thank you. >> John: Yeah, tell us a little bit about, you know, first of all, what you do as far as the company's concerned and about your relationship with AWS and I know you're exhibiting just over our shoulder here so, its a big week for you and for them. >> Matt: I mean the energy here is unlike any other event I've been to, it's fantastic, you can't even describe what this feels like, you have to really be here to really appreciate it so it's just been, it's my first show, being here and it's just absolutely great to see, you know, all the companies collaborating, people getting together and working together. So from the show perspective, I mean it's just fantastic. So we're just happy to be a part of it and Fortinet is doing a lot of great things with AWS. I think our synergies are really well aligned, we have a lot of commonality in our DNA and our culture in history. So, you know, we love to, we're innovators. We love technology and we really hang our hat on that. So as a security ISV you can the products, that's always important right, the products that are involved in it but it's really about the theory or philosophy behind it that we really look towards to accelerate our partnership. >> John: Yeah. I mean, I don't know how much booth time you spend but I'm just always curious at shows. What's the chatter about? You know, when people come up what are they most interested about? You know, what's been like in your mind an overall theme or that recurring theme that you're hearing a lot from potential customers here? >> It's really diverse so it's not just one talk track. It's really a number of different points or elements or what's important. You look around you see IOT, you see dev-ops, you see a number of different things that are kind of bubbling up and you saw all the announcements from AWS and Bare-Metal so that's gonna change things quite a bit. So it was really surprising to see, you know some of our announcements this week were really important. >> John: You've had a big week. >> Matt: We had a great week. >> John: Yeah. >> Matt: We had some really special things that we'd been working on that got announced this week. You know FortiSandboxes and On Demand now in AWS. So we're the only sandbox available in AWS. I think that's very compelling and that's a pretty useful thing. The WAF rules that was a launch yesterday that happened and we're part of the role set so you can take some of the role sets it goes out to our fort of guard enforces it. And then finally they became fabric partner. So fabric really is for us an ecosystem of products. But not only our products it's really about working with other collaboration partners but sometimes competitors and that's okay with us because we believe that's really the only way security's gonna be effective. >> Justin: We were talking before and you were explaining some of the portfolio approach that Fortinet takes to security. We've always been talking about defense in depth as being a thing that you should do with security and really there is no one magic silver bullet that you can use. You have to have different tools for different use cases. And you've got lots of different products that all work well together but they also work well with other products. Which is quite interesting, that fabric concept. Could you maybe give us a bit more color on what the fabric is and some of the portfolio products that plug in? >> Absolutely. So to your first point, we have eight products in AWS and available. It's really about creating a security stack of enforcement because one product necessarily won't do the entire job you need it to do. So we have complementary products, we have, you know, bespoke products, or pointed products. So we have, like I was saying, eight. That's the most out of any other security ISV in the marketplace today. So I think that's a huge competitive advantage. And really what's important is that you really need to see, have a single pane of glass console to look to look at your environments. >> Yeah. >> Statistics say around 65% of organizations or enterprises will have a hybrid environment. So kinda the legacy bespoke, or the legacy traditional networks, and then they're gonna have obviously AWS in instances and it's really important for security that correlation and automation to see across your entire network and footprint that you have. Really all the products to us are all the same whether you deploy them on-premise, off-premise, in the cloud, private cloud, public cloud, really doesn't matter to us. It's all the same sort of look and feel for our products. >> Yeah, I am hearing from all the security people both vendor and on the customer side that I speak to that there is a real collaboration going on in security right now. And we were talking just before we went to air that the security has just blown up in the last sort of four or five years. What used to be a bit of an afterthought is now front of mind for a lot of customers. So they're using some of the products like Fortinet to be able to say "well I want to solve this and this is something I need to do today but I also need it to work with other things that I'm doing". So it's interesting that Fortinet's chosen to take that partnering approach particularly something like your relationship with AWS with web application firewalls that you're doing. That's a real partnership approach where you're saying "we do something quite well but Amazon can use this to give us access to more and more customers". Is that part of Fortinet's core way of doing things? Has that always been the case? >> Yeah, I think, you know the history and sort of DNA of Fortinet it was kinda founded on let's do it ourselves. Let's build it because we believe we can build it the best. And so kinda through the generation of that like you said, you know, security is one of the things that it was sort of geeky and kinda cool sorta specific like people didn't really understand security all that well but now it's headline news and changes market cap literally overnight. Right, we see that a lot in the news and unfortunately some nasty things happen to peoples' information. So if you look at that our CFO talked about digital trust a number of years ago. And really, you want to do business with companies you trust and that's so important. So when you give your credit card information, your social security number, that's important, right. You want somebody to take caution when jotting down that information, right. So, for us, we saw it as a competitive advantage because how it really started for us before the fabric was threat information sharing. So we have an initiative where we work with others in the marketplace who are security vendors to share threat data and to make that more useful for companies because really that's what's gonna win. And sharing and looking at the portfolio it really goes back Fortiguard