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Simon Kofkin-Hansen, IBM | VeeamON 2020


 

>> From around the globe, it's theCUBE with digital coverage of VeeamON 2020 brought to you by Veeam. >> Welcome back, I'm Stu Miniman, and this is theCUBE's coverage of VeeamON 2020 online. Of course, instead of all gathering together in Las Vegas, we were getting to talk to participants of the community where they are around the globe. Happy to welcome to the program, first time guest on the program, he's part of the opening keynote I'm sure most of you saw, Simon Kofkin-Hansen, chief technology officer for VMware Solutions inside of IBM. Simon, thanks so much for joining us. >> Thank you Stu, it's a pleasure to be here. >> All right, so you know, obviously we know IBM quite well. We at theCUBE at you know, the virtual events, both RedHat Summit and IBM Think not too long in the past there. Talking a lot about you know, the open hybrid cloud many of the messages that I hear from Veeam remind me of what I heard at their environments you know, it, multicloud environment, we need flexibility in what we're doing, we, you know, need to of course you know, data is such an important piece of what's going on. Maybe before we get into it too much, give us a little bit about you know, your role there, where you fit into that whole discussion of what IBM is with Cloud. >> So Stu, yeah, I'm the chief technology officer of IBM, of Veeam solutions on the IBM cloud. Primarily involved and helped create the partnership that exists between IBM and VMware today. Basically, I'm providing automated solutions for our clients. Automated, secure solutions for our clients around the VMware and the IBM Cloud infrastructure space. >> Yeah, well, Simon, it's interesting stuff, you've got some good history there, maybe you might remind our audience you know, I remember at VMWorld, before there was a big partnership, that VMware made with a certain public cloud provider that gets talked about a lot, IBM was the first and if I saw you know, correctly, I'd love for you to be able to provide the data behind it. There are more VMware customers on the IBM Cloud than any other cloud is what I believe is the data I saw, I think. So bring us in little bit more, explain that relationship. >> So yes, we were, as IBM, beginning of all of this, I mean VMware and IBM have had a long relationship. And in fact, IBM manages over 850,000 predominantly VMware workloads on-prems, and have done for the last 10+ years. But in the latest iteration of this partnership, we brought together our automation and our codified experience from dealing with these, our client accounts around the world and brought that expertise along with VMware's product side to align this automated stdc stack on cloud platforms. And first to market with that automated stdc stack called VMware Cloud Foundation. First to market out and we've had a great ongoing relationship since then. It's really resonated with many of our clients and our enterprise clients out there. >> All right well Simon, one of the most important pieces of that, you know, VMware stdc message is that I have VMware, I know how, I manage that environment, and it's got a really robust ecosystem, so, of course Veeam started exclusively in the VMware environments, now lives across many environments, but you know the comment I've made on some of these interviews for VeeamON is, wherever the VMware solution and VMware Cloud goes, Veeam could just go along for the ride, really, if it were. There's obviously some integration work and testing, but help dig into a little bit, what that means for you know, solutions like Veeam tying into what VMware is doing, and what VMware is doing in the IBM Cloud. >> Well particularly at the beginning of this relationship, part of this partnership with VMware was its rich partner ecosystem. And I was given the remit and had the luxury to choose the best of the best products that's out there. Which wasn't necessarily IBM's products in this particular space. Obviously we chose Veeam for backup. I mean Veeam's reputation out there's the backup, it's known as the market leader for the backup of its actual workloads. So it was very important for us to embrace that ecosystem. And it's been a great partnership from the very, very beginning. Getting the backup products out into our platform and as we've done more recently, bringing in the new enhancements like Veeam Cloud Connect to deal with data replication and more use cases around migration and the movement of data in a hybrid cloud sense. And Veeam has been right there with us every step of the way. >> Yeah, so Simon, you're a CTO, so bring us in a little bit architecturally because when I think about hybrid cloud or even you know having to move my data between you know different data centers, you know there are, you know, the physics challenges, and you know sometimes I can, you know, get closer, I can (microphone cuts out) through there, and then there's the financial considerations. So give us to how we have to think about that, what is data movement in 2020, you know, what considerations do we have to have here, and how does IBM maybe differentiate a little bit from some others? >> So I'll answer your first question, I'll answer some of the last questions first. What does data movement in 2020 look like? Well, to be perfectly honest, Stu, we never imagined what would happen this year, but data mobility and the movement of data in a hybrid scenario has never been more acute or prevalent because of the stage that the world is currently in and the conditions that we're living in today. Being able to use familiar based tooling that represents what is used in an on-premises state, over in the cloud, enabling Veeam, or people who have existing investments in Veeam, to use that tooling for multiple different use cases. Not just backup, but that actual data replication functionality has become ever more prevalent in these cases. I was saying similar messages back in 2019 and 2018 and as long as back in 2010. I feel as though, I look at that, it's been almost a decade now, talking about the need or the capabilities of hybrid cloud and this movement of data. But I've absolutely seen an absolute increase in it over the last few years and particularly in 2020 in this current situation. The major difference from an IMB perspective is I would say, is our openness, and our, how we're dealing with the openness in the community, and our commitment to open source. Our flexibility, our security, and the way we actually deal with the enterprise. And one of the major differentiations is the security to the core. Actually building up the security, looking at the secure elements, making sure their data is safe from tampering, it's encrypted both in transit and at rest. And these are many of the factors that our enterprise clients actually demand of us and particularly when we look at the regulated industries with their heavy focus on the financial services sector. And Veeam, with its capabilities and its ability to both do the backup and migration functionality, sort of clients are expecting a two-for-one deal, in these days when they're trying to cut costs, and get out of their own data centers in an effort to cut their costs. >> Excellent. Well, Simon, you know you laid out really the imperative for enterprises, you know today and how they're dealing with that, bring us in as to what differentiates the IBM-Veeam relationship versus just IBM is open and flexible, so there are a lot of options. You know what particularly is there about Veeam that makes that relationship special? >> Well, I think it all down to the partnership and the deep willingness to work together. The research that we're doing in the products, yeah? Looking at ways that we can take Veeam beyond the VMware space and into bare metals and containers. But maintaining that level of security and flexibility that clients demand. I mean, many clients, if they've invested in a particular technology to do their backups, back up and DR, because of the heavy data requirements are still one of the most important if not the most important use case that many cloud users or many of our clients actually go for. So having that partnership with Veeam, in not only dealing with the traditional base, which is the VMware backups, but really pushing the boundaries and looking how we can extend that into migrations, into containers, and bare metal, by still keeping that level of security and flexibility. It's a difficult balance. Sometimes to make it more secure, you have to make things less flexible. And vise-versa, having things more flexible, they become less secure. So being willing to work us and actually define that difficult balance, and still provide the level of the user experience and the level of functionality that our clients demand, and keeping both client sets happy, both IBM and Veeam. It's challenging at times, but I guess it's what makes the job interesting and exciting. >> Yeah Simon, I'm actually glad you mentioned containers as one of the you know, modernization efforts going on there. Of course from Veeam's standpoint, when vSphere 7 rolls out, that they are being supported in you know one of the first work in that. I'd love to hear your viewpoint, what you're hearing from customers, how you expect, as a VMware partner for cloud, that movement of VMs and containers and how they're going together. What should we be looking for as that kind of matures and progresses? >> So I would absolutely watch this space. Particularly as we move into this. Containers and VMs living very much side-by-side. With VMware's announcements around Project Pacific and tanzu, it's very interesting. It's certainly a furor around the market. And we as IBM are very closely working with them with our acquisition last year of RedHat and its containerization platform. All while maintaining our ability in the OpenShift community around Kubernetes. So Stu, obviously I'm privy to a lot more information which I really can't really say and dig into too much detail around this particular angle but just to say that, watch this space. There's a lot going to happen. You're going to see a lot of announcements in the back half of 2020 and in the first few halves of 2021, particularly around the carburetions between containers and VMs and seeing how the different offerings from the different companies shape-- (mic cuts out) interesting times ahead. >> Yeah, absolutely. Simon, maybe you're right, don't want to get you in trouble as looking too much into the future, but maybe bring us into, I'm sure you're having lots of conversations with customers, what's their mindset, you talked about, you know, there's bare metals, virtualization, containers, you know application modernization, I've always said the long haul of the dent in any transformation and modernization (mic stutters) doing, so you know, 'cause some of the challenges and opportunities that you're hearing from customers that you and your partner are helping to solve? >> So some of the challenges around this containerization is containerization (mic stutters) is taking a lot longer and its taking a lot more time than we originally anticipated or expected. So the realization is actually hitting that VMware is going to be around for a while. I mean, the idea that people are thinking that they're just going to transform their applications, or all their VMs over a six or 12-month period, is just not reality. So we're living in this hybrid platform way, where you have VMware, you have virtual machines, and containers coexisting. Certain parts of the application, namely the, if I take the three-tier web app as an example, consisting of a http server, an application server, and a database. When you containerize that, or modernize that, it's very easy to modernize the http server, which turns into the ingress/egress servers on the container. It's very easy to modernize the application server, which is fairly static and you can just put a container. But as we know, Stu, data is sticky. So what many enterprises the data migration, or the way that the database is transformed, is the thing that takes the longest. So we're seeing out there in the enterprises people who are running their apps both with the ingress/egress service, the application server container containerized, but the database still living on a virtual machine, for a extended period of time. And until that made the final jump or chone their data service, they make that move. I do see this being, I personally, I honestly don't believe in my lifetime VMs will actually disappear. Because we're seeing that in some cases it's actually too costly for organizations to actually transform their applications or there's no real business case. It works perfectly well with the existing process. There's no need to modernize. But they're looking at ways and what parts of the architecture can be modernized, and containers are definitely the future for all the attributes that we know and love. But there is going to be this hybrid world. So having tools and partners like Veeam, who are willing to cross the ecosphere of the different platforms, is critical for our clients today and critical for partnerships that we have. Like the one we have with Veeam. >> All right well Simon, it goes back to one of those IT maxims, you know, is IT always additive. We almost never really get rid of anything, we just keep adding to it and changing it and as you said, data is that critical component and I think you highlighted nicely how you know, Veeam fits in you know, very much for that story. So Simon, thank you so much for joining us, pleasure having you on the program, glad to have you in theCUBE alumni ranks at this point. >> Thank you Stu, and thank you, it was a pleasure. Take care. >> All right stay tuned for lots more coverage from VeeamON 2020 online, I'm Stu Miniman, and thanks for watching theCUBE. (calm music)

Published Date : Jun 17 2020

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From around the globe, it's theCUBE of the community where Thank you Stu, it's many of the messages around the VMware and the IBM is the data I saw, I think. and have done for the last 10+ years. of the most important pieces and the movement of data and you know sometimes I can, you know, and the way we actually the imperative for enterprises, and still provide the level as one of the you know, and in the first few halves I've always said the long haul of the dent and containers are definitely the future and as you said, data is Thank you Stu, and thank I'm Stu Miniman, and thanks

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Brad Smith & Simon Ponsford | AWS re:Invent 2022


 

foreign continued coverage of AWS re invent my name is Savannah Peterson and I am very excited to be joined by two brilliant blokes in the space of efficiency and performance whether you're on Prem or in the cloud today's discussion is going to be fascinating please welcome Brad and Simon to the show how are you Simon coming in from the UK how you feeling well thank you excellent and Brad we have you coming in from Seattle how are you this morning doing fine thank you excellent and feeling bookish given your background love that I know that you both really care about efficiency and performance it's a very hot topic both of the show and in the industry right now I'm curious I'm going to open it up with you Simon what challenges and I think you've actually continued to tackle these throughout the course of your career what challenges were you facing and wanting to solve when you started yellow dog um really we're just looking at cloud and coming from an on-premise environment really wanted to be able to make accessing Cloud particularly a volume to be simple and straightforward um if you look at today at the number of instance types available from the major Cloud providers there's more than seven thousand different instance types whereas on-prem you go along you select your processes you select your systems it's already be really easy when you hit the cloud you've just got this amazing amount of choice so really it was all about how can you make Intelligent Decisions for you know are you going to run your workload how to match it with what you've got on premise and that was really the inspiration for Rafael so staying there for just a second what does yellow dog provide customers is a SAS system so um you get to it by accessing through the yellow platform and what it allows people to do is to be able to make Intelligent Decisions about where to run their workload would that be on premise or in the cloud it has a wealth of information it understands the costs the performance the latency and the availability of every different instance type in all different clouds it really allows people to uh to be able to make use of that information provision exactly what they need and to be able to run their workloads yeah it also includes a provisioner and it also includes a scheduler as well which is a cloud native scheduler so it's designed to be able to cope with um with cloud in terms of things like spots and interruptions and be able to uh to reschedule and fail over between clouds if there's ever need to do so yeah that sounds incredible and I know this means a lot for partners like AMD Brad talk to me about the partnership and what this means for AMD for your customers yeah absolutely it you know we're excited to be aligned with the uh with a company like yellow dog it's it's um you know the the importance of compute is becoming more and more prevalent every day and it's it's always been top of mind but especially now when you think about what the uh what the economy and the rest of the world is kind of facing over the next you know probably a year or longer it's so important that um that you're able to maximize your dollars and your spend and doing away with uh with uh with absolute certainty that you've got the right type of people behind you uh ensuring that you're your dollars are being spent very wisely and the great thing about yell dogs that they have tremendous insight into uh into cost optimization computer optimization across the entire Globe their their indexes is quite remarkable and what it does is it allows uh customers to actually see just how performant and cost efficient AMD is so it allows us to really put our best foot forward and and gives customers a chance to understand something that they probably weren't uh more familiar with the fact that uh that AMD uh is a tremendous a tremendous value in the marketplace yeah and and uh Simon can you tell us a little bit more about the yellow dog index I'm glad you brought that up Brad yes the yellow index is uh is essentially it's live it's available for anyone to access you can just go to index.yam.tech and you'll be able to see pretty much every single instance type that's available from all the major Cloud providers and be able to make your selection are you looking for GPU type nodes are you looking for AMD processors are you looking just for performance essentially what you're able to do is create a live view of effectively what's available in different data centers around the world and the price at this moment in time also just uh as Brad mentioned in terms of you know cost efficiency and uh and being taking green values seriously as we should we should do the yellow index also has the ability to be able to see at that point in time where the best place to be at a runner job is based upon the lowest carbon impact of running at this moment in time and that for many organizations gives an amazing Insight in not just about being able to find the the understand fishing processes but being able to ensure the greenest energy possible is powering that process when you want to be able to run your workload it's so powerful what you just said and I think when we exactly it's not just about it's not just about power but it's about place when we are are looking at Global Computing at scale what I know that there's ESG advantages in and ESG being a very hot topic when we're talking about AMW on AWS and and and leveraging tools like yellow dog what other sorts of advantages Beyond being least carbon impactful can your Mutual customers benefit from so it's not like I say there's many other features you know a very important thing when you're running a high performance Computing workload is being able to match the instruction set that you're running on premise and then being able to use that in the cloud as well and also to be able to make Intelligent Decisions of where should something run should would something be more efficient um to build on premise should we always try and maximize our on-premise resources before going into the cloud there's a lot about being able to just be able to make decisions and yellow itself it makes thousands of decisions per second to be in a workout where the the best and most optimized places to to run your workload yeah so Brad you work with a lot of companies at scale what type of scale is possible when leveraging Technologies like AMD and yellow dog combined well you know I love the fact that you mentioned uh you know HPC and it's one of the areas that actually is most exciting for for me personally and for and for AMD with the combination of yellow dog and AWS and AWS launched the very first HPC uh instance type last year and you know we're we're we haven't even begun to answer a question we haven't gotten to see um the full-scale capability in the cloud when it comes to these uh these very coordinated and very refined workloads that are running at massive scale and and uh you know we've got some some products we'll be launched in the near future as well that are incredibly performant and you know to be honest I don't think I don't think we have even come close to seeing the scale relative to somebody's very optimized workloads in HPC uh that that we're capable of so um we're excited we're excited for the next few years to see how how we can wrap in um some of the tremendous success that AMD has had on-prem in these these these massive compute centers and replicating that same success inside AWS with companies like yellow dog it's uh it we're excited to see what uh what's what's going to come forward can you give us a preview of anything on the record that gets you really excited about the future I was going to ask you what what had you looking forward to 2023 and Beyond but nothing well not nothing official of course uh but um I will say this you know AMD has recently successful had the launch for Genoa uh it's our next next-gen release and it is um it is proving to be it absolutely is the dominant compute engine it at this point that exists and you know when you start to couple that with the the prowess of AWS you know you could see that over time becoming something potentially that um you know um can really start to change the compute landscape quite a bit so we're hopeful that you know in the future we'll have something along those lines uh with AWS and others and um we're very uh we're very bullish in that area love it uh Simon what about you you've been passionate about low carbon I.T for a long time is carbon neutral Tech in our future what I realize is a bold and lofty claim for you but feel free to give us any of your future predictions um yeah so well I started here trying to build solutions for you know many years ago so 2006 um I was part of a team that launched the the world's lowest powered Windows PC that was actually based on the AMD technology back then so uh you can tell that AMD have been working on a low power for us for a long time in terms of carbon neutral yes I think um certainly there's a there's a few data centers around the world now that are getting very close to uh to carbon neutral some of which may have already achieved it so that's really interesting but so you know the the second part of that is really the the manufacturer of everything that goes into those Services systems and being able to to get to uh you know a net zero on those over a period of time and when we do that which is yeah not without challenges but but certainly possible then we really will have carbon neutral I.T which will be uh a benefit to everyone you know mankind itself yeah casual statement and I have to say that I wholeheartedly agree I think that it's one of the greater challenges of Our Generation especially as what we're able to do in HPC in particular since we're talking about it is only going to grow and scale and magnitude and the amount of data that we have to organize certain process is is wild even today so I love that I'm curious is there anything that you can share with us that's in the pipeline for Yellow Dog anything coming up in the future that's very exciting um so we're coming up very soon um we're going to release something called um version 4 again log which contains um what we call a resource framework which is all about making sure you've got everything you need before you run a job either on-prem or in the cloud so that might be anything from making sure you've got the right licenses making sure that your data is all in the right location making sure you've got all aspects of your workflow ready before you start launching compute and start really but you know burning through dollars with computer could potentially sat there uh not not doing anything until other tasks keep catch up so we're really excited about this new V4 release which will uh which will come out very soon awesome we can't wait to learn more about that hopefully here again on the cube Brad what do Partnerships with companies like yellowdog meme for you and for the customers that you're able to serve yeah it's it's incredibly important I it's you know there's one of the difficulties in in compute that we have today especially in Cloud compute there's there's so much available at this point I mean there was a point in time it was very simple and straightforward it's not even close to being that anymore green so you know one of the things I love about yellow dog itself is actually it does a great they do a great job of making very complex situations and environments fairly simple to understand especially from a business perspective and so one of the things that we love about it is it actually helps our customers you know the AMD direct customers better understand how to properly use our technology and to get the most out of it and so it's difficult for us to articulate that message because you know we are a Semiconductor Company so sometimes it's a little tough to be able to articulate workloads and applications in the way that our customer base will be able to understand but you know it's it's so critical to have companies like yellow dog in the middle that can actually you know make that translation for us directly to the customer um you know and and especially too when you start thinking about ESG and environmental relationships and I'd like to make a comment and one of the things that is fantastic about AMD AWS and yellow we all share the same Mission and we're very public about those missions about just being better to the to the planet and um you know AMD has taken some very aggressive uh targets through 2025 much beyond anything that the industry has expected and you know because of that we are you know we are the most um we are the most power efficient xa6 product on the marketplace and it's not even close and you know I look forward to the day when uh you know you start looking at instance types inside these public Cloud providers in conjunction with the old dog and you can actually even start to see maybe potentially what that carbon footprint is based on those decisions you make on compute and um you know considering that more than half to spend for everybody is generally compute in these environments it's critical to really know what your true impact in the world is and um it's just one of the best parts about a partnership like this oh what a wonderful note to close on and I love both the Synergy between all the partners on a technology level but most importantly on a mission level because none of it matters if we don't have a planet that we can continue to innovate on so I'm I'm really grateful that you're both here fighting a good fight working together and also making a lot of information available for companies of all different sizes as they're navigating very complex decision trees in and operating their stack so thank you both Simon and Brad I really appreciate your time it's been incredibly insightful and thank you to our audience for tuning in to our continuing coverage of AWS re invent here on thecube my name is Savannah Peterson and I look forward to learning more with you soon foreign [Music]

Published Date : Nov 21 2022

SUMMARY :

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Alex Ellis, OpenFaaS | Kubecon + Cloudnativecon Europe 2022


 

(upbeat music) >> Announcer: TheCUBE presents KubeCon and CloudNativeCon Europe, 2022. Brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain, a KubeCon, CloudNativeCon Europe, 2022. I'm your host, Keith Townsend alongside Paul Gillon, Senior Editor, Enterprise Architecture for SiliconANGLE. We are, I think at the half point way point this to be fair we've talked to a lot of folks in open source in general. What's the difference between open source communities and these closed source communities that we attend so so much? >> Well open source is just it's that it's open it's anybody can contribute. There are a set of rules that manage how your contributions are reflected in the code base. What has to be shared, what you can keep to yourself but the it's an entirely different vibe. You know, you go to a conventional conference where there's a lot of proprietary being sold and it's all about cash. It's all about money changing hands. It's all about doing the deal. And open source conferences I think are more, they're more transparent and yeah money changes hands, but it seems like the objective of the interaction is not to consummate a deal to the degree that it is at a more conventional computer conference. >> And I think that can create an uneven side effect. And we're going to talk about that a little bit with, honestly a friend of mine Alex Ellis, founder of OpenFaaS. Alex welcome back to the program. >> Thank you, good to see Keith. >> So how long you've been doing OpenFaaS? >> Well, I first had this idea that serverless and function should be run on your own hardware back in 2016. >> Wow and I remember seeing you at DockerCon EU, was that in 2017? >> Yeah, I think that's when we first met and Simon Foskett took us out to dinner and we got chatting. And I just remember you went back to your hotel room after the presentation. You just had your iPhone out and your headphones you were talking about how you tried to OpenWhisk and really struggled with it and OpenFaaS sort of got you where you needed to be to sort of get some value out of the solution. >> And I think that's the magic of these open source communities in open source conferences that you can try stuff, you can struggle with it, come to a conference either get some advice or go in another direction and try something like a OpenFaaS. But we're going to talk about the business perspective. >> Yeah. >> Give us some, like give us some hero numbers from the project. What types of organizations are using OpenFaaS and what are like the download and stars all those, the ways you guys measure project success. >> So there's a few ways that you hear this talked about at KubeCon specifically. And one of the metrics that you hear the most often is GitHub stars. Now a GitHub star means that somebody with their laptop like yourself has heard of a project or seen it on their phone and clicked a button that's it. There's not really an indication of adoption but of interest. And that might be fleeting and a blog post you might publish you might bump that up by 2000. And so OpenFaaS quite quickly got a lot of stars which encouraged me to go on and do more with it. And it's now just crossed 30,000 across the whole organization of about 40 different open source repositories. >> Wow that is a number. >> Now you are in ecosystem where Knative is also taken off. And can you distinguish your approach to serverless or FaaS to Knatives? >> Yes so, Knative isn't an approach to FaaS. That's simply put and if you listen to Aikas Ville from the Knative project, he was working inside Google and wished that Kubernetes would do a little bit more than what it did. And so he started an initiative with some others to start bringing more abstractions like Auto Scaling, revision management so he can have two versions of code and and shift traffic around. And that's really what they're trying to do is add onto Kubernetes and make it do some of the things that a platform might do. Now OpenFaaS started from a different angle and frankly, two years earlier. >> There was no Kubernetes when you started it. >> It kind of led in the space and and built out that ecosystem. So the idea was, I was working with Lambda and AWS Alexa skills. I wanted to run them on my own hardware and I couldn't. And so OpenFaaS from the beginning started from that developer experience of here's my code, run it for me. Knative is a set of extensions that may be a building block but you're still pretty much working with Kubernetes. We get calls come through. And actually recently I can't tell you who they are but there's a very large telecommunications provider in the US that was using OpenFaaS, like yourself heard of Knative and in the hype they switched. And then they switched back again recently to OpenFaaS and they've come to us for quite a large commercial deal. >> So did they find Knative to be more restrictive? >> No, it's the opposite. It's a lot less opinionated. It's more like building blocks and you are dealing with a lot more detail. It's a much bigger system to manage, but don't get me wrong. I mean the guys are very friendly. They have their sort of use cases that they pursue. Google's now donated the project to CNCF. And so they're running it that way. Now it doesn't mean that there aren't FaaS on top of it. Red Hat have a serverless product VMware have one. But OpenFaaS because it owns the whole stack can get you something that's always been very lean, simple to use to the point that Keith in his hotel room installed it and was product with it in an evening without having to be a Kubernetes expert. >> And that is and if you remember back that was very anti-Kubernetes. >> Yes. >> It was not a platform I thought that was. And for some of the very same reasons, I didn't think it was very user friendly. You know, I tried open with I'm thinking what enterprise is going to try this thing, especially without the handholding and the support needed to do that. And you know, something pretty interesting that happened as I shared this with you on Twitter, I was having a briefing by a big microprocessor company, one of the big two. And they were showing me some of the work they were doing in Cloud-native and the way that they stretch test the system to show me Auto Scaling. Is that they bought up a OpenFaaS what is it? The well text that just does a bunch of, >> The cows maybe. >> Yeah the cows. That does just a bunch of texts. And it just all, and I'm like one I was amazed at is super simple app. And the second one was the reason why they discovered it was because of that simplicity is just a thing that's in your store that you can just download and test. And it was open fast. And it was this big company that you had no idea that was using >> No >> OpenFaaS. >> No. >> How prevalent is that? That you're always running into like these surprises of who's using the solution. >> There are a lot of top tier companies, billion dollar companies that use software that I've worked on. And it's quite common. The main issue you have with open source is you don't have like the commercial software you talked about, the relationships. They don't tell you they're using it until it breaks. And then they may come in incognito with a personal email address asking for things. What they don't want to do often is lend their brands or support you. And so it is a big challenge. However, early on, when I met you, BT, live person the University of Washington, and a bunch of other companies had told us they were using it. We were having discussions with them took them to Kubecon and did talks with them. You can go and look at them in the video player. However, when I left my job in 2019 to work on this full time I went to them and I said, you know, use it in production it's useful for you. We've done a talk, we really understand the business value of how it saves you time. I haven't got a way to fund it and it won't exist unless you help they were like sucks to be you. >> Wow that's brutal. So, okay let me get this right. I remember the story 2019, you leave your job. You say I'm going to do OpenFaaS and support this project 100% of your time. If there's no one contributing to the project from a financial perspective how do you make money? I've always pitched open source because you're the first person that I've met that ran an open source project. And I always pitched them people like you who work on it on their side time. But they're not the Knatives of the world, the SDOs, they have full time developers. Sponsored by Google and Microsoft, etc. If you're not sponsored how do you make money off of open source? >> If this is the million dollar question, really? How do you make money from something that is completely free? Where all of the value has already been captured by a company and they have no incentive to support you build a relationship or send you money in any way. >> And no one has really figured it out. Arguably Red Hat is the only one that's pulled it off. >> Well, people do refer to Red Hat and they say the Red Hat model but I think that was a one off. And we quite, we can kind of agree about that in a business. However, I eventually accepted the fact that companies don't pay for something they can get for free. It took me a very long time to get around that because you know, with open source enthusiast built a huge community around this project, almost 400 people have contributed code to it over the years. And we have had full-time people working on it on and off. And there's some people who really support it in their working hours or at home on the weekends. But no, I had to really think, right, what am I going to offer? And to begin with it would support existing customers weren't interested. They're not really customers because they're consuming it as a project. So I needed to create a product because we understand we buy products. Initially I just couldn't find the right customers. And so many times I thought about giving up, leaving it behind, my family would've supported me with that as well. And they would've known exactly why even you would've done. And so what I started to do was offer my insights as a community leader, as a maintainer to companies like we've got here. So Casting one of my customers, CSIG one of my customers, Rancher R, DigitalOcean, a lot of the vendors you see here. And I was able to get a significant amount of money by lending my expertise and writing content that gave me enough buffer to give the doctors time to realize that maybe they do need support and go a bit further into production. And over the last 12 months, we've been signing six figure deals with existing users and new users alike in enterprise. >> For support >> For support, for licensing of new features that are close source and for consulting. >> So you have proprietary extensions. Also that are sort of enterprise class. Right and then also the consulting business, the support business which is a proven business model that has worked >> Is a proven business model. What it's not a proven business model is if you work hard enough, you deserve to be rewarded. >> Mmh. >> You have to go with the system. Winter comes after autumn. Summer comes after spring and you, it's no point saying why is it like that? That's the way it is. And if you go with it, you can benefit from it. And that's what the realization I had as much as I didn't want to do it. >> So you know this community, well you know there's other project founders out here thinking about making the leap. If you're giving advice to a project founder and they're thinking about making this leap, you know quitting their job and becoming the next Alex. And I think this is the perception that the misperception out there. >> Yes. >> You're, you're well known. There's a difference between being well known and well compensated. >> Yeah. >> What advice would you give those founders >> To be. >> Before they make the leap to say you know what I'm going to do my project full time. I'm going to lean on the generosity of the community. So there are some generous people in the community. You've done some really interesting things for individual like contributions etc but that's not enough. >> So look, I mean really you have to go back to the MBA mindset. What problem are you trying to solve? Who is your target customer? What do they care about? What do they eat and drink? When do they go to sleep? You really need to know who this is for. And then customize a journey for them so that they can come to you. And you need some way initially of funneling those people in qualifying them because not everybody that comes to a student or somebody doing a PhD is not your customer. >> Right, right. >> You need to understand sales. You need to understand a lot about business but you can work it out on your way. You know, I'm testament to that. And once you have people you then need something to sell them that might meet their needs and be prepared to tell them that what you've got isn't right for them. 'cause sometimes that's the one thing that will build integrity. >> That's very hard for community leaders. It's very hard for community leaders to say, no >> Absolutely so how do you help them over that hump? I think of what you've done. >> So you have to set some boundaries because as an open source developer and maintainer you want to help everybody that's there regardless. And I think for me it was taking some of the open source features that companies used not releasing them anymore in the open source edition, putting them into the paid developing new features based on what feedback we'd had, offering support as well but also understanding what is support. What do you need to offer? You may think you need a one hour SLA for a fix probably turns out that you could sell a three day response time or one day response time. And some people would want that and see value in it. But you're not going to know until you talk to your customers. >> I want to ask you, because this has been a particular interest of mine. It seems like managed services have been kind of the lifeline for pure open source companies. Enabling these companies to maintain their open source roots, but still have a revenue stream of delivering as a service. Is that a business model option you've looked at? >> There's three business models perhaps that are prevalent. One is OpenCore, which is roughly what I'm following. >> Right. >> Then there is SaaS, which is what you understand and then there's support on pure open source. So that's more like what Rancher does. Now if you think of a company like Buoyant that produces Linkerd they do a bit of both. So they don't have any close source pieces yet but they can host it for you or you can host it and they'll support you. And so I think if there's a way that you can put your product into a SaaS that makes it easier for them to run then you know go for it. However, we've OpenFaaS, remember what is the core problem we are solving, portability So why lock into my cloud? >> Take that option off the table, go ahead. >> It's been a long journey and I've been a fan since your start. I've seen the bumps and bruises and the scars get made. If you're open source leader and you're thinking about becoming as famous as Alex, hey you can do that, you can put in all the work become famous but if you want to make a living, solve a problem, understand what people are willing to pay for that problem and go out and sell it. Valuable lessons here on theCUBE. From Valencia, Spain I'm Keith Townsend along with Paul Gillon and you're watching theCUBE the leader in high-tech coverage. (Upbeat music)

Published Date : May 19 2022

SUMMARY :

Brought to you by Red Hat, What's the difference between what you can keep to yourself And I think that can create that serverless and function you went back to your hotel room that you can try stuff, the ways you guys measure project success. and a blog post you might publish And can you distinguish your approach and if you listen to Aikas Ville when you started it. and in the hype they switched. and you are dealing And that is and if you remember back and the support needed to do that. that you can just download and test. like these surprises of and it won't exist unless you help you leave your job. to support you build a relationship Arguably Red Hat is the only a lot of the vendors you see here. that are close source and for consulting. So you have proprietary extensions. is if you work hard enough, And if you go with it, that the misperception out there. and well compensated. to say you know what I'm going so that they can come to you. And once you have people community leaders to say, no Absolutely so how do you and maintainer you want to help everybody have been kind of the lifeline perhaps that are prevalent. that you can put your product the table, go ahead. and the scars get made.

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Wrap with Stu Miniman | Red Hat Summit 2022


 

(bright music) >> Okay, we're back in theCUBE. We said we were signing off for the night, but during the hallway track, we ran into old friend Stu Miniman who was the Director of Market Insights at Red Hat. Stu, friend of theCUBE done the thousands of CUBE interviews. >> Dave, it's great to be here. Thanks for pulling me on, you and I hosted Red Hat Summit before. It's great to see Paul here. I was actually, I was talking to some of the Red Hatters walking around Boston. It's great to have an event here. Boston's got strong presence and I understand, I think was either first or second year, they had it over... What's the building they're tearing down right down the road here. Was that the World Trade Center? I think that's where they actually held it, the first time they were here. We hosted theCUBE >> So they moved up. >> at the Hines Convention Center. We did theCUBE for summit at the BCEC next door. And of course, with the pandemic being what it was, we're a little smaller, nice intimate event here. It's great to be able to room the hall, see a whole bunch of people and lots watching online. >> It's great, it's around the same size as those, remember those Vertica Big Data events that we used to have here. And I like that you were commenting out at the theater and the around this morning for the keynotes, that was good. And the keynotes being compressed, I think, is real value for the attendees, you know? 'Cause people come to these events, they want to see each other, you know? They want to... It's like the band getting back together. And so when you're stuck in the keynote room, it's like, "Oh, it's okay, it's time to go." >> I don't know that any of us used to sitting at home where I could just click to another tab or pause it or run for, do something for the family, or a quick bio break. It's the three-hour keynote I hope has been retired. >> But it's an interesting point though, that the virtual event really is driving the physical and this, the way Red Hat marketed this event was very much around the virtual attendee. Physical was almost an afterthought, so. >> Right, this is an invite only for in-person. So you're absolutely right. It's optimizing the things that are being streamed, the online audience is the big audience. And we just happy to be in here to clap and do some things see around what you're doing. >> Wonderful see that becoming the norm. >> I think like virtual Stu, you know this well when virtual first came in, nobody had a clue with what they were doing. It was really hard. They tried different things, they tried to take the physical and just jam it into the virtual. That didn't work, they tried doing fun things. They would bring in a famous person or a comedian. And that kind of worked, I guess, but everybody showed up for that and then left. And I think they're trying to figure it out what this hybrid thing is. I've seen it both ways. I've seen situations like this, where they're really sensitive to the virtual. I've seen others where that's the FOMO of the physical, people want physical. So, yeah, I think it depends. I mean, reinvent last year was heavy physical. >> Yeah, with 15,000 people there. >> Pretty long keynotes, you know? So maybe Amazon can get away with it, but I think most companies aren't going to be able to. So what is the market telling you? What are these insights? >> So Dave just talking about Amazon, obviously, the world I live in cloud and that discussion of cloud, the journey that customers are going on is where we're spending a lot of the discussions. So, it was great to hear in the keynote, talked about our deep partnerships with the cloud providers and what we're doing to help people with, you like to call it super cloud, some call it hybrid, or multi-cloud... >> New name. (crosstalk) Meta-Cloud, come on. >> All right, you know if Che's my executive, so it's wonderful. >> Love it. >> But we'll see, if I could put on my VR Goggles and that will help me move things. But I love like the partnership announcement with General Motors today because not every company has the needs of software driven electric vehicles all over the place. But the technology that we build for them actually has ramifications everywhere. We've working to take Kubernetes and make it smaller over time. So things that we do at the edge benefit the cloud, benefit what we do in the data center, it's that advancement of science and technology just lifts all boats. >> So what's your take on all this? The EV and software on wheels. I mean, Tesla obviously has a huge lead. It's kind of like the Amazon of vehicles, right? It's sort of inspired a whole new wave of innovation. Now you've got every automobile manufacturer kind of go and after. That is the future of vehicles is something you followed or something you have an opinion on Stu? >> Absolutely. It's driving innovation in some ways, the way the DOS drove innovation on the desktop, if you remember the 64K DOS limit, for years, that was... The software developers came up with some amazing ways to work within that 64K limit. Then when it was gone, we got bloatware, but it actually does enforce a level of discipline on you to try to figure out how to make software run better, run more efficiently. And that has upstream impacts on the enterprise products. >> Well, right. So following your analogy, you talk about the enablement to the desktop, Linux was a huge influence on allowing the individual person to write code and write software, and what's happening in the EV, it's software platform. All of these innovations that we're seeing across industries, it's how is software transforming things. We go back to the mark end reasons, software's eating the world, open source is the way that software is developed. Who's at the intersection of all those? We think we have a nice part to play in that. I loved tha- Dave, I don't know if you caught at the end of the keynote, Matt Hicks basically said, "Our mission isn't just to write enterprise software. "Our mission is based off of open source because open source unlocks innovation for the world." And that's one of the things that drew me to Red Hat, it's not just tech in good places, but allowing underrepresented, different countries to participate in what's happening with software. And we can all move that ball forward. >> Well, can we declare victory for open source because it's not just open source products, but everything that's developed today, whether proprietary or open has open source in it. >> Paul, I agree. Open source is the development model period, today. Are there some places that there's proprietary? Absolutely. But I had a discussion with Deepak Singh who's been on theCUBE many times. He said like, our default is, we start with open source code. I mean, even Amazon when you start talking about that. >> I said this, the $70 billion business on open source. >> Exactly. >> Necessarily give it back, but that say, Hey, this is... All's fair in tech and more. >> It is interesting how the managed service model has sort of rescued open source, open source companies, that were trying to do the Red Hat model. No one's ever really successfully duplicated the Red Hat model. A lot of companies were floundering and failing. And then the managed service option came along. And so now they're all cloud service providers. >> So the only thing I'd say is that there are some other peers we have in the industry that are built off open source they're doing okay. The recent example, GitLab and Hashicorp, both went public. Hashi is doing some managed services, but it's not the majority of their product. Look at a company like Mongo, they've heavily pivoted toward the managed service. It is where we see the largest growth in our area. The products that we have again with Amazon, with Microsoft, huge growth, lots of interest. It's one of the things I spend most of my time talking on. >> I think Databricks is another interesting example 'cause Cloudera was the now company and they had the sort of open core, and then they had the proprietary piece, and they've obviously didn't work. Databricks when they developed Spark out of Berkeley, everybody thought they were going to do kind of a similar model. Instead, they went for all in managed services. And it's really worked well, I think they were ahead of that curve and you're seeing it now is it's what customers want. >> Well, I mean, Dave, you cover the database market pretty heavily. How many different open source database options are there today? And that's one of the things we're solving. When you look at what is Red Hat doing in the cloud? Okay, I've got lots of databases. Well, we have something called, it's Red Hat Open Database Access, which is from a developer, I don't want to have to think about, I've got six different databases, which one, where's the repository? How does all that happen? We give that consistency, it's tied into OpenShift, so it can help abstract some of those pieces. we've got same Kafka streaming and we've got APIs. So it's frameworks and enablers to help bridge that gap between the complexity that's out there, in the cloud and for the developer tool chain. >> That's really important role you guys play though because you had this proliferation, you mentioned Mongo. So many others, Presto and Starbursts, et cetera, so many other open source options out there now. And companies, developers want to work with multiple databases within the same application. And you have a role in making that easy. >> Yeah, so and that is, if you talk about the question I get all the time is, what's next for Kubernetes? Dave, you and I did a preview for KubeCon and it's automation and simplicity that we need to be. It's not enough to just say, "Hey, we've got APIs." It's like Dave, we used to say, "We've got standards? Great." Everybody's implementation was a little bit different. So we have API Sprawl today. So it's building that ecosystem. You've been talking to a number of our partners. We are very active in the community and trying to do things that can lift up the community, help the developers, help that cloud native ecosystem, help our customers move faster. >> Yeah API's better than scripts, but they got to be managed, right? So, and that's really what you guys are doing that's different. You're not trying to own everything, right? It's sort of antithetical to how billions and trillions are made in the IT industry. >> I remember a few years ago we talked here, and you look at the size that Red Hat is. And the question is, could Red Hat have monetized more if the model was a little different? It's like, well maybe, but that's not the why. I love that they actually had Simon Sinek come in and work with Red Hat and that open, unlocks the world. Like that's the core, it's the why. When I join, they're like, here's a book of Red Hat, you can get it online and that why of what we do, so we never have to think of how do we get there. We did an acquisition in the security space a year ago, StackRox, took us a year, it's open source. Stackrox.io, it's community driven, open source project there because we could have said, "Oh, well, yeah, it's kind of open source and there's pieces that are open source, but we want it to be fully open source." You just talked to Gunnar about how he's RHEL nine, based off CentOS stream, and now developing out in the open with that model, so. >> Well, you were always a big fan of Whitehurst culture book, right? It makes a difference. >> The open organization and right, Red Hat? That culture is special. It's definitely interesting. So first of all, most companies are built with the hierarchy in mind. Had a friend of mine that when he joined Red Hat, he's like, I don't understand, it's almost like you have like lots of individual contractors, all doing their things 'cause Red Hat works on thousands of projects. But I remember talking to Rackspace years ago when OpenStack was a thing and they're like, "How do you figure out what to work on?" "Oh, well we hired great people and they work on what's important to them." And I'm like, "That doesn't sound like a business." And he is like, "Well, we struggle sometimes to that balance." Red Hat has found that balance because we work on a lot of different projects and there are people inside Red Hat that are, you know, they care more about the project than they do the business, but there's the overall view as to where we participate and where we productize because we're not creating IP because it's all an open source. So it's the monetizations, the relationships we have our customers, the ecosystems that we build. And so that is special. And I'll tell you that my line has been Red Hat on the inside is even more Red Hat. The debates and the discussions are brutal. I mean, technical people tearing things apart, questioning things and you can't be thin skinned. And the other thing is, what's great is new people. I've talked to so many people that started at Red Hat as interns and will stay for seven, eight years. And they come there and they have as much of a seat at the table, and when I talk to new people, your job, is if you don't understand something or you think we might be able to do it differently, you better speak up because we want your opinion and we'll take that, everybody takes that into consideration. It's not like, does the decision go all the way up to this executive? And it's like, no, it's done more at the team. >> The cultural contrast between that and your parent, IBM, couldn't be more dramatic. And we talked earlier with Paul Cormier about has IBM really walked the walk when it comes to leaving Red Hat alone. Naturally he said, "Yes." Well what's your perspective. >> Yeah, are there some big blue people across the street or something I heard that did this event, but look, do we interact with IBM? Of course. One of the reasons that IBM and IBM Services, both products and services should be able to help get us breadth in the marketplace. There are times that we go arm and arm into customer meetings and there are times that customers tell us, "I like Red Hat, I don't like IBM." And there's other ones that have been like, "Well, I'm a long time IBM, I'm not sure about Red Hat." And we have to be able to meet all of those customers where they are. But from my standpoint, I've got a Red Hat badge, I've got a Red Hat email, I've got Red Hat benefits. So we are fiercely independent. And you know, Paul, we've done blogs and there's lots of articles been written is, Red Hat will stay Red Hat. I didn't happen to catch Arvin I know was on CNBC today and talking at their event, but I'm sure Red Hat got mentioned, but... >> Well, he talks about Red Hat all time. >> But in his call he's talking backwards. >> It's interesting that he's not here, greeting this audience, right? It's again, almost by design, right? >> But maybe that's supposed to be... >> Hundreds of yards away. >> And one of the questions being in the cloud group is I'm not out pitching IBM Cloud, you know? If a customer comes to me and asks about, we have a deep partnership and IBM will be happy to tell you about our integrations, as opposed to, I'm happy to go into a deep discussion of what we're doing with Google, Amazon, and Microsoft. So that's how we do it. It's very different Dave, from you and I watch really closely the VMware-EMC, VMware-Dell, and how that relationship. This one is different. We are owned by IBM, but we mostly, it does IBM fund initiatives and have certain strategic things that are done, absolutely. But we maintain Red Hat. >> But there are similarities. I mean, VMware crowd didn't want to talk about EMC, but they had to, they were kind of forced to. Whereas, you're not being forced to. >> And then once Dell came in there, it was joint product development. >> I always thought a spin in. Would've been the more effective, of course, Michael Dell and Egon wouldn't have gotten their $40 billion out. But I think a spin in was more natural based on where they were going. And it would've been, I think, a more dominant position in the marketplace. They would've had more software, but again, financially it wouldn't have made as much sense, but that whole dynamic is different. I mean, but people said they were going to look at VMware as a model and it's been largely different because remember, VMware of course was a separate company, now is a fully separate company. Red Hat was integrated, we thought, okay, are they going to get blue washed? We're watching and watching, and watching, you had said, well, if the Red Hat culture isn't permeating IBM, then it's a failure. And I don't know if that's happening, but it's definitely... >> I think a long time for that. >> It's definitely been preserved. >> I mean, Dave, I know I read one article at the beginning of the year is, can Arvin make IBM, Microsoft Junior? Follow the same turnaround that Satya Nadella drove over there. IBM I think making some progress, I mean, I read and watch what you and the team are all writing about it. And I'll withhold judgment on IBM. Obviously, there's certain financial things that we'd love to see IBM succeed. We worry about our business. We do our thing and IBM shares our results and they've been solid, so. >> Microsoft had such massive cash flow that even bomber couldn't screw it up. Well, I mean, this is true, right? I mean, you think about how were relevant Microsoft was in the conversation during his tenure and yet they never got really... They maintained a position so that when the Nadella came in, they were able to reascend and now are becoming that dominant player. I mean, IBM just doesn't have that cash flow and that luxury, but I mean, if he pulls it off, he'll be the CEO of the decade. >> You mentioned partners earlier, big concern when the acquisition was first announced, was that the Dells and the HP's and the such wouldn't want to work with Red Hat anymore, you've sort of been here through that transition. Is that an issue? >> Not that I've seen, no. I mean, the hardware suppliers, the ISVs, the GSIs are all very important. It was great to see, I think you had Accenture on theCUBE today, obviously very important partner as we go to the cloud. IBM's another important partner, not only for IBM Cloud, but IBM Services, deep partnership with Azure and AWS. So those partners and from a technology standpoint, the cloud native ecosystem, we talked about, it's not just a Red Hat product. I constantly have to talk about, look, we have a lot of pieces, but your developers are going to have other tools that they're going to use and the security space. There is no such thing as a silver bullet. So I've been having some great conversations here already this week with some of our partners that are helping us to round out that whole solution, help our customers because it has to be, it's an ecosystem. And we're one of the drivers to help that move forward. >> Well, I mean, we were at Dell Tech World last week, and there's a lot of talk about DevSecOps and DevOps and Dell being more developer friendly. Obviously they got a long way to go, but you can't have that take that posture and not have a relationship with Red Hat. If all you got is Pivotal and VMware, and Tansu >> I was thrilled to hear the OpenShift mention in the keynote when they talked about what they were doing. >> How could you not, how could you have any credibility if you're just like, Oh, Pivotal, Pivotal, Pivotal, Tansu, Tansu. Tansu is doing its thing. And they smart strategy. >> VMware is also a partner of ours, but that we would hope that with VMware being independent, that does open the door for us to do more with them. >> Yeah, because you guys have had a weird relationship with them, under ownership of EMC and then Dell, right? And then the whole IBM thing. But it's just a different world now. Ecosystems are forming and reforming, and Dell's building out its own cloud and it's got to have... Look at Amazon, I wrote about this. I said, "Can you envision the day where Dell actually offers competitive products in its suite, in its service offering?" I mean, it's hard to see, they're not there yet. They're not even close. And they have this high say/do ratio, or really it's a low say/do, they say high say/do, but look at what they did with Nutanix. You look over- (chuckles) would tell if it's the Cisco relationship. So it's got to get better at that. And it will, I really do believe. That's new thinking and same thing with HPE. And, I don't know about Lenovo that not as much of an ecosystem play, but certainly Dell and HPE. >> Absolutely. Michael Dell would always love to poke at HPE and HP really went very far down the path of their own products. They went away from their services organization that used to be more like IBM, that would offer lots of different offerings and very much, it was HP Invent. Well, if we didn't invent it, you're not getting it from us. So Dell, we'll see, as you said, the ecosystems are definitely forming, converging and going in lots of different directions. >> But your position is, Hey, we're here, we're here to help. >> Yeah, we're here. We have customers, one of the best proof points I have is the solution that we have with Amazon. Amazon doesn't do the engineering work to make us a native offering if they didn't have the customer demand because Amazon's driven off of data. So they came to us, they worked with us. It's a lot of work to be able to make that happen, but you want to make it frictionless for customers so that they can adopt that. That's a long path. >> All right, so evening event, there's a customer event this evening upstairs in the lobby. Microsoft is having a little shin dig, and then serves a lot of customer dinners going on. So Stu, we'll see you out there tonight. >> All right, thanks you. >> Were watching a brewing somewhere. >> Keynotes tomorrow, a lot of good sessions and enablement, and yeah, it's great to be in person to be able to bump some people, meet some people and, Hey, I'm still a year and a half in still meeting a lot of my peers in person for the first time. >> Yeah, and that's kind of weird, isn't it? Imagine. And then we kick off tomorrow at 10:00 AM. Actually, Stephanie Chiras is coming on. There she is in the background. She's always a great guest and maybe do a little kickoff and have some fun tomorrow. So this is Dave Vellante for Stu Miniman, Paul Gillin, who's my co-host. You're watching theCUBEs coverage of Red Hat Summit 2022. We'll see you tomorrow. (bright music)

Published Date : May 11 2022

SUMMARY :

but during the hallway track, Was that the World Trade Center? at the Hines Convention Center. And I like that you were It's the three-hour keynote that the virtual event really It's optimizing the things becoming the norm. and just jam it into the virtual. aren't going to be able to. a lot of the discussions. Meta-Cloud, come on. All right, you know But the technology that we build for them It's kind of like the innovation on the desktop, And that's one of the things Well, can we declare I mean, even Amazon when you start talking the $70 billion business on open source. but that say, Hey, this is... the managed service model but it's not the majority and then they had the proprietary piece, And that's one of the And you have a role in making that easy. I get all the time is, are made in the IT industry. And the question is, Well, you were always a big fan the relationships we have our customers, And we talked earlier One of the reasons that But in his call he's talking that's supposed to be... And one of the questions I mean, VMware crowd didn't And then once Dell came in there, Would've been the more I think a long time It's definitely been at the beginning of the year is, and that luxury, the HP's and the such I mean, the hardware suppliers, the ISVs, and not have a relationship with Red Hat. the OpenShift mention in the keynote And they smart strategy. that does open the door for us and it's got to have... the ecosystems are definitely forming, But your position is, Hey, is the solution that we have with Amazon. So Stu, we'll see you out there tonight. Were watching a brewing person for the first time. There she is in the background.

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Nandi Leslie, Raytheon | WiDS 2022


 

(upbeat music) >> Hey everyone. Welcome back to theCUBE's live coverage of Women in Data Science, WiDS 2022, coming to live from Stanford University. I'm Lisa Martin. My next guest is here. Nandi Leslie, Doctor Nandi Leslie, Senior Engineering Fellow at Raytheon Technologies. Nandi, it's great to have you on the program. >> Oh it's my pleasure, thank you. >> This is your first WiDS you were saying before we went live. >> That's right. >> What's your take so far? >> I'm absolutely loving it. I love the comradery and the community of women in data science. You know, what more can you say? It's amazing. >> It is. It's amazing what they built since 2015, that this is now reaching 100,000 people 200 online event. It's a hybrid event. Of course, here we are in person, and the online event going on, but it's always an inspiring, energy-filled experience in my experience of WiDS. >> I'm thoroughly impressed at what the organizers have been able to accomplish. And it's amazing, that you know, you've been involved from the beginning. >> Yeah, yeah. Talk to me, so you're Senior Engineering Fellow at Raytheon. Talk to me a little bit about your role there and what you're doing. >> Well, my role is really to think about our customer's most challenging problems, primarily at the intersection of data science, and you know, the intersectional fields of applied mathematics, machine learning, cybersecurity. And then we have a plethora of government clients and commercial clients. And so what their needs are beyond those sub-fields as well, I address. >> And your background is mathematics. >> Yes. >> Have you always been a math fan? >> I have, I actually have loved math for many, many years. My dad is a mathematician, and he introduced me to, you know mathematical research and the sciences at a very early age. And so, yeah, I went on, I studied in a math degree at Howard undergrad, and then I went on to do my PhD at Princeton in applied math. And later did a postdoc in the math department at University of Maryland. >> And how long have you been with Raytheon? >> I've been with Raytheon about six years. Yeah, and before Raytheon, I worked at a small to midsize defense company, defense contracting company in the DC area, systems planning and analysis. And then prior to that, I taught in a math department where I also did my postdoc, at University of Maryland College Park. >> You have a really interesting background. I was doing some reading on you, and you have worked with the Navy. You've worked with very interesting organizations. Talk to the audience a little bit about your diverse background. >> Awesome yeah, I've worked with the Navy on submarine force security, and submarine tracking, and localization, sensor performance. Also with the Army and the Army Research Laboratory during research at the intersection of machine learning and cyber security. Also looking at game theoretic and graph theoretic approaches to understand network resilience and robustness. I've also supported Department of Homeland Security, and other government agencies, other governments, NATO. Yeah, so I've really been excited by the diverse problems that our various customers have you know, brought to us. >> Well, you get such great experience when you are able to work in different industries and different fields. And that really just really probably helps you have such a much diverse kind of diversity of thought with what you're doing even now with Raytheon. >> Yeah, it definitely does help me build like a portfolio of topics that I can address. And then when new problems emerge, then I can pull from a toolbox of capabilities. And, you know, the solutions that have previously been developed to address those wide array of problems, but then also innovate new solutions based on those experiences. So I've been really blessed to have those experiences. >> Talk to me about one of the things I heard this morning in the session I was able to attend before we came to set was about mentors and sponsors. And, you know, I actually didn't know the difference between that until a few years ago. But it's so important. Talk to me about some of the mentors you've had along the way that really helped you find your voice in research and development. >> Definitely, I mean, beyond just the mentorship of my my family and my parents, I've had amazing opportunities to meet with wonderful people, who've helped me navigate my career. One in particular, I can think of as and I'll name a number of folks, but Dr. Carlos Castillo-Chavez was one of my earlier mentors. I was an undergrad at Howard University. He encouraged me to apply to his summer research program in mathematical and theoretical biology, which was then at Cornell. And, you know, he just really developed an enthusiasm with me for applied mathematics. And for how it can be, mathematics that is, can be applied to epidemiological and theoretical immunological problems. And then I had an amazing mentor in my PhD advisor, Dr. Simon Levin at Princeton, who just continued to inspire me, in how to leverage mathematical approaches and computational thinking for ecological conservation problems. And then since then, I've had amazing mentors, you know through just a variety of people that I've met, through customers, who've inspired me to write these papers that you mentioned in the beginning. >> Yeah, you've written 55 different publications so far. 55 and counting I'm sure, right? >> Well, I hope so. I hope to continue to contribute to the conversation and the community, you know, within research, and specifically research that is computationally driven. That really is applicable to problems that we face, whether it's cyber security, or machine learning problems, or others in data science. >> What are some of the things, you're giving a a tech vision talk this afternoon. Talk to me a little bit about that, and maybe the top three takeaways you want the audience to leave with. >> Yeah, so my talk is entitled "Unsupervised Learning for Network Security, or Network Intrusion Detection" I believe. And essentially three key areas I want to convey are the following. That unsupervised learning, that is the mathematical and statistical approach, which tries to derive patterns from unlabeled data is a powerful one. And one can still innovate new algorithms in this area. Secondly, that network security, and specifically, anomaly detection, and anomaly-based methods can be really useful to discerning and ensuring, that there is information confidentiality, availability, and integrity in our data >> A CIA triad. >> There you go, you know. And so in addition to that, you know there is this wealth of data that's out there. It's coming at us quickly. You know, there are millions of packets to represent communications. And that data has, it's mixed, in terms of there's categorical or qualitative data, text data, along with numerical data. And it is streaming, right. And so we need methods that are efficient, and that are capable of being deployed real time, in order to detect these anomalies, which we hope are representative of malicious activities, and so that we can therefore alert on them and thwart them. >> It's so interesting that, you know, the amount of data that's being generated and collected is growing exponentially. There's also, you know, some concerning challenges, not just with respect to data that's reinforcing social biases, but also with cyber warfare. I mean, that's a huge challenge right now. We've seen from a cybersecurity perspective in the last couple of years during the pandemic, a massive explosion in anomalies, and in social engineering. And companies in every industry have to be super vigilant, and help the people understand how to interact with it, right. There's a human component. >> Oh, for sure. There's a huge human component. You know, there are these phishing attacks that are really a huge source of the vulnerability that corporations, governments, and universities face. And so to be able to close that gap and the understanding that each individual plays in the vulnerability of a network is key. And then also seeing the link between the network activities or the cyber realm, and physical systems, right. And so, you know, especially in cyber warfare as a remote cyber attack, unauthorized network activities can have real implications for physical systems. They can, you know, stop a vehicle from running properly in an autonomous vehicle. They can impact a SCADA system that's, you know there to provide HVAC for example. And much more grievous implications. And so, you know, definitely there's the human component. >> Yes, and humans being so vulnerable to those social engineering that goes on in those phishing attacks. And we've seen them get more and more personal, which is challenging. You talking about, you know, sensitive data, personally identifiable data, using that against someone in cyber warfare is a huge challenge. >> Oh yeah, certainly. And it's one that computational thinking and mathematics can be leveraged to better understand and to predict those patterns. And that's a very rich area for innovation. >> What would you say is the power of computational thinking in the industry? >> In industry at-large? >> At large. >> Yes, I think that it is such a benefit to, you know, a burgeoning scientist, if they want to get into industry. There's so many opportunities, because computational thinking is needed. We need to be more objective, and it provides that objectivity, and it's so needed right now. Especially with the emergence of data, and you know, across industries. So there are so many opportunities for data scientists, whether it's in aerospace and defense, like Raytheon or in the health industry. And we saw with the pandemic, the utility of mathematical modeling. There are just so many opportunities. >> Yeah, there's a lot of opportunities, and that's one of the themes I think, of WiDS, is just the opportunities, not just in data science, and for women. And there's obviously even high school girls that are here, which is so nice to see those young, fresh faces, but opportunities to build your own network and your own personal board of directors, your mentors, your sponsors. There's tremendous opportunity in data science, and it's really all encompassing, at least from my seat. >> Oh yeah, no I completely agree with that. >> What are some of the things that you've heard at this WiDS event that inspire you going, we're going in the right direction. If we think about International Women's Day tomorrow, "Breaking the Bias" is the theme, do you think we're on our way to breaking that bias? >> Definitely, you know, there was a panel today talking about the bias in data, and in a variety of fields, and how we are, you know discovering that bias, and creating solutions to address it. So there was that panel. There was another talk by a speaker from Pinterest, who had presented some solutions that her, and her team had derived to address bias there, in you know, image recognition and search. And so I think that we've realized this bias, and, you know, in AI ethics, not only in these topics that I've mentioned, but also in the implications for like getting a loan, so economic implications, as well. And so we're realizing those issues and bias now in AI, and we're addressing them. So I definitely am optimistic. I feel encouraged by the talks today at WiDS that you know, not only are we recognizing the issues, but we're creating solutions >> Right taking steps to remediate those, so that ultimately going forward. You know, we know it's not possible to have unbiased data. That's not humanly possible, or probably mathematically possible. But the steps that they're taking, they're going in the right direction. And a lot of it starts with awareness. >> Exactly. >> Of understanding there is bias in this data, regardless. All the people that are interacting with it, and touching it, and transforming it, and cleaning it, for example, that's all influencing the veracity of it. >> Oh, for sure. Exactly, you know, and I think that there are for sure solutions are being discussed here, papers written by some of the speakers here, that are driving the solutions to the mitigation of this bias and data problem. So I agree a hundred percent with you, that awareness is you know, half the battle, if not more. And then, you know, that drives creation of solutions >> And that's what we need the creation of solutions. Nandi, thank you so much for joining me today. It was a pleasure talking with you about what you're doing with Raytheon, what you've done and your path with mathematics, and what excites you about data science going forward. We appreciate your insights. >> Thank you so much. It was my pleasure. >> Good, for Nandi Leslie, I'm Lisa Martin. You're watching theCUBE's coverage of Women in Data Science 2022. Stick around, I'll be right back with my next guest. (upbeat flowing music)

Published Date : Mar 7 2022

SUMMARY :

have you on the program. This is your first WiDS you were saying You know, what more can you say? and the online event going on, And it's amazing, that you know, and what you're doing. and you know, the intersectional fields and he introduced me to, you And then prior to that, I and you have worked with the Navy. have you know, brought to us. And that really just And, you know, the solutions that really helped you that you mentioned in the beginning. 55 and counting I'm sure, right? and the community, you and maybe the top three takeaways that is the mathematical and so that we can therefore and help the people understand And so, you know, Yes, and humans being so vulnerable and to predict those patterns. and you know, across industries. and that's one of the themes I think, completely agree with that. that inspire you going, and how we are, you know And a lot of it starts with awareness. that's all influencing the veracity of it. And then, you know, that and what excites you about Thank you so much. of Women in Data Science 2022.

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Simon Guest, Generali Vitality & Nils Müller-Sheffer, Accenture | AWS Executive Summit 2021


 

welcome back to the cube's presentation of the aws executive summit at re invent 2021 made possible by accenture my name is dave vellante we're going to look at how digital infrastructure is helping to transform consumer experiences specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who change their behavior to live healthier lives a real passion of of mine and getting to the really root cause of health with me now are simon guest who's the chief executive officer of generality vitality gmbh and niels mueller who's the managing director at the cloud first application engineering lead for the european market at accenture gentlemen welcome to the cube thanks for having us you're very welcome simon generally vitality it's a really interesting concept that you guys have envisioned and now put into practice tell us how does it all work sure no problem and thanks for for having us on dave it's a pleasure to be here so look uh generally vitality is in its uh it's core pretty simple concepts so it's uh it's a program that you have on your phone and the idea of this program is that it's a it's a wellness coach for you as an individual and it's going to help you to understand your health and where you are in terms of the state of your health at the moment and it's going to take you on a journey to improve your your lifestyle and your wellness and hopefully help you to lead a healthier and a more sort of mindful life i guess is is the best way of summarizing it from um from our point of view with insurance company of course you know our historical role has always been to uh be the company that's there if something goes wrong you know so if unfortunately you pass away or you have sickness in your in your life or in your family's life that's that's historically been our role but what we see with generality vitality is something a little bit different so it's a program that really is uh supposed to be with you every day of your life to help you to live a healthier life it's something that we already have in in four european markets in fact in five from this week i'm a little bit behind the time so we're live already in in germany in france in austria and italy and in spain and fundamentally what we what we do dave is too is to say to customers look if you want to understand your health if you want to improve it by moving a little bit more by visiting the doctor more by eating healthier by healthy choices on a daily basis we're going to help you to do that and we're going to incentivize you for going on this journey and making healthy choices and we're going to reward you for for doing the same so you know we partner up with with great companies like garmin like adidas like big brands that are let's say invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well make good choices be healthy have an insurance company that partners you along that journey and if you do that we're going to reward you for for that so you know we're here not just in the difficult times which of course is one of our main roles but we're here as a partner as a lifetime partner to you too to help you feel better and live a better life i love it i mean it sounds so simple but but it's i'm sure it's very complicated to to make the technology simple for the user you've got mobile involved you've got the back end and we're going to get into some of the tech but first i want to understand the member engagement and some of the lifestyle changes simon that you've analyzed what's the feedback that you're getting from your customers what does the data tell you how do the incentives work as well what what is the incentive for the the member to actually do the right thing sure look i think actually the the covered uh situation that we've had in the last sort of two years has really crystallized the fact that this is something that we really ought to be doing and something that our customers really value so i mean look just to give you a bit of a sort of information about how it works for for customers so what we try to do with them is is to get customers to understand uh their current health situation you know using their phone so uh you know we ask our customers to go through a sort of health assessment around how they live what they eat how they sleep you know and to go through that sort of process uh and to give them what a vitality age which is a sort of uh you know sort of actuarial comparison with their real age so i'm i'm 45 but unfortunately my my vitality age is 49 and it means i have some work to do to bring that back together uh and what we see is that you know two-thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life and if what if what they are doing is having an impact on their life expectancy and their lifespan and their health span so how long are they going to live healthier for so you see them really engaging in this in this approach of understanding their current situation then what we know actually because the program is built around this model that uh really activity and moving and exercise is the biggest contributor to living a healthier life we know that the majority of deaths are caused by lifestyle illness is like you know poor nutrition and smoking and drinking alcohol and not exercising and so a lot of the program is really built around getting people to move more and it's not about being an athlete it's about you know getting off the the underground one station earlier walking home or making sure you do your 10 000 steps a day and what we see is that that sort of 40 of our customers are on a regularly basis linking either their phone or their their exercise device to our program and downloading that data so that they can see how how much they are exercising and at the same time what we do is we set we set our customers weekly challenges to say look if you can move a little bit more than last week we are going to to reward you for that and we see that you know almost half of our customers are achieving this weekly goal every week and it's really a fantastic level of engagement that normally is an insurer uh we don't see the way the rewards work is is pretty simple it's similar in a way to an airline program so every good choice you make every activity you do every piece of good food that you eat when you check your on your health situation we'll give you points and the more points you get you go through through a sort of status approach of starting off at the bottom status and ending up at a gold and then a platinum status and the the higher up you get in the status that the higher the value of the rewards that we give you so almost a quarter of our customers now and this is accelerated through provide they've reached that platinum status so they are the most engaged customers that we we have and those ones who are really engaging in the in the program and what we really try to create is this sort of virtuous circle that says if you live well you make good choices you improve your health you you progress through the program and we give you better and stronger and more uh valuable rewards for for doing that and some of those rewards are are around health and wellness so it might be that you get you get a discount on on gym gear from adidas it might be that you get a discount on a uh on a device from garmin or it might be actually on other things so we also give people amazon vouchers we also give people uh discounts on holidays and another thing that we we did actually in the last year which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations because we we work in generality with a with a sort of um campaign called the human safety net which is helping out the poorest people in society and some what our customers do a lot of the time is instead of taking those financial rewards for themselves they convert it into a charitable donation so we're actually also thinking wellness and feeling good and insurance and some societal good so we're really trying to create a virtuous circle of uh of engagement with our customers i mean that's a powerful cocktail i love it you got the the data because if i see the data then i can change my behavior you got the gamification piece you actually have you know hard dollar rewards you could give those to charities and and you've got the the most important which is priceless can't put a value on good health i got one more question for simon and niels i'd love you to chime in as well on this question how did you guys decide simon to engage with accenture and aws and the cloud to build out this platform what's the story behind that collaboration was there unique value that you saw that that you wanted to tap that you feel like they bring to the table what was your experience yeah look i mean we worked at accenture as well because the the the sort of construct of this vitality proposition is a pretty a pretty complex one so you mentioned that the idea is simple but the the build is not so uh is not so simple and that that's the case so accenture's been part of that journey uh from the beginning they're one of the partners that we work with but specifically around the topic of rewards uh you know we're we're a primarily european focused organization but when you take those countries that i mentioned even though we're next to each other geographically we're quite diverse and what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go and get to market with an increasing amount of efficiency and and to do that we needed to work with somebody who understood our business has this historical let's say investment in in the vitality concept so so knows how to bring it to life but that what then could really support us in making uh what can be a complex piece of work as simple and as as replicable as possible across multiple markets because we don't want to go reinventing the wheel every time we do we move to a new market so we need to find a balance between having a consistent product a consistent technology offer a consistent customer experience with the fact that we we operate in quite diverse markets so this was let's say the the reason for more deeply engaging with accenture on this journey thank you very much niels why don't you comment on on that as well i'd love to to get your thoughts and and really really it's kind of your role here i mean accenture global si deep expertise in industry but also technology what are your thoughts on this topic yeah i'd love to love to comment so when we started the journey it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets have a central solution that can act as a template for the different markets but then also have the opportunity to localize different languages different partners for the rewards there's different reward partners in the different markets so we needed to build in an asset basically that could work as a tempos centrally standardizing things but also leaving enough flexibility to to then localize in the individual markets and if we talk about some of the more specific requirements so one one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the basically the authentication needs to happen and we somehow needed to still find a holistic solution that comes through the central platform and we were able to do that at the end through the aws cognito service sort of wrapping the individual markets uh local idp systems and by now we've even extended that solution to have a standalone cloud native kind of idp solution in place for markets that do not have a local idp solution in place or don't want to use it for for this purpose yeah so you had you had data you have you had the integration you've got local laws you mentioned the flexibility you're building ecosystems that are unique to the to the local uh both language and and cultures uh please you had another comment i interrupted you yeah i know i just wanted to expand basically on the on the requirements so that was the central one being able to roll this out in a standardized way across the markets but then there were further requirements for example like being able to operate that platform with very low operations overhead there is no large i.t team behind generally vitality that you know works to serve us or can can act as this itis backbone support so we needed to have basically a solution that runs itself that runs on autopilot and that was another big big driver for first of all going to cloud but second of all making specific choices within cloud so we specifically chose to build this as a cloud native solution using for example manage database services you know with automatic backup with automatic ability to restore data that scales automatically that you know has all this built in which usually maybe a database administrator would take care of and we applied that concept basically to every component to everything we looked at we we applied this requirement of how can this run on autopilot how can we make this as much managed by itself within the cloud as possible and then land it on these services and for example we also used the the api gateway from from aws for our api services that also came in handy when for example we had some response time issues with the third party we needed to call and then we could just with a flick of a button basically introduce caching on the level of the api gateway and really improve the user experience because the data you know wasn't updated so much so it was easier to cache so these are all experiences i think that that proved in the end that we made the right choices here and the requirements that that drove that to to have a good user experience niels would you say that the architecture is is a sort of a data architecture specifically is it a decentralized data architecture with sort of federated you know centralized governance or is it more of a centralized view what if you could talk about that yeah it's it's actually a centralized platform basically so the core product is the same for all the markets and we run them as different tenants basically on top of that infrastructure so the data is separated in a way obviously by the different tenants but it's in a central place and we can analyze it in a central fashion if if the need arises from from the business and the reason i ask that simon is because essentially i look at this as a as largely a data offering for your customers and so niels you were talking about the local language and simon as well i would imagine that that the local business lines have specific requirements and specific data requirements and so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security that's not a trivial challenge i wonder if you both could comment on that yeah maybe maybe i'll give a start and then simon can chime in so um what we're specifically doing is managing the rewards experience right so so our solution will take care of tracking what rewards have been earned for what customer what rewards have been redeemed what rewards can be unlocked on the next level and we we foreshadow a little bit to to motivate to incentivize the customer and as that data sits in an aws database in a tenant by tenant fashion and you can run analysis on top of that maybe what you're getting into is also the let's say the exercise data the fitness device tracking data that is not specifically part of what my team has built but i'm sure simon can comment a little bit on that angle as well yeah please yeah sure sure yeah sure so look i think them the topic of data and how we use it uh in our business is a very is very interesting one because it's um it's not historically being seen let's say as the remit of insurers to go beyond the you know the the data that you need to underwrite policies or process claims or whatever it might be but actually we see that this is a whole point around being able to create some shared value in in this kind of product and and what i mean by that is uh look if you are a customer and you're buying an insurance policy it might be a life insurance or health insurance policy from from generali and we are giving you access to this uh to this program and through that program you are living a healthier life and that might have a you know a positive impact on generali in terms of you know maybe we're going to increase our market share or maybe we're going to lower claims or we're going to generate value out of that then one of the points of this program is that we then share that value back with customers through the rewards on the platform that we that we've built here and of course being able to understand that data and to quantify it and to value that data is an important part of the of the the different stages of how you of how much value you are creating and it's also interesting to know that you know in a couple of our markets we we operate in the corporate space so not with retail customers but with with organizations and one of the reasons that those companies give vitality to their employees is that they want to see things like the improved health of a workforce they want to see higher presenteeism lower absenteeism of employees and of course being able to demonstrate that there's a sort of correlation between participation in the vitality program and things like that is also is also important and as we've said the markets are very different so we need to be able to to take the data uh that we have out of the vitality program uh and be able in in the company that that i'm managing to to interpret that data so that in our insurance businesses we are able to make good decisions about the kind of insurance products we i think what's interesting to uh to make clear is that actually that the kind of health data that we generate stays purely within the vitality business itself and what we do inside the vitality business is to analyze that data and say okay is this is this also helping our insurance businesses to to drive uh yeah you know better top line and bottom line in the in the relevant business lines and this is different per company and per mark so yeah being able to interrogate that data understand it apply it in different markets and different uh distribution systems and different kinds of approaches to insurance is an is an important one yes it's an excellent example of a digital business in in you know we talk about digital transformation what does that mean this is what it means i i'd love i mean it must be really interesting board discussions because you're transforming an industry you're lowering overall cost i mean if people are getting less sick that's more profit for your company and you can choose to invest that in new products you can give back some to your corporate clients you can play that balancing act you can gain market share and and you've got some knobs to turn some levers uh for your stakeholders which is which is awesome neil something that i'm interested in i mean it must have been really important for you to figure out how to determine and measure success i mean you're obviously removed it's up it's up to generality vitality to get adoption for for their customers but at the same time the efficacy of your solution is going to determine you know the ease of of of delivery and consumption so so how did you map to the specific goals what were some of the key kpis in terms of mapping to their you know aggressive goals besides the things we already touched on i think one thing i would mention is the timeline right so we we started the team ramping in january or february and then within six months basically we had the solution built and then we went through a extensive test phase and within the next six months we had the product rolled out to three markets so this speed to value speed to market that we were able to achieve i think is one of the key um key criteria that also simon and team gave to us right there was a timeline and that timeline was not going to move so we needed to make a plan adjust to that timeline and i think it's both a testament to to the team's work that they did that we made this timeline but it also is enabled by technologies like cloud i have to say if i go back five years ten years if if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally there would have been no way to do this in 12 months right that's for sure yeah i mean simon you're a technology company i mean insurance has always been a tech heavy company but but as niels just mentioned if you had to do that with it departments in each region so my question is is now you've got this it's almost like non-recurring engineering costs you've got that it took one year to actually get the first one done how fast are you able to launch into new markets just from a technology perspective not withstanding any you know local regulations and figuring out to go to market is that compressed yeah so if you are specifically technology-wise i think we would be able to set up a new market including localizations that often involves translation of because in europe you have all the different languages and so on at i would say four to six weeks we probably could stand up a localized solution in reality it takes more like six to nine months to get it rolled out because there's many other things involved obviously but just our piece of the solution we can pretty quickly localize it to a new market but but simon that means that you can spend time on those other factors you don't have to really worry so much about the technology and so you've launched in multiple european markets what do you see for the future of this program come to america you know you can fight you can find that this program in america dave but with one of our competitors we're not we're not operating so much in uh but you can find it if you want to become a customer for sure but yes you're right so look i think from from our perspective uh you know to put this kind of business into a new market it's not it's not an easy thing because what we're doing is not offering it just as a as a service on a standalone basis to customers we want to link it with with insurance business in the end we are an insurance business and we want to to see the value that comes from that so there's you know there's a lot of effort that has to go into making sure that we land it in the right way also from a customer publishing point of view with our distribution and they are they are quite different so so yeah look coming to the question of what's next i mean it comes in three stages for me so as i mentioned we are uh in five markets already uh in next in the first half of 2022 we'll also come to to the czech republic and poland uh which we're excited to to do and that will that will basically mean that we we have this business in in the seven main uh general markets in europe related to life and health business which is the most natural uh let's say fit for something like vitality then you know the next the sort of second part of that is to say okay look we have a program that's very heavily focused around uh activity and rewards and that that's a good place to start but you know wellness these days is not just about you know can you move a bit more than you did historically it's also about mental well-being it's about sleeping good it's about mindfulness it's about being able to have a more holistic approach to well-being and and covert has taught us and customer feedback has taught us actually that this is something where we need to to go and here we need to have the technology to move there as well so to be able to work with partners that are not just based on on on physical activity but also also on mindfulness so this is how one other way we'll develop the proposition and i think the third one which is more strategic and and we are you know really looking into is there's clearly something in the whole uh perception of incentives and rewards which drives a level of engagement between an insurer like generali and its customers that it hasn't had historically so i think we need to learn you know forget you know forgetting about the specific one of vitality being a wellness program but if there's an insurer there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that and it creates value for us as an insurer then then this is probably you know a place we want to investigate more and to be able to do that in in other areas means we need to have the technology available that is as i said before replicable faster market can adapt quickly to to other ideas that we have so we can go and test those in in different markets so yes we have to we have to complete our scope on vitality we have to get that to scale and be able to manage all of this data at scale all of those rewards at real scale and uh to have the technology that allows us to do that without without thinking about it too much and then to say okay how do we widen the proposition and how do we take the concept of vitality that sits behind vitality to see if we can apply it to other areas of our business and that's really what the future is is going to look like for us you know the the isolation era really taught us that if you're not a digital business you're out of business and pre-kov a lot of these stories were kind of buried uh but the companies that have invested in digital are now thriving and this is an awesome example jeff another point is that jeff amebacher one of the founders of cloudera early facebook employee famously said about 10 12 years ago the best and greatest engineering minds of our my generation are trying to figure out how to get people to click on ads and this is a wonderful example of how to use data to change people's lives so guys congratulations best of luck really awesome example of applying technology to create an important societal outcome really appreciate you your time on the cube thank you thanks bye-bye all right and thanks for watching this segment of thecube's presentation of the aws executive summit at reinvent 2021 made possible by accenture keep it right there for more deep dives [Music] you