platform. Everything kind of points back to that as far as the threat vectors, right. >> You mention that there'd been problems, obviously, there's a headline a week, right. And that's kind of the point of the question I want to get at here with you. In a way, from a consumer standpoint, we're almost desensitized a little bit because oh god another one, right. Another breach, another problem so what kind of mind set are you fighting in terms of you can have 1000 wins but one loss or a million wins but one loss it's another headline it's another problem and it's another barrier for you. I mean, how do you look at that from a philosophical approach as a company and a mind set approach as a company? >> That's a great question, right. So there is kind of this, I think in the industry, there's this consensus that it's not a question of if it's a question of when. And so, that's a little hard to stomach, right. >> John: Cause you wanna win them all. >> You're saying, hey look, right you wanna win 100% of the time and that's just the reality of life, right. Yeah, of course, right. So, of course we look at it as a layered approach. So if you, I'll use a very simple analogy but I think it's sort of effective. If you lock your front door, if you lock your windows, if you put on your alarm system, you have cameras, and then ideally you live in a gated neighborhood. They're just layers to ensure that if someone comes by to look at your environment, and they go "man that's too hard, it's just too much work. There's cameras there, I can tell they have a dog, it's way too complicated I'm getting into that". And that's what security really should be. Security should be a multi layer approach that uses complementary products that coordinate and orchestrate together and automate and those are really important things when it comes to security and keeping the bad guys out. So you sort of want to have this security posture that's just so many layers of defense that it's very hard to penetrate. >> So when's someone's thinking about what they've currently got in there like looking at their threat model that they might have and what their risk would be at the moment. How would you help customers to evaluate well, what should I do next? We were talking with someone else on the cube earlier today about well okay, you need to do the basics first. You need to brush your teeth. How do you help customers identify what is the 'locking your front door'? What is the 'I need to buy a dog'? What is the 'I need to make sure I've got all my windows locked'? >> Matt: Right. >> So how do you help customers figure that out? >> That's a great question. Always when we talk with customers we evaluate their environment, very bespoke and sort of custom-tailored. That's very important to understand exactly what you're trying to solve. However, just like your credit score, we believe that there should be a security competency score. So it's sort of an in depth evaluation of your network, the holistic security posture, how that looks, and so we're now offering that in our new platform. To come in and offer sort of a security threat score, if you will, to say how effective we think you are. So I think that helps. >> Justin: It's like a maturity model. >> What's that? >> It's like a maturity model. >> Matt: Yep, exactly so I think that's gonna help a lot of people make sense out of it. And there's different parameters and how we report that back to our customers that sort of makes sense and then we say, "well we believe these products should be the products that you choose and this is the kind of security posture you have". And, you know the reality is, if you're connected to the internet you have to get out and things have to get it. >> [One Of The Hosts] Yeah. >> So you just have to have that layered approach. >> John: It used to be like it was a cost decision way back. Now reputation's on the line, you said market cap as you pointed out. I mean, the risks and the exposure and the damage is exponentially worse today than it was just three, four years ago, right. >> I think it even seems different from like six months ago. You know, it's really insane to think that companies could disappear based upon what happens with that information. We don't want to be the ambulance chaser, that's not our philosophy but it's about being protected and it's about being you know. I think with with security, retrospectively going back, is not all that useful. With security, it's better to kinda take the work and do it up front and we believe that that's what's really changing in the market that pivot to when you design a network security is arm and arm with networking or you know in this case, in AWS' case, how you move workloads elastically to the cloud. I mean those are all considerations now and I think you see that in the marketplace and in AWS' launch, like we said in the WAF rules. I think that's one step closer to marrying security with the function of what you're trying to do in the cloud. >> Justin: Yeah, and it needs to evolve over time as well. So again, you start with the basics, and even as your business changes you might be in completely on-site today but if you go to cloud, well now I need to do cloud-based security things. You have to start thinking about it in a different way. So hopefully customers are looking at things and looking at the portfolio approach and saying "okay, today I might need one product but tomorrow, well, I'm gonna need something else, I'm gonna need two or three or four". And as you say, if I've got something that plays well with others, then I can make a decision yesterday that well, actually I can still use this. I don't suddenly have to throw everything I did a year ago, throw it all away and start again from scratch. >> Matt: Sure, absolutely and that's the fun of what we do. Working in technology, it moves so fast. That's why we all do it I think. Because it's, to be close to it and to be a part of it I mean, that's why I get up everyday it's the coolest thing we get to do. And so because of that, you're right. We don't even know what's gonna happen in 2019. I mean think about the change in just one year's time. The velocity, and what we're seeing that AWS is accomplishing in short periods of time you really need to move quickly. And that's our commitment absolutely as a security company. >> John: And fortunately, you're busy. Right, and fortunately you're busy but because the risks are greater the threats are bigger so all the more reason for the success that you've had obviously and the continued success. We wish you that and thank you for being here on The Cube. We appreciate it. >> Matt: Thanks for having me. >> John: Yeah, always good to see you. That wraps up our coverage here on the cube for my colleague, Mr. Warren, and all of us behind the scenes. Thank you for joining us here, live from AWS Reinvent in Las Vegas. (light music)