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Danielle Cook & John Forman | KubeCon CloudNativeCon NA 2021


 

>>I want to welcome back to the cubes coverage. We're here at another event in person I'm John furrier, host of the cube. We've got to CNCF coop con cloud native con for in-person 2021. And we're back. It's a hybrid event and we're streaming lives on all channels, as well as all the folks watching a great guest kicking off the show here from the co-chairs from cataract coast. Is that right? Danielle Cook. Who's the vice president at Fairwinds and John Foreman director at Accenture. Thanks for coming on your co-chair. Your third co-chair is not here, but you guys are here to talk about the cloud maturity model. Pretty mature funding is flowing tons of announcements. We're going to have a startup on $200 million. They're announcing in funding and observability of all of all hot spaces. Um, so the maturity is it's the journey in the cloud native space now is crossed over to mainstream. That's the we've been telling that story for a couple of years. Now, you guys have been working on this. Tell us about the cloud maturity model you guys worked on. >>So we got together earlier this year because we, um, four of us had been working on maturity models. So Simon Forester, who is one of the co-chairs, who isn't here, he had worked on a maturity model that looked at your legacy journey, all the way to cloud native, um, myself, I had been part of the Fairwinds team working on the Kubernetes maturity model. So, and then, um, we have Robbie, who's not here. And John Foreman, who we all got together, they had worked on a maturity model and we put it together and I've been working since February to go, what is cloud native maturity and what are the stages you need to go through to achieve maturity. So put this together and now we have this great model that people can use to take them from. I have no idea what cloud native is to the steps they can take to actually be a mature organization. >>And, you know, you've made it when you have a book here. So just hold that up to the camera real quick. So you can see it. It's very much in spirit of the community, but in all seriousness, it book's great, but this is a real need. What was the pain point? What was jumping out at you guys on the problem? Was it just where people like trying to get more cloud native, they want to go move faster. It was a confusing, what were the problems you solve in? >>Well, and if anything is, if we start at the beginning, right, there was during the cloud journey DevSecOps and the Kootenays being a thing that then there's journeys to DevSecOps tributaries as well. But everything is leading to cloud native. It's about the journey to cloud native. So everybody, you know, we're taught to go John, the ecosystem's an eyesore man. If I look at, you know, landscape, >>The whole map I >>Need, it's just like in trend map, it's just so confusing what we do. So every time we go to, I revert the wheel and I get them from zero to hero. So we just put together a model instead that we can re reuse yeah. As a good reference architecture. So from that is a primary, how we built because the native trademark you have with us today. So it's a five scale model from one to five what's twice today, or how to, to, you know, what our job is getting to a five where they could optimize a really rocket rolling. >>You know, it's interesting. I love these inflection points and, you know, being a student of history and the tech business there's moments where things are the new thing, and they're really truly new things like first-time operationalized dev ops. I mean the hardcore dev ops or early adopters we've been doing that, you know, we know that, but now mainstream, like, okay, this is a real disruption in a positive way. So the transformation is happening and it's new, new roles, new, new workflows, new, uh, team formations. So there's a, it's complicated in the sense of getting it up and running so I can see the need. How can you guys share your data on where people are? Because now you have more data coming in, you have more people doing dev ops, more cloud native development, and you mentioned security shepherds shifting left. Where's the data tell you, is it, as you said, people are more like a two or more. What's the, what's the data say? >>So we've had, so part of pulling this model together was your experience at Accenture, helping clients, the Fairwinds, um, experience, helping people manage Kubernetes. And so it's from out dozens of clusters that people have managed going, okay, where are people? And they don't even know where they are. So if we provide the guidelines from them, they can read it and go, oh, I am at about two. So the data is actually anecdotal from our experiences at our different companies. Um, but we, you know, we we've made it so that you can self identify, but we've also recognized that you might be at stage two for one application, but five for another application. So just because you're on this journey, doesn't mean everything is in, >>It's not boiler plate. It's really unique to every enterprise because they everyone's different >>Journey. Put you in journey with these things. A big part of this also torn apart one to five, your clients wants to in denial, you know? So, so Mr. CX level, you are level two. We are not, there's no way we would deal with this stuff for years. You've got to be a five. No, sorry. You're too. >>So >>There's use denial also about this. People think they do a cloud-native director rolling, and I'm looking at what they're doing and go, okay, do you do workups security? And they go, what's that? I go, exactly. So we really need to peel back the onion, start from seed year out and we need to be >>All right. So I want to ask more about the, um, the process and how that relates to the themes are involved. What are some of the themes around the maturity model that you guys can share that you see that people can look at and say, how do I self identify? What's the process will come to expect? >>Well, one of the things we did when we were putting it together was we realized that there were themes coming out amongst the maturity model itself. So we realized there's a whole people layer. There's a whole policy layer process and technology. So this maturity model does not just look at, Hey, this is the tech you need to do. It looks at how you introduce cloud native to your organization. How do you take the people along with it? What policies you need to put in place the process. So we did that first and foremost, but one of the things that was super important to all of us was that security was ever present throughout it. Because as everything is shifting left, you need to be looking at security from day one and considering how it's going to happen and roll out from your developers all the way to your compliance people. Um, it's super important. And one of the themes throughout. >>So, so it would be safe to say, then that security was a catalyst for the maturity models because you gotta be mature. I mean, security, you don't fool around security. >>About the last year when I created the program for, since I worked with Cheryl Holland, from CCF, we put together the community certification, her special program. I saw a need where security was a big gap in communities. Nobody knew anything about it. They wanted to use the old rack and stack ways of doing it. They wanted to use their tray micro tombs from yesteryear, and that doesn't work anymore. You need a new set of tools for Kubernetes. It's the upgrade system. It's different way of doing things. So that knowledge is critical. So I think you're part of this again, on this journey was getting certifications out there for people to understand how to do better. Now, the next phase of that now it's how do we put all these pieces together and built this roadmap? >>Well, it's a great group. You guys have the working groups hard to pronounce the name, but, uh, it's a great effort because one of the things I'm hearing and we've been reporting this one, the Cubans looking angle is the modern software developers want speed, and they don't want to wait for the old slow groups now and security, and it are viewed as blockers and like slow things down. And so you start to see a trend where those groups could provide policy and then start putting, feeding up, uh, data models that allow the developers in real time to do their coding, to shift left and to be efficient and move on and code not be waiting for weeks or days >>Comes to play. So today is the age of Caleb's right now, get up this emerging we're only to have now where everything is code policies, code, securities, code policies, cookie figures, code. That is the place for, and then again, walk a fusion more need for a cargo office. >>Okay. What's your thoughts on that? >>So I think what's really important is enabling service ownership, right? You need the developers to be able to do security, see policy, see it live and make sure that, you know, you're not your configuration, isn't stopping the build or getting into production. So, you know, we made sure that was part of the maturity model. Like you need to be looking continuous scanning throughout checking security checking policy. What is your process? Um, and we, you know, we made that ever present so that the developers are the ones who are making sure that you're getting to Kubernetes, you're getting to cloud native and you're doing it. >>Well, the folks watching, if you don't know the cloud native landscape slide, that ecosystem slide, it's getting bigger and bigger. There's more new things emerging. You see role of software abstractions coming in, automation and AI are coming in. So it makes it very challenging if you want to jump right in lifting and shifting to the clouds, really easy check, been there, done that, but companies want to refactor their applications, not just replatform refactoring means completely taking advantage of these higher level services. So, so it's going to be hard to navigate. So I guess with all that being said, what you guys advice to people who are saying, I need the navigation. I need to have the blueprint. What do I do? How do I get involved? And how do I leverage this? >>We want people to, you can go on to get hub and check out our group and read the maturity model. You can understand it, self identify where you're at, but we want people to get involved as well. So if they're seeing something that like, actually this needs to be adjusted slightly, please join the group. The cardiograph is group. Um, you can also get copies of our book available on the show. So if you, um, if you know, you can read it and it takes you line by line in a really playful way as to where you should be at in the maturity model. >>And on top of that, if you come Thursday was Sonia book. And of course, a lot of money, one day, I promise >>You guys are good. I gotta ask, you know, the final question is like more and more, just more personal commentary. If you don't mind, as teams start to change, this is obviously causing a lot of positive transformation if done, right? So the roles and the teams are starting to change. Hearing SRS are now not just the dev ops guys provisioning they're part of the, of the scale piece, the developers shifting left, new kind of workflows, the role of certain engineers and developers now, new team formations. Why were you guys seeing that evolve? Is there any trends that you see around how people are reconfiguring their team makeup? >>I think a lot of things is going to a single panic last tonight, where I'm taking dev and ops and putting them one panel where I can see everything going on in my environment, which is very critical. So right now we're seeing a pre-training where every client wants to be able to have the holy grail of a secret credit class to drive to that. But for you to get there, there's a lot of work you've got to do overnight that will not happen. And that's where this maturity model, I think again, will enhance that ability to do that. >>There's a cultural shift happening. I mean, people are changing there's new skillsets and you know, obviously there's a lot of people who don't have the skill. So it's super important that people work with Kubernetes, get certified, use the maturity model to help them know what skills they need. >>And it's a living document too. It's not, I mean, a book and I was living book. It's going to evolve. Uh, what areas you think are going to come next? So you guys have to predict if you had to see kind of where the pieces are going. Uh, obviously with cloud, everything's getting, you know, more Lego blocks to play with more coolness you have in the, in this world. What's coming next with Sue. Do you guys see any, any, uh, forecasts or >>We're working with each one of the tag groups within the CNCF to help us build it out and come up with what is next based on their expertise in the area. So we'll see lots more coming. Um, and we hope that the maturity grows and because of something that everybody relies on and that they can use alongside the landscape and the trail map. And, um, >>It's super valuable. I think you guys need a plug for any people want to, how they join. If I want to get involved, how do I, what do I do? >>Um, you can join the Carter Garfish group. You can check us out on, get hub and see all the information there. Um, we have a slack channel within the CNCF and we have calls every other Tuesday that people can see the pools. >>Awesome. Congratulations, we'll need it. And super important as people want to navigate and start building out, you know, you've got to edge right around the corner there it's happening real fast. Data's at the edge. You got cloud at the edge. Azure, AWS, Google. I mean, they're pushing really hardcore 5g, lot changes. >>Everybody wants to cloud today. Now one client is, one is more cloud. At least both the cloud is comfortable playing everywhere. One pump wife had DevOps. >>It's distributed computing back in the modern era. Thank you so much for coming on the keep appreciating. Okay. I'm Jennifer here for cube con cloud native con 2021 in person. It's a hybrid event. We're here live on the floor show floor, bringing you all the coverage. Thanks for watching station all day. Next three days here in Los Angeles. Thanks for watching. >>Thank you.

Published Date : Oct 26 2021

SUMMARY :

but you guys are here to talk about the cloud maturity model. are the stages you need to go through to achieve maturity. So you can see it. It's about the journey to cloud native. So from that is a primary, how we built because the native trademark you have with us I mean the hardcore dev ops or early adopters we've been doing that, you know, So the data is actually anecdotal from our It's not boiler plate. so Mr. CX level, you are level two. and I'm looking at what they're doing and go, okay, do you do workups security? What are some of the themes around the maturity model that you guys can share that you see that people can look at and say, So this maturity model does not just look at, Hey, this is the tech you need to I mean, security, you don't fool around security. Now, the next phase of that now it's how do we put all these pieces together and built this roadmap? And so you start to see a trend where those groups could provide policy and then start putting, feeding up, So today is the age of Caleb's right now, get up this emerging we're only to have now where everything Um, and we, you know, we made that ever present so that the developers So I guess with all that being said, what you guys advice to We want people to, you can go on to get hub and check out our group and read the maturity And on top of that, if you come Thursday was Sonia book. So the roles and the teams are starting to change. But for you to get there, there's a lot of work you've got to do overnight that will not happen. new skillsets and you know, obviously there's a lot of people who don't have the skill. So you guys have to predict if you had to see kind of where the pieces are going. landscape and the trail map. I think you guys need a plug for any people want to, how they join. Um, you can join the Carter Garfish group. you know, you've got to edge right around the corner there it's happening real fast. At least both the cloud is comfortable playing everywhere. We're here live on the floor show floor, bringing you all the coverage.

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Simon Guest Nil V2 | AWS Executive Summit 2021


 

(upbeat music) >> Welcome back to theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. My name is Dave Vellante. We're going to look at how digital infrastructure is helping to transform consumer experiences, specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who changed their behavior to live healthier lives, a real passion of mine, and getting to the really root cause of health. With me now are Simon Guest, who's the Chief Executive Officer of Generali Vitality, GmbH, and Nils Muller-Sheffer, who's the Managing Director at the Cloud First Application Engineering Lead for the European market at Accenture. Gentlemen, welcome to theCUBE. >> Thanks for having us. >> You're very welcome Simon. Simon, Generali Vitality is a really interesting concept that you guys have envisioned and now put it into practice. Tell us how does it all work? >> Sure. No problem. And thanks for having us on David, pleasure to be here. So look, Generali Vitality is in its core a pretty simple concept. It's a program that you have on your phone. And the idea of this program is that it's a wellness coach for you as an individual, and it's going to help you to understand your health and where you are in terms of the state of your health at the moment, and it's going to take you on a journey to improve your lifestyle and your wellness, and hopefully help you to live a healthier and a more sort of mindful life, I guess, is the best way of summarizing it. From our point of view as an insurance company, of course, our historical role has always been to be the company that's there if something goes wrong. So if unfortunately you pass away or you have sickness in your life or your family's life, that's historically been our role. But what we see with Generali Vitality is something a little bit different. So it's a program that really is supposed to be with you every day of your life to help you to live a healthier life. It's something that we already have in for European markets and in fact, in five from this week, I'm a little bit behind the times. So we're live already in Germany, in France, in Austria, in Italy and in Spain. And fundamentally what we do Dave, is to say to customers, "Look, if you want to understand your health, if you want to improve it by moving a little bit more, or by visiting the doctor more, by eating healthier, by healthy choices on a daily basis, we're going to help you to do that. And we're going to incentivize you for going on this journey and making healthy choices. And we're going to reward you for doing the same." So, we partner up with great companies like Garmin, like Adidas, like big brands that are, let's say, invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well, make good choices, be healthy, have an insurance company that partners you along that journey. And if you do that, we've going to reward you for that. So, we're here not just in a difficult times, which of course is one of our main roles, but we're here as a partner, as a lifetime partner to you to help you feel better and live a better life. >> I love it, I mean, it sounds so simple, but I'm sure it's very complicated to make the technology simple for the user. You've got mobile involved, you've got the back end and we're going to get into some of the tech, but first I want to understand the member engagement and some of the lifestyle changes Simon that you've analyzed. What's the feedback that you're getting from your customers? What does the data tell you? How do the incentives work as well? What is the incentive for the member to actually do the right thing? >> Sure, I think actually that the COVID situation that we've had in the last sort of two years is really crystallized the fact that this is something that we really ought to be doing and something that our customers really value. Just to give you a bit of a sort of information about how it works for our customers. So what we try to do with them, is to get customers to understand their current health situation, using their phone. So, we asked our customers to go through a sort of health assessments around how they live, what they eat, how they sleep, and to go through that sort of process and to give them all the Vitality age, which is a sort of actuarial comparison with their real age. So I'm 45, but unfortunately my Vitality age is 49 and it means I have some work to do to bring that back together. And what we see is that, two thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life. And if what they are doing is having an impact on their life expectancy and their lifespan and their health span. So how long are they going to live healthier for? So you see them really engaging in this approach of understanding that current situation. Then what we know actually, because the program is built around this model that's really activity and moving, and exercise is the biggest contributors to living a healthier life. We know that the majority of deaths are caused by lifestyle illnesses like poor nutrition and smoking and drinking alcohol and not exercising. And so a lot of the program is really built around getting people to move more. And it's not about being an athlete. It's about, getting off the underground one station earlier and walking home or making sure you do your 10,000 steps a day. And what we see is that that sort of 40% of our customers are on a regularly basis linking either their phone or their exercise device to our program and downloading that data so that they can see how much they are exercising. And at the same time, what we do is we set our customers weekly challenges to say, look, if you can move a little bit more than last week, we are go into to reward you for that. And we see that almost half of our customers are achieving this weekly goal every week. And it's really a level of engagement that normally as an insurer, we don't see. The way that rewards work is pretty simple. It's similar in a way to an airline program. So every good choice you make every activity to every piece of good food that you eat. When you check your on your health situation, we'll give you points. And the more points you get, you go through through a sort of status approach of starting off at the bottom status and ending up at a golden and a platinum status. And the higher up you get in the status, the higher the value of the rewards that we give you. So almost a quarter of our customers now, and this has accelerated through COVID have reached that platinum status. So they are the most engaged customers that we have and those ones who are really engaging in the program. And what we really tried to create is this sort of virtuous circle that says If you live well, you make good choices, you improve your health, you progress through the program and we give you better and stronger and more valuable rewards for doing that. And some of those rewards are around health and wellness. So it might be that you get a discounts on gym gear from Adidas, it might be that you get a discount on a device from Garmin, or it might be actually on other things. We also give people Amazon vouchers. We also give people discounts on holidays. And another thing that we did actually in the last year, which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations. Because we work in generosity with a sort of campaign called The Human Safety Net, which is helping out the poorest people in society. And so what our customers do a lot of the time is instead of taking those financial rewards for themselves, they convert it into a charitable donation. So we're actually also linking wellness and feeling good and insurance and some societal goods. So we're really trying to create a virtuous circle of engagement with our customers. >> That's a powerful cocktail. I love it. You've got the data, because if I see the data, then I can change my behavior. You've got the gamification piece. You actually have hard dollar rewards. You could give those to charities and you've got the most important, which is priceless, you can't put a value on good health. I got one more question for Simon and Nils I'd love for you to chime in as well on this question. How did you guys decide, Simon, to engage with Accenture and AWS and the cloud to build out this platform? What's the story behind that collaboration? Was there unique value that you saw that you wanted to tap, that you feel like they bring to the table? What was your experience? >> Yeah, we work with Accenture as well because the sort of constructs of this Vitality proposition is a pretty complex one. So you mentioned that the idea is simple, but the build is not so simple and that's the case. So Accenture has been part of that journey from the beginning. They are one of the partners that we work with, but specifically around the topic of rewards, we're primarily European focused organization, but when you take those countries that I mentioned, even though we're next to each other geographically, we're quite diverse. And what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go get to market with an increasing amounts of efficiency. And to do that, we needed to work with somebody who understood our business, has this historical, let's say investment in the Vitality concepts and so knows how to bring it to life, but then could really support us in making what can be a complex piece of work, as simple, as replicable as possible across multiple markets, because we don't want to go reinventing the wheel every time we knew we moved to a new market. So we need to find a balance between having a consistent product, a consistent technology offer, a consistent customer experience with the fact that we operate in quite diverse markets. So this was, let's say the reason for more deeply engaging with Accenture on this journey. >> Thank you very much, Nils, why don't you comment on that as well? I'd love to get your thoughts and really is kind of your role here, an Accenture global SI, deep expertise in industry, but also technology, what are your thoughts on this topic? >> Yeah, I'd love to love to comment. So when we started the journey, it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets, have a central solution that can act as a template for the different markets, but then also have the opportunity to localize different languages, different partners for the rewards, there's different reward partners in the different markets. So we needed to build an asset basically that could work as a template, centrally standardizing things, but also leaving enough flexibility to then localize in the individual markets. And if we talk about some of the most specific requirements, so one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the, basically the authentication needs to happen. And if we somehow needed to still find a holistic solution that comes through the central platform, and we were able to do that at the end through the AWS cognitive service, sort of wrapping the individual markets, local IDP systems. And by now we've even extended that solution to have a standalone cloud native kind of IDP solution in place for markets that do not have a local IDP solution in place, or don't want to use it for this purpose. >> So you had data, you had the integration, you've got local laws, you mentioned the flexibility, you're building ecosystems that are unique to the local, both language and cultures. Please, you had another comment, I interrupted you. >> No, I just wanted to expand basically on the requirements. So that was the central one being able to roll this out in a standardized way across the markets, but then there were further requirements. For example, like being able to operate the platform with very low operations overhead. There is no large IT team behind Generali Vitality that, works disservice or can act as this backbone support. So we needed to have basically a solution that runs itself that runs on autopilot. And that was another big, big driver for first of all, going to cloud, but second of all, making specific choices within cloud. So we specifically chose to build this as a cloud native solution using for example, managed database services, with automatic backup, with automatic ability to restore data that scales automatically that has all this built in which usually maybe in a database administrator would take care of. And we applied that concept basically to every component, to everything we looked at, we applied this requirement of how can this run on autopilot? How can we make this as much managed by itself within the cloud as possible, and then lend it on these services. For example, we also use the API gateway from AWS for our API services that also came in handy when, for example, we had some response time issues with the third party we needed to call. And then we could just with a flick of a button basically, introduced caching on the level of the API gateway and really improve the user experience because the data wasn't updated so much, so it was easier to cache. So these are all experiences I think that that proved in the end that we made the right choices here and the requirements that drove that to have a good user experience. >> Would you say that the architecture is a sort of a, data architecture specifically, is it a decentralized data architecture with sort of federated, centralized governance? Or is it more of a centralized view, wonder if you could talk about that? >> Yeah, it's actually a centralized platform basically. So the core product is the same for all the markets and we run them as different tenants basically on top of the infrastructure. So the data is separated in a way, obviously by the different tenants, but it's in a central place and we can analyze it in a central fashion if the need arises from the business. >> And the reason I asked that Simon is because essentially I look at this as largely a data offering for your customers. And so Nils, you were talking about the local language and Simon as well. I would imagine that the local business lines have specific requirements and specific data requirements. And so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security. And that's not a trivial challenge. I wonder if you both could comment on that. >> Yeah, maybe I'll give a start and then Simon can chime in. So what we're specifically doing is managing the rewards experience, so our solution will take care of tracking what rewards have been earned for what customer, what rewards have been redeemed, what rewards can be unlocked on the next level, and we foreshadow a little bit to motivate incentivize the customer and asset that data sits in an AWS database by tenant fashion. And you can run analysis on top of that. Maybe what you're getting into is also the, let's say the exercise data, the fitness device tracking data that is not specifically part of what my team has built, but I'm sure Simon can comment a little bit on that angle as well. >> Yeah, please. >> Yeah, sure. I think the topic of data and how we use it in our business is a very interesting one because it's not historically been seen, let's say as the remit of insurance to go beyond the data that you need to underwrite policies or process claims or whatever it might be. But actually we see that this is a whole point around being able to create some shared value in this kind of products. And what I mean by that is, if you are a customer and you're buying an insurance policy, it might be a life insurance or health insurance policy from Generali, and we're not giving you access to this program. And through that program, you are living a healthier life and that might have a positive impact on generosity in terms of, maybe we're going to increase our market share, or maybe we are going through lower claims, or we're going to generate value of that then. One of the points of this program is we then share that value back with customers, through the rewards on the platform that we've built here. And of course, being able to understand that data and to quantify it and to value that data is an important part of the different stages of how much value you are creating. And it's also interesting to know that, in a couple of our markets, we operate in the corporate space. So not with retail customers, but with organizations. And one of the reasons that those companies give Vitality to their employees is that they want to see things like the improved health of a workforce. They want to see higher presenteeism, lower absenteeism of employees, and of course, being able to demonstrate that there's a sort of correlation between participation in the Vitality program and things like that is also important. And as we've said, the markets are very different. So we need to be able to take the data that we have out of the Vitality Program and be able in the company that I'm managing to interpret that data so that in our insurance businesses, we are able to make good decisions about kind of insurance product we have. I think what's interesting to make clear is that actually that the kind of health data that we generate states purely within the Vitality business itself and what we do inside the Vitality business is to analyze that data and say, is this also helping our insurance businesses to drive better top line and bottom line in the relevant business lines? And this is different per company. Being able to interrogate that data, understand it, apply it in different markets, in different distribution systems and different kinds of approaches to insurance is an important one, yes. >> It's an excellent example of a digital business and we talked about digital transformation. What does that mean? This is what it means. It must be really interesting board discussions because you're transforming an industry, you're lowering overall costs. I mean, if people are getting less sick, that's more profit for your company and you can choose to invest that in new products, you can give back some to your corporate clients, you can play that balancing act, you can gain market share. And you've got some knobs to turn, some levers, for your stakeholders, which is awesome. Nils, something that I'm interested in, it must've been really important for you to figure out how to determine and measure success. Obviously it's up to Generali Vitality to get adoption for their customers, but at the same time, the efficacy of your solution is going to determine, the ease of delivery and consumption. So, how did you map to the specific goals? What were some of the key KPIs in terms of mapping to their aggressive goals. >> Besides the things we already touched on, I think one thing I would mention is the timeline. So, we started the team ramping in January, February, and then within six months basically, we had the solution built and then we went through a extensive test phase. And within the next six months we had the product rolled out to three markets. So this speed to value, speed to market that we were able to achieve, I think is one of the key criteria that also Simon and team gave to us. There was a timeline and that time I was not going to move. So we needed to make a plan, adjust to that timeline. And I think it's both a testament to the team's work that we met this timeline, but it also is enabled by a technology stack cloud. I have to say, if I go back five years, 10 years, if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally, there would've been no way to do this in 12 months, that's for sure. >> Yeah, Simon, you're a technology company. I mean, insurance has always been a tech heavy company, but as Nils just mentioned, if you had to do that with IT departments in each region. So my question is now you've got this, it's almost like nonrecurring engineering costs, it took one year to actually get the first one done, how fast are you able to launch into new markets just from a technology perspective, not withstanding local regulations and figuring out the go to market? Is that compressed? >> So you asked specifically technology-wise I think we would be able to set up a new market, including localizations that often involves translation of, because in Europe you have all the different languages and so on, I would say four to six weeks, we probably could stand up a localized solution. In reality, it takes more like six to nine months to get it rolled out because there's many other things involved, obviously, but just our piece of the solution, we can pretty quickly localize it to a new market. >> But Simon, that means that you can spend time on those other factors, you don't have to really worry so much about the technology. And so you've launched in multiple European markets, what do you see for the future of this program? Come to America. >> You can find that this program in America Dave, but with one of our competitors, we're not operating so much in the US, but you can find it if you want to become a customer for sure. But yes, you're right. I think from our perspective, to put this kind of business into a new market is not an easy thing because what we're doing is not offering it just as a service on a standalone basis to customers, we want to link it with insurance business. In the end, we are an insurance business, and we want to see the value that comes from that. So there's a lot of effort that has to go into making sure that we land it in the right way, also from a customer proposition points of view with our distribution, they are all quite different. Coming to the question of what's next? It comes in three stages for me. So as I mentioned, we are in five markets already. In the first half of 2022, we'll also come to the Czech Republic and Poland, which we're excited to do. And that will basically mean that we have this business in the seven main Generali markets in Europe related to life and health business, which is the most natural at let's say fit for something like Vitality. Then, the sort of second part of that is to say, we have a program that is very heavily focused around activity and rewards, and that's a good place to start, but, wellness these days is not just about, can you move a bit more than you did historically, it's also about mental wellbeing, it's about sleeping good, it's about mindfulness, it's about being able to have a more holistic approach to wellbeing and COVID has taught us, and customer feedback has taught is actually that this is something where we need to go. And here we need to have the technology to move there as well. So to be able to work with partners that are not just based on physical activity, but also on mindfulness. So this is how one other way we will develop the proposition. And I think the third one, which is more strategic and we are really looking into is, there's clearly something in the whole perception of incentives and rewards, which drives a level of engagement between an insurer like Generali and its customers that it hasn't had historically. So I think we need to learn, forgetting about the specific one or Vitality being a wellness program, but if there's an insurer, there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that. And it creates value for us as an insurer, then this is probably a place that we'd want to investigate more. And to be able to do that in other areas means we need to have the technology available, that is, as I said before, replicable faster market can adapt quickly to other ideas that we have, so we can go and test those in different markets. So yes, we have to, we have to complete our scope on Vitality, We have to get that to scale and be able to manage all of this data at scale, all of those rewards that real scale, and to have the technology that allows us to do that without thinking about it too much. And then to say, okay, how do we widen the proposition? And how do we take the concept that sits behind Vitality to see if we can apply it to other areas of our business. And that's really what the future is going to look like for us. >> The isolation era really taught us that if you're not a digital business, you're out of business, and pre COVID, a lot of these stories were kind of buried, but the companies that have invested in digital are now thriving. And this is an awesome example, and another point is that Jeff Hammerbacher, one of the founders of Cloudera, early Facebook employee, famously said about 10, 12 years ago, "The best and greatest engineering minds of my generation are trying to figure out how to get people to click on ads." And this is a wonderful example of how to use data to change people's lives. So guys, congratulations, best of luck, really awesome example of applying technology to create an important societal outcome. Really appreciate your time on theCUBE. Thank you. >> Bye-bye. >> All right, and thanks for watching this segment of theCUBE's presentation of the AWS Executive Summit at re:Invent 2021 made possible by Accenture. Keep it right there for more deep dives. (upbeat music)

Published Date : Oct 21 2021

SUMMARY :

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Simon Davies, Splunk | Splunk .conf21


 

>>Hey, welcome to the cubes coverage of splunk.com 21. I'm licensed Lisa Martin here. I've got some in Demis with me, a VP in APAC at Splunk Simon. Welcome to the program. >>So here we are, unfortunately at another virtual conference, but there has been a tremendous amount of there's an understatement, right? That we've seen in the last 18 months. We've seen this massive distribution of the workforce. We've seen huge increases in the threat landscape. We've seen things like solar winds, ransomware, increasing significantly acceleration and digital transformation. As companies tried to do whatever they could to enable digital workspaces. I wanted to unpack with you, uh, this 20, 21 state of security report that Splunk has. What are some of the key findings? And then we'll dig into some of the things that you're seeing in the APAC region. >>Yeah, look, we're excited about the report. It really highlighted, I think what a lot of organizations are going through. Um, one of the statistics that stood out for me was, um, 75% of infrastructure users are multi-cloud, but expecting to get that these expecting to increase to 87% of customers will be using multicloud environments. So the reason why that's important is the complexity that creates, uh, for cyber professionals in terms of trying to protect and defend, um, becomes exponentially harder with every new iteration or generation of infrastructure that companies consume. Um, most interesting. Um, we actually saw about a third of users or already using three cloud providers, but that is going to grow to 50% of, of customers will grow to being using three cloud providers or more within the next two years. So again, just that, that trend is going to continue. Uh, the leveraging of cloud infrastructures is a core way of businesses digitizing and modernizing. Um, and as cyber professionals, we have to think about how we're going to address that. >>Definitely. One of the things that I've been seeing and hearing in the last 18 months from a security perspective is that organizations say, you know, it's, it's really not a matter of if we get hit with ransomware, it's when, and I was really surprised to see the, that the state of security report found that 70% of security and it leaders worry they're going to be hit by a solar winds style attack. So the security landscape changing dramatically in the last 18 months. >>Yeah, absolutely. I think the, the, the research is feeding back what we were already hearing from the customers, um, around how this is a critical, uh, motion. And I think the one thing that we've seen as well as the board level agenda now, the risk and cyber has, and, uh, an organization's ability to react or recover. Um, when you have an, an event, um, is now becoming a high priority for organizations, we're seeing a lot of increased spending in cybersecurity as this becomes more and more, um, pretty for organizations for breasts. So yeah, the, the, on the ground experiences certainly matching what we're seeing in the research there. Um, and all of that is a data problem, right? Security is a data problem when something happens, how do I, how do I know? Where, how do I know when, how do I know what, and then how do I know what actions to take based upon the data that we need to get? >>So security being a data problem talked about the complexity of the multi-cloud environments, that percentages of organizations that are adopting that now what that trend is moving towards. Also complexity, I can imagine with data volumes only increasing, what are some of the key challenges that APAC organizations specifically are seeing as they are accelerating digital transformation and doing what they can to enable this distributed workforce? >>Yeah. So, so the hybrid multicloud environment you use, I guess, an indicator of increased complexity, I think we often overlook the fact that I think the hybrid world is here to stay as well. So nobody is a hundred percent cloud and nobody's a hundred percent on prem anymore. It's very much an environment now where I need to, um, I need to protect and defend across that entire surface area and increasingly with edge computing. Um, and as we're looking at, uh, organizations pushing, processing out to the edge of their, um, their operations and whether that's a distributed workforce or sensor-based environments, um, that becomes critical as well. We've got organizations like Intel, uh, that use us to basically monitor not only the cyber infrastructure, but the entire customer infrastructure that they're providing the fabric by census of course, environments, where you can imagine that the security becomes even more important. >>So I think that complexity and the data sources that are now being generated and the explosion of that is, is kind of critical. Um, for apex specifically, we saw some interesting trends we saw about 37% of organizations are using data to now support the compliance environments. Um, about 36% are bringing in non-security data. Um, and about 36%, it really started to use AI or machine learning tools to help them in that, that large scale data volume processing, um, that they weren't able to do before. And then lastly, security analytics really is starting to become, uh, a critical tool in the arsenal of cyber professionals with 34% of organizations saying they're already using some form of security analytics to help them address the threat actors. >>Is there a silver lining in terms of the it folks and the security folks becoming better collaborating better? Anything that you've seen in this report? >>Uh, well in the report, but also in the way that we're seeing SOC organizations use tools. Um, so, uh, the orchestration remediation and automation is a big industry trend, particularly when you look at things like implementing zero trust and how you would use that for, um, putting that additional layer of protection around an organization. Um, and that's where the ability to identify using machine learning or AI, uh, trends or events, understand the actions that need to be taken, understand the data sources that help address and remediate those and be able to automate that frees up the time and cyber security professionals. Um, and that's a critical step we're seeing because there's a shortage of skills and that's been an ongoing challenge, not only in Asia Pacific, but I think worldwide, >>Right. It has been a challenge worldwide. I was actually doing some cyber security work in the last month or so. And I read that this is the fifth consecutive year of that cybersecurity skills gap. So definitely a challenge there, but also if you flip the coin and opportunity. So in terms of some of those challenges that you mentioned, what are some of the key things that organizations and APAC can do to confront and combat those security challenges that are no doubt just only going to grow? >>Yeah, so I think, I think it's about, um, visibility, uh, and getting control, uh, and that's where again, data becomes key to that. So making sure you're capturing the right data, making sure that data is available, um, to your professionals, or if you're using a service provider, making sure that data is captured and available to the service providers, because that is increasingly what we see as the critical step to be able to, when something happens, how do you recover what your meantime to remediation, um, as, as the kind of critical motion. And so that's, again, what we could coming back to is security is a data problem. >>Security is a data problem. Got it. I do want to, uh, unpack a little bit some of the visibility challenges. That is one of the things that was identified. You mentioned that with so much complexity, multi-cloud being, uh, as, as hybrid work, something that's going to stay, what are some of the things that organizations can do and how can Splunk help to remove and mitigate those visibility challenges? >>So we've we just another interesting piece of research, um, it's called the state of data innovation report. Um, that really looked at the way organizations that categorize that data and organizations that actually build a data strategy, um, are actually much more prepared to react, uh, to engage and then to leverage that data for competitive differentiation in their markets. Um, and interestingly 33% of APAC organizations particularly rated their usage of data as better, uh, than, um, the industry average. Um, and 54% of APAC organizations already said they're using technologies like observability, which really helps them innovate around the data. Thinking about that next generation of service they're trying to provide. >>Did you see those are great numbers? It's about a third, um, are, are working on implementing technologies 54% were focused on that observability. Did you see any industries in particular that really leading edge there? Of course, every industry being affected by the pandemic, but I'm just curious if there were any, any ones that stood out >>So many great customer examples that we've got, uh, where we see organizations thinking differently about the way they engage their customers as a result of the digital transformation. Um, for me, one of the ones that stands out is Lenovo, um, you know, 50 billion plus multinational company servicing 180 markets around the world, um, when they looked at their observability approach and tried to understand how they were going to approach troubleshooting, um, when they had issues, if you think about the e-commerce experience for their consumers, um, they were able to reduce the, uh, reduce the downtime, um, and improve, um, the remediation time when there were incidents, uh, even though they had a 300% increase in traffic. And so for the ability for an organization to handle that kind of surge in digital, uh, interactions with their customers and do that to have clear visibility, using metrics, traces, and logs, to understanding exactly what's going on across complex, siloed multi, uh, services, uh, environments was, was critical to the Novo success. And, um, you know, not only from a cybersecurity point of view, but also having real time visibility into their infrastructure became critical as they service their customers. >>Right? One of the things I think we learned Simon during the pandemic, one of the many things is that access to real-time data real-time visibility real time, rather than visibility is no longer a nice to have it's. It was something that in the beginning was sort of organizations needing it to survive. Now organizations needing it to thrive it's that, that real-time visibility is really table stakes for organizations in any industry. >>W we, we kind of saw organizations go through three phases. There was the react phase. Then there was the adapt phase. So, you know, reacting was, first of all, kind of keep my people safe. The adapt phase was how am I going to work? And now we're seeing that next generation, which is really the evolve phase, right? Given the pandemic is still well COVID is still with us. Um, whether it's your, most of the countries, which are treating it more as an endemic or whether you're on the number of the countries still on that journey. And you're in Asia Pacific, we see different levels of, of vaccination status, different levels of, uh, companies starting to open up or countries starting to open up their borders and, um, life getting back to the, what is the new normal, um, all of that is still gonna evolve with a different way of working, moving forward, a different way of engaging our customers and our, our, uh, constituents, if you're a public sector, organization and data is underlying all of that. And for that, where we're kind of excited to be helping some of the largest organizations with that across, across the region, >>Did it is absolutely critical. You know, one of the things that we've also, I think observed in the last year and a half is the, the patients or the fuses of people getting smaller and smaller. So for organizations to have that visibility into data so that they can service their customers, whether it be healthcare or financial services or the tech sector for, for example, the access to that data is critical for brand reputation, reducing churn. And of course, ensuring that the customers are getting what they need to from that data. >>Yeah. A hundred percent. Um, gosh, so many examples across the region. One of the ones that jumps to mind is Flinders university, right? When, when they had to go remote, they had to go virtual, um, 25,000 students overnight, um, suddenly needing to be interacting by digital channels. How do you keep them secure? How do you keep them safe? How do you get insights, uh, in terms of the services that they need to, to protect that student population? >>So if you, if you kind of distill this down into data opportunities for organizations, we'll start with APAC, what do you think the top three data opportunities are of security as a data problem? What are the opportunities to combat that for an organization to be really successful? >>So I think, I think visibility is the first one. So making sure we're capturing the data, making sure we're capturing the right data. Um, and so the ability, uh, not only to capture the data, but to time sequence the data so I can actually understand what's happened. And when, um, the second then is, is, uh, control. Um, so ensuring that the right people have access to the right data, but we, we control that in a way that is specific to our organization. Um, and then lastly compliance. Um, and I think we're seeing a lot of new legislation starts coming around critical infrastructure, um, recognizing the importance of the digital infrastructure to the broader economy, um, and making sure that you're compliant with that critical infrastructure kind of requirements and environments as well as then the traditional regulated industries such as healthcare and financial services, um, become critical in that approach. So thinking about those three elements, and then thinking about how do I then use tools like automation and security analytics to really accelerate, um, the capabilities that we have as an organization. >>So observability control compliance, give me the 32nd pitch of how Splunk can help organizations achieve all three of those. >>So observability really is about getting insights into all of your environments. So, uh, it's all about metrics, traces and logs, which is about understanding exactly what's going on with every experience of every digital interaction I have with every customer and the ability to Splunk through that with zero, uh, zero sampling or full fidelity of that data is something we see our customers, particularly Navy, um, security, uh, look for me to it's all about orchestration and analytics. So how do I, how do I get that understanding that, that user behavior understanding the analytics around that, and then how machine learning becomes a critical part of that to help me scale my cyber infrastructure and defend. And then lastly resilience is really the core for all it systems in a digital world. Um, and being able to not only harden deliver resilient services like going over, I was able to do the 300% increase in their web traffic. Um, but also when something does go wrong and be able to remediate quickly become critical as well. >>Right? That quick remediation is because, like I was saying earlier, it's no longer a, if we get hit it's when organizations need to have that resilience baked in. Well, Simon, thank you for joining me, breaking down. Some of those reports what's going on in APAC, some of the trends and also some of the opportunities, security being a data problem, um, and organizations, what they can do to remediate that we appreciate your time. Thanks for having my pleasure for Simon Davies and Lisa Martin. You're watching the cubes coverage of splunk.com 21.

Published Date : Oct 20 2021

SUMMARY :

Welcome to the program. of the workforce. Um, one of the statistics that stood out for me was, um, 75% One of the things that I've been seeing and hearing in the last 18 months from Um, and all of that is a data problem, So security being a data problem talked about the complexity of the multi-cloud environments, Um, and as we're looking at, uh, organizations pushing, processing out to the edge Um, and about 36%, it really started to use AI or machine learning tools to help them in that, Um, and that's a critical step we're seeing because there's a shortage and combat those security challenges that are no doubt just only going to grow? as the critical step to be able to, when something happens, how do you recover what your meantime That is one of the things that was identified. Um, that really looked at the way organizations that categorize Of course, every industry being affected by the pandemic, Um, for me, one of the ones that stands out is Lenovo, um, you know, 50 billion plus multinational One of the things I think we learned Simon during the pandemic, one of the many things is that access to across the region, And of course, ensuring that the customers are getting what they need to from One of the ones that jumps to mind is Flinders university, right? Um, so ensuring that the right people have access to the right data, but we, So observability control compliance, give me the 32nd pitch of how Splunk the ability to Splunk through that with zero, uh, zero sampling or full fidelity of that data is something we see um, and organizations, what they can do to remediate that we appreciate your time.

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Simon McCormack, Aruba | Aruba & Pensando Announce New Innovations


 

(fastpaced upbeat music) >> Welcome back to theCubes coverage of the power of N and the collaborations between HPE Aruba and Pensando. Where the two companies are setting out to create a new category in network switching. Joining me now is Simon McCormack, who looks after product management at HPE Aruba. Welcome Simon. Good to see you. >> Good morning. Thanks for having me today. >> You're very welcome. So Simon, we've been talking all day about the Aruba switching fabric that you're bringing to market, embedding the Pensando technology. Can you tell us what's the primary value prop that AFC brings to its customers? >> Sure. Aruba Fabric Composer. This is orchestration and management for the Aruba wide switching platform. Primarily for data centers. It does a lot of things. I'll give you three key ones just to get a feel for it. So in data center networking, there's a lot of complex technologies. I'm afraid to say, lease spines, overlays, underlays, EDP and OSPF BGP. I can throw out loads of acronyms for you. Fabric Composer can really simplify through a bunch of intent based workflows, the deployment and management of these fabrics. We can do it either interactively through a UI or fully API driven, if you want to. So it really takes away a lot of the plexity there makes it dead easy to deploy these and that scale. Number two, in a data center, a lot of compute storage hypervisor technologies that you have to interact with the THEO network products. So in Fabric Composer, we built an integration layer into it that interacts with other orchestrators, vCenter, VMware vcenter is a good example of that. So an operator may make changes to vCenter that affect the network. You don't want to call the network team for it. Fabric Composer can automate that network side configuration on the Aruba switch, making your day to operations, insertion of new services, much more simpler. And then finally, number three, because we've got all these capabilities I've just told you about. We actually have a great typology model that we build from it. And we can use that to visualize this virtual to physical network layer that is really powerful for troubleshooting the environment. >> Great? So three things, actually four right. To simplify or integrate and automate. And it's kind of two and two way, I'm going to to call it. and then the visualization piece for troubleshooting. Awesome. What about security policy? How are you thinking about that in this release? >> Yeah, so that's where in this release, we're extending it with the Pensando PSM technologies embedded into the 10K. Now we can use Aruba Fabric Composer to actually orchestrate the policy in addition to the network. So you think about today, Fabric Composer does network primarily. You bring policy into it. You've got one single pane of glass now that does network and policy. It actually provides a really powerful capabilities for operators of different skill sets to be able to manage and orchestrate this environment. >> What about the sort of operational model as it pertains to the network and security, I'm interested in how flexible that is. For instance, if a customer wants to use their own tooling or operational frameworks. What if they want to leverage multi-vendor fabrics like a third-party spine? How do you deal with all of that? >> Yeah, and I think that's, we built that into essentially the DNA of this technology is that we're, we're expecting to often go into brownfield environments. Where they've already got best practices for security and networking. They've already got networking vendors there. The 10K is a very powerful lease switch on its own. We want those lease switches to go in all of these different environments, not just Greenfield. It's really great for Greenfield. And I'm going to explain this a little bit in a few ways. First of all, the technology we have with Aruba fabric Composer and Pensando PSM, you can do a pure operational split between them SecOps, NetOps. A lot of customers that's how they deal with it. They've got the security operations team, network operations team. If they're split, you can use the two tools and make a fantastic product using that. However, if they're not split, and you've got a single policy for it. You can use Aruba Fabric Composer to do both of them. So you've got the options there and we fully embrace that in the architecture of what we built. This extends to multiple layers for the technology build as well. Again, as I said, the 10K's is a lease switch, it can connect to third-party spines. So you could use Fabric Composer to manage this lease Spitch and the policy you could use Fabric Composer just to manage the least switch and connect and interoperate the lease to the spine, or you can do a full Aruba solution, the full Aruba spine and use that operating model. There's one final thing in this area is fabric Composers are a UI based orchestrator, API driven. Some customers love it. Some customers love their CLIs. We fully embrace the operational model where customers still use their own APIs and their own CLIs. So the customer may be using Ansible to automate through API. They can still use that directly to the switch and they can use it to AFC and mix the two. If you talk directly to a switch and change it, Fabric Composer detects it and basically sinks its configuration together. So we can insert all or any part of this solution into existing or new Netflix. >> Yeah, that's nice. Right? Because I mean, so there's the network hard guys, right they, they want that CLI access. So you you're accommodating that. And then as well, being able to bring those SecOps view and the netOps view together is important because let's say, let's face it. A lot of organizations, especially some of the smaller ones, they don't actually have a full blown SecOps team. That's really the netOps responsibility. And so that's nice flexibility, you can handle both worlds. How about segmentation? What a customer is telling you that they want regarding segmentation and how are you guys approaching that? >> Yeah, I mean, it's, it's actually a key feature of what we're doing in this area. Now the iland segmentation generates it's kind of a wide area with many layers to it and we could talk about it for hours. So let me talk briefly about some of the areas we're going into when it comes to the segmentation. But particularly of a compute and virtual type environment. So when you, when you're typically creating policies in today's world, current policies based on addresses, IP addresses, or Mac addresses. You have lots of rules and big lists of addresses. It's really annoying. Customers generally don't talk in addresses. They talk in machines and names of machines. So if you think about what I've already told you with the Fabric Composer, we've already got these hooks in the compute hypervisor layer. So we didn't know about the virtual machines? So it said obviously, a natural extension now for you to be able to create these policies based on the machines. So there's, there's a scale problem in policy distribution at two levels, at the top and the bottom. The top level is your chronic create the policy. You've got this massive distribution addresses. So Fabric Composer can really help you by allowing you to then create these groups, sensible groups, using the names then you can distribute. The 10K solution with the distributed architecture of the bottom layer, now allows us to distribute these policies and rules across your racks within your data center. So it scales really well, but that's one level I've described. You know, you're creating groups of machines with names, so it's easier to define it, but there's auto and automation angle to this as well. You might not want to even create it interactively. Now a lot of customers with VMware vCenter, For example, are tagging the virtual machines. So the tag tells you a group information. Again, Fabric Composer can already get the tag within its database model. So we can use the tag now either to fully automate or use as a hint to creating these groups. So now I've got a really simple way to basically just categorize my machines into the groups so that now I can push rules down onto them. And there's one, one final thing that I just want to tell you before, before we move on. There's, there's often a zero trust model you want to do in the data center for segmentation. Meaning I've got two virtual machines on the same network on the same host. Normally they can talk to each other, nothing's stopping them, but sometimes you want to isolate even those two. You can do it in products like vCenter with PV land technologies. A bit cumbersome to configure on the vSphere side, you got to match it with what you see on the switch side. It's one of those that's a real headache, unless you've got an orchestrator to do it. So Fabric Composer could basically orchestrate this isolated solution. You're now grouping your machines and you're saying they're isolated. We can do the smarts and both of the vCenter side and the switch side, get them in sync, get it all configured. And now the masses can start to do this kind of segmentation at scale. >> Got it. Thank you Simon. Can the Fabric Composer kind of be used as the primary prism for troubleshooting? How do you handle troubleshooting and this art combined architecture? Who, who do I call when there's a problem? How do you approach that? >> Well, definitely start by calling me or actually call my product first, so fabric Composer. If you're using it, use that as the front tool for what you're going to try and figure out what's going on. There is a global health dashboard. It encompasses networking security policy across the solution, across the fabric. So that's your, tells you what's going on immediately. Down to port stats on what's happening within the physical topology of the network. Down to the end-to-end view, we have in terms of policy connectivity between machines. So Fabric Composer is your first port of call, but we built a solution here that we don't want to hide the pieces underneath it. Any networking guy knows when they're deep troubleshooting networking stuff, they're going to end up with the switch. So you started the orchestrator, but sometimes in the deep troubleshooting, not day-to-day, hopefully. You'll go to the switch and you'll troubleshoot that way. We've got the same technology here with the policy, with the firewall rules, with Pensando PSM. We still fully embrace for deep troubleshooting, go to Pensando PSM. They have really advanced tools in their bag of tricks in the product to give you advanced troubleshooting down to the policy layer. They have a really powerful firewall log capability, where you can search and sort, and see exactly what role is allowing or stopping any traffic going through the environment. And the two orchestrated model, we really like it 'cause it scales really well. It allows Fabric Composer to remain lightweight, PSM focused on the policy orchestration bit. But again, if your that customer that wants to do single pane of glass use Fabric Composer for the standard day-to-day stuff. But you've got the tools there to do the advanced troubleshooting between the different elements that we have within the Pensando and the Aruba tools. >> Yeah, really well thought out. You got the simplification angle nailed, the integration automation we talked about that, the visualization and the topology map, zero trust. And then remediation with deep^ened inspection. Simon, thanks so much for taking us through the announcements. Really appreciate your insights and time today. >> Thank you very much. >> You're welcome. Okay. Keep it right there, this is Dave Vellante for theCube. More content from the HPE Aruba Pensando announcements coming right up. (soothing music)

Published Date : Oct 20 2021

SUMMARY :

coverage of the power of N for having me today. about the Aruba switching fabric lot of the plexity there I'm going to to call it. embedded into the 10K. What about the sort and the policy you could and the netOps view together is important So the tag tells you a group information. as the primary prism for troubleshooting? that as the front tool You got the simplification angle nailed, More content from the HPE

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Simon McCormack, Aruba


 

(upbeat music) >> Welcome back to the cubes coverage of the power of N and the collaborations between HPE Aruba and Pensando. Where the two companies are setting out to create a new category in network switching. Joining me now is Simon McCormack, who looks after product management at HPE Aruba. Welcome Simon. Good to see you. >> Good morning. Thanks for having me today. >> You're very welcome. So Simon, we've been talking all day about the Aruba switching fabric that you're bringing to market embedding the Pensando technology. Can you tell us what's the primary value prop that AFC brings to its customers? >> Sure. Aruba fabric composer. This is orchestration and management for the Aruba wide switching platform, primarily for data centers. It does a lot of things. I'll give you three key ones just to get a feel for it. So in data center, networking, there's a lot of complex technologies. I'm afraid to say, lease spines, overlays, underlays, EDPs, OSPs PGP. I can throw out loads of acronyms for you. Fabric composer can really simplify through a bunch of intent based workflows, the deployment and management of these fabrics. We can do it either interactively through a UI or fully API driven if you want to. So it really takes away a lot of the complexity there makes it dead easy to deploy these and that scale. Number two, in a data center, a lot of compute storage hypervisor technologies that you have to interact with with your network products. So in fabric composer, we built an integration layer into it, that interacts with other orchestrators. V-Center, VMware Vcenter is a good example of that. So an operator may make changes to V-Center that affect the network. You don't want to call the network team for it. Fabric composer can automate that network side configuration on the Aruba switch, making your day to operations, insertion of new services, much more simpler. And then finally, number three, because we've got all these capabilities I've just told you about. We actually have a great typology model that we build from it. And we can use that to visualize this virtual to physical network layer that is really powerful for troubleshooting the environment. >> Great, so three things actually for right simplify, you integrate and automate, and it's kind of two and two way I'm going to call it and then the visualization piece for troubleshooting. Awesome. What about security policy? How are you thinking about that in this release? >> Yeah, so that's where in this release, we're extending it with the Persando PSM technologies embedded into the 10 K. Now we can use Aruba fabric composer to actually orchestrate the policy in addition to the network. So you think about today, fabric poser does network primarily you bring policy into it, you've got one single pane of glass now that doesn't network in policy, it actually provides a really powerful capabilities for operators of different skill sets to be able to manage and orchestrate this environment. >> What about the sort of operational model as it pertains to the network and security, I'm interested in how flexible that is. Like for instance, if a customer wants to use their own tooling or operational frameworks or frameworks so what if they want to leverage multi-vendor fabrics like a third-party spine? How do you deal with all of that? >> Yeah, and I think that's, we built that into essentially the DNA of this technology is that where we're expecting to often go into brownfield environments where they've already got best practices for security and networking. They've already got networking vendors there. The 10 K the very powerful lease switch on its own. We want those lease switches to go in all of these different environments, not just Greenfield. It's really great for Greenfield. And I'm going to explain this a little bit in a few ways. First of all, the technology we have with Aruba fabric composer and Pensando PSM, you can do a pure operational split between them. SecOps, NetOps a lot of customers that's how they deal with it. They've got the security operations team network operations team. If they're split, you can use the two tools and make a fantastic product using that. However, they're not split and you've got a single policy for it. You can use Aruba fabric composer to do both of them. So you've got the options there and we fully embrace that in the architecture of what we built. This extends to multiple layers for the technology build as well. Again, as I said, the 10 K's at Leafs, which it can connect to third-party spines. So you could use fabric composer to manage this lead switch and the policy you could use fabric composer just to manage the lease switch and connect and inter-operate the Leaf's to a spine, or you can do a full Aruba solution, the full Rube Leaf spine and use that operating model. There's one final thing in this area is fabri Composers are a UI based orchestrator, API driven. Some customers love it. Some customers that love their CLIs, we fully embrace the operational model where customers still use their own API APIs and their own CLIs. So the customer may be using Ansible to automate through API. They can still use that directly to the switch and they can use it to AFC and mix the two. If you talk directly to a switch and change it, fabric composer detects it and basically sinks its configuration together. So we can insert all or any part of this solution into existing or new Networks. >> Yeah, that's nice. Right? Because I mean, so there's the network hard guys, they want that CLI access, so you you're accommodating that. And then as well, being able to bring those SecOps view and the NetOps view together is important because let's face it. A lot of organizations, especially some of the smaller ones, they don't actually have a full blown SecOps team, that's really the NetOps responsibility. And so that's nice flexibility. You can handle both worlds. How about segmentation? When a customer is telling you that they want regarding segmentation and how are you guys approaching that? >> Yeah, I mean, it's actually a key feature of what we're doing in this area. Now the land segmentation generates it's kind of a wide area with many layers to it and we could talk about it for hours. So let me talk briefly about some of the areas we're going into when it comes to the segmentation, particularly the compute-virtual type environment. So when you, you're typically creating policies in today's world, current policies based on addresses, IP addresses, or Mac addresses. You have lots of rules and big lists of addresses. It's really annoying. Customers generally don't talk in addresses. They talk in machines and names of machines. So if you think about what I've already told you with a fabric composer. We've already got these hooks in the compute hypervisor layer. So what do we know about the virtual machines? So it's undoubtedly a natural extension now for you to be able to create these policies based on the machines. So there's a scale problem in policy distribution, at two levels, at the top and the bottom. The top level is your chronic create the policy. You've got this massive distribution addresses. So fabric composer can really help you by allowing you to then create these groups, sensible groups, using the names. Then you can distribute the 10 K solution with the distributed architecture of the bottom layer, now allows us to distribute these policies and rules across your racks within your data center. So it scales really well, but that's one level I've described. You know, you're creating groups of machines with names, so it's easier to define it, but there's also an automation angle to this as well. You might not want to even create it interactively. A lot of customers with VMware Vcenter for example, are tagging the virtual machines. So the tag tells you a group information. Again, fabric composer can already get the tag within its database model. So we can use the tag now either to fully automate or use as a hint to creating these groups. So now I've got a really simple way to basically just categorize my machines into the groups so that now I can push rules down onto the, and there's one, final thing that I just want to tell you before we move on, There's often a zero trust model you want to do in the data center for segmentation, meaning I've got two virtual machines on the same network on the same host. Normally they can talk to each other, nothing's stopping them, but sometimes you want to isolate even those two. You can do it in products like V-Center with PV land technologies. A bit cumbersome to configure on the VSphere side, you've got to match it with what you see on the switch side. It's one of those, that's a real headache, unless you've got an orchestrator to do it. So fabric composer could basically orchestrate this isolated solution. You're now grouping the machines and you're saying they're isolated. We can do the smarts and both of the center side and the switch side, get them in sync, get it all configured. And now the masses can start to do this kind of segmentation at scale. >> Got it. Thank you Simon. Can the fabric composer kind of be used as the primary prism for troubleshooting? How do you handle troubleshooting and this art combined architecture? Who, who do I call when there's a problem? How do you approach that? >> Well, definitely start by calling me or actually call my product first, so fabric composer. If you're using it, use that as the front tool for what you're going to try and figure out what's going on. There is a global health dashboard. It encompasses networking security policy across the solution, across the fabric. So that's your tells you what's going on immediately, down to port stats on what's happening within the physical topology of the network down to the end to end view, we have in terms of policy connectivity between machines. So fabric composer is your first port of call, but we built a solution here that we don't want to hide the pieces underneath it. Any networking guy knows when they're deep troubleshooting networking stuff, they're going to end up at the switch. So you started the orchestrator, but sometimes in the deep troubleshooting, not day-to-day hopefully, you'll go to the switch and you'll troubleshoot that way. We've got the same technology here with the policy, with the firewall rules, with Pensando PSM, we still fully embrace. For deep troubleshooting, go to Pensando PSM. They have really advanced tools in their bag of tricks in the product to give you advanced troubleshooting down to the policy layer that they have a really powerful firewall log capability, where you can search and sort and see exactly what role is allowing or stopping any traffic going through the environment. And the two orchestrated model, we really like it because it scales really well. It allows fabric composer to remain lightweight, PSM focused on the policy orchestration bit. But again, if you're the customer that wants to do single pane of glass, use fabric composer for the standard day-to-day stuff. But you've got the tools there to do the advanced troubleshooting between the different elements that we have within the Pensando and the Aruber tools. >> Yeah, really well thought out, you get the simplification angle nailed, the integration automation we talked about that, the visualization and a topology map, zero trust, and then remediation with deepened spend inspection. Simon, thanks so much for taking us through the announcements, really appreciate your insights and time today. >> Thank you very much. >> You're welcome. Okay. Keep it right there. This is Dave Vellante for theCUBE. More content from the HPE Aruba Pensando announcements, coming right up. (soft music)

Published Date : Oct 14 2021

SUMMARY :

coverage of the power of N and for having me today. about the Aruba switching fabric So it really takes away a lot of the How are you thinking about embedded into the 10 K. What about the sort of and the policy you could use that's really the NetOps responsibility. So the tag tells you a group information. Can the fabric composer kind the product to give you advanced the visualization and a More content from the HPE

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Patrick Moorhead, Moor Insights | HPE Discover 2021


 

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we finally, it feels like the on prem guys are finally getting their cloud act together. Um it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean the public cloud has been around for about 10 years and still only 20% around 20% of the data in 20% of the applications are there now will be a very important ones and I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud. And I feel like when amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have a classic on, on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's, it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very, a quick way. And uh you know what they've learned, The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. Uh it just depends on what do you want to lock yourself into, but super exciting and what H. P. E. You know, when they further acts in the sea with Green Lake, I think it was four years ago, uh I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine as I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but so, but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but, but I look at it differently, I wonder what your take is. I, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here we're gonna spend $100 billion like the internet. Here you go build. And so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a Polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point. And that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp as you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody's sort of following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see. First off some of their, Um, announcements on, on how it's going and they talked about $428 billion 1200 customers over 900 partners and 95% retention. And I think that's important. Anybody who's in the lead and remember what aws I used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it is A. S. A. P. Hana. Ml apps HPC with Francis, VD. I was Citrus and video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic, with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that Western european carriers use and they're now extending that to five G. And um, so more horizontal, uh, and, and more vertical. That was the one of the big swipes, uh, that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay. Okay. So, so the other piece of that of course is standardization right there there because there was a, there was a, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse. Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way, is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say, the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say the White House customers that HP Yeah, >>Well done. So, you know, and I hear your point about we're 10 years in plus. And to me this is like a mandate. I mean, this is okay, good, good job guys about time. But if I had a, you know, sort of look at the big player, it's like we have an oligopoly here in this, in this business. It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in antony's like, okay, here's what we're going to announce that, you know, a while ago. So, and they seem to have done a good job with Wall Street and they got a simple model, you know, Dell is obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together. So they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale, codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP ES sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these players here, So Cisco, ironically has sells the most software of any of those players that you mentioned, uh with the exception of IBM um and yeah, C I >>CSDB two. Yeah, >>yeah, they're the they're the number two security player, uh Microsoft, number one, So and I think the evaluation on the street uh indicate that shows that I feel like Dell tech is a very broad play because not only do they have servers, storage, networking insecurity, but they also have Pcs and devices. So it's a it's a scale and end play with a focus on VM ware solutions, not exclusively of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table. I think with h P e, what you're bringing the table is nimble. When HP and HP split, the number one thing that I said was that ah, h P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster. And that is what I've seen as it relates to the moat, which is a unique uh competitive advantage. Quite frankly, I'm still looking for that day uh in in in what that is. And I think in this industry it's nearly impossible. And I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that as your can't if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E. When it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development. I think that is a landing place where H P. E already does pretty well can come in and expand its footprint. >>You know, that's really interesting um, observations. So, and I would agree with you. It's kind of like, this is a copycat industry. It's like the west coast offense like the NFL, >>so, >>so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer because all of a sudden you saw companies like them, you always had a long term relationship with H P E, but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really is a execution, isn't it? But go ahead please. >>Dave if I had to pick something that I think HP HPV needs to always be ahead in as a service and listen you and I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're going to have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right? Because it, it I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like Anna Quinn X play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's like you said, outpost was the sort of signal. Okay, We're coming on prem. Clearly the on prem uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere and that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding, dominating in the edge with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do >>you say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge, whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong in Mcdonald's, there's nobody there that can help uh they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road And it has a 5GV 2 x communication cameras can't see around corners. But that car communicating ahead, that ran into the stop sign can, through Vita X talked to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky, let's make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built complete architecture is to do that, putting compute into five G base stations, heck, I just, there was an announcement this week of google cloud and its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kinda whose stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we could take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba, it's fantastic and they also managed it in the right way. I mean it was part of HB but it was, it was managed a lot more loosely then, you know, a company that might get sucked into the board and I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies, but it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security, uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloaded video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion. >>Well, I have you we have a ton of time here, but I I don't pick your brain about intel the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war, you got there battling a. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean he had a great run there and I think it is a very positive move. I've never seen the energy at Intel. Probably in the last 10 years that I've seen today. I actually got a chance to talk with Pat. I visited Pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they built out there networking business, they build out a storage business um with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at A. M. B. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles they integrate into the larger chips called S. O. C. S. B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arm Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the Arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on on the planet. So here we have A and D. Who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S and then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition date. Competition is great. You know, when there's not competition in Cpus and Gpus, we know what happens, right. Uh, the B just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to, and then, oh, by the way, the custom Chip providers, WS has created no less than 15 custom semiconductors started with networking uh, and, and nitro and building out an edge that surrounded the general compute and then it moved to Inferential to for inference trainee um, is about to come out for training Graviton and gravitas to for general purpose CPU and then you've got Apple. So innovation is huge and you know, I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors, software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You've got to 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the qualcomm NXP deal. You just don't know what china is going to do. I think the Eu with some conditions is gonna let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see, wants to see this happen. Japan and Korea. I think we'll allow this china is the odd man out. >>In a word, the future of H. P. E. Is blank >>as a service >>patrick Moorehead. Always a pleasure my friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back. >>Mm.

Published Date : Jun 23 2021

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Patrick Moorehead is here of moor insights and strategy is the It's great to see you and it's great to see you in the meetings that were in. So you know, let's get into it. And then there's this edges like jump ball, what are you seeing in the marketplace? the conversation was over right now, what you have is cloud native folks building out hybrid I like to determine as I think you should use the term veteran. the cloud to be as big as it's become over the last 10 years. let's talk about the horses on the track. And I think that that says a lot uh that H P E. Is making with what they call Lighthouse. I think a simplification to Green Lake that it needs to truly So, and they seem to have done a good job with Wall Street and any of those players that you mentioned, uh with the exception of IBM Yeah, And I would posit that that any, even the cloud folks, if you say, It's like the west coast offense like the NFL, so the moat comes from, you know, brand execution and your other And Dave, you have the public, you have the public cloud, arm is exploding, dominating in the edge with center in the sky, let's make that happen, that is to be in near real time And and that, do you see that as a competitive And then when you integrate compute Well, I have you we have a ton of time here, but I I don't pick your brain about And I did, I do feel like the industry on CPU started to stagnate You've got to 2 to 13 to 1 10 to 1. I think the U. S. Is absolutely going to let Thanks so much for coming back in the cube. I appreciate that. The leader and enterprise tech coverage.

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Patrick Moorhead, Moor Insights | HPE Discover 2021


 

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So, you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we we finally, it feels like the on prem guys are finally getting their cloud act together. Um, it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean, the public cloud has been around for about 10 years and still only 20%. Around 20% of the data in 20% of the applications are there now, albeit very important ones. And I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud and I feel like when Amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have the classic on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very quick way. And uh, you know what they've learned. The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. It just depends on what do you want to lock yourself into, but super exciting. And what H. P. E. When they threw the acts in the sea with Green Lake, I think it was four years ago, I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine is I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but but but so but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but I look at it differently. I wonder what you're taking. I think, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here, we're going to spend $100 billion like the internet here you go build. And and so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point and that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp. As you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody started following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see, first off some of their, Um, announcements on, on how it's going. And they talked about 4, $28 billion 1200 customers over 900 partners and 95% retention. And I think that's important anybody who's in the lead and remember what Aws used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it was S. A. P. Hana Ml apps HPC with Francis V. I was Citrus in video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that western european carriers use and they're now extending that to five G. And um, so more horizontal uh and and more vertical. That was the one of the big swipes uh that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay, Okay. So, so the other piece of that of course is standardization right there there because there was a, there was, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse, Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh, is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say, the white house customers at HP. Yeah, >>Well done. So, you know, and I hear your point about 10 years in, you know, plus and to me this is like a mandate. I mean, this is okay. Good, good job guys about time. But if I had a, you know, sort of look at the big players, like, can we have an oligopoly here in this, in this business? It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in Antonio's like, okay, here's what we're going to announce that, you know, while ago, so, and they seem to have done a good job with Wall Street and they get a simple model, you know, Dell's obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together, so they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP? Es sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these these players here. So Cisco, ironically, has sells the most software of any of those players that you mentioned, uh with the exception of IBM. Um, and yeah, C >>ICSDB two. Yeah, >>yeah, they're the they're the number two security player, uh, Microsoft, number one. So and I think the evaluation on the street uh indicate that shows that I feel like uh Deltek is a is a very broad play because not only do they have servers, storage, networking and security, but they also have Pcs and devices, so it's a it's a scale and end play with a focus on VM ware solutions, not exclusively, of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table, I think with h P E, what your bring to the table is nimble. When HP and HP split, the number one thing that I said was that uh huh H P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um, and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster and that is what I've seen as it relates to the moat, which is a unique uh, competitive advantage. Quite frankly, I'm still looking for that day in, in, in what that is and I think in this industry it's nearly impossible and I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that Azure can't, if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E, when it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development, I think that is a landing place where H P E already does pretty well can come in and expand its footprint, >>you know, that's really interesting um, observations. So, and I would agree with you, it's kind of like, this is a copycat industry, it's like the west coast offense, like the NFL >>and >>so, so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer, because all of a sudden you saw companies like them, you always had a long term relationship with H P E but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really >>is an execution, >>isn't it? But go ahead, please >>Dave if I had to pick something that I think HP HPV needs to always be ahead and as a service and listen, you know, I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're gonna have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right, Because it, it, I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like ANna Quinn x play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's as you said, outpost was the sort of signal. Okay, We're coming on prem clearly the on prem, uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere. And that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding is dominating in the edge with with with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do you >>say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge. Whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, Physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong and Mcdonald's, there's nobody there that can help uh, they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road and it has a five G V two X communication cameras can't see around corners, but that car communicating ahead, that ran into the stop sign, can I through vi to X. Talk to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky to make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built Complete architectures to do that, putting compute into 5G base stations. Heck, I just, there was an announcement this week of google cloud in its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kind of who's stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we can take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba it's fantastic. And they also managed it in the right way. I mean, it was part of HB but it was it was managed a lot more loosely then, you know, a company that might get sucked into the board. And I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies. But it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, um a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloading video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion >>while I have you, we have a ton of time here, but I I don't pick your brain about intel, the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war. You got there, battling A. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean, he had a great run there and I think it is a very positive move. I've never seen the energy At Intel probably in the last 10 years that I've seen today. I actually got a chance to talk with pat. I visited pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they've built out there networking business, they build out a storage business um with with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at AMG. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles, they integrate into the larger chips called S. O. C S B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arms Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on the planet. So here we have AMG who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S. And then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition. Date. Competition is great. You know, when there's not competition in CPUs and Gpus, we know what happens right. Uh, the beach just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to and then, oh, by the way, you have the custom Chip providers. WS has created no less than 15 custom semiconductors started with networking and nitro and building out an edge that surrounded the general computer. And then it moved to Inferential for inference trainee um, is about to come out for training Graviton and Gravitas to for general purpose CPU and then you've got apple. So innovation is huge and I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You got a 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the Qualcomm NXp deal. You just don't know what china is going to do. I think the EU with some conditions is going to let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see wants to see this happen, Japan and Korea I think we'll allow this china is the odd man out. >>In a word, the future of h p. E is blank >>as a service >>patrick Moorehead. Always a pleasure. My friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back.

Published Date : Jun 10 2021

SUMMARY :

Patrick Moorehead is here of moor insights and strategy is the It's great to see you and it's great to see you in the meetings that were in. I think it's resonating with customers. And then there's this edges like jump ball, what are you seeing in the marketplace? the conversation was over right now, what you have is cloud native folks building out hybrid I like to determine is I think you should use the term veteran. the cloud to be as big as it's become over the last 10 years. let's talk about the horses on the track. I like the retention part that H P E. Is making with what they call Lighthouse, Right? the type of the storage and the amount of the storage you get. and they seem to have done a good job with Wall Street and they get a simple model, you know, So Cisco, ironically, has sells the most software Yeah, posit that that any, even the cloud folks, if you say, you know, that's really interesting um, observations. so, so the moat comes from, you know, brand execution and the lead and as a service holistically doesn't mean they're going to be there forever, is dominating in the edge with with with apple and amazon Alexa center in the sky to make that happen, that is to be in near real time And and that, do you see that as a competitive And then when you integrate compute intel, the future of intel. And I did, I do feel like the industry on CPU started to stagnate You got a 2 to 13 to 1 10 to 1. I think the U. S. Is absolutely going to let Thanks so much for coming back in the cube. I appreciate that. The leader and enterprise tech coverage.

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Simon Maple, Snyk | DockerCon 2021


 

>>mhm Yes. >>Hello and welcome back to the cubes coverage of dr khan 2021 virtual. I'm john Kerry hosted the Q got a great cube segment here. Simon Maple Field C T Oh it's technique. Great company security shifting left great to have you on Simon. Thanks for thanks for stopping by >>absolute pleasure. Thank you very much for having me. >>So you guys were on last year the big partnership with DR Conn remember that interview vividly because it was really the beginning at the beginning but really come to me the mainstream of shifting left as devops. It's not been it's been around for a while. But as a matter of practice as containers have been going super mainstream. Super ballistic in the developer community then you're seeing what's happening. It's containers everywhere. Security Now dev sec apps is the standard. So devops great infrastructure as code. We all know that but now it's def sec ops is standard. This is the real deal. Give us the update on what's going on with sneak. >>Absolutely, yeah. And you know, we're still tireless in our approach of trying to get make sure developers don't just have the visibility of security but are very much empowered in terms of actually fixing issues and secure development is what we're really striving for. So yeah, the update, we're still very, very deep into a partnership with DACA. We have updates on DR desktop which allows developers to scan the containers on the command line, providing developers that really fast feedback as as early as possible. We also have uh, you know, new updates and support for running Docker scan on Lennox. Um, and yeah, you know, we're still there on the Docker hub and providing that security insights um, to, to users who are going to Docker hub to grab their images. >>Well, for the folks watching maybe for the first time, the sneak Docker partnership, we went in great detail last year was the big reveal why Docker and sneak partnership, what is the evolution of that partnership over the year? They speak highly of you guys as a developer partner. Why Doctor? What's the evolution looked like? >>It's a it's a really great question. And I think, you know, when you look at the combination of DACA and sneak well actually let's take let's take each as an individual. Both companies are very, very developer focused. First of all, right, so our goals and will be strife or what we what we tirelessly spend their time doing is creating features and creating, creating an environment in which a developer you can do what they need to do as easily as possible. And that, you know, everyone says they want to be developer friendly, They want to be developer focused. But very few companies can achieve. And you look at a company like doctor, you're a company like sneak it really, really provides that developer with the developer experience that they need to actually get things done. Um, and it's not just about being in a place that a developer exists. It's not enough to do that. You need to provide a developer with that experience. So what we wanted to do was when we saw doctor and extremely developer friendly environment and a developer friendly company, when we saw the opportunity there to partner with Yoko, we wanted to provide our security developer friendliness and developer experience into an already developed a friendly tool. So what the partnership provides is the ease of, you know, deploying code in a container combined with the ease of testing your code for security issues and fixing security issues in your code and your container and pulling it together in one place. Now, one of the things which we as a as a security company um pride ourselves on is actually not necessarily saying we provide security tools. One of what our favorite way of saying is we're a developer tooling company. So we provide tools that are four developers now in doing that. It's important you go to where the developers are and developers on DACA are obviously in places like the Docker hub or the Docker Cli. And so it's important for us to embed that behavior and that ease of use inside Dhaka for us to have that uh that that flow. So the developer doesn't need to leave the Docker Cli developer that doesn't need to leave Docker hub in order to see that data. If you want to go deeper, then there are probably easier ways to find that data perhaps with sneak or on the sneak site or something like that. But the core is to get that insight to get that visibility and to get that remediation, you can see that directly in in the in the Dhaka environment. And so that's what makes the relationship so so powerful. The fact that you combine everything together and you do it at source >>and doing it at the point of code. >>Writing >>code is one of the big things I've always liked about the value proposition is simple shift left. Um So let's just step back for a second. I got to ask you this question because this I wanted to make sure we get this on the table. What are the main challenges uh and needs to, developers have with container security? What are you seeing as the main top uh A few things that they need to have right now for the challenges uh with container security? >>Yeah, it's a it's a very good question. And I think to answer that, I think we need to um we need to think of it in a couple of ways. First of all, you've just got developers security uh in general, across containers. Um And the that in itself is there are different levels at which developers engage with containers. Um In some organizations, you have security teams that are very stringent in terms of what developers can and can't do in other organizations. It's very much the developer that that chooses their environment, chooses their parent image, et cetera. And so there when a developer has many, many choices in which they need to need to decide on, some of those choices will lead to more issues, more risk. And when we look at a cloud native environment, um uh Let's take let's take a node uh image as an example, the number of different uh images tags you can choose from as a developer. It's you know, there are hundreds, probably thousands. That you can actually you can actually choose. What is the developer gonna do? Well, are they going to just copy paste from another doctor file, for example, most likely. What if there are issues in that docker file? They're just gonna copy paste that across mis configurations that exist. Not because the developer is making the wrong decision, but because the developer very often doesn't necessarily know that they need to add a specific directive in. Uh So it's not necessarily what you add in a conflict file, but it's very often what you admit. So there are a couple of things I would say from a developer point of view that are important when we think about cloud security, the first one is just that knowledge that understanding what they need to do, why they need to do it. Secure development doesn't need to be, doesn't mean they need to be deep in security. It means they need to understand how they can develop securely and what what the best decisions that could come from guard rails, from the security team that they provide the development team to offer. But that's the that's an important error of secure development. The second thing and I think one of the most important things is understanding or not understanding necessarily, but having the information to get an act on those things early. So we know the length of time that developers are uh working on a branch or working on um some some code changes that is reducing more and more and more so that we can push to production very, very quickly. Um What we need to do is make sure that as a developer is making their changes, they can make the right decision at the right time and they have the right information at that time. And a lot of this could be getting information from tools, could be getting information from your team where it could be getting information from your production environments and having that information early is extremely important to make. That decision. May be in isolation with your team in an autonomous way or with advice from the security team. But I would say those are the two things having that information that will allow you to make that action, that positive change. Um uh and and yeah, understanding and having that knowledge about how you can develop security. >>All right. So I have a security thing. So I'm a development team and by the way, this whole team's thing is a huge deal. I think we'll get to that. I want to come back to that in a second but just throw this out there. Got containers, got some security, it's out there and you got kubernetes clusters where containers are coming and going. Sometimes containers could have malware in them. Um and and this is, I've heard this out and about how do how that happens off container or off process? How do you know about it? Is that infected by someone else? I mean is it gonna be protected? How does the development team once it's released into the wild, so to speak. Not to be like that, but you get the idea, it's like, okay, I'm concerned off process this containers flying around. What is it How do you track all >>and you know, there's a there's a few things here that are kind of like potential potential areas that, you know, we can trip up when we think about malware that's running um there are certain things that we need to that we need to consider and what we're really looking at here are kind of, what do we have in place in the runtime that can kind of detect these issues are happening? How do we block that? And how do you provide that information back to the developer? The area that I think is, and that is very, very important in order to in order to be able to identify monitor that those environments and then feed that back. So that that that's the kind of thing that can be that can be fixed. Another aspect is, is the static issues and the static issues whether that's in your os in your OS packages, for example, that could be key binaries that exist in your in your in your docker container out the box as well or of course in your application, these are again, areas that are extremely important to detect and they can be detected very very early. So some things, you know, if it's malware in a package that has been identified as malware then absolutely. That can be that can be tracked very very early. Sometimes these things need to be detected a little bit later as well. But yeah, different tools for different for different environments and wear sneak is really focused. Is this static analysis as early as possible. >>Great, great insight there. Thanks for sharing that certainly. Certainly important. And you know, some companies classes are locked down and all of sudden incomes, you know, some some malware from a container, people worried about that. So I want to bring that up. Uh The other thing I want to ask you is this idea of end to end security um and this is a team formation thing we're seeing where modern teams have essentially visibility of their workload and to end. So this is a huge topic. And then by the way it might integrate their their app might integrate with other processes to that's great for containers as well and observe ability and microservices. So this is the trend. What's in it for the developer? If I work with sneak and docker, what benefits do I get if I want to go down that road of having these teams began to end, but I want the security built in. >>Mhm. Yeah, really, really important. And I think what's what's most important there is if we don't look end to end, there are component views and there are applications. If we don't look into end, we could have our development team fixing things that realistically aren't in production anyway or aren't the key risks that are potentially hurting us in our production environment. So it's important to have that end to end of you so that we have the right insights and can prioritize what we need to identify and look at early. Um, so I think, I think that visibility into end is extremely important. If we think about who, who is re fixing uh certain issues, again, this is gonna depend from dog to walk, but what we're seeing more and more is this becoming a developer lead initiative to not just find or be given that information, but ultimately fixed. They're getting more and more responsible for DR files for for I see for for their application code as well. So one of the areas which we've looked into as well is identifying and actually running in cuba Netease workloads to identify where the most important areas that a developer needs to look at and this is all about prioritization. So, you know, if the developer has just a component view and they have 100 different images, 100 different kubernetes conflicts, you know, et cetera. Where do they prioritize, where do they spend their time? They shouldn't consider everything equal. So this identification of where the workloads are running and what um is causing you the most risk as a business and as an organization, that is the data. That can be directly fed back into your, your your vulnerability data and then you can prioritize based on the kubernetes workloads that are in your production and that can be fed directly into the results in the dashboards. That's neat. Can provide you as well. So that end to end story really provides the context you need in order to not just develop securely, but act and action issues in a proper way. >>That's a great point. Context matters here because making it easy to do the right thing as early as possible, the right time is totally an efficiency productivity gain, you see in that that's clearly what people want. It's a great formula, success, reduce the time it takes to do something, reduced the steps and make it easy. Right, come on, that's a that's a formula. Okay, so I gotta bring that to the next level. When I ask you specifically around automation, this is one the hot topic and def sec ops, automation is part of it. You got scale, you got speed, you've got a I machine learning, you go out of all these new things. Microservices, how do you guys fit into the automation story? >>It's a great question. And you know, one of the recent reports that we that we did based on a survey data this year called the state of a state of cloud, native applications security. We we asked the question how automated our people in their in their deployment pipelines and we found some really strong correlations between value from a security point of view um in terms of in terms of having that automation in it, if I can take you through a couple of them and then I'll address that question about how we can be automated in that. So what we found is a really strong correlation as you would expect with security testing in ci in your source code repositories and all the way through the deployment ci and source code were the two of the most most well tested areas across the pipeline. However the most automated teams were twice as likely to test in I. D. S. And testing your CLS in local development. And now those are areas that are really hard to automate if at all because it's developers running running their cli developers running and testing in their I. D. So the having a full automation and full uh proper testing throughout the sclc actually encourages and and makes developers test more in their development environment. I'm not saying there's causation there but there's definite correlation. A couple of other things that this pushes is um Much much more likely to test daily or continuously being automated as you would expect because it's part of the bills as part of your monitoring. But crucially uh 73% of our respondents were able to fix a critical issue in less than a week as opposed to just over 30% of people that were not automated, so almost double people are More likely to fix within a week. 36% of people who are automated can fix a critical security issue in less than a day as opposed to 8% of people who aren't automated. So really strong data that correlates being automated with being able to react now. If you look at something like Sneak what if our um goals of obviously being developer friendly developer first and being able to integrate where developers are and throughout the pipeline we want to test everywhere and often. Okay, so we start as far left as we can um integrating into, you know, CLS integrating into Docker hub, integrating into into doctors can so at the command line you type in doctors can you get sneak embedded in DHAKA desktop to provide you those results so as early as possible, you get that data then all the way through to to uh get reposed providing that testing and automatically testing and importing results from there as well as as well as other repositories, container repositories, being at a poor from there and test then going into ci being able to run container tests in C I to make sure we're not regressing and to choose what we want to do their whether we break, whether we continue with with raising an issue or something like that, and then continuing beyond that into production. So we can monitor tests and automatically send pull requests, etcetera. As and when new issues or new fixes occur. So it's about integrating at every single stage, but providing some kind of action. So, for example, in our ui we provide the ability to say this is the base level you should be or could be at, it will reduce your number of vulnerabilities by X and as a result you're going to be that much more secure that action ability across the pipeline. >>That's a great, great data dump, that's a masterclass right there on automation. Thanks for sharing that sign. I appreciate it. I gotta ask you the next question that comes to my mind because I think this is kind of the dots connect for the customer is okay. I love this kind of hyper focus on containers and security. You guys are all over it, shift left as far as possible, be there all the time, test, test, test all through the life cycle of the code. Well, the one thing that is popping up as a huge growth areas, obviously hybrid cloud devops across both environments and the edge, whether it's five G industrial or intelligent edge, you're gonna have kubernetes clusters at the edge now. So you've got containers. The relationship to kubernetes and then ultimately cloud native work clothes at, say, the edge, which has data has containers. So there's a lot of stuff going on all over the place. What's your, what's your comment there for customer says, Hey, you know, I got, this is my architecture that's happening to me now. I'm building it out. We're comfortable with kubernetes put in containers everywhere, even on the edge how to sneak fit into that story. >>Yeah, really, really great question. And I think, you know, a lot of what we're doing right now is looking at a developer platform. So we care about, we care about everything that a developer can check in. Okay, so we care about get, we care about the repositories, we care about the artifact. So um, if you look at the expansion of our platform today, we've gone from code that people uh, third party libraries that people test. We added containers. We've also added infrastructure as code. So Cuban eighties conflicts, Terror form scripts and things like that. We're we're able to look at everything that the developer touches from their code with sneak code all the way through to your to your container. And I see, so I think, you know, as we see more and more of this pushing out into the edge, cuba Nitties conflict that that, you know, controls a lot of that. So much of this is now going to be or not going to be, but so much of the environment that we need to look at is in the configurations or the MIS configurations in that in those deployment scripts, um, these are some of the areas which which we care a lot about in terms of trying to identify those vulnerabilities, those miS configurations that exist within within those scripts. So I can see yeah more and more of this and there's a potential shift like that across to the edge. I think it's actually really exciting to be able to see, to be able to see those uh, those pushing across. I don't necessarily see any other, any, you know, different security threats or the threat landscape changing as a result of that. Um there could be differences in terms of configurations, in terms of miS configurations that that that could increase as a result, but, you know, a lot of this and it just needs to be dealt with in the appropriate way through tooling through, through education of of of of how that's done. >>Well, obviously threat vectors are all gonna look devops like there's no perimeter. So they're everywhere right? Looking at I think like a hacker to be being there. Great stuff. Quick question on the future relationship with DR. Obviously you're betting a lot here on that container relationship, a good place to start. A lot of benefits there. They have dependencies, they're going to have implications. People love them, they love to use them, helps old run with the new and helps the new run better. Certainly with kubernetes, everything gets better together. What's the future with the DACA relationship? Take us through how you see it. >>So yeah, I mean it's been an absolute blast the doctor and you know, even from looking at some of the internal internal chats, it's been it's been truly wonderful to see the, the way in which both the doctor and sneak from everything from an engineering point of view from a marketing, from a product team. It's been a pleasure to, it's been a pleasure to see that relationship grow and flourish. And, and I think there's two things, first of all, I think it's great that as companies, we, we both worked very, very well together. I think as as as users um seeing, you know, doctor and and and sneak work so so seamlessly and integrated a couple of things. I would love to see. Um, I think what we're gonna see more and more and this is one of the areas that I think, um you know, looking at the way sneak is going to be viewing security in general. We see a lot of components scanning a lot, a lot of people looking at a components can and seeing vulnerabilities in your components. Can I think what we need to, to to look more upon is consolidating a lot of the a lot of the data which we have in and around different scans. What I would love to see is perhaps, you know, if you're running something through doctors can how can you how can you view that data through through sneak perhaps how can we get that closer integration through the data that we that we see. So I would love to see a lot more of that occur, you know, within that relationship and these are kind of like, you know, we're getting to that at that stage where we see integration, it just various levels. So we have the integration where we have we are embedded but how can we make that better for say a sneak user who also comes to the sneak pages and wants to see that data through sneak. So I would love to see at that level uh more there where as I mentioned, we have we have some some additional support as well. So you can run doctors can from from Lenox as well. So I can see more and more of that support rolling out but but yeah, in terms of the future, that's where I would love to see us uh to grow more >>and I'll see in the landscape side on the industry side, um, security is going beyond the multiple control planes out there. Kubernetes surveillance service matches, etcetera, continues to be the horizontally scalable cloud world. I mean, and you got you mentioned the edge. So a lot more complexity to rein in and make easier. >>Yeah, I mean there's a lot more complexity, you know, from a security point of view, the technology is the ability to move quickly and react fast in production actually help security a lot because you know, being able to spin a container and make changes and and bring a container down. These things just weren't possible, you know, 10 years ago, 20 years ago. Pre that it's like it was it's insanely hard compared trying to trying to do that compared to just re spinning a container up. However, the issue I see from a security point of view, the concerns I see is more around a culture and an education point of view of we've got all this great tech and it's it's awesome but we need to do it correctly. So making sure that as you mentioned with making the right decision, what we want to make sure is that right decision is also the easy decision and the clear decision. So we just need to make sure that as we as we go down this journey and we're going down it fast and it's not gonna, I don't see it slowing down, we're going fast down that journey. How do we make, how do we prepare ourselves for that? We're already seeing, you know, miss configurations left, right and center in the news, I am roles as three buckets, etcetera. These are they're they're simpler fixes than we than we believe, right? We just need to identify them and and make those changes as needed. So we just need to make sure that that is in place as we go forward. But it's exciting times for sure. >>It's really exciting. And you got the scanning and right at the point of coding automation to help take that basic mis configuration, take that off the table. Not a lot of manual work, but ultimately get to that cloud scale cool stuff. >>Simon, thank you >>for coming on the cube dr khan coverage. Really appreciate your time. Drop some nice commentary there. Really appreciate it. Thank you. >>My pleasure. Thank you very much. >>Simon Maple Field C T. O. A sneak hot startup. Big partner with Docker Security, actually built in deVOPS, is now dead. Say cops. This is dr khan cube 2021 virtual coverage. I'm sean for your host. Thanks for watching. Mm.

Published Date : May 28 2021

SUMMARY :

Great company security shifting left great to have you on Simon. Thank you very much for having me. So you guys were on last year the big partnership with DR Conn remember that interview Um, and yeah, you know, we're still there on the Docker hub and providing that security They speak highly of you guys So the developer doesn't need to leave the Docker Cli developer that doesn't need to leave Docker hub in order I got to ask you this question because this I wanted to make sure we get this on the table. the number of different uh images tags you can choose from Not to be like that, but you get the idea, it's like, So some things, you know, if it's malware in a package that has been identified And you know, So it's important to have that end to end of you so that we success, reduce the time it takes to do something, reduced the steps and make it easy. doctors can so at the command line you type in doctors can you get sneak embedded in DHAKA desktop in containers everywhere, even on the edge how to sneak fit into that story. And I think, you know, a lot of what we're doing right now is looking at What's the future with the DACA relationship? So I would love to see a lot more of that occur, you know, So a lot more complexity to rein in and make easier. So making sure that as you mentioned with making the And you got the scanning and right at the point of coding automation to help take that for coming on the cube dr khan coverage. Thank you very much. actually built in deVOPS, is now dead.

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Breaking Analysis: Best of theCUBE on Cloud


 

>> Narrator: From theCUBE Studios in Palo Alto, in Boston bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> The next 10 years of cloud, they're going to differ dramatically from the past decade. The early days of cloud, deployed virtualization of standard off-the-shelf components, X86 microprocessors, disk drives et cetera, to then scale out and build a large distributed system. The coming decade is going to see a much more data-centric, real-time, intelligent, call it even hyper-decentralized cloud that will comprise on-prem, hybrid, cross-cloud and edge workloads with a services layer that will obstruct the underlying complexity of the infrastructure which will also comprise much more custom and varied components. This was a key takeaway of the guests from theCUBE on Cloud, an event hosted by SiliconANGLE on theCUBE. Welcome to this week's Wikibon CUBE Insights Powered by ETR. In this episode, we'll summarize the findings of our recent event and extract the signal from our great guests with a couple of series and comments and clips from the show. CUBE on Cloud is our very first virtual editorial event. It was designed to bring together our community in an open forum. We ran the day on our 365 software platform and had a great lineup of CEOs, CIOs, data practitioners technologists. We had cloud experts, analysts and many opinion leaders all brought together in a day long series of sessions that we developed in order to unpack the future of cloud computing in the coming decade. Let me briefly frame up the conversation and then turn it over to some of our guests. First, we put forth our view of how modern cloud has evolved and where it's headed. This graphic that we're showing here, talks about the progression of cloud innovation over time. A cloud like many innovations, it started as a novelty. When AWS announced S3 in March of 2006, nobody in the vendor or user communities really even in the trade press really paid too much attention to it. Then later that year, Amazon announced EC2 and people started to think about a new model of computing. But it was largely tire kickers, bleeding-edge developers that took notice and really leaned in. Now the financial crisis of 2007 to 2009, really created what we call a cloud awakening and it put cloud on the radar of many CFOs. Shadow IT emerged within departments that wanted to take IT in bite-sized chunks and along with the CFO wanted to take it as OPEX versus CAPEX. And then I teach transformation that really took hold. We came out of the financial crisis and we've been on an 11-year cloud boom. And it doesn't look like it's going to stop anytime soon, cloud has really disrupted the on-prem model as we've reported and completely transformed IT. Ironically, the pandemic hit at the beginning of this decade, and created a mandate to go digital. And so it accelerated the industry transformation that we're highlighting here, which probably would have taken several more years to mature but overnight the forced March to digital happened. And it looks like it's here to stay. Now the next wave, we think we'll be much more about business or industry transformation. We're seeing the first glimpses of that. Holger Mueller of Constellation Research summed it up at our event very well I thought, he basically said the cloud is the big winner of COVID. Of course we know that now normally we talk about seven-year economic cycles. He said he was talking about for planning and investment cycles. Now we operate in seven-day cycles. The examples he gave where do we open or close the store? How do we pivot to support remote workers without the burden of CAPEX? And we think that the things listed on this chart are going to be front and center in the coming years, data AI, a fully digitized and intelligence stack that will support next gen disruptions in autos, manufacturing, finance, farming and virtually every industry where the system will expand to the edge. And the underlying infrastructure across physical locations will be hidden. Many issues remain, not the least of which is latency which we talked about at the event in quite some detail. So let's talk about how the Big 3 cloud players are going to participate in this next era. Well, in short, the consensus from the event was that the rich get richer. Let's take a look at some data. This chart shows our most recent estimates of IaaS and PaaS spending for the Big 3. And we're going to update this after earning season but there's a couple of points stand out. First, we want to make the point that combined the Big 3 now account for almost $80 billion of infrastructure spend last year. That $80 billion, was not all incremental (laughs) No it's caused consolidation and disruption in the on-prem data center business and within IT shops companies like Dell, HPE, IBM, Oracle many others have felt the heat and have had to respond with hybrid and cross cloud strategies. Second while it's true that Azure and GCP they appear to be growing faster than AWS. We don't know really the exact numbers, of course because only AWS provides a clean view of IaaS and passwords, Microsoft and Google. They kind of hide them all ball on their numbers which by the way, I don't blame them but they do leave breadcrumbs and clues on growth rates. And we have other means of estimating through surveys and the like, but it's undeniable Azure is closing the revenue gap on AWS. The third is that I like the fact that Azure and Google are growing faster than AWS. AWS is the only company by our estimates to grow its business sequentially last quarter. And in and of itself, that's not really enough important. What is significant is that because AWS is so large now at 45 billion, even at their slower growth rates it grows much more in absolute terms than its competitors. So we think AWS is going to keep its lead for some time. We think Microsoft and AWS will continue to lead the pack. You know, they might converge maybe it will be a 200 just race in terms of who's first who's second in terms of cloud revenue and how it's counted depending on what they count in their numbers. And Google look with its balance sheet and global network. It's going to play the long game and virtually everyone else with the exception of perhaps Alibaba is going to be secondary players on these platforms. Now this next graphic underscores that reality and kind of lays out the competitive landscape. What we're showing here is survey data from ETR of more than 1400 CIOs and IT buyers and on the vertical axis is Net Score which measures spending momentum on the horizontal axis is so-called Market Share which is a measure of pervasiveness in the data set. The key points are AWS and Microsoft look at it. They stand alone so far ahead of the pack. I mean, they really literally, it would have to fall down to lose their lead high spending velocity and large share of the market or the hallmarks of these two companies. And we don't think that's going to change anytime soon. Now, Google, even though it's far behind they have the financial strength to continue to position themselves as an alternative to AWS. And of course, an analytics specialist. So it will continue to grow, but it will be challenged. We think to catch up to the leaders. Now take a look at the hybrid zone where the field is playing. These are companies that have a large on-prem presence and have been forced to initiate a coherent cloud strategy. And of course, including multicloud. And we include Google in this so pack because they're behind and they have to take a differentiated approach relative to AWS, and maybe cozy up to some of these traditional enterprise vendors to help Google get to the enterprise. And you can see from the on-prem crowd, VMware Cloud on AWS is stands out as having some, some momentum as does Red Hat OpenShift, which is it's cloudy, but it's really sort of an ingredient it's not really broad IaaS specifically but it's a component of cloud VMware cloud which includes VCF or VMware Cloud Foundation. And even Dell's cloud. We would expect HPE with its GreenLake strategy. Its financials is shoring up, should be picking up momentum in the future in terms of what the customers of this survey consider cloud. And then of course you could see IBM and Oracle you're in the game, but they don't have the spending momentum and they don't have the CAPEX chops to compete with the hyperscalers IBM's cloud revenue actually dropped 7% last quarter. So that highlights the challenges that that company facing Oracle's cloud business is growing in the single digits. It's kind of up and down, but again underscores these two companies are really about migrating their software install basis to their captive clouds and as well for IBM, for example it's launched a financial cloud as a way to differentiate and not take AWS head-on an infrastructure as a service. The bottom line is that other than the Big 3 in Alibaba the rest of the pack will be plugging into hybridizing and cross-clouding those platforms. And there are definitely opportunities there specifically related to creating that abstraction layer that we talked about earlier and hiding that underlying complexity and importantly creating incremental value good examples, snowfallLike what snowflake is doing with its data cloud, what the data protection guys are doing. A company like Loomio is headed in that direction as are others. So, you keep an eye on that and think about where the white space is and where the value can be across-clouds. That's where the opportunity is. So let's see, what is this all going to look like? How does the cube community think it's going to unfold? Let's hear from theCUBE Guests and theCUBE on Cloud speakers and some of those highlights. Now, unfortunately we don't have time to show you clips from every speaker. We are like 10-plus hours of video content but we've tried to pull together some comments that summarize the sentiment from the community. So I'm going to have John Furrier briefly explain what theCUBE on Cloud is all about and then let the guests speak for themselves. After John, Pradeep Sindhu is going to give a nice technical overview of how the cloud was built out and what's changing in the future. I'll give you a hint it has to do with data. And then speaking of data, Mai-Lan Bukovec, who heads up AWS is storage portfolio. She'll explain how she views the coming changes in cloud and how they look at storage. Again, no surprise, it's all about data. Now, one of the themes that you'll hear from guests is the notion of a distributed cloud model. And Zhamak Deghani, he was a data architect. She'll explain her view of the future of data architectures. We also have thoughts from analysts like Zeus Karavalla and Maribel Lopez, and some comments from both Microsoft and Google to compliment AWS's view of the world. In fact, we asked JG Chirapurath from Microsoft to comment on the common narrative that Microsoft products are not best-to-breed. They put out a one dot O and then they get better, or sometimes people say, well, they're just good enough. So we'll see what his response is to that. And Paul Gillin asks, Amit Zavery of Google his thoughts on the cloud leaderboard and how Google thinks about their third-place position. Dheeraj Pandey gives his perspective on how technology has progressed and been miniaturized over time. And what's coming in the future. And then Simon Crosby gives us a framework to think about the edge as the most logical opportunity to process data not necessarily a physical place. And this was echoed by John Roese, and Chris Wolf to experience CTOs who went into some great depth on this topic. Unfortunately, I don't have the clips of those two but their comments can be found on the CTO power panel the technical edge it's called that's the segment at theCUBE on Cloud events site which we'll share the URL later. Now, the highlight reel ends with CEO Joni Klippert she talks about the changes in securing the cloud from a developer angle. And finally, we wrap up with a CIO perspective, Dan Sheehan. He provides some practical advice on building on his experience as a CIO, COO and CTO specifically how do you as a business technology leader deal with the rapid pace of change and still be able to drive business results? Okay, so let's now hear from the community please run the highlights. >> Well, I think one of the things we talked about COVID is the personal impact to me but other people as well one of the things that people are craving right now is information, factual information, truth, textures that we call it. But here this event for us Dave is our first inaugural editorial event. Rob, both Kristen Nicole the entire cube team, SiliconANGLE on theCUBE we're really trying to put together more of a cadence. We're going to do more of these events where we can put out and feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires of people making things happen, but it's often the people under them that are the real Newsmakers. >> If you look at the architecture of cloud data centers the single most important invention was scale-out. Scale-out of identical or near identical servers all connected to a standard IP ethernet network. That's the architecture. Now the building blocks of this architecture is ethernet switches which make up the network, IP ethernet switches. And then the server is all built using general purpose x86 CPU's with DRAM, with SSD, with hard drives all connected to inside the CPU. Now, the fact that you scale these server nodes as they're called out was very, very important in addressing the problem of how do you build very large scale infrastructure using general purpose compute but this architecture, Dave is a compute centric architecture. And the reason it's a compute centric architecture is if you open this, is server node. What you see is a connection to the network typically with a simple network interface card. And then you have CPU's which are in the middle of the action. Not only are the CPU's processing the application workload but they're processing all of the IO workload what we call data centric workload. And so when you connect SSDs and hard drives and GPU is everything to the CPU, as well as to the network you can now imagine that the CPU is doing two functions. It's running the applications but it's also playing traffic cop for the IO. So every IO has to go to the CPU and you're executing instructions typically in the operating system. And you're interrupting the CPU many many millions of times a second. Now general purpose CPU and the architecture of the CPU's was never designed to play traffic cop because the traffic cop function is a function that requires you to be interrupted very, very frequently. So it's critical that in this new architecture where does a lot of data, a lot of these stress traffic the percentage of workload, which is data centric has gone from maybe one to 2% to 30 to 40%. >> The path to innovation is paved by data. If you don't have data, you don't have machine learning you don't have the next generation of analytics applications that helps you chart a path forward into a world that seems to be changing every week. And so in order to have that insight in order to have that predictive forecasting that every company needs, regardless of what industry that you're in today, it all starts from data. And I think the key shift that I've seen is how customers are thinking about that data, about being instantly usable. Whereas in the past, it might've been a backup. Now it's part of a data Lake. And if you can bring that data into a data lake you can have not just analytics or machine learning or auditing applications it's really what does your application do for your business and how can it take advantage of that vast amount of shared data set in your business? >> We are actually moving towards decentralization if we think today, like if it let's move data aside if we said is the only way web would work the only way we get access to various applications on the web or pages to centralize it We would laugh at that idea. But for some reason we don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organizations that are beyond the bounds of organization. And then look back and say, okay, if that's the trend of our industry in general, given the fabric of compensation and data that we put in, you know, globally in place then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me that requires a paradigm shift a full stack from how we organize our organizations how we organize our teams, how we put a technology in place to look at it from a decentralized angle. >> I actually think we're in the midst of the transition to what's called a distributed cloud, where if you look at modernized cloud apps today they're actually made up of services from different clouds. And also distributed edge locations. And that's going to have a pretty profound impact on the way we go vast. >> We wake up every day, worrying about our customer and worrying about the customer condition and to absolutely make sure we dealt with the best in the first attempt that we do. So when you take the plethora of products we've dealt with in Azure, be it Azure SQL be it Azure cosmos DB, Synapse, Azure Databricks, which we did in partnership with Databricks Azure machine learning. And recently when we sort of offered the world's first comprehensive data governance solution and Azure overview, I would, I would humbly submit to you that we are leading the way. >> How important are rankings within the Google cloud team or are you focused mainly more on growth and just consistency? >> No, I don't think again, I'm not worried about we are not focused on ranking or any of that stuff. Typically I think we are worried about making sure customers are satisfied and the adding more and more customers. So if you look at the volume of customers we are signing up a lot of the large deals we did doing. If you look at the announcement we've made over the last year has been tremendous momentum around that. >> The thing that is really interesting about where we have been versus where we're going is we spend a lot of time talking about virtualizing hardware and moving that around. And what does that look like? And creating that as more of a software paradigm. And the thing we're talking about now is what does cloud as an operating model look like? What is the manageability of that? What is the security of that? What, you know, we've talked a lot about containers and moving into different, DevSecOps and all those different trends that we've been talking about. Like now we're doing them. So we've only gotten to the first crank of that. And I think every technology vendor we talked to now has to address how are they are going to do a highly distributed management insecurity landscape? Like, what are they going to layer on top of that? Because it's not just about, oh, I've taken a rack of something, server storage, compute, and virtualized it. I know have to create a new operating model around it in a way we're almost redoing what the OSI stack looks like and what the software and solutions are for that. >> And the whole idea of we in every recession we make things smaller. You know, in 91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year, 2000 windows the next bubble burst and the recession afterwards we moved from Unix servers to Wintel windows and Intel x86 and eventually Linux as well. Again, we made things smaller going from million dollar servers to $5,000 servers, shorter lib servers. And that's what we did in 2008, 2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There's nothing in the physical world that actually even lives but we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade. They're going to make it even smaller not just in space, which is size, with functions and containers and virtual machines, but also in time. >> So I think the right way to think about edges where can you reasonably process the data? And it obviously makes sense to process data at the first opportunity you have but much data is encrypted between the original device say and the application. And so edge as a place doesn't make as much sense as edge as an opportunity to decrypt and analyze it in the care. >> When I think of Shift-left, I think of that Mobius that we all look at all of the time and how we deliver and like plan, write code, deliver software, and then manage it, monitor it, right like that entire DevOps workflow. And today, when we think about where security lives, it either is a blocker to deploying production or most commonly it lives long after code has been deployed to production. And there's a security team constantly playing catch up trying to ensure that the development team whose job is to deliver value to their customers quickly, right? Deploy as fast as we can as many great customer facing features. They're then looking at it months after software has been deployed and then hurrying and trying to assess where the bugs are and trying to get that information back to software developers so that they can fix those issues. Shifting left to me means software engineers are finding those bugs as they're writing code or in the CIC CD pipeline long before code has been deployed to production. >> During this for quite a while now, it still comes down to the people. I can get the technology to do what it needs to do as long as they have the right requirements. So that goes back to people making sure we have the partnership that goes back to leadership and the people and then the change management aspects right out of the gate, you should be worrying about how this change is going to be how it's going to affect, and then the adoption and an engagement, because adoption is critical because you can go create the best thing you think from a technology perspective. But if it doesn't get used correctly, it's not worth the investment. So I agree, what is a digital transformation or innovation? It still comes down to understand the business model and injecting and utilizing technology to grow our reduce costs, grow the business or reduce costs. >> Okay, so look, there's so much other content on theCUBE on Cloud events site we'll put the link in the description below. We have other CEOs like Kathy Southwick and Ellen Nance. We have the CIO of UI path. Daniel Dienes talks about automation in the cloud and Appenzell from Anaplan. And a plan is not her company. By the way, Dave Humphrey from Bain also talks about his $750 million investment in Nutanix. Interesting, Rachel Stevens from red monk talks about the future of software development in the cloud and CTO, Hillary Hunter talks about the cloud going vertical into financial services. And of course, John Furrier and I along with special guests like Sergeant Joe Hall share our take on key trends, data and perspectives. So right here, you see the coupon cloud. There's a URL, check it out again. We'll, we'll pop this URL in the description of the video. So there's some great content there. I want to thank everybody who participated and thank you for watching this special episode of theCUBE Insights Powered by ETR. This is Dave Vellante and I'd appreciate any feedback you might have on how we can deliver better event content for you in the future. We'll be doing a number of these and we look forward to your participation and feedback. Thank you, all right, take care, we'll see you next time. (upbeat music)

Published Date : Jan 22 2021

SUMMARY :

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Dheeraj Pandey, Nutanix | theCUBE on Cloud 2021


 

>> Hi, and this is theCUBE on Cloud. I'm Stu Miniman and really excited to welcome to a special Fireside Chat. CUBE Alumni has been on the program so many times. We always love talking to founders. We like talking to deep thinkers and that's why he was one of the early ones that I reached out to when we were working on this event. When we first started conversations, we were looking at how hyperscalers really were taking adoption of the brand new technologies, things like flash, things like software defined networking, and how that would invade the enterprise. That of course has had a huge impact, help create a category called hyperconverged infrastructure and I'm talking about Dheeraj Pandey. He is the founder, chairman, and CEO of Nutanix, taking HCI from hyperconverged infrastructure to hybrid cloud infrastructure. So Dheeraj, welcome to the Fireside Chat. Thank you so much for joining us. >> Thank you, Stu, and thank you for the last 10 years that we've grown together, both theCUBE and Nutanix and myself as a leader in the last 10 years. So bringing HCI from hyperconverged to hybrid cloud just reminds me of how the more things change, the more they remain the same. So looking forward to a great discussion here. >> So talk about that early discussion, what the hyperscalers were doing, how can the enterprise take advantage of that? Over time, enterprise has matured and looked a little bit more like the hyperscalers. Hybrid cloud of course is on everyone's lip, as well as we've seen the hyperscalers themselves look more and more like the enterprise. So hybrid and multicloud is where we are today. We think it'll be in the future. But give us a little bit as to how you've seen that progression today and where are we going down the road here? >> Yeah, I think I talked about this during my .NEXT keynote. And the whole idea of, in every recession, we make things smaller. In '91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year 2000 when there was the next bubble burst and the recession afterwards, we moved from Unix servers to Wintel: Windows and Intel, x86 and eventually Linux as well. Again we made things smaller going from million dollar servers to $5,000 servers, shorter lived servers. And that's what we did in 2008/2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There is nothing in the physical world that actually went lives. But we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade, they're going to make it even smaller, not just in space which is size with functions and containers and virtual machines, but also in time. So space and time, we're talking about hourly billing and monthly billing and a one-year term as opposed to really going and committing to five or seven years of hardware and CapEx. So I think as you make things smaller, I mean, and this is true for as consumers, we have short attention spans, things are going fast. The cycle of creative destruction of virtual machines is shrinking as well. So I think in many cases, we know we've gone and created this autonomy, massive sprawl. Like we created a massive sprawl of Intel servers back in '95 and 2005. Then we have to use virtualization to go and consolidate all of it, created beautiful data centers of Intel servers with VMware software. And then we created a massive sprawl of data centers, of consolidated data centers with one click private cloud in the last five years and hopefully in the next five too. But I think we're also now creating a proliferation of clouds. There is a sprawl, massive sprawl of cost centers and such. So we need yet another layer of software for governance to reign in on that chaos, hence the need for a new HCI, hybrid cloud infrastructure. >> Yeah, it's fascinating to kind of watch that progression over time. There was a phenomenal Atlantic article. I think it was from like the 1940s or 1950s where somebody took what was happening post-World War II and projected things out. We're talking really pre the internet, but just the miniaturization and the acceleration, kind of the Moore's law discussion. If you take things out, where it would go. When I talked to Amazon, they said the one thing that we know for sure, I'm talking to Amazon.com is that people will want it faster and cheaper in the future. I don't know which robot or drone or things that they have. But absolutely there are those certain characteristics. So from a leadership standpoint, Dheeraj, talk about these changes? We had the wave of virtualization, the wave of containerization, you talked about functions in serverless. Those are tools. But at the end of the day, it's about the outcomes and how do we take advantage of things? So how as a leader do you make sure that you know where to take the company as these technology waves and changes impact what you're doing? >> Yeah, it's a great point. I mean, we celebrate things in IT a lot, but we don't talk about what does it take? What's the underlying fabric to really use these things successfully and better than others and not just use buzzwords, because new buzzwords will come in the next three years. For example AI and ML has been a great buzzword for the last three, four years. But there's very few companies, probably less than even half a percent who know how to leverage machine learning, even understand the difference between machine learning and AI. And a lot of it comes down to a few principles. There's a culture principles, not the least of which is how you celebrate failure, because now you're doing shorter, smaller things. You've got a more agile, you'll have more velocity. Gone are the days of waterfall where you're doing yearly planning and pre-year releases and such. So as we get into this new world, not everything will be perfect, and you've got to really learn to pick yourself up and recover quickly, heal quickly and such. So that is the fundamental tenet of Silicon Valley. And we got to really go and use this more outside the Valley as well in every company out there. Whether it's East Coast company, the Midwest company that are outside the U.S. I think this idea that you will be vulnerable, more vulnerable as you go and learn to do things faster and shorter. I think product management is a term that we don't fully understand, and this is about the why before the how and the what. We quickly jump to the what: containers and functions and databases, servers, and AI, and ML, they're the what. But how do you really start with the why? You know my fascination for one of my distant mentors, Simon Sinek and how he thinks about most companies just focusing on the what, while very few actually start with why, then the how, then the what itself. And product management has to play a key role in this, which also subsumes design, thinking about simplification and elegance and reducing friction. I think again, very few companies, probably no more than 1% of the companies really understand what it means to start with design and APIs, user experience APIs for developers before you even get to writing any single line of code. So I think to me, that's leadership. When you can stay away from instant gratification of the end result, but start with the why, then the how, then the what. >> Yeah, as we know in the technology space, oftentimes the technology is the easy part. It's helping to drive that change. I think back to the early days when we were talking, it was, hyperconverge, it was a threat to storage. We're going to put you out of a job. And we'd always go and say, "Look, no, no, no. We're not putting you out of a job. We're going to free you up to do the things that you want to do. That security project that's been sitting on the shelf for six months, you can go do that. Helping build new parts of the business. Those things that you can do." It's that shifting a mindset can be so difficult. And Dheeraj, I mean, you look at 2020, everyone has had to shift their mindset for everything. I was spending half my time on the road. I don't miss the hotels. I do miss seeing lots and lots of people in person. So what's your advice for people, how they can stay malleable, be open to some change? What are you seeing out there? What advice do you give there? >> Yeah, I think, as you said, inertia is at the core of most things in our lives, including what we saw in healthcare for the last 20, 30 years. I mean, there was so much regulation. The doctor's community had to move forward, nurses had to move forward. I mean, not just providers, but insurance companies. And finally, all of a sudden, we're talking about telehealth because of the pandemic. We are talking about online learning. I mean the things that higher ed refused to do. I mean if you think about the last 20 years of what had happened with the cost of higher ed, I mean it's 200% growth when the cost of television has gone down by probably 100, 200% with more features. Healthcare, higher ed, education in general, all of a sudden is coming for this deep shock because of the pandemic. And I think it's these kind of black swan moments that really changed the world. And I know it's a cliche to say this. But I feel like we are going to be in a new normal, and we have been forced to this new change of digital. I mean, you and I are sitting and talking over the internet. It's a little awkward right now because there's a little bit of a delay in the way I'm looking at things. But I know it's going to directionally be right. I mean, we will go in a way where it just become seamless over time. So change is the only constant. And I believe that I think what we've seen in the pandemic is just the beginning of what digital will mean going forward. And I think the more people embrace it, the faster we do it. Speed is going to be the name of the game when it comes to survival and thriving in this new age. >> Dheeraj, it's interesting. We do hope, I'm a technologist. I know you're an optimist when it comes to things. So we always look at those silver linings. Like I hope healthcare and education will be able to move forward fast. Higher education costs, inequity out there for access to medicine. It would be wonderful if we could help solve some of that, despite this global pandemic. One of the other results, Dheeraj, we talked about some very shifts in the marketplace, the large tech players really have emerged in winter so far in 2020. I can't help, but watch the stock market. And Apple is bigger than ever, Amazon, Google, all ended up in front of Congress to talk about if they've gotten too big. You've partnered with Amazon, Microsoft, and Google. They are potentially a threat but also a partner. From your standpoint, have they gotten too much power? Do we have an inequity in the tech world that they are creating the universes that they will just kind of block off and limit innovation? What's your take on big tech? >> Yeah, I mean, I feel like there's always been big something. I mean, if you go back to the '90s, Amazon, not Amazon, IBM was big, and Microsoft was big, and AT&T was big. I mean, there's always been big companies because the consumer effect that they've had as well, I mean. And I think what we're seeing right now is no different. I mean, at the end of the day, the great thing about this country is that there's always disruption happening. And sometimes small is way better and way more competitive than big. Now at the same time, I do look up to the way some of them have organized themselves. Like the way Amazon has organized itself is really unique and creative with general managers and very independent, highly autonomous groups. So some of these organizations will definitely survive and thrive in scale. And yet for others, I think decision-making and staying competitive and staying scrappy will come a lot harder. So to me when I look at these big names and what Congress is talking about and such, I feel like there's no different than 20, 30, 40 years ago. I mean, we talked about Rockefeller and the oil giants back from 100 years ago. And so in many ways, I mean, the more things change, the more they remain the same. All we have to do is we have to walk over to where the customer is. And that's what we've done with the partnerships. Like in Amazon and Azure, we're saying look, we can even use your commits and credits. I mean, that is a very elegant way to go to where the customer is, rather than force them to where we are. And the public cloud is facing this too. They've come to realize in the last two years that they cannot force all of enterprise computing to come to hyperscalers data centers. They'll have to take in these bite-size smaller clouds to where the customer is, where the customer's machines are, where the customers people are, where the customers data is. That's where we also take to disperse the cloud itself. So I think there's going to be a yin yang where we'll try to walk with the customer to where we want them to be, whether it's hyperscaler data center or the notion of hybrid cloud infrastructure. But many a time, we've got to walk over to where they are. I mean, and outside the U.S, I mean, the cloud is such a nuanced word. I mean, we're talking about sovereignty, we're talking about data gravity, we're talking about economics of owning versus renting. This trifecta, the laws of the land, the laws of physics, and the laws of economics will dictate many of these things as well. So I think the big folks are also humble and vulnerable to realize that there's nothing more powerful than market forces. And I think the rest will take care of itself. >> Yeah, my quick commentary on that, Dheeraj, I think most of us look back at AT&T and felt the government got it wrong. The way they broke it up and ended up consolidating back together, it didn't necessarily help consumers. Microsoft on the other hand might've had a little bit too much power and was leveraging that against competition and really squashing innovation. So in general, it's good to see that the politics are looking at that and chore felt. The last time I watched things, they were a little bit more educated than some previous times there, where it was almost embarrassing to watch our representatives fumbling around with technology. So it's always good to question authority, question what they have. And one of the things you've brought up many times is you're open to listening and you're bringing in new ideas. I remember one conversation I had with you is there's that direction that you hold on to, but you will assess and do new data. You've made adjustments in the product portfolio and direction based on your customers, based on the ecosystem. And you've mentioned some of the, bring thoughts that you've brought into the company and you share. So you mentioned black swan that seem to head you brought to one of the European .NEXT shows. It was great to be able to see that author and read through advisors like Condoleezza Rice who you've had at the conferences a couple of times. Where are you getting some of your latest inspiration from, any new authors or podcasts that you'd be recommending to the audience? >> Yeah, I look at adjacencies, obviously Simon has been great. He was .NEXT, talked about the Infinite Game. And we'll talk about the Infinite Game with Nutanix too with respect to also my decision. But Brene Brown was been very close to Nutanix. I was just looking at her latest podcast, and she was sitting with the author of Stretch, Scott Sonnenschein, and it's a fascinating read and a great listen, by the way, I think for worth an hour, talking about scrappiness, and talking about resourcefulness. What does it mean to really be resourceful? And we need that even more so as we go through this recession, as we are sheltered in place. I think it's an adjacency to everything that Brene does. And I was just blown away by just listening to it. I'd a love for others to even have a listen and learn to understand what we can do within our families, with our budgets, with our companies, with our startups. I mean, with CUBE, I mean, what does it mean to be scrappy? And celebrate scrappiness and resourcefulness, more so than AI always need more. I think I just found it fascinating in the last week itself listening through it. >> John Farinacci talk many times that founder, startup, that being able to pull themselves up, be able to drive forward, overcome obstacles. So Dheeraj, do you tee it up? It sounds like is the next step for you. There's a transition under discussion. Bain has made an investment. There's a search for new CEO. Are you saying there's a book club in your future to be able to get things ready? Why don't you explain a little bit, 11 years took the company public, over 6,500 employees public company. So tell us a little bit about that decision-making process and what you expect to see in the future? >> Yeah, it's probably one of the hardest things as an entrepreneur is to let go, because it's a creation that you followed from scratch, from nothing. And it was a process for me to rethink about what's next for the company and then what's next for me? And me and the company were so tightly coupled that I was like, wow, at some point, this has to be a little bit more like the way Bill Gates did it with Microsoft, and there's going to be buton zone and you will then start to realize that your identity is different from the company's identity. And maybe the company is built for bigger, better things. And maybe you're built for bigger, better things. And how do you really start to first do this decoupling of the identity? And it's really hard. I mean, I'm sure that parents go through this. I mean, our children are still very young. Our eldest is nine going on 10 and our twin girls are six. I know at some point in the next 10 years, eight to 10 years, we'll have to figure out what it means to let go. And I'm already doing this with my son. I tell him you're born free. I mean, the word born free which drives my wife crazy sometimes. I say this to them, it's about independence. And I think the company is also born free to really think about a life outside of me, as well outside of founder. And that was a very important process for me as I was talking to the board for the last six, seven, eight months. And when the Bain deal came in, I thought it was a great time. We ended the fiscal really well, all things considered. We had a good quarter. The transition has been a journey of a lifetime, the business model transition I speak of. Really three years, I mean, I have aged probably 10 years in these last three years. But I think I would not replaced it for anything. Just the experience of learning what it means to change as a public company when you have short-term goals and long-term goals, we need the conviction, knowing what's right, because otherwise we would not have survived this cloud movement, all this idea of actually becoming a subscription company, changing the core of the business in the on-prem world itself. It's a king to change the wings of a plane at 40,000 feet where none of the passengers blink. It's been phenomenal ride last 11 years, but it's also been nonstop monomaniacal. I mean, I use the word marathon for this, and I figured it's a good time to say figure out a way to let go of this, and think of what's bigger better for Nutanix. And going from zero to a billion six in annual billings, and looking at billion six to 3 billion to four to five, I think it'd be great &to look at this from afar. And at the same time, I think there's vulnerability. I mean, I've made the company vulnerable. I've made myself vulnerable. We don't know who the next leader will be. And I think the next three to six months is one of the most important baton zones that I have ever experienced to be a part of. So looking forward to make sure that baton doesn't fall, redefine what good to great looks like, both for the company and for myself. And at the same time, go read more. I mean, I've been passionate about developers in the last 10 years, 11 years. I was a developer myself. This company, Nutanix, was really built by developers for IT. And I'm learning more about the developer as a consumer. How do you think about their experience? Not just the things that we throw at them from open source point of view and from cloud and technologies and AI and ML point of view, but really their lives, having them think about revenue and business and really blurring the lines between architects and product managers and developers. I think it's just an unfathomable problem we've created in IT that I would love to go and read and write more about. >> Yeah, so many important things you said there. I absolutely think that there are certain things everybody of course will think of you for a long time with Nutanix, but there is that separation between the role in the company and the person itself, and really appreciated how much you've always shared along those lines. So last question I have and you hit it up a little bit when you talked about developers. Take off your Nutanix hat for a second here, now what do we need to do to make sure that the next decade is successful in this space, cloud as a general guideline? Yes, we know we have skill gap. We know we need more people, we need more diversity. But there's so much that we need and there's so much opportunity, but what do you see and any advice areas that you think are critical for success in the future? >> Yeah, I mean, you hit up on something that I have had a passion for, probably more late in this world, more so than conspicuous, and and you hit upon it right now, diversity and inclusion. It's an unresolved problem in the developer community: the black developer, the woman developer. The idea of, I mean, we've two girls, they're twins. I'd love for them to embrace computer science and even probably do a PhD. I mean, I was a dropout. I'd love for them to do better than I did. Get, embrace things that are adjacent to biology and computer science. Go solve really hard problems. And we've not done those things. I mean, we've not looked at the community of developers and said, you know, they are the maker. And they work with managers and the maker manager world is two different worlds. How do you make this less friction? And how do you make this more delightful? And how do you think of developers as business, as if they are the folks who run the business? I think there's a lot that's missing there. And again, we throw a lot of jargons at them, and we talk a lot about automation and tools and such. But those are just things. I think the last 10, 11 years of me really just thinking about product and product portfolio and design and the fact that we have so many developers at Nutanix. I think it has been a mind-boggling experience, thinking about the why and the how and the what of the day in the life of, the month in the life of, and thinking about simple things like OKRs. I mean, we are throwing these jargons of OKRs at them: productivity, offshoring, remote work, over the zoom design sessions. It's just full of conflict and friction. So I think there is an amazing opportunity for Nutanix. There's an amazing opportunity for the industry to elevate this where the the woman developer can speak up in this world that's full of so many men. The black developer can speak up. And all of us can really think of this as something that's more structured, more productive, more revenue-driven, more customer in rather than developer out. That's really been some of the things that have been in my head, things that are still unresolved at Nutanix that I'm pretty sure at many of the places out there. That's what thinking and reading and writing about. >> Well, Dheeraj, first of all, thank you so much again for participating here. It's been great having you in theCUBE community, almost since the inception of us doing it back in 2010. Wish you the best of luck in the current transition. And absolutely look forward to talking more in the future. >> Thank you. And again, a big fan of the tremor rate of John, Dave, and you. Always learn so much from you, folks. Looking forward to be a constant student. Thank you. >> Thank you for joining us at theCUBE on Cloud. Lots more coverage here. Be sure to look throughout the site, engage in the chats, and give us your feedback. We're here to help you with the virtual events. I'm Stu Miniman as always. Thanks for watching.

Published Date : Jan 22 2021

SUMMARY :

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Simon Crosby, SWIM.AI | theCUBE on Cloud 2021


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Hi. I'm still Minuteman. And welcome back to the Cube on Cloud. Talking about really important topics is toe how developers we're changing how they build their applications where they live. Of course. Long discussion we've had for a number of years, you know? How do things change in hybrid environment? We've been talking for years. Public cloud and Private Cloud and really excited for this session. We're gonna talk about how edge environment and ai impact that. So happy to walk back. One of our cube alumni, Simon Crosby, is currently the chief technology officer with swim. Got plenty of viewpoints on AI the edge and knows the developer world. Well, Simon, welcome back. Thanks so much for joining us. >>Thank you, sir, for having me. >>All right. So let let let's start start for a second. Let's talk about developers, you know, used to be, you know, for for years we talked about, you know, what's the level of abstraction we get? Does it sit? You know, you know, do I put it on bare metal? Do I virtualized it? Do I contain Arise it. Do I make it serve? Ellis? Ah, lot of those things. You know that the app developer doesn't want to even think about. But location matters a whole lot when we're talking about things like a I where do I have all my data? That I could do my training? Where do I actually have to do the processing? And, of course, edge. Just changes by orders of magnitude, Some of the things like Leighton see, and where data lives and everything like that. So with that as a set up would love to get just your framework as to what you're hearing from developers and what will gettinto Some of the solutions that that you and your team are helping them toe do their jobs >>where you're up to lights to the data onslaught is very riel. Companies that I deal with are facing more and more real time data from products from their infrastructure from their partners, whatever it happens to be, and they need to make decisions rapidly. And the problem that they're facing is that traditional ways of processing that data or to so so perhaps the big data approach which by now is a bit old. It's been long in the tooth, Um, where you stored it and then you analyze it later is problematic. First of all, data streams of boundless so you don't really know winter analyze. But second, you can't store all. And so the story and analyze approach has to change and swim is trying to do something about this by adopting a process off. Analyze um, on the fly. So as dead is generate as you receive events, you don't bother Saw them. You you analyze them, and then if you have tow you still the data. But you you need to analyze as you receive data. Andre react immediately to be able to generate reasonable insights or predictions that can drive commerce and decisions in the real world. >>Yeah, absolutely. I remember back, you know, the early days of big data, you know, real time got thrown around a little, but it was usually I need to react fast enough toe. Make sure we don't, you know, lose the customer, we react toe something. But it was we gather all the data and let's move compute to the data. Uh, today is you talk about real time streams are so important. We've been talking about observe ability for last couple of years to just really understand the systems and the outputs More than, uh, looking back historically at where things were waiting for alerts. So could you give us some examples, if you would, Is toe You know that those streams, you know what is so important about being able to interact and leverage that data when you need it? And, boy, it's great if we can if we can use it then and not have to store it and think about it later. Obviously, there's some benefits there because >>every product nowadays has a CPU, right? And so there's more and more data and just let me give you an example. Um, swim processes real time data from more than 100 million mobile devices in real time, Um, in for a mobile operator. And what we're doing there is We're optimizing connection quality between devices and the network. Now that volume of data is more than four petabytes per day. Okay, now there is simply no way you could ever store that and analyze it later. The interesting thing about this is that if you adopt and analyze. And then if you really have to store architecture, you get to take advantage of Muslim. So you're running at CPU memory speeds instead of a disc speed, and so that gives you a million fold speed up. And it also means you don't have the Leighton see problem off reaching out to her boat storage, dead base or whatever. And so that reduces cost so we can do it all about 10% of the infrastructure that they previously had for her do style implementation. >>So maybe would help if we just explain when we say edge, people think of a lot of different things. Is it? You know, on I o. T device sitting out into the edge Are we talking about the telecom edge? We're watching a WS for years, you know, Spider out their services and into various environment. So what when you talk about the type of solutions you're doing and what your customers have is that the Telkom edges that the, you know, actual device edge, you know, where where does processing happen and where do these, you know, services that that work on it live? >>Uh, so I think the right way to think about edges. Where can you reasonably process the data? And it obviously makes sense to process data at the first opportunity you have. But much data is encrypted between the original device. Say Onda. The application and so edge as a place doesn't make as much sense as edge as an opportunity to decrypt and analyze data in the clear. So is computing is not so much a place in my view as the first opportunity you have to process state in the clear and to make sense of it. And then edge makes sense in terms of Leighton, see, by locating compute as close as possible to the sources of data, um, to reduce latency and maximize your ability to get insights. You know, Andre return to uses in, you know, quickly. So edge for me often is the cloud >>excellent. One of the other things I I think about back from, you know, the big data days or even earlier It was that how long it took to get from the raw data to processing that data, to be able to getting some insight and then being able to take action. Uh, it sure sounds like we're trying to collapse That completely. Is that you know, how do we do that? You know, Can we actually, you know, build the system so that we can, you know, in that real time continuous model that you talk about, You know? So what character movements? One >>of the wonderful things about cloud computing is that two major abstractions really served us on. Those are rest which expect this computing and databases and rest means in the old server can do the job for me. And then the database is just a napi I call away. The problem with that is that it's desperately slow. So when I say desperately slow, I mean, it's probably thrown away the last 10 years, Um, was law. Just think about this way. Your CPU runs at gigahertz and the network runs at milliseconds. So by definition, every time you reach out to a data store, you're going a million times slower than your Cebu. That's terrible. It's absolutely tragic. Okay, so a model which is much more effective is to have and in memory, computing architecture er in which you engage in state will computation. So instead of having to reach out to a database every time to update the database and whatever you know, store something and then fetch it again a few moments later when the next event arrives. You keep state in memory and you compute on the fly as data arrives and that way you get a million times speed up. You also end up with this tremendous cost direction because you don't end up with as many instances having to compute by comparison. So let me give you a quick example. If you go to a traffic dots from the AI, you can see, um, the real time state off the traffic infrastructure in Palo Alto. And, um, each one of those, um intersections is predicting its own future. Now, the volume of data from just a few 100 lights in Palo Alto is about four terabyte today. And sure, you can deal with this in AWS Lambda. There are lots and lots of servers up there. But the problem is that the end to end per event leighton see, is about 100 milliseconds. And you know, if I'm dealing with 30,000 events a second, that's just too much so solving that problem with a stateless architectures is extraordinarily expensive. You know, more than $5000 a month. Where is the staple architectural? Which you could think of as an evolution all for, uh, you know, something reactive or the actor model, Um, get you, You know, something like 1/10 of the cost. Okay, so cloud is fabulous for things that need to scale wide, but a state formal is required for dealing with things which update you rapidly or regularly about their changes in state. >>Yeah, absolutely. I You know, I think about if we were talking, I mentioned before AI training models often, if you look at something like autonomous vehicles, the massive amounts of data that it needs to process, you know, has to happen in the public cloud. Um, but then that gets pushed back down to the end device. In this case, it's a car because it needs to be able to react in real time and get fed at a regular update. The new training algorithms that that it has there. Um what are you saying? You know, we >>were reviews on on this training approach and the science in general, and that is that there aren't enough the scientists or no smart people to train these algorithms, deploy them to the edge and so on. And so there is an alternative worldview, which is a much simpler one, and that is that relatively simple algorithms deployed at scale to staple representatives. Their school, you know, digital twins off things, um, can deliver enormous improvements in behavior. Um, as things learn for themselves. So the way I think the at least this edge world gets smaller is that relatively simple models off things will learn for themselves for their own futures based on what they can see and and then react. And so this idea that we have lots and lots of very scientists dealing with vast amounts of information in the cloud, Um, it's suitable for certain algorithms, but it doesn't work for the vast majority of our applications. >>So where are we with the state of what the developers need to think about? You mentioned that there's compute in most devices. That's true, but you know they need some special in video chip set out there. Are there certain programming languages that that you're seeing more prevalent? Yeah, you know, interoperability. Give us a little bit of toe, you know, some tips and tricks for for those developing >>super so number one a staple architectures is fundamental and sure react is well known. Andi, there are, For example, on er lang swim is another. So I'm going to use some language. And I would encourage you to look at Cem O s or G to go from play there. A staple architecture, ER which allows actors small, concurrent objects to Stapley evolve their own state based on updates from the real world is fundamental. But the way in swim, we use data to build these models. So, um, these little agents for things we call them Web agents because the object I'd is a your I, um they staple evolved by processing their own real world data safely representing it. And then they do this wonderful thing, which is build a model on the fly, and they build a model by linking to things that they're related to. So a knit section would link to all of its sensors. But it would also licked all of its neighbors because the neighbors and linking is like a sub in pubs up and it allows that Web agent then to continually analyze, learn and predict on the fly. And so every one of these concurrent objects is doing this job off and analyzing its own raw data and then predicting from that and streaming the results so and swim you get stream board data in. And what streams out is predictions. Predictions about the future state off the infrastructure, and that's a very powerful staple approach, which can run all the memory. No stories required, by the way. It's still persistence. If you lose the no, you can just come back up and carry on. But there's no need to store huge amounts of raw data if you don't need it. And let me just be clear. The volumes of raw data from the real world are staggering, right? So for Porter by today from Palo Alto. But Las Vegas, about 60 terabytes today from the traffic lights, Um, no more than 100 million mobile devices is is tens of petabytes per day, which is just too much the store. >>Well, Simon, you'd mentioned that we we have a shortage when it comes to data scientists and the people that could be involved in those things. How about from the developer side? Do most enterprises that you're talking to? Do they have the skill set? Is the ecosystem mature enough for the company take involved? Or what do we need to do? Looking forward, toa help companies be able to take advantage of this opportunity. >>Yeah, So there is a huge change in terms of, I guess just cloud native skills. Um, and this is exacerbated. The more you get out into, I guess what you could think of as traditional kind of companies, all of whom have tons and tons of data sources. So we need to make it easy and swim tries to do this by effectively using skills of people already have Java or JavaScript and giving them easy ways to develop, deploy and then run applications without thinking about them. So instead of finding developers to notions of place and where databases are and all that sort of stuff, if they can write simple, object oriented programs about things like intersections and push buttons, a pedestrian lights, and in road loops and so on and simply relate basic objects in their world to each other, then we let data build the model by essentially creating these little concurrent objects for each thing, and they will then link to each other and solve the problem. We end up solving a huge problem for developers to which is that they don't need to acquire complicated cloud native skill sets to get to work. >>Well, absolutely. Simon, that's something we've been trying to do for a long time. Is to truly simplify things. I wanna let you have the final word. Uh, if you look out there, uh, the opportunity that challenge in the space, what final takeaways would would you get our audience? >>So very simple. If you adopt a staple competing Achter should like swim, you get to go a million times faster. The applications always have an answer. They analyze, learn and predict on the fly, and they go million times faster. They use 10% less. No. So 10% off the infrastructure of a store than analyze approach. And it's the way of the future. >>Simon Crosby. Thanks so much for sharing. Great having you on the program. >>Thank you too. >>And thank you for joining. I'm stew Minuteman. Thank you. As always for watching the cube. Yeah,

Published Date : Jan 22 2021

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theCube On Cloud 2021 - Kickoff


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle, everybody to Cuban cloud. My name is Dave Volonte, and I'll be here throughout the day with my co host, John Ferrier, who was quarantined in an undisclosed location in California. He's all good. Don't worry. Just precautionary. John, how are you doing? >>Hey, great to see you. John. Quarantine. My youngest daughter had covitz, so contact tracing. I was negative in quarantine at a friend's location. All good. >>Well, we wish you the best. Yeah, well, right. I mean, you know what's it like, John? I mean, you're away from your family. Your basically shut in, right? I mean, you go out for a walk, but you're really not in any contact with anybody. >>Correct? Yeah. I mean, basically just isolation, Um, pretty much what everyone's been kind of living on, kind of suffering through, but hopefully the vaccines are being distributed. You know, one of the things we talked about it reinvent the Amazon's cloud conference. Was the vaccine on, but just the whole workflow around that it's gonna get better. It's kind of really sucky. Here in the California area, they haven't done a good job, a lot of criticism around, how that's rolling out. And, you know, Amazon is now offering to help now that there's a new regime in the U. S. Government S o. You know, something to talk about, But certainly this has been a terrible time for Cove it and everyone in the deaths involved. But it's it's essentially pulled back the covers, if you will, on technology and you're seeing everything. Society. In fact, um, well, that's big tech MIT disinformation campaigns. All these vulnerabilities and cyber, um, accelerated digital transformation. We'll talk about a lot today, but yeah, it's totally changed the world. And I think we're in a new generation. I think this is a real inflection point, Dave. You know, modern society and the geo political impact of this is significant. You know, one of the benefits of being quarantined you'd be hanging out on these clubhouse APS, uh, late at night, listening to experts talk about what's going on, and it's interesting what's happening with with things like water and, you know, the island of Taiwan and China and U. S. Sovereignty, data, sovereignty, misinformation. So much going on to talk about. And, uh, meanwhile, companies like Mark injuries in BC firm starting a media company. What's going on? Hell freezing over. So >>we're gonna be talking about a lot of that stuff today. I mean, Cuba on cloud. It's our very first virtual editorial event we're trying to do is bring together our community. It's a it's an open forum and we're we're running the day on our 3 65 software platform. So we got a great lineup. We got CEO Seo's data Practitioners. We got a hard core technologies coming in, cloud experts, investors. We got some analysts coming in and we're creating this day long Siri's. And we've got a number of sessions that we've developed and we're gonna unpack. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy new administration. What does that mean for tech and for big tech in General? John, what can you add to that? >>Well, I think one of the things that we talked about Cove in this personal impact to me but other people as well. One of the things that people are craving right now is information factual information, truth texture that we call it. But hear this event for us, Davis, our first inaugural editorial event. Robbo, Kristen, Nicole, the entire Cube team Silicon angle, really trying to put together Morva cadence we're gonna doom or of these events where we can put out feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires with people making things happen. But it's often the people under there that are the rial newsmakers amid savory, for instance, that Google one of the most impressive technical people, he's gotta talk. He's gonna present democratization of software development in many Mawr riel people making things happen. And I think there's a communal element. We're going to do more of these. Obviously, we have, uh, no events to go to with the Cube. So we have the cube virtual software that we have been building and over years and now perfecting and we're gonna introduce that we're gonna put it to work, their dog footing it. We're gonna put that software toe work. We're gonna do a lot mawr virtual events like this Cuban cloud Cuban startup Cuban raising money. Cuban healthcare, Cuban venture capital. Always think we could do anything. Question is, what's the right story? What's the most important stories? Who's telling it and increase the aperture of the lens of the industry that we have and and expose that and fastest possible. That's what this software, you'll see more of it. So it's super exciting. We're gonna add new features like pulling people up on stage, Um, kind of bring on the clubhouse vibe and more of a community interaction with people to meet each other, and we'll roll those out. But the goal here is to just showcase it's cloud story in a way from people that are living it and providing value. So enjoy the day is gonna be chock full of presentations. We're gonna have moderated chat in these sessions, so it's an all day event so people can come in, drop out, and also that's everything's on demand immediately after the time slot. But you >>want to >>participate, come into the time slot into the cube room or breakout session. Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. So >>when you're in that home page when you're watching, there's a hero video there. Beneath that, there's a calendar, and you'll see that red line is that red horizontal line of vertical line is rather, it's a linear clock that will show you where we are in the day. If you click on any one of those sessions that will take you into the chat, we'll take you through those in a moment and share with you some of the guests that we have upcoming and and take you through the day what I wanted to do. John is trying to set the stage for the conversations that folks are gonna here today. And to do that, I wanna ask the guys to bring up a graphic. And I want to talk to you, John, about the progression of cloud over time and maybe go back to the beginning and review the evolution of cloud and then really talk a little bit about where we think it Z headed. So, guys, if you bring up that graphic when a W S announced s three, it was March of 2000 and six. And as you recall, John you know, nobody really. In the vendor and user community. They didn't really pay too much attention to that. And then later that year, in August, it announced E C two people really started. They started to think about a new model of computing, but they were largely, you know, chicken tires. And it was kind of bleeding edge developers that really leaned in. Um what? What were you thinking at the time? When when you saw, uh, s three e c to this retail company coming into the tech world? >>I mean, I thought it was totally crap. I'm like, this is terrible. But then at that time, I was thinking working on I was in between kind of start ups and I didn't have a lot of seed funding. And then I realized the C two was freaking awesome. But I'm like, Holy shit, this is really great because I don't need to pay a lot of cash, the Provisional Data center, or get a server. Or, you know, at that time, state of the art startup move was to buy a super micro box or some sort of power server. Um, it was well past the whole proprietary thing. But you have to assemble probably anyone with 5 to 8 grand box and go in, and we'll put a couple ghetto rack, which is basically, uh, you know, you put it into some coasting location. It's like with everybody else in the tech ghetto of hosting, still paying monthly fees and then maintaining it and provisioning that's just to get started. And then Amazon was just really easy. And then from there you just It was just awesome. I just knew Amazon would be great. They had a lot of things that they had to fix. You know, custom domains and user interface Council got better and better, but it was awesome. >>Well, what we really saw the cloud take hold from my perspective anyway, was the financial crisis in, you know, 709 It put cloud on the radar of a number of CFOs and, of course, shadow I T departments. They wanted to get stuff done and and take I t in in in, ah, pecs, bite sized chunks. So it really was. There's cloud awakening and we came out of that financial crisis, and this we're now in this 10 year plus boom um, you know, notwithstanding obviously the economic crisis with cove it. But much of it was powered by the cloud in the decade. I would say it was really about I t transformation. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, >>and it >>creates this mandate to go digital. So you've you've said a lot. John has pulled forward. It's accelerated this industry transformation. Everybody talks about that, but and we've highlighted it here in this graphic. It probably would have taken several more years to mature. But overnight you had this forced march to digital. And if you weren't a digital business, you were kind of out of business. And and so it's sort of here to stay. How do you see >>You >>know what this evolution and what we can expect in the coming decades? E think it's safe to say the last 10 years defined by you know, I t transformation. That's not gonna be the same in the coming years. How do you see it? >>It's interesting. I think the big tech companies are on, but I think this past election, the United States shows um, the power that technology has. And if you look at some of the main trends in the enterprise specifically around what clouds accelerating, I call the second wave of innovations coming where, um, it's different. It's not what people expect. Its edge edge computing, for instance, has talked about a lot. But industrial i o t. Is really where we've had a lot of problems lately in terms of hacks and malware and just just overall vulnerabilities, whether it's supply chain vulnerabilities, toe actual disinformation, you know, you know, vulnerabilities inside these networks s I think this network effects, it's gonna be a huge thing. I think the impact that tech will have on society and global society geopolitical things gonna be also another one. Um, I think the modern application development of how applications were written with data, you know, we always been saying this day from the beginning of the Cube data is his integral part of the development process. And I think more than ever, when you think about cloud and edge and this distributed computing paradigm, that cloud is now going next level with is the software and how it's written will be different. You gotta handle things like, where's the compute component? Is it gonna be at the edge with all the server chips, innovations that Amazon apple intel of doing, you're gonna have compute right at the edge, industrial and kind of human edge. How does that work? What's Leighton see to that? It's it really is an edge game. So to me, software has to be written holistically in a system's impact on the way. Now that's not necessarily nude in the computer science and in the tech field, it's just gonna be deployed differently. So that's a complete rewrite, in my opinion of the software applications. Which is why you're seeing Amazon Google VM Ware really pushing Cooper Netease and these service messes in the micro Services because super critical of this technology become smarter, automated, autonomous. And that's completely different paradigm in the old full stack developer, you know, kind of model. You know, the full stack developer, his ancient. There's no such thing as a full stack developer anymore, in my opinion, because it's a half a stack because the cloud takes up the other half. But no one wants to be called the half stack developer because it doesn't sound as good as Full Stack, but really Cloud has eliminated the technology complexity of what a full stack developer used to dio. Now you can manage it and do things with it, so you know, there's some work to done, but the heavy lifting but taking care of it's the top of the stack that I think is gonna be a really critical component. >>Yeah, and that that sort of automation and machine intelligence layer is really at the top of the stack. This this thing becomes ubiquitous, and we now start to build businesses and new processes on top of it. I wanna I wanna take a look at the Big Three and guys, Can we bring up the other The next graphic, which is an estimate of what the revenue looks like for the for the Big three. And John, this is I asked and past spend for the Big Three Cloud players. And it's It's an estimate that we're gonna update after earning seasons, and I wanna point a couple things out here. First is if you look at the combined revenue production of the Big Three last year, it's almost 80 billion in infrastructure spend. I mean, think about that. That Z was that incremental spend? No. It really has caused a lot of consolidation in the on Prem data center business for guys like Dell. And, you know, um, see, now, part of the LHP split up IBM Oracle. I mean, it's etcetera. They've all felt this sea change, and they had to respond to it. I think the second thing is you can see on this data. Um, it's true that azure and G C P they seem to be growing faster than a W s. We don't know the exact numbers >>because >>A W S is the only company that really provides a clean view of i s and pass. Whereas Microsoft and Google, they kind of hide the ball in their numbers. I mean, I don't blame them because they're behind, but they do leave breadcrumbs and clues about growth rates and so forth. And so we have other means of estimating, but it's it's undeniable that azure is catching up. I mean, it's still quite distance the third thing, and before I want to get your input here, John is this is nuanced. But despite the fact that Azure and Google the growing faster than a W s. You can see those growth rates. A W s I'll call this out is the only company by our estimates that grew its business sequentially last quarter. Now, in and of itself, that's not significant. But what is significant is because AWS is so large there $45 billion last year, even if the slower growth rates it's able to grow mawr and absolute terms than its competitors, who are basically flat to down sequentially by our estimates. Eso So that's something that I think is important to point out. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, well, nonetheless, Microsoft in particular, they're they're closing the gap steadily, and and we should talk more about the competitive dynamics. But I'd love to get your take on on all this, John. >>Well, I mean, the clouds are gonna win right now. Big time with the one the political climate is gonna be favoring Big check. But more importantly, with just talking about covert impact and celebrating the digital transformation is gonna create a massive rising tide. It's already happening. It's happening it's happening. And again, this shift in programming, uh, models are gonna really kinda accelerating, create new great growth. So there's no doubt in my mind of all three you're gonna win big, uh, in the future, they're just different, You know, the way they're going to market position themselves, they have to be. Google has to be a little bit different than Amazon because they're smaller and they also have different capabilities, then trying to catch up. So if you're Google or Microsoft, you have to have a competitive strategy to decide. How do I wanna ride the tide If you will put the rising tide? Well, if I'm Amazon, I mean, if I'm Microsoft and Google, I'm not going to try to go frontal and try to copy Amazon because Amazon is just pounding lead of features and scale and they're different. They were, I would say, take advantage of the first mover of pure public cloud. They really awesome. It passed and I, as they've integrated in Gardner, now reports and integrated I as and passed components. So Gardner finally got their act together and said, Hey, this is really one thing. SAS is completely different animal now Microsoft Super Smart because they I think they played the right card. They have a huge installed base converted to keep office 3 65 and move sequel server and all their core jewels into the cloud as fast as possible, clarified while filling in the gaps on the product side to be cloud. So you know, as you're doing trends job, they're just it's just pedal as fast as you can. But Microsoft is really in. The strategy is just go faster trying. Keep pedaling fast, get the features, feature velocity and try to make it high quality. Google is a little bit different. They have a little power base in terms of their network of strong, and they have a lot of other big data capabilities, so they have to use those to their advantage. So there is. There is there is competitive strategy game application happening with these companies. It's not like apples, the apples, In my opinion, it never has been, and I think that's funny that people talk about it that way. >>Well, you're bringing up some great points. I want guys bring up the next graphic because a lot of things that John just said are really relevant here. And what we're showing is that's a survey. Data from E. T. R R Data partners, like 1400 plus CEOs and I T buyers and on the vertical axis is this thing called Net score, which is a measure of spending momentum. And the horizontal axis is is what's called market share. It's a measure of the pervasiveness or, you know, number of mentions in the data set. There's a couple of key points I wanna I wanna pick up on relative to what John just said. So you see A W S and Microsoft? They stand alone. I mean, they're the hyper scale er's. They're far ahead of the pack and frankly, they have fall down, toe, lose their lead. They spend a lot on Capex. They got the flywheel effects going. They got both spending velocity and large market shares, and so, but they're taking a different approach. John, you're right there living off of their SAS, the state, their software state, Andi, they're they're building that in to their cloud. So they got their sort of a captive base of Microsoft customers. So they've got that advantage. They also as we'll hear from from Microsoft today. They they're building mawr abstraction layers. Andy Jassy has said We don't wanna be in that abstraction layer business. We wanna have access to those, you know, fine grain primitives and eso at an AP level. So so we can move fast with the market. But but But so those air sort of different philosophies, John? >>Yeah. I mean, you know, people who know me know that I love Amazon. I think their product is superior at many levels on in its way that that has advantages again. They have a great sass and ecosystem. They don't really have their own SAS play, although they're trying to add some stuff on. I've been kind of critical of Microsoft in the past, but one thing I'm not critical of Microsoft, and people can get this wrong in the marketplace. Actually, in the journalism world and also in just some other analysts, Microsoft has always had large scale eso to say that Microsoft never had scale on that Amazon owned the monopoly on our franchise on scales wrong. Microsoft had scale from day one. Their business was always large scale global. They've always had infrastructure with MSN and their search and the distributive how they distribute browsers and multiple countries. Remember they had the lock on the operating system and the browser for until the government stepped in in 1997. And since 1997 Microsoft never ever not invested in infrastructure and scale. So that whole premise that they don't compete well there is wrong. And I think that chart demonstrates that there, in there in the hyper scale leadership category, hands down the question that I have. Is that there not as good and making that scale integrate in because they have that legacy cards. This is the classic innovator's dilemma. Clay Christensen, right? So I think they're doing a good job. I think their strategy sound. They're moving as fast as they can. But then you know they're not gonna come out and say We don't have the best cloud. Um, that's not a marketing strategy. Have to kind of hide in this and get better and then double down on where they're winning, which is. Clients are converting from their legacy at the speed of Microsoft, and they have a huge client base, So that's why they're stopping so high That's why they're so good. >>Well, I'm gonna I'm gonna give you a little preview. I talked to gear up your f Who's gonna come on today and you'll see I I asked him because the criticism of Microsoft is they're, you know, they're just good enough. And so I asked him, Are you better than good enough? You know, those are fighting words if you're inside of Microsoft, but so you'll you'll have to wait to see his answer. Now, if you guys, if you could bring that that graphic back up I wanted to get into the hybrid zone. You know where the field is. Always got >>some questions coming in on chat, Dave. So we'll get to those >>great Awesome. So just just real quick Here you see this hybrid zone, this the field is bunched up, and the other companies who have a large on Prem presence and have been forced to initiate some kind of coherent cloud strategy included. There is Michael Michael, multi Cloud, and Google's there, too, because they're far behind and they got to take a different approach than a W s. But as you can see, so there's some real progress here. VM ware cloud on AWS stands out, as does red hat open shift. You got VM Ware Cloud, which is a VCF Cloud Foundation, even Dell's cloud. And you'd expect HP with Green Lake to be picking up momentum in the future quarters. And you've got IBM and Oracle, which there you go with the innovator's dilemma. But there, at least in the cloud game, and we can talk about that. But so, John, you know, to your point, you've gotta have different strategies. You're you're not going to take out the big too. So you gotta play, connect your print your on Prem to your cloud, your hybrid multi cloud and try to create new opportunities and new value there. >>Yeah, I mean, I think we'll get to the question, but just that point. I think this Zeri Chen's come on the Cube many times. We're trying to get him to come on lunch today with Features startup, but he's always said on the Q B is a V C at Greylock great firm. Jerry's Cloud genius. He's been there, but he made a point many, many years ago. It's not a winner. Take all the winner. Take most, and the Big Three maybe put four or five in there. We'll take most of the markets here. But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second tier cloud, large scale model. I don't want to say tear to cloud. It's coming to sound like a sub sub cloud, but a new category of cloud on cloud, right? So meaning if you get a snowflake, did I think this is a tale? Sign to what's coming. VM Ware Cloud is a native has had huge success, mainly because Amazon is essentially enabling them to be successful. So I think is going to be a wave of a more of a channel model of indirect cloud build out where companies like the Cube, potentially for media or others, will build clouds on top of the cloud. So if Google, Microsoft and Amazon, whoever is the first one to really enable that okay, we'll do extremely well because that means you can compete with their scale and create differentiation on top. So what snowflake did is all on Amazon now. They kind of should go to azure because it's, you know, politically correct that have multiple clouds and distribution and business model shifts. But to get that kind of performance they just wrote on Amazon. So there's nothing wrong with that. Because you're getting paid is variable. It's cap ex op X nice categorization. So I think that's the way that we're watching. I think it's super valuable, I think will create some surprises in terms of who might come out of the woodwork on be a leader in a category. Well, >>your timing is perfect, John and we do have some questions in the chat. But before we get to that, I want to bring in Sargi Joe Hall, who's a contributor to to our community. Sargi. Can you hear us? All right, so we got, uh, while >>bringing in Sarpy. Let's go down from the questions. So the first question, Um, we'll still we'll get the student second. The first question. But Ronald ask, Can a vendor in 2021 exist without a hybrid cloud story? Well, story and capabilities. Yes, they could live with. They have to have a story. >>Well, And if they don't own a public cloud? No. No, they absolutely cannot. Uh hey, Sergey. How you doing, man? Good to see you. So, folks, let me let me bring in Sergeant Kohala. He's a He's a cloud architect. He's a practitioner, He's worked in as a technologist. And there's a frequent guest on on the Cube. Good to see you, my friend. Thanks for taking the time with us. >>And good to see you guys to >>us. So we were kind of riffing on the competitive landscape we got. We got so much to talk about this, like, it's a number of questions coming in. Um, but Sargi we wanna talk about you know, what's happening here in Cloud Land? Let's get right into it. I mean, what do you guys see? I mean, we got yesterday. New regime, new inaug inauguration. Do you do you expect public policy? You'll start with you Sargi to have What kind of effect do you think public policy will have on, you know, cloud generally specifically, the big tech companies, the tech lash. Is it gonna be more of the same? Or do you see a big difference coming? >>I think that there will be some changing narrative. I believe on that. is mainly, um, from the regulators side. A lot has happened in one month, right? So people, I think are losing faith in high tech in a certain way. I mean, it doesn't, uh, e think it matters with camp. You belong to left or right kind of thing. Right? But parlor getting booted out from Italy s. I think that was huge. Um, like, how do you know that if a cloud provider will not boot you out? Um, like, what is that line where you draw the line? What are the rules? I think that discussion has to take place. Another thing which has happened in the last 23 months is is the solar winds hack, right? So not us not sort acknowledging that I was Russia and then wish you watching it now, new administration might have a different sort of Boston on that. I think that's huge. I think public public private partnership in security arena will emerge this year. We have to address that. Yeah, I think it's not changing. Uh, >>economics economy >>will change gradually. You know, we're coming out off pandemic. The money is still cheap on debt will not be cheap. for long. I think m and a activity really will pick up. So those are my sort of high level, Uh, >>thank you. I wanna come back to them. And because there's a question that chat about him in a But, John, how do you see it? Do you think Amazon and Google on a slippery slope booting parlor off? I mean, how do they adjudicate between? Well, what's happening in parlor? Uh, anything could happen on clubhouse. Who knows? I mean, can you use a I to find that stuff? >>Well, that's I mean, the Amazons, right? Hiding right there bunkered in right now from that bad, bad situation. Because again, like people we said Amazon, these all three cloud players win in the current environment. Okay, Who wins with the U. S. With the way we are China, Russia, cloud players. Okay, let's face it, that's the reality. So if I wanted to reset the world stage, you know what better way than the, you know, change over the United States economy, put people out of work, make people scared, and then reset the entire global landscape and control all with cash? That's, you know, conspiracy theory. >>So you see the riches, you see the riches, get the rich, get richer. >>Yeah, well, that's well, that's that. That's kind of what's happening, right? So if you start getting into this idea that you can't actually have an app on site because the reason now I'm not gonna I don't know the particular parlor, but apparently there was a reason. But this is dangerous, right? So what? What that's gonna do is and whether it's right or wrong or not, whether political opinion is it means that they were essentially taken offline by people that weren't voted for that. Weren't that when people didn't vote for So that's not a democracy, right? So that's that's a different kind of regime. What it's also going to do is you also have this groundswell of decentralized thinking, right. So you have a whole wave of crypto and decentralized, um, cyber punks out there who want to decentralize it. So all of this stuff in January has created a huge counterculture, and I had predicted this so many times in the Cube. David counterculture is coming and and you already have this kind of counterculture between centralized and decentralized thinking and so I think the Amazon's move is dangerous at a fundamental level. Because if you can't get it, if you can't get buy domain names and you're completely blackballed by by organized players, that's a Mafia, in my opinion. So, uh, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, it could be done to me. Just the fact that it could be done will promote a swing in the other direction. I >>mean, independent of of, you know, again, somebody said your political views. I mean Parlor would say, Hey, we're trying to clean this stuff up now. Maybe they didn't do it fast enough, but you think about how new parlor is. You think about the early days of Twitter and Facebook, so they were sort of at a disadvantage. Trying to >>have it was it was partly was what it was. It was a right wing stand up job of standing up something quick. Their security was terrible. If you look at me and Cory Quinn on be great to have him, and he did a great analysis on this, because if you look the lawsuit was just terrible. Security was just a half, asshole. >>Well, and the experience was horrible. I mean, it's not It was not a great app, but But, like you said, it was a quick stew. Hand up, you know, for an agenda. But nonetheless, you know, to start, get to your point earlier. It's like, you know, Are they gonna, you know, shut me down? If I say something that's, you know, out of line, or how do I control that? >>Yeah, I remember, like, 2019, we involved closing sort of remarks. I was there. I was saying that these companies are gonna be too big to fail. And also, they're too big for other nations to do business with. In a way, I think MNCs are running the show worldwide. They're running the government's. They are way. Have seen the proof of that in us this year. Late last year and this year, um, Twitter last night blocked Chinese Ambassador E in us. Um, from there, you know, platform last night and I was like, What? What's going on? So, like, we used to we used to say, like the Chinese company, tech companies are in bed with the Chinese government. Right. Remember that? And now and now, Actually, I think Chinese people can say the same thing about us companies. Uh, it's not a good thing. >>Well, let's >>get some question. >>Let's get some questions from the chat. Yeah. Thank you. One is on M and a subject you mentioned them in a Who do you see is possible emanate targets. I mean, I could throw a couple out there. Um, you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. I think they're doing some really interesting things. What do you see? >>Nothing. Hashi Corp. And anybody who's doing things in the periphery is a candidate for many by the big guys, you know, by the hyper scholars and number two tier two or five hyper scholars. Right. Uh, that's why sales forces of the world and stuff like that. Um, some some companies, which I thought there will be a target, Sort of. I mean, they target they're getting too big, because off their evaluations, I think how she Corpuz one, um, >>and >>their bunch in the networking space. Uh, well, Tara, if I say the right that was acquired by at five this week, this week or last week, Actually, last week for $500 million. Um, I know they're founder. So, like I found that, Yeah, there's a lot going on on the on the network side on the anything to do with data. Uh, that those air too hard areas in the cloud arena >>data, data protection, John, any any anything you could adhere. >>And I think I mean, I think ej ej is gonna be where the gaps are. And I think m and a activity is gonna be where again, the bigger too big to fail would agree with you on that one. But we're gonna look at white Spaces and say a white space for Amazon is like a monster space for a start up. Right? So you're gonna have these huge white spaces opportunities, and I think it's gonna be an M and a opportunity big time start ups to get bought in. Given the speed on, I think you're gonna see it around databases and around some of these new service meshes and micro services. I mean, >>they there's a There's a question here, somebody's that dons asking why is Google who has the most pervasive tech infrastructure on the planet. Not at the same level of other to hyper scale is I'll give you my two cents is because it took him a long time to get their heads out of their ads. I wrote a piece of around that a while ago on they just they figured out how to learn the enterprise. I mean, John, you've made this point a number of times, but they just and I got a late start. >>Yeah, they're adding a lot of people. If you look at their who their hiring on the Google Cloud, they're adding a lot of enterprise chops in there. They realized this years ago, and we've talked to many of the top leaders, although Curry and hasn't yet sit down with us. Um, don't know what he's hiding or waiting for, but they're clearly not geared up to chicken Pete. You can see it with some some of the things that they're doing, but I mean competed the level of Amazon, but they have strength and they're playing their strength, but they definitely recognize that they didn't have the enterprise motions and people in the DNA and that David takes time people in the enterprise. It's not for the faint of heart. It's unique details that are different. You can't just, you know, swing the Google playbook and saying We're gonna home The enterprises are text grade. They knew that years ago. So I think you're going to see a good year for Google. I think you'll see a lot of change. Um, they got great people in there. On the product marketing side is Dev Solution Architects, and then the SRE model that they have perfected has been strong. And I think security is an area that they could really had a lot of value it. So, um always been a big fan of their huge network and all the intelligence they have that they could bring to bear on security. >>Yeah, I think Google's problem main problem that to actually there many, but one is that they don't They don't have the boots on the ground as compared to um, Microsoft, especially an Amazon actually had a similar problem, but they had a wide breath off their product portfolio. I always talk about feature proximity in cloud context, like if you're doing one thing. You wanna do another thing? And how do you go get that feature? Do you go to another cloud writer or it's right there where you are. So I think Amazon has the feature proximity and they also have, uh, aske Compared to Google, there's skills gravity. Larger people are trained on AWS. I think Google is trying there. So second problem Google is having is that that they're they're more focused on, I believe, um, on the data science part on their sort of skipping the cool components sort of off the cloud, if you will. The where the workloads needs, you know, basic stuff, right? That's like your compute storage and network. And that has to be well, talk through e think e think they will do good. >>Well, so later today, Paul Dillon sits down with Mids Avery of Google used to be in Oracle. He's with Google now, and he's gonna push him on on the numbers. You know, you're a distant third. Does that matter? And of course, you know, you're just a preview of it's gonna say, Well, no, we don't really pay attention to that stuff. But, John, you said something earlier that. I think Jerry Chen made this comment that, you know, Is it a winner? Take all? No, but it's a winner. Take a lot. You know the number two is going to get a big chunk of the pie. It appears that the markets big enough for three. But do you? Does Google have to really dramatically close the gap on be a much, much closer, you know, to the to the leaders in orderto to compete in this race? Or can they just kind of continue to bump along, siphon off the ad revenue? Put it out there? I mean, I >>definitely can compete. I think that's like Google's in it. Then it they're not. They're not caving, right? >>So But But I wrote I wrote recently that I thought they should even even put mawr oven emphasis on the cloud. I mean, maybe maybe they're already, you know, doubling down triple down. I just I think that is a multi trillion dollar, you know, future for the industry. And, you know, I think Google, believe it or not, could even do more. Now. Maybe there's just so much you could dio. >>There's a lot of challenges with these company, especially Google. They're in Silicon Valley. We have a big Social Justice warrior mentality. Um, there's a big debate going on the in the back channels of the tech scene here, and that is that if you want to be successful in cloud, you have to have a good edge strategy, and that involves surveillance, use of data and pushing the privacy limits. Right? So you know, Google has people within the country that will protest contract because AI is being used for war. Yet we have the most unstable geopolitical seen that I've ever witnessed in my lifetime going on right now. So, um, don't >>you think that's what happened with parlor? I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. The parlor went over the line, but I would also think that a lot of the employees, whether it's Google AWS as well, said, Hey, why are we supporting you know this and so to your point about social justice, I mean, that's not something. That >>parlor was not just social justice. They were trying to throw the government. That's Rob e. I think they were in there to get selfies and being protesters. But apparently there was evidence from what I heard in some of these clubhouse, uh, private chats. Waas. There was overwhelming evidence on parlor. >>Yeah, but my point is that the employee backlash was also a factor. That's that's all I'm saying. >>Well, we have Google is your Google and you have employees to say we will boycott and walk out if you bid on that jet I contract for instance, right, But Microsoft one from maybe >>so. I mean, that's well, >>I think I think Tom Poole's making a really good point here, which is a Google is an alternative. Thio aws. The last Google cloud next that we were asked at they had is all virtual issue. But I saw a lot of I T practitioners in the audience looking around for an alternative to a W s just seeing, though, we could talk about Mano Cloud or Multi Cloud, and Andy Jassy has his his narrative around, and he's true when somebody goes multiple clouds, they put you know most of their eggs in one basket. Nonetheless, I think you know, Google's got a lot of people interested in, particularly in the analytic side, um, in in an alternative, hedging their bets eso and particularly use cases, so they should be able to do so. I guess my the bottom line here is the markets big enough to have Really? You don't have to be the Jack Welch. I gotta be number one and number two in the market. Is that the conclusion here? >>I think so. But the data gravity and the skills gravity are playing against them. Another problem, which I didn't want a couple of earlier was Google Eyes is that they have to boot out AWS wherever they go. Right? That is a huge challenge. Um, most off the most off the Fortune 2000 companies are already using AWS in one way or another. Right? So they are the multi cloud kind of player. Another one, you know, and just pure purely somebody going 200% Google Cloud. Uh, those cases are kind of pure, if you will. >>I think it's gonna be absolutely multi cloud. I think it's gonna be a time where you looked at the marketplace and you're gonna think in terms of disaster recovery, model of cloud or just fault tolerant capabilities or, you know, look at the parlor, the next parlor. Or what if Amazon wakes up one day and said, Hey, I don't like the cubes commentary on their virtual events, so shut them down. We should have a fail over to Google Cloud should Microsoft and Option. And one of people in Microsoft ecosystem wants to buy services from us. We have toe kind of co locate there. So these are all open questions that are gonna be the that will become certain pretty quickly, which is, you know, can a company diversify their computing An i t. In a way that works. And I think the momentum around Cooper Netease you're seeing as a great connective tissue between, you know, having applications work between clouds. Right? Well, directionally correct, in my opinion, because if I'm a company, why wouldn't I wanna have choice? So >>let's talk about this. The data is mixed on that. I'll share some data, meaty our data with you. About half the companies will say Yeah, we're spreading the wealth around to multiple clouds. Okay, That's one thing will come back to that. About the other half were saying, Yeah, we're predominantly mono cloud we didn't have. The resource is. But what I think going forward is that that what multi cloud really becomes. And I think John, you mentioned Snowflake before. I think that's an indicator of what what true multi cloud is going to look like. And what Snowflake is doing is they're building abstraction, layer across clouds. Ed Walsh would say, I'm standing on the shoulders of Giants, so they're basically following points of presence around the globe and building their own cloud. They call it a data cloud with a global mesh. We'll hear more about that later today, but you sign on to that cloud. So they're saying, Hey, we're gonna build value because so many of Amazon's not gonna build that abstraction layer across multi clouds, at least not in the near term. So that's a really opportunity for >>people. I mean, I don't want to sound like I'm dating myself, but you know the date ourselves, David. I remember back in the eighties, when you had open systems movement, right? The part of the whole Revolution OS I open systems interconnect model. At that time, the networking stacks for S N A. For IBM, decadent for deck we all know that was a proprietary stack and then incomes TCP I p Now os I never really happened on all seven layers, but the bottom layers standardized. Okay, that was huge. So I think if you look at a W s or some of the comments in the chat AWS is could be the s n a. Depends how you're looking at it, right? And you could say they're open. But in a way, they want more Amazon. So Amazon's not out there saying we love multi cloud. Why would they promote multi cloud? They are a one of the clouds they want. >>That's interesting, John. And then subject is a cloud architect. I mean, it's it is not trivial to make You're a data cloud. If you're snowflake, work on AWS work on Google. Work on Azure. Be seamless. I mean, certainly the marketing says that, but technically, that's not trivial. You know, there are latent see issues. Uh, you know, So that's gonna take a while to develop. What? Do your thoughts there? >>I think that multi cloud for for same workload and multi cloud for different workloads are two different things. Like we usually put multiple er in one bucket, right? So I think you're right. If you're trying to do multi cloud for the same workload, that's it. That's Ah, complex, uh, problem to solve architecturally, right. You have to have a common ap ice and common, you know, control playing, if you will. And we don't have that yet, and then we will not have that for a for at least one other couple of years. So, uh, if you if you want to do that, then you have to go to the lower, lowest common denominator in technical sort of stock, if you will. And then you're not leveraging the best of the breed technology off their from different vendors, right? I believe that's a hard problem to solve. And in another thing, is that that that I always say this? I'm always on the death side, you know, developer side, I think, uh, two deaths. Public cloud is a proxy for innovative culture. Right. So there's a catch phrase I have come up with today during shower eso. I think that is true. And then people who are companies who use the best of the breed technologies, they can attract the these developers and developers are the Mazen's off This digital sort of empires, amazingly, is happening there. Right there they are the Mazen's right. They head on the bricks. I think if you don't appeal to developers, if you don't but extensive for, like, force behind educating the market, you can't you can't >>put off. It's the same game Stepping story was seeing some check comments. Uh, guard. She's, uh, linked in friend of mine. She said, Microsoft, If you go back and look at the Microsoft early days to the developer Point they were, they made their phones with developers. They were a software company s Oh, hey, >>forget developers, developers, developers. >>You were if you were in the developer ecosystem, you were treated his gold. You were part of the family. If you were outside that world, you were competitors, and that was ruthless times back then. But they again they had. That was where it was today. Look at where the software defined businesses and starve it, saying it's all about being developer lead in this new way to program, right? So the cloud next Gen Cloud is going to look a lot like next Gen Developer and all the different tools and techniques they're gonna change. So I think, yes, this kind of developer ecosystem will be harnessed, and that's the power source. It's just gonna look different. So, >>Justin, Justin in the chat has a comment. I just want to answer the question about elastic thoughts on elastic. Um, I tell you, elastic has momentum uh, doing doing very well in the market place. Thea Elk Stack is a great alternative that people are looking thio relative to Splunk. Who people complain about the pricing. Of course it's plunks got the easy button, but it is getting increasingly expensive. The problem with elk stack is you know, it's open source. It gets complicated. You got a shard, the databases you gotta manage. It s Oh, that's what Ed Walsh's company chaos searches is all about. But elastic has some riel mo mentum in the marketplace right now. >>Yeah, you know, other things that coming on the chat understands what I was saying about the open systems is kubernetes. I always felt was that is a bad metaphor. But they're with me. That was the TCP I peep In this modern era, C t c p I p created that that the disruptor to the S N A s and the network protocols that were proprietary. So what KUBERNETES is doing is creating a connective tissue between clouds and letting the open source community fill in the gaps in the middle, where kind of way kind of probably a bad analogy. But that's where the disruption is. And if you look at what's happened since Kubernetes was put out there, what it's become kind of de facto and standard in the sense that everyone's rallying around it. Same exact thing happened with TCP was people were trashing it. It is terrible, you know it's not. Of course they were trashed because it was open. So I find that to be very interesting. >>Yeah, that's a good >>analogy. E. Thinks the R C a cable. I used the R C. A cable analogy like the VCRs. When they started, they, every VC had had their own cable, and they will work on Lee with that sort of plan of TV and the R C. A cable came and then now you can put any TV with any VCR, and the VCR industry took off. There's so many examples out there around, uh, standards And how standards can, you know, flair that fire, if you will, on dio for an industry to go sort of wild. And another trend guys I'm seeing is that from the consumer side. And let's talk a little bit on the consuming side. Um, is that the The difference wouldn't be to B and B to C is blood blurred because even the physical products are connected to the end user Like my door lock, the August door lock I didn't just put got get the door lock and forget about that. Like I I value the expedience it gives me or problems that gives me on daily basis. So I'm close to that vendor, right? So So the middle men, uh, middle people are getting removed from from the producer off the technology or the product to the consumer. Even even the sort of big grocery players they have their APs now, uh, how do you buy stuff and how it's delivered and all that stuff that experience matters in that context, I think, um, having, uh, to be able to sell to thes enterprises from the Cloud writer Breuder's. They have to have these case studies or all these sample sort off reference architectures and stuff like that. I think whoever has that mawr pushed that way, they are doing better like that. Amazon is Amazon. Because of that reason, I think they have lot off sort off use cases about on top of them. And they themselves do retail like crazy. Right? So and other things at all s. So I think that's a big trend. >>Great. Great points are being one of things. There's a question in there about from, uh, Yaden. Who says, uh, I like the developer Lead cloud movement, But what is the criticality of the executive audience when educating the marketplace? Um, this comes up a lot in some of my conversations around automation. So automation has been a big wave to automate this automate everything. And then everything is a service has become kind of kind of the the executive suite. Kind of like conversation we need to make everything is a service in our business. You seeing people move to that cloud model. Okay, so the executives think everything is a services business strategy, which it is on some level, but then, when they say Take that hill, do it. Developers. It's not that easy. And this is where a lot of our cube conversations over the past few months have been, especially during the cova with cute virtual. This has come up a lot, Dave this idea, and start being around. It's easy to say everything is a service but will implement it. It's really hard, and I think that's where the developer lead Connection is where the executive have to understand that in order to just say it and do it are two different things. That digital transformation. That's a big part of it. So I think that you're gonna see a lot of education this year around what it means to actually do that and how to implement it. >>I'd like to comment on the as a service and subject. Get your take on it. I mean, I think you're seeing, for instance, with HP Green Lake, Dell's come out with Apex. You know IBM as its utility model. These companies were basically taking a page out of what I what I would call a flawed SAS model. If you look at the SAS players, whether it's salesforce or workday, service now s a P oracle. These models are They're really They're not cloud pricing models. They're they're basically you got to commit to a term one year, two year, three year. We'll give you a discount if you commit to the longer term. But you're locked in on you. You probably pay upfront. Or maybe you pay quarterly. That's not a cloud pricing model. And that's why I mean, they're flawed. You're seeing companies like Data Dog, for example. Snowflake is another one, and they're beginning to price on a consumption basis. And that is, I think, one of the big changes that we're going to see this decade is that true cloud? You know, pay by the drink pricing model and to your point, john toe, actually implement. That is, you're gonna need a whole new layer across your company on it is quite complicated it not even to mention how you compensate salespeople, etcetera. The a p. I s of your product. I mean, it is that, but that is a big sea change that I see coming. Subject your >>thoughts. Yeah, I think like you couldn't see it. And like some things for this big tech exacts are hidden in the plain >>sight, right? >>They don't see it. They they have blind spots, like Look at that. Look at Amazon. They went from Melissa and 200 millisecond building on several s, Right, Right. And then here you are, like you're saying, pay us for the whole year. If you don't use the cloud, you lose it or will pay by month. Poor user and all that stuff like that that those a role models, I think these players will be forced to use that term pricing like poor minute or for a second, poor user. That way, I think the Salesforce moral is hybrid. They're struggling in a way. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform for other people to build on top off. But they're having a little trouble there because because off there, such pricing and little closeness, if you will. And, uh, again, I'm coming, going, going back to developers like, if you are not appealing to developers who are writing the latest and greatest code and it is open enough, by the way open and open source are two different things that we all know that. So if your platform is not open enough, you will have you know, some problems in closing the deals. >>E. I want to just bring up a question on chat around from Justin didn't fitness. Who says can you touch on the vertical clouds? Has your offering this and great question Great CP announcing Retail cloud inventions IBM Athena Okay, I'm a huge on this point because I think this I'm not saying this for years. Cloud computing is about horizontal scalability and vertical specialization, and that's absolutely clear, and you see all the clouds doing it. The vertical rollouts is where the high fidelity data is, and with machine learning and AI efforts coming out, that's accelerated benefits. There you have tow, have the vertical focus. I think it's super smart that clouds will have some sort of vertical engine, if you will in the clouds and build on top of a control playing. Whether that's data or whatever, this is clearly the winning formula. If you look at all the successful kind of ai implementations, the ones that have access to the most data will get the most value. So, um if you're gonna have a data driven cloud you have tow, have this vertical feeling, Um, in terms of verticals, the data on DSO I think that's super important again, just generally is a strategy. I think Google doing a retail about a super smart because their whole pitches were not Amazon on. Some people say we're not Google, depending on where you look at. So every of these big players, they have dominance in the areas, and that's scarce. Companies and some companies will never go to Amazon for that reason. Or some people never go to Google for other reasons. I know people who are in the ad tech. This is a black and we're not. We're not going to Google. So again, it is what it is. But this idea of vertical specialization relevant in super >>forts, I want to bring to point out to sessions that are going on today on great points. I'm glad you asked that question. One is Alan. As he kicks off at 1 p.m. Eastern time in the transformation track, he's gonna talk a lot about the coming power of ecosystems and and we've talked about this a lot. That that that to compete with Amazon, Google Azure, you've gotta have some kind of specialization and vertical specialization is a good one. But of course, you see in the big Big three also get into that. But so he's talking at one o'clock and then it at 3 36 PM You know this times are strange, but e can explain that later Hillary Hunter is talking about she's the CTO IBM I B M's ah Financial Cloud, which is another really good example of specifying vertical requirements and serving. You know, an audience subject. I think you have some thoughts on this. >>Actually, I lost my thought. E >>think the other piece of that is data. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise around data that >>billions of dollars in >>their day there's billions of dollars and that's the title of the session. But we did the trillion dollar baby post with Jazzy and said Cloud is gonna be a trillion dollars right? >>And and the point of Alan Answer session is he's thinking from an individual firm. Forget the millions that you're gonna save shifting to the cloud on cost. There's billions in ecosystems and operating models. That's >>absolutely the business value. Now going back to my half stack full stack developer, is the business value. I've been talking about this on the clubhouses a lot this past month is for the entrepreneurs out there the the activity in the business value. That's the new the new intellectual property is the business logic, right? So if you could see innovations in how work streams and workflow is gonna be a configured differently, you have now large scale cloud specialization with data, you can move quickly and take territory. That's much different scenario than a decade ago, >>at the point I was trying to make earlier was which I know I remember, is that that having the horizontal sort of features is very important, as compared to having vertical focus. You know, you're you're more healthcare focused like you. You have that sort of needs, if you will, and you and our auto or financials and stuff like that. What Google is trying to do, I think that's it. That's a good thing. Do cook up the reference architectures, but it's a bad thing in a way that you drive drive away some developers who are most of the developers at 80 plus percent, developers are horizontal like you. Look at the look into the psyche of a developer like you move from company to company. And only few developers will say I will stay only in health care, right? So I will only stay in order or something of that, right? So they you have to have these horizontal capabilities which can be applied anywhere on then. On top >>of that, I think that's true. Sorry, but I'll take a little bit different. Take on that. I would say yes, that's true. But remember, remember the old school application developer Someone was just called in Application developer. All they did was develop applications, right? They pick the framework, they did it right? So I think we're going to see more of that is just now mawr of Under the Covers developers. You've got mawr suffer defined networking and software, defined storage servers and cloud kubernetes. And it's kind of like under the hood. But you got your, you know, classic application developer. I think you're gonna see him. A lot of that come back in a way that's like I don't care about anything else. And that's the promise of cloud infrastructure is code. So I think this both. >>Hey, I worked. >>I worked at people solved and and I still today I say into into this context, I say E r P s are the ultimate low code. No code sort of thing is right. And what the problem is, they couldn't evolve. They couldn't make it. Lightweight, right? Eso um I used to write applications with drag and drop, you know, stuff. Right? But But I was miserable as a developer. I didn't Didn't want to be in the applications division off PeopleSoft. I wanted to be on the tools division. There were two divisions in most of these big companies ASAP. Oracle. Uh, like companies that divisions right? One is the cooking up the tools. One is cooking up the applications. The basketball was always gonna go to the tooling. Hey, >>guys, I'm sorry. We're almost out of time. I always wanted to t some of the sections of the day. First of all, we got Holder Mueller coming on at lunch for a power half hour. Um, you'll you'll notice when you go back to the home page. You'll notice that calendar, that linear clock that we talked about that start times are kind of weird like, for instance, an appendix coming on at 1 24. And that's because these air prerecorded assets and rather than having a bunch of dead air, we're just streaming one to the other. So so she's gonna talk about people, process and technology. We got Kathy Southwick, whose uh, Silicon Valley CEO Dan Sheehan was the CEO of Dunkin Brands and and he was actually the c 00 So it's C A CEO connecting the dots to the business. Daniel Dienes is the CEO of you I path. He's coming on a 2:47 p.m. East Coast time one of the hottest companies, probably the fastest growing software company in history. We got a guy from Bain coming on Dave Humphrey, who invested $750 million in Nutanix. He'll explain why and then, ironically, Dheeraj Pandey stew, Minuteman. Our friend interviewed him. That's 3 35. 1 of the sessions are most excited about today is John McD agony at 403 p. M. East Coast time, she's gonna talk about how to fix broken data architectures, really forward thinking stuff. And then that's the So that's the transformation track on the future of cloud track. We start off with the Big Three Milan Thompson Bukovec. At one oclock, she runs a W s storage business. Then I mentioned gig therapy wrath at 1. 30. He runs Azure is analytics. Business is awesome. Paul Dillon then talks about, um, IDs Avery at 1 59. And then our friends to, um, talks about interview Simon Crosby. I think I think that's it. I think we're going on to our next session. All right, so keep it right there. Thanks for watching the Cuban cloud. Uh huh.

Published Date : Jan 22 2021

SUMMARY :

cloud brought to you by silicon angle, everybody I was negative in quarantine at a friend's location. I mean, you go out for a walk, but you're really not in any contact with anybody. And I think we're in a new generation. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy But the goal here is to just showcase it's Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. that will take you into the chat, we'll take you through those in a moment and share with you some of the guests And then from there you just It was just awesome. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, And if you weren't a digital business, you were kind of out of business. last 10 years defined by you know, I t transformation. And if you look at some of the main trends in the I think the second thing is you can see on this data. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, So you know, as you're doing trends job, they're just it's just pedal as fast as you can. It's a measure of the pervasiveness or, you know, number of mentions in the data set. And I think that chart demonstrates that there, in there in the hyper scale leadership category, is they're, you know, they're just good enough. So we'll get to those So just just real quick Here you see this hybrid zone, this the field is bunched But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second Can you hear us? So the first question, Um, we'll still we'll get the student second. Thanks for taking the time with us. I mean, what do you guys see? I think that discussion has to take place. I think m and a activity really will pick up. I mean, can you use a I to find that stuff? So if I wanted to reset the world stage, you know what better way than the, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, mean, independent of of, you know, again, somebody said your political views. and he did a great analysis on this, because if you look the lawsuit was just terrible. But nonetheless, you know, to start, get to your point earlier. you know, platform last night and I was like, What? you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. for many by the big guys, you know, by the hyper scholars and if I say the right that was acquired by at five this week, And I think m and a activity is gonna be where again, the bigger too big to fail would agree with Not at the same level of other to hyper scale is I'll give you network and all the intelligence they have that they could bring to bear on security. The where the workloads needs, you know, basic stuff, right? the gap on be a much, much closer, you know, to the to the leaders in orderto I think that's like Google's in it. I just I think that is a multi trillion dollar, you know, future for the industry. So you know, Google has people within the country that will protest contract because I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. I think they were in there to get selfies and being protesters. Yeah, but my point is that the employee backlash was also a factor. I think you know, Google's got a lot of people interested in, particularly in the analytic side, is that they have to boot out AWS wherever they go. I think it's gonna be a time where you looked at the marketplace and you're And I think John, you mentioned Snowflake before. I remember back in the eighties, when you had open systems movement, I mean, certainly the marketing says that, I think if you don't appeal to developers, if you don't but extensive She said, Microsoft, If you go back and look at the Microsoft So the cloud next Gen Cloud is going to look a lot like next Gen Developer You got a shard, the databases you gotta manage. And if you look at what's happened since Kubernetes was put out there, what it's become the producer off the technology or the product to the consumer. Okay, so the executives think everything is a services business strategy, You know, pay by the drink pricing model and to your point, john toe, actually implement. Yeah, I think like you couldn't see it. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform the ones that have access to the most data will get the most value. I think you have some thoughts on this. Actually, I lost my thought. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise But we did the trillion dollar baby post with And and the point of Alan Answer session is he's thinking from an individual firm. So if you could see innovations Look at the look into the psyche of a developer like you move from company to company. And that's the promise of cloud infrastructure is code. I say E r P s are the ultimate low code. Daniel Dienes is the CEO of you I path.

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Simon Crosby Dirty | Cube On Cloud


 

>> Hi, I'm Stu Miniman, and welcome back to theCUBE on Cloud talking about really important topics as to how developers, were changing how they build their applications, where they live, of course, long discussion we've had for a number of years. You know, how do things change in hybrid environments? We've been talking for years, public cloud and private cloud, and really excited for this session. We're going to talk about how edge environment and AI impact that. So happy to welcome back one of our CUBE alumni, Simon Crosby, is currently the Chief Technology Officer with Swim. He's got plenty of viewpoints on AI, the edge and knows the developer world well. Simon, welcome back. Thanks so much for joining us. >> Thank you, Stu, for having me. >> All right, so let's start for a second. Let's talk about developers. You know, it used to be, you know, for years we talked about, you know, what's the level of abstraction we get. Does it sit, you know, do I put it on bare metal? Do I virtualize it? Do I containerize it? Do I make it serverless? A lot of those things, you know that the app developer doesn't want to even think about but location matters a whole lot when we're talking about things like AI where do I have all my data that I could do my training? Where do I actually have to do the processing? And of course, edge just changes by orders of magnitude. Some of the things like latency and where data lives and everything like that. So with that as a setup, would love to get just your framework as to what you're hearing from developers and what we'll get into some of the solutions that you and your team are helping them to do their jobs. >> Well, you're absolutely right, Stu. The data onslaught is very real. Companies that I deal with are facing more and more real-time data from products from their infrastructure, from their partners whatever it happens to be and they need to make decisions rapidly. And the problem that they're facing is that traditional ways of processing that data are too slow. So perhaps the big data approach, which by now is a bit old, it's a bit long in the tooth, where you store data and then you analyze it later, is problematic. First of all, data streams are boundless. So you don't really know when to analyze, but second you can't store it all. And so the store then analyze approach has to change and Swim is trying to do something about this by adopting a process of analyze on the fly, so as data is generated, as you receive events you don't bother to store them. You analyze them, and then if you have to, you store the data, but you need to analyze as you receive data and react immediately to be able to generate reasonable insights or predictions that can drive commerce and decisions in the real world. >> Yeah absolutely. I remember back in the early days of big data, you know, real time got thrown around a little but it was usually I need to react fast enough to make sure we don't lose the customer, react to something, but it was, we gather all the data and let's move compute to the data. Today as you talk about, you know, real time streams are so important. We've been talking about observability for the last couple of years to just really understand the systems and the outputs more than looking back historically at where things were waiting for alerts. So could you give us some examples if you would, as to you know, those streams, you know, what is so important about being able to interact and leverage that data when you need it? And boy, it's great if we can use it then and not have to store it and think about it later, obviously there's some benefits there, because-- >> Well every product nowadays has a CPU, right? And so there's more and more data. And just let me give you an example, Swim processes real-time data from more than a hundred million mobile devices in real time, for a mobile operator. And what we're doing there is we're optimizing connection quality between devices and the network. Now that volume of data is more than four petabytes per day, okay. Now there is simply no way you can ever store that and analyze it later. The interesting thing about this is that if you adopt and analyze, and then if you really have to store architecture, you get to take advantage of Moore's Law. So you're running at CPU memory speeds instead of at disk speed. And so that gives you a million fold speed up, and it also means you don't have the latency problem of reaching out to, or about storage, database, or whatever. And so that reduces costs. So we can do it on about 10% of the infrastructure that they previously had for Hadoop style implementation. >> So, maybe it would help if we just explain. When we say edge people think of a lot of different things, is it, you know an IOT device sitting out at the edge? Are we talking about the Telecom edge? We've been watching AWS for years, you know, spider out their services and into various environments. So when you talk about the type of solutions you're doing and what your customers have, is it the Telecom edge? Is it the actual device edge, you know, where does processing happen and where do these you know, services that work on it live? >> So I think the right way to think about edge is where can you reasonably process the data? And it obviously makes sense to process data at the first opportunity you have, but much data is encrypted between the original device, say, and the application. And so edge as a place doesn't make as much sense as edge as an opportunity to decrypt and analyze data in the clear. So edge computing is not so much a place in my view as the first opportunity you have to process data in the clear and to make sense of it. And then edge makes sense, in terms of latency, by locating, compute, as close as possible to the sources of data, to reduce latency and maximize your ability to get insights and return them to users, you know, quickly. So edge for me often is the cloud. >> Excellent, one of the other things I think about back from, you know, the big data days or even earlier, it was that how long it took to get from the raw data to processing that data, to be able to getting some insight, and then being able to take action. It sure sounds like we're trying to collapse that completely, is that, you know, how do we do that? You know, can we actually, you know, build the system so that we can, you know, in that real time, continuous model that you talk about, you know. Take care of it and move on. >> So one of the wonderful things, one of the wonderful things about cloud computing is that two major abstractions have really served us. And those are rest, which is static disk computing, and databases. And rest means any old server can do the job for me and then the database is just an API call away. The problem with that is that it's desperately slow. So when I say desperately slow, I mean, it's probably thrown away the last 10 years of Moore's law. Just think about it this way. Your CPU runs at gigahertz and the network runs at milliseconds. So by definition, every time you reach out to a data store you're going a million times slower than your CPU. That's terrible. It's absolutely tragic, okay. So a model which is much more effective is to have an in-memory computer architecture in which you engage in staple computation. So instead of having to reach out to a database every time to update the database and whatever, you know, store something, and then fetch it again a few moments later when the next event arrives, you keep state in memory and you compute on the fly as data arrives. And that way you get a million times speed up. You also end up with this tremendous cost reduction because you don't end up with as many instances having to compute, by comparison. So let me give you a quick example. If you go to a traffic.swim.ai you can see the real time state of the traffic infrastructure in Palo Alto. And each one of those intersections is predicting its own future. Now, the volume of data from just a few hundred lights in Palo Alto is about four terabytes a day. And sure you can deal with this in AWS Lambda. There are lots and lots of servers up there. But the problem is that the end to end per event latency is about 100 milliseconds. And, you know, if I'm dealing with 30,000 events a second, that's just too much. So solving that problem with a stateless architecture is extraordinarily expensive, more than $5,000 a month. Whereas the staple architecture which you could think of as an evolution of, you know, something reactive or the actor model, gets you, you know something like a 10th of the cost, okay. So cloud is fabulous for things that need to scale wide but a staple model is required for dealing with things which update you rapidly or regularly about their changes in state. >> Yeah, absolutely. You know, I think about if, I mentioned before AI training models, often, if you look at something like autonomous vehicles, the massive amounts of data that it needs to process, you know, has to happen in the public cloud. But then that gets pushed back down to the end device, in this case it's a car, because it needs to be able to react in real time and gets fed at a regular update, the new training algorithms that it has there. What are you seeing-- >> I have strong reason on this training approach and data science in general, and that is that there aren't enough data scientists or, you know, smart people to train these algorithms, deploy them to the edge and so on. And so there is an alternative worldview which is a much simpler one and that is that relatively simple algorithms deployed at scale to staple representatives, let's call them digital twins of things, can deliver enormous improvements in behavior as things learn for themselves. So the way I think the, at least this edge world, gets smarter is that relatively simple models of things will learn for themselves, create their own futures, based on what they can see and then react. And so this idea that we have lots and lots of data scientists dealing with vast amounts of information in the cloud is suitable for certain algorithms but it doesn't work for the vast majority of applications. >> So where are we with the state of what, what do developers need to think about? You mentioned that there's compute in most devices. That's true, but, you know, do they need some special Nvidia chip set out there? Are there certain programming languages that you are seeing more prevalent, interoperability, give us a little bit of, you know, some tips and tricks for those developing. >> Super, so number one, a staple architecture is fundamental and sure React is well known and there are ACA for example, and Spurling. Swim is another so I'm going to use some language and I would encourage you to look at swimos.org to go from play there. A staple architecture, which allows actors, small concurrent objects to stapely evolve their own state based on updates from the real world is fundamental. By the way, in Swim we use data to build these models. So these little agents, for things, we call them web agents because the object ID is a URI, they stapley evolve by processing their own real-world data, stapley representing it, And then they do this wonderful thing which is build a model on the fly. And they build a model by linking to things that they're related to. So a need section would link to all of its sensors but it would also link to all of its neighbors because the neighbors and linking is like a sub in Pub/Sub, and it allows that web agent then to continually analyze, learn, and predict on the fly. And so every one of these concurrent objects is doing this job of analyzing its own raw data and then predicting from that and streaming the result. So in Swim, you get streamed raw data in and what streams out is predictions, predictions about the future state of the infrastructure. And that's a very powerful staple approach which can run all their memory, no storage required. By the way, it's still persistent, so if you lose a node, you can just come back up and carry on but there's no need to store huge amounts of raw data if you don't need it. And let me just be clear. The volumes of raw data from the real world are staggering, right? So four terabytes a day from Palo Alto, but Las Vegas about 60 terabytes a day from the traffic lights. More than 100 million mobile devices is tens of petabytes per day, which is just too much to store. >> Well, Simon, you've mentioned that we have a shortage when it comes to data scientists and the people that can be involved in those things. How about from the developers side, do most enterprises that you're talking to do they have the skillset? Is the ecosystem mature enough for the company to get involved? What do we need to do looking forward to help companies be able to take advantage of this opportunity? >> Yeah, so there is this huge challenge in terms of, I guess, just cloud native skills. And this is exacerbated the more you get added to. I guess what you could think of is traditional kind of companies, all of whom have tons and tons of data sources. So we need to make it easy and Swim tries to do this by effectively using skills that people already have, Java or JavaScript, and giving them easy ways to develop, deploy, and then run applications without thinking about them. So instead of binding developers to notions of place and where databases are and all that sort of stuff if they can write simple object-oriented programs about things like intersections and push buttons, and pedestrian lights, and inroad loops and so on, and simply relate basic objects in the world to each other then we let data build the model by essentially creating these little concurrent objects for each thing, and they will then link to each other and solve the problem. We end up solving a huge problem for developers too, which is that they don't need to acquire complicated cloud-native skillsets to get to work. >> Well absolutely, Simon, it's something we've been trying to do for a long time is to truly simplify things. Want to let you have the final word. If you look out there, the opportunity, the challenge in the space, what final takeaways would you give to our audience? >> So very simple. If you adopt a staple competing architecture, like Swim, you get to go a million times faster. The applications always have an answer. They analyze, learn and predict on the fly and they go a million times faster. They use 10% less, no, sorry, 10% of the infrastructure of a store than analyze approach. And it's the way of the future. >> Simon Crosby, thanks so much for sharing. Great having you on the program. >> Thank you, Stu. >> And thank you for joining I'm Stu Miniman, thank you, as always, for watching theCUBE.

Published Date : Jan 5 2021

SUMMARY :

So happy to welcome back that you and your team and then you analyze it and leverage that data when you need it? And so that gives you a Is it the actual device edge, you know, at the first opportunity you have, so that we can, you and whatever, you know, store something, you know, has to happen or, you know, smart people that you are seeing more and I would encourage you for the company to get involved? the more you get added to. Want to let you have the final word. And it's the way of the future. Great having you on the program. And thank you for

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Dheeraj Pandey, Nutanix | CUBE On Cloud


 

>> Hi, and this is theCUBE on Cloud. I'm Stu Miniman and really excited to welcome to a special Fireside Chat. CUBE Alumni has been on the program so many times. We always love talking to founders. We like talking to deep thinkers and that's why he was one of the early ones that I reached out to when we were working on this event. When we first started conversations, we were looking at how hyperscalers really were taking adoption of the brand new technologies, things like flash, things like software defined networking, and how that would invade the enterprise. That of course has had a huge impact, help create a category called hyperconverged infrastructure and I'm talking about Dheeraj Pandey. He is the founder, chairman, and CEO of Nutanix, taking HCI from hyperconverged infrastructure to hybrid cloud infrastructure. So Dheeraj, welcome to the Fireside Chat. Thank you so much for joining us. >> Thank you, Stu, and thank you for the last 10 years that we've grown together, both theCUBE and Nutanix and myself as a leader in the last 10 years. So bringing HCI from hyperconverged to hybrid cloud just reminds me of how the more things change, the more they remain the same. So looking forward to a great discussion here. >> So talk about that early discussion, what the hyperscalers were doing, how can the enterprise take advantage of that? Over time, enterprise has matured and looked a little bit more like the hyperscalers. Hybrid cloud of course is on everyone's lip, as well as we've seen the hyperscalers themselves look more and more like the enterprise. So hybrid and multicloud is where we are today. We think it'll be in the future. But give us a little bit as to how you've seen that progression today and where are we going down the road here? >> Yeah, I think I talked about this during my .NEXT keynote. And the whole idea of, in every recession, we make things smaller. In '91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year 2000 when there was the next bubble burst and the recession afterwards, we moved from Unix servers to Wintel: Windows and Intel, x86 and eventually Linux as well. Again we made things smaller going from million dollar servers to $5,000 servers, shorter lived servers. And that's what we did in 2008/2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There is nothing in the physical world that actually went lives. But we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade, they're going to make it even smaller, not just in space which is size with functions and containers and virtual machines, but also in time. So space and time, we're talking about hourly billing and monthly billing and a one-year term as opposed to really going and committing to five or seven years of hardware and CapEx. So I think as you make things smaller, I mean, and this is true for as consumers, we have short retention spans, things are going fast. The cycle of creative destruction of virtual machines is shrinking as well. So I think in many cases, we know we've gone and created this autonomy, massive sprawl. Like we created a massive sprawl of Intel servers back in '95 and 2005. Then we have to use virtualization to go and consolidate all of it, created beautiful data centers of Intel servers with VMware software. And then we created a massive sprawl of data centers, of consolidated data centers with one click private cloud in the last five years and hopefully in the next five too. But I think we're also now creating a proliferation of clouds. There is a sprawl, massive sprawl of cost centers and such. So we need yet another layer of software for governance to reign in on that chaos, hence the need for a new HCI, hybrid cloud infrastructure. >> Yeah, it's fascinating to kind of watch that progression over time. There was a phenomenal Atlantic article. I think it was from like the 1940s or 1950s where somebody took what was happening post-World War II and projected things out. We're talking really pre the internet, but just the miniaturization and the acceleration, kind of the Moore's law discussion. If you take things out, where it would go. When I talked to Amazon, they said the one thing that we know for sure, I'm talking to Amazon.com is that people will want it faster and cheaper in the future. I don't know which robot or drone or things that they have. But absolutely there are those certain characteristics. So from a leadership standpoint, Dheeraj, talk about these changes? We had the wave of virtualization, the wave of containerization, you talked about functions in serverless. Those are tools. But at the end of the day, it's about the outcomes and how do we take advantage of things? So how as a leader do you make sure that you know where to take the company as these technology waves and changes impact what you're doing? >> Yeah, it's a great point. I mean, we celebrate things in IT a lot, but we don't talk about what does it take? What's the underlying fabric to really use these things successfully and better than others and not just use buzzwords, because new buzzwords will come in the next three years. For example AI and ML has been a great buzzword for the last three, four years. But there's very few companies, probably less than even half a percent who know how to leverage machine learning, even understand the difference between machine learning and AI. And a lot of it comes down to a few principles. There's a culture principles, not the least of which is how you celebrate failure, because now you're doing shorter, smaller things. You've got a more agile, you'll have more velocity. Gone are the days of waterfall where you're doing yearly planning and pre-year releases and such. So as we get into this new world, not everything will be perfect, and you've got to really learn to pick yourself up and recover quickly, heal quickly and such. So that is the fundamental tenet of Silicon Valley. And we got to really go and use this more outside the Valley as well in every company out there. Whether it's East Coast company, the Midwest company that are outside the U.S. I think this idea that you will be vulnerable, more vulnerable as you go and learn to do things faster and shorter. I think product management is a term that we don't fully understand, and this is about the why before the how and the what. We quickly jump to the what: containers and functions and databases, servers, and AI, and ML, they're the what. But how do you really start with the why? You know my fascination for one of my distant mentors, Simon Sinek and how he thinks about most companies just focusing on the what, while very few actually start with why, then the how, then the what itself. And product management has to play a key role in this, which also subsumes design, thinking about simplification and elegance and reducing friction. I think again, very few companies, probably no more than 1% of the companies really understand what it means to start with design and APIs, user experience APIs for developers before you even get to writing any single line of code. So I think to me, that's leadership. When you can stay away from instant gratification of the end result, but start with the why, then the how, then the what. >> Yeah, as we know in the technology space, oftentimes the technology is the easy part. It's helping to drive that change. I think back to the early days when we were talking, it was, hyperconverge, it was a threat to storage. We're going to put you out of a job. And we'd always go and say, "Look, no, no, no. We're not putting you out of a job. We're going to free you up to do the things that you want to do. That security project that's been sitting on the shelf for six months, you can go do that. Helping build new parts of the business. Those things that you can do." It's that shifting a mindset can be so difficult. And Dheeraj, I mean, you look at 2020, everyone has had to shift their mindset for everything. I was spending half my time on the road. I don't miss the hotels. I do miss seeing lots and lots of people in person. So what's your advice for people, how they can stay malleable, be open to some change? What are you seeing out there? What advice do you give there? >> Yeah, I think, as you said, inertia is at the core of most things in our lives, including what we saw in healthcare for the last 20, 30 years. I mean, there was so much regulation. The doctor's community had to move forward, nurses had to move forward. I mean, not just providers, but insurance companies. And finally, all of a sudden, we're talking about telehealth because of the pandemic. We are talking about online learning. I mean the things that higher ed refused to do. I mean if you think about the last 20 years of what had happened with the cost of higher ed, I mean it's 200% growth when the cost of television has gone down by probably 100, 200% with more features. Healthcare, higher ed, education in general, all of a sudden is coming for this deep shock because of the pandemic. And I think it's these kind of black swan moments that really changed the world. And I know it's a cliche to say this. But I feel like we are going to be in a new normal, and we have been forced to this new change of digital. I mean, you and I are sitting and talking over the internet. It's a little awkward right now because there's a little bit of a delay in the way I'm looking at things. But I know it's going to directionally be right. I mean, we will go in a way where it just become seamless over time. So change is the only constant. And I believe that I think what we've seen in the pandemic is just the beginning of what digital will mean going forward. And I think the more people embrace it, the faster we do it. Speed is going to be the name of the game when it comes to survival and thriving in this new age. >> Dheeraj, it's interesting. We do hope, I'm a technologist. I know you're an optimist when it comes to things. So we always look at those silver linings. Like I hope healthcare and education will be able to move forward fast. Higher education costs, inequity out there for access to medicine. It would be wonderful if we could help solve some of that, despite this global pandemic. One of the other results, Dheeraj, we talked about some very shifts in the marketplace, the large tech players really have emerged in winter so far in 2020. I can't help, but watch the stock market. And Apple is bigger than ever, Amazon, Google, all ended up in front of Congress to talk about if they've gotten too big. You've partnered with Amazon, Microsoft, and Google. They are potentially a threat but also a partner. From your standpoint, have they gotten too much power? Do we have an inequity in the tech world that they are creating the universes that they will just kind of block off and limit innovation? What's your take on big tech? >> Yeah, I mean, I feel like there's always been big something. I mean, if you go back to the '90s, Amazon, not Amazon, IBM was big, and Microsoft was big, and AT&T was big. I mean, there's always been big companies because the consumer effect that they've had as well, I mean. And I think what we're seeing right now is no different. I mean, at the end of the day, the great thing about this country is that there's always disruption happening. And sometimes small is way better and way more competitive than big. Now at the same time, I do look up to the way some of them have organized themselves. Like the way Amazon has organized itself is really unique and creative with general managers and very independent, highly autonomous groups. So some of these organizations will definitely survive and thrive in scale. And yet for others, I think decision-making and staying competitive and staying scrappy will come a lot harder. So to me when I look at these big names and what Congress is talking about and such, I feel like there's no different than 20, 30, 40 years ago. I mean, we talked about Rockefeller and the oil giants back from 100 years ago. And so in many ways, I mean, the more things change, the more they remain the same. All we have to do is we have to walk over to where the customer is. And that's what we've done with the partnerships. Like in Amazon and Azure, we're saying look, we can even use your commits and credits. I mean, that is a very elegant way to go to where the customer is, rather than force them to where we are. And the public cloud is facing this too. They've come to realize in the last two years that they cannot force all of enterprise computing to come to hyperscalers data centers. They'll have to take in these bite-size smaller clouds to where the customer is, where the customer's machines are, where the customers people are, where the customers data is. That's where we also take to disperse the cloud itself. So I think there's going to be a yin yang where we'll try to walk with the customer to where we want them to be, whether it's hyperscaler data center or the notion of hybrid cloud infrastructure. But many a time, we've got to walk over to where they are. I mean, and outside the U.S, I mean, the cloud is such a nuanced word. I mean, we're talking about sovereignty, we're talking about data gravity, we're talking about economics of owning versus renting. This trifecta, the laws of the land, the laws of physics, and the laws of economics will dictate many of these things as well. So I think the big folks are also humble and vulnerable to realize that there's nothing more powerful than market forces. And I think the rest will take care of itself. >> Yeah, my quick commentary on that, Dheeraj, I think most of us look back at AT&T and felt the government got it wrong. The way they broke it up and ended up consolidating back together, it didn't necessarily help consumers. Microsoft on the other hand might've had a little bit too much power and was leveraging that against competition and really squashing innovation. So in general, it's good to see that the politics are looking at that and chore felt. The last time I watched things, they were a little bit more educated than some previous times there, where it was almost embarrassing to watch our representatives fumbling around with technology. So it's always good to question authority, question what they have. And one of the things you've brought up many times is you're open to listening and you're bringing in new ideas. I remember one conversation I had with you is there's that direction that you hold on to, but you will assess and do new data. You've made adjustments in the product portfolio and direction based on your customers, based on the ecosystem. And you've mentioned some of the, bring thoughts that you've brought into the company and you share. So you mentioned black swan that seem to head you brought to one of the European .NEXT shows. It was great to be able to see that author and read through advisors like Condoleezza Rice who you've had at the conferences a couple of times. Where are you getting some of your latest inspiration from, any new authors or podcasts that you'd be recommending to the audience? >> Yeah, I look at adjacencies, obviously Simon has been great. He was .NEXT, talked about the Infinite Game. And we'll talk about the Infinite Game with Nutanix too with respect to also my decision. But Brene Brown was been very close to Nutanix. I was just looking at her latest podcast, and she was sitting with the author of Stretch, Scott Sonnenschein, and it's a fascinating read and a great listen, by the way, I think for worth an hour, talking about scrappiness, and talking about resourcefulness. What does it mean to really be resourceful? And we need that even more so as we go through this recession, as we are sheltered in place. I think it's an adjacency to everything that Brene does. And I was just blown away by just listening to it. I'd a love for others to even have a listen and learn to understand what we can do within our families, with our budgets, with our companies, with our startups. I mean, with CUBE, I mean, what does it mean to be scrappy? And celebrate scrappiness and resourcefulness, more so than AI always need more. I think I just found it fascinating in the last week itself listening through it. >> John Farinacci talk many times that founder, startup, that being able to pull themselves up, be able to drive forward, overcome obstacles. So Dheeraj, do you tee it up? It sounds like is the next step for you. There's a transition under discussion. Bain has made an investment. There's a search for new CEO. Are you saying there's a book club in your future to be able to get things ready? Why don't you explain a little bit, 11 years took the company public, over 6,500 employees public company. So tell us a little bit about that decision-making process and what you expect to see in the future? >> Yeah, it's probably one of the hardest things as an entrepreneur is to let go, because it's a creation that you followed from scratch, from nothing. And it was a process for me to rethink about what's next for the company and then what's next for me? And me and the company were so tightly coupled that I was like, wow, at some point, this has to be a little bit more like the way Bill Gates did it with Microsoft, and there's going to be buton zone and you will then start to realize that your identity is different from the company's identity. And maybe the company is built for bigger, better things. And maybe you're built for bigger, better things. And how do you really start to first do this decoupling of the identity? And it's really hard. I mean, I'm sure that parents go through this. I mean, our children are still very young. Our eldest is nine going on 10 and our twin girls are six. I know at some point in the next 10 years, eight to 10 years, we'll have to figure out what it means to let go. And I'm already doing this with my son. I tell him you're born free. I mean, the word born free which drives my wife crazy sometimes. I say this to them, it's about independence. And I think the company is also born free to really think about a life outside of me, as well outside of founder. And that was a very important process for me as I was talking to the board for the last six, seven, eight months. And when the Bain deal came in, I thought it was a great time. We ended the fiscal really well, all things considered. We had a good quarter. The transition has been a journey of a lifetime, the business model transition I speak of. Really three years, I mean, I have aged probably 10 years in these last three years. But I think I would not replaced it for anything. Just the experience of learning what it means to change as a public company when you have short-term goals and long-term goals, we need the conviction, knowing what's right, because otherwise we would not have survived this cloud movement, all this idea of actually becoming a subscription company, changing the core of the business in the on-prem world itself. It's a king to change the wings of a plane at 40,000 feet where none of the passengers blink. It's been phenomenal ride last 11 years, but it's also been nonstop monomaniacal. I mean, I use the word marathon for this, and I figured it's a good time to say figure out a way to let go of this, and think of what's bigger better for Nutanix. And going from zero to a billion six in annual billings, and looking at billion six to 3 billion to four to five, I think it'd be great &to look at this from afar. And at the same time, I think there's vulnerability. I mean, I've made the company vulnerable. I've made myself vulnerable. We don't know who the next leader will be. And I think the next three to six months is one of the most important baton zones that I have ever experienced to be a part of. So looking forward to make sure that baton doesn't fall, redefine what good to great looks like, both for the company and for myself. And at the same time, go read more. I mean, I've been passionate about developers in the last 10 years, 11 years. I was a developer myself. This company, Nutanix, was really built by developers for IT. And I'm learning more about the developer as a consumer. How do you think about their experience? Not just the things that we throw at them from open source point of view and from cloud and technologies and AI and ML point of view, but really their lives, having them think about revenue and business and really blurring the lines between architects and product managers and developers. I think it's just an unfathomable problem we've created in IT that I would love to go and read and write more about. >> Yeah, so many important things you said there. I absolutely think that there are certain things everybody of course will think of you for a long time with Nutanix, but there is that separation between the role in the company and the person itself, and really appreciated how much you've always shared along those lines. So last question I have and you hit it up a little bit when you talked about developers. Take off your Nutanix hat for a second here, now what do we need to do to make sure that the next decade is successful in this space, cloud as a general guideline? Yes, we know we have skill gap. We know we need more people, we need more diversity. But there's so much that we need and there's so much opportunity, but what do you see and any advice areas that you think are critical for success in the future? >> Yeah, I mean, you hit up on something that I have had a passion for, probably more late in this world, more so than conspicuous, and and you hit upon it right now, diversity and inclusion. It's an unresolved problem in the developer community: the black developer, the woman developer. The idea of, I mean, we've two girls, they're twins. I'd love for them to embrace computer science and even probably do a PhD. I mean, I was a dropout. I'd love for them to do better than I did. Get, embrace things that are adjacent to biology and computer science. Go solve really hard problems. And we've not done those things. I mean, we've not looked at the community of developers and said, you know, they are the maker. And they work with managers and the maker manager world is two different worlds. How do you make this less friction? And how do you make this more delightful? And how do you think of developers as business, as if they are the folks who run the business? I think there's a lot that's missing there. And again, we throw a lot of jargons at them, and we talk a lot about automation and tools and such. But those are just things. I think the last 10, 11 years of me really just thinking about product and product portfolio and design and the fact that we have so many developers at Nutanix. I think it has been a mind-boggling experience, thinking about the why and the how and the what of the day in the life of, the month in the life of, and thinking about simple things like OKRs. I mean, we are throwing these jargons of OKRs at them: productivity, offshoring, remote work, over the zoom design sessions. It's just full of conflict and friction. So I think there is an amazing opportunity for Nutanix. There's an amazing opportunity for the industry to elevate this where the the woman developer can speak up in this world that's full of so many men. The black developer can speak up. And all of us can really think of this as something that's more structured, more productive, more revenue-driven, more customer in rather than developer out. That's really been some of the things that have been in my head, things that are still unresolved at Nutanix that I'm pretty sure at many of the places out there. That's what thinking and reading and writing about. >> Well, Dheeraj, first of all, thank you so much again for participating here. It's been great having you in theCUBE community, almost since the inception of us doing it back in 2010. Wish you the best of luck in the current transition. And absolutely look forward to talking more in the future. >> Thank you. And again, a big fan of the tremor rate of John, Dave, and you. Always learn so much from you, folks. Looking forward to be a constant student. Thank you. >> Thank you for joining us at theCUBE on Cloud. Lots more coverage here. Be sure to look throughout the site, engage in the chats, and give us your feedback. We're here to help you with the virtual events. I'm Stu Miniman as always. Thanks for watching.

Published Date : Jan 5 2021

SUMMARY :

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Sabita Davis and Patrick Zeimet | Io-Tahoe Adaptive Data Governance


 

>>from around the globe. It's the Cube presenting adaptive data governance brought >>to you by >>Iota Ho. In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs Evita Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you can get to know your data and quickly on. We also want to encourage you to engage with Sabina and Patrick. Use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Sabetta, take it away. All right. >>Thanks, Lisa. Great to be here as Lisa mentioned guys. I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. A said My name's Patrick Samit. I'm the enterprise data engineer here at Iota Ho. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>I couldn't agree more, Pat. So, guys, what patent? I patent. I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted toe walk. You guys through some of those client questions, slash pain points that we're hearing from different industries and different roles and demo how our platform here, like Tahoe, is used for automating those, uh, automating Dozier related tasks. So with that said, are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one, So I'm a data practitioner. I just started my job. ABC Bank. I have over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I talk to help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of Excel and something similar to video, which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing. You can see here visualization of the data relationships created by the I Ho Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um, So is the data catalog automatically populated? Correct. Okay, so So what? I'm using iota. Hope at what I'm getting is this complete, unified automated platform without the added cost, of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column Underscore ones and custom variable underscore tents that are always such a joy to deal with. Uh, now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Personally, I'm a big fan of this >>view, >>as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought. Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. Now you notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships. Uh, and you can leverage to try and make new and powerful relationships within your data. So I hope that answers the first part of your question. >>Eso So this is really cool. And I can see how this could be leverage quickly. Now. What if I added new data sources or your multiple data sources and needed toe? Identify what data sensitive. Can I Oh, Tahoe, Detect that. >>Yeah, definitely. Within the i o ta platform. There already over 300 pre defined policies such as HIPAA, ferpa, C, c, p, a and the like. One can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And is something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface, so one can work these into the action items within your project management systems. And I think this lends to the collaboration as a team can work through the discovery simultaneously. And as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota how you can be sure you're in compliance. >>Um, so I'm glad you mentioned compliance because that's extremely important to my organization. >>So >>what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely. The collaboration and documentation that the iota ho interface lends itself to can really help you build that confidence that your compliance is sound. >>Does >>that answer your question about sense of data? >>Definitely so. So path. I have the next question for you. So we're planning on migration on guy. Have a set of reports I need to migrate. But what I need to know is that well, what what data sources? Those report those reports are dependent on and what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>So let's say I add another data source. I can still see that Unified 3 60 view. >>Yeah, One feature that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished along for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for this visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. Now, this also provides tabular output in case you need it for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions along to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust it? So what I'm interested in knowing really is is it in a fit state for Meteo use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. another service that iota hope provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, uh, >>so you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. I hope that helps answer your questions about that quality. >>Oh, definitely. So I have another one for you here. Path. So I get now the value of IATA who brings by automatically captured all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed. One can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions, allowing insight into the strength of these business rules. It is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, so those custom rules can I apply that across data sources? >>Yeah. You can bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out >>to us. We >>are website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Erin. >>Impact. If I could ask you one quick question, how do you advise customers? You just walk in this great example This banking example that you and city to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules as well as identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>Um, no, I think actually passed something that pretty well, I mean, just just by automating all those manual tasks, I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation started. >>Excellent. Savita and Pat, Thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality so that you can maximize the value of it. Thanks for watching.

Published Date : Dec 10 2020

SUMMARY :

from around the globe. for how you can get to know your data and quickly on. I'm the enterprise account executive here in Ohio. I'm the enterprise data engineer here at Iota Ho. So we spoke with both your technical and your non technical So I have data kept in Data Lakes, legacy data, sources, even the cloud. Typically, the first step is to catalog the data and then start mapping the relationships Um, So is the data catalog automatically populated? Uh, now, by leveraging this interface, we can start to answer the first part of your question So I hope that answers the first part of your question. And I can see how this could be leverage quickly. to run against their data along for flexibility and efficiency and running the policies that affect organization. policies that apply to my organization? And I think this lends to the collaboration as a team can work through the discovery that before were other than if you were going to be using a human. interface lends itself to can really help you build that confidence that your compliance is I have the next question for you. Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within I can still see that Unified 3 60 view. Yeah, One feature that is particularly helpful is the ability to add data sources after the data Does it conform to the right format? hope provides is the ability to write custom data quality rules and understand how well the data needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia I hope that helps answer your questions about that quality. So I have another one for you here. to be involved with the data life cycle and take ownership over the rules that fall within their domain. so long as you could tie them to that unified definition. we understand your pain, so please feel free to reach out to us. help you guys automate all those manual task to help save you time and money. you. This banking example that you and city to talk through. Yeah, I think the number one thing that customers could do to get started with our platform so we we encourage you just reach out to us. Make sure that it's quality so that you can maximize the value of it.

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IO TAHOE EPISODE 4 DATA GOVERNANCE V2


 

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique

Published Date : Dec 10 2020

SUMMARY :

adaptive data governance brought to you by Iota Ho. Gentlemen, it's great to have you on the program. Lisa is good to be back. Great. Listen, we're gonna start with you. But to really try to address these customer concerns because, you know, we wanna we So it's exciting a J from the CEO's level. It's real satisfying to see how we're able. Let's let's go back over to you. But they need to understand what kind of data they have, what shape it's in what's dependent lot of a lot of frameworks these days are hardwired, so you can set up a set It's the technical metadata coming together with policies Is this book enterprise companies are doing now? help the organizations to digest their data is to And if it was me eating that food with you guys, I would be not using chopsticks. So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Well, as she digs into the databases, she starts to see that So a J talk us through some examples of where But I think it helped do this Bring it to life a little bit. And one of the things I was thinking when you were talking through some We can see that on the the graphic that we've just How are you seeing those technologies being think you know this But the very first step is understanding what you have in normalizing that So if I start to see this pattern of date one day to elsewhere, I'm going to say, in the beginning about what you guys were doing with Oracle. So Oracle came to us and said, you know, we can see things changing in 2021 a. J. Lester thank you so much for joining me on this segment Thank you. is the Cube, your global leader in high tech coverage. Enjoy the best this community has to offer on the Cube, Gentlemen, it's great to have you joining us in this in this panel. Can you talk to the audience a little bit about the first Bank of One of the oldest ignored the old in Africa because of the history And how does it help the first Bank of Nigeria to be able to innovate faster with the point, we have new technologies that allow you to do this method data So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. Now it changed the reality, so they needed to adapt. I wanted to go to you as we talk about in the spirit of evolution, technology is changing. customer and for the customer means that we will help them with our technology and our resource is to achieve doing there to help your clients leverage automation to improve agility? So here's the first lunch on the latest innovation Some of the things that we've talked about, Otherwise, everything grinds to a halt, and you risk falling behind your competitors. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation different sources to find duplicates, which you can then re And one of the when Santiago was talking about folks really kind of adapted that. Minimize copies of the data can help everyone in this shift to remote working and a lot of the the and on the site fast, especially changes are changing so quickly nowadays that you need to be What you guys were doing there to help your customers I always tell them you better start collecting your data. Gentlemen, thank you for sharing all of your insights. adaptive data governance brought to you by Iota Ho. In this next segment, we're gonna be talking to you about getting to know your data. Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. I'm the enterprise data engineer here in Ohio Tahoe. So with that said are you ready for the first one, Pat? So I have data kept in Data Lakes, legacy data, sources, even the cloud. Typically, the first step is to catalog the data and then start mapping the relationships Um so is the data catalog automatically populated? i b naturally John to these focal points that coincide with these key columns following These air ones that are machine learning algorithms have predicted to be relationships Eso So this is really cool, and I can see how this could be leverage quickly now. such as hip for C, C, P. A and the like one can choose which of these policies policies that apply to my organization? And it's something that clients leverage fairly often to utilize this So I'm glad you mentioned compliance because that's extremely important to my organization. interface lends itself to really help you build that confidence that your compliance is Andi, I have a set of reports I need to migrate. Yeah, it's a fantastic questions to be toe identifying critical data elements, I can still see that unified 3 60 view. Yeah, One future that is particularly helpful is the ability to add data sources after So now I know a little bit about my data. the data pertains to these rules. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what the minutia to see which data elements are of the highest quality. no longer have to rely on reports about reports, but instead just come to this one So I get now the value of IATA who brings by automatically capturing all those technical to be involved with the data life cycle and take ownership over the rules that fall within their domain. Yeah, you could bring in as many data sources as you need, so long as you could manual task to help save you time and money. you. this banking example that you instantly to talk through. Yeah, I think the number one thing that customers could do to get started with our so we we encourage you just reach out to us. folks about how to get to know your data. into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria

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Greg Bukowski & Simon Blanks, BMC Software | AWS re:Invent 2020 Partner Network Day


 

>> Narrator: From around the globe. It's theCUBE with digital coverage of AWS re;Invent 2020 special coverage sponsored by AWS global partner network. >> Welcome to theCUBE. This is our coverage of AWS reinvent 2020 with special coverage of the APN partner experience. I'm Lisa Martin I've got a couple of gentlemen from BMC software joining me. Please welcome Greg Bukowski, the technology solutions director and Simon Blanks, area vice president Gentlemen it's great to have you on theCUBE virtual. >> Great to be here Lisa. >> Representing social distancing from across the country here. So guys, I'd like to just start Greg with you give our audience an understanding of your role technology solutions director your role and responsibilities at BMC. >> Sure I play the role of a field CTO. So I actually am aligned with our strategic CTO office and I bring their message to our customers all of our strategic customers within North America. >> And Simon, tell us a little bit about your role as area vice president. >> Well first of all, thanks for having us I have responsibility for our channels and our partners in the Americas. So I get to work both within our organization with our customers and with our partners to help them grow, to help us grow and deliver value to our customers. >> Speaking of your customers Simon the last year has been incredibly challenging and brought on a lot of challenges but opportunities. Talk to me about how that has impacted BMCs customers. >> That's a great question. You know, I think our customers are wanting to simplify that they're wanting to focus on what makes them win, right and get away from the things that, you know are not the competitive advantage. We see a lot of customers wanting to get out of the day-to-day operation of the data centers and migrate to the world of AWS but it's not as easy as we would all like it there's lots of challenges. AWS consulting partners are there to help them. One of the largest areas of challenges we see that they are having to address is manage these millions of IT assets that are constantly changing and some of them they don't even know exist and moving those to AWS, but moving them quickly, securely and of course, in a cost-effective manner. >> Talk to me a little bit about some of the speed like in the last nine months, have you seen an acceleration of those customers wanting to move workloads to AWS as we think of way back when the pandemic started and every business had to suddenly send workforces home no access to a data center or very limited. Is that something that you've seen speed up the last few months? >> Yeah we believe it's not only gained in velocity but will continue. We don't think that some of these changes to how a business is conducted are going to stop once the vaccine comes out. So yeah and you know the complexity of making this happen, you know it's difficult, especially in some of the very large organizations be it banks or telecoms or manufacturers or retailers you know it's not an easy chore and you know we've experienced some great wins in that area and helping some of our most strategic customers make that happen. >> So talk to me a little bit about Simon, what's your elevator pitch when you're going and i know you talk with customers, you talk with partners how do you describe BMC and what you guys deliver? >> Well BMC is a 40 year old company with 6,000 employees. we help 93% of the global 1000 manage their IT infrastructure right. In addition to that we help thousands of other customers with the same problems. So, you know what I tell organizations is we're there to help them be successful and to make things tick. >> Awesome thank you. So Greg, talk to me about more about the BMC solutions. You said in your role, you're also field CTO. What are some of the BMC solutions that you recommended AWS consulting partners consider to help customers, especially in this time as you're seeing more and more migrations AWS? >> Yeah I think that's a great point, Lisa. I mean, with the pandemic coming in, you know there was an initial pullback right that we saw from our customers and now as that trend, you know as the summer came on, not that it's gotten less, right. I mean obviously it's a big concern for customers but the realization of how they're going to operationalize themselves and still be a tech driven company and tech driven organization has really accelerated their digital transformation and it's driven more than anything the adoption of cloud technologies and to move into that cloud space it's brought about understanding customers how did they become more digital and to do that they have to connect their services. So underlying that challenge is really what we wanted to bring today to talk about is that BMC has an industry leading solution it's called a BMC discovery solution and it automatically goes within an organization's footprint and understands the dependencies between their infrastructure and their applications. That's really difficult, right? Typically we can just find assets, right? A lot of solutions out there can do that. What BMC does or what our solution does. That's unique in this space is that it understands relationships so that you understand from an application viewpoint which ultimately ties back to a business service into the software that runs on those assets into the applications that are supporting that as well as the platforms and infrastructure and that becomes more and more complex to date. What we see with our customers as they have cloud services they've got containers, they've got on-premise stuff. So we're working with customers today, right? We are the largest retailers in the US working with them to actually transform how they're doing business continuity. So it becomes not only an acceleration but a risk aversion program for them as well as a cost savings effort of trying to adopt that understanding those services from both within their data center, through the mainframe back into their cloud, right and understanding all those interdependencies so that they can run their business more efficiently. >> So Greg have you automated what used to be a traditionally manual lengthy process of that discovery. >> I think that is the key point Lisa. I mean when partners look to us for what value we can bring to them it's about accelerating that time all about reducing the time through automation what used to be a manual effort of understanding how these things connect and being able to having go talk to the application teams. We worked with a large bank as well. They were using other solutions in the marketplace and were taking six to nine months to map a single business service which is complex right it's got about a dozen applications that support it. We brought in our solution and they did it in three hours with one piece of information from an application team. It was unbelievable, right and these are the stories we hear all the time from our customers and this is a great solution that we have that runs in AWS. That's part of our AWS migration competency that we have and you know this is why we're here today on theCUBE. >> Well that speed improvement is massive as you just talked about Greg you know, when you think of organizations now that there is no time, there is no six to nine months to figure things out anymore right. Especially because we've all learned, I think a lot in the last nine months, professionally and personally but there's competition out there. That's ready to come and be nimble and faster and maybe with less legacy than any type of whether it's a retailer or a financial institution. So being able to get in there and discover and align this business and IT services folks to discover what they have, where they should move it that fast is really something that sounds to me like not just a survival mechanism, keeping the lights on during a strange time, but something that may even set apart the winners and the losers of tomorrow. >> Absolutely right. I mean you have to be able to tie into your existing infrastructure for print that traditional legacy or heritage as we call it for print that you have, that still runs your core business. Right, if you're a retailer it's probably some kind of supply chain rate If you're a bank it's all the financial transaction stuff that you do but then also adopt the technology and innovation that exists within the fintech space for a financial services customer and bringing that together and when you're doing that at the native integration point a lot of it comes into the cloud services, right and that's really where they're going to get the acceleration to attack new markets grow their margin in that space and that's where they need partners to help them. To adopt and learn those technologies and integrate those additionally, right we have other advanced capabilities that we offer from an AWS migration competency standpoint around cloud optimization. So when those services are running in there we also do a cost optimization that doesn't look at it from the infrastructure standpoint but actually it takes the same discovery data and lines it back to the lines of business. So the line of business now has visibility into if they're going to change what their operating model is how that's going to affect the cost in the backend services they can optimize their resources. >> So Simon looking at the capabilities that BMC is delivering. Talk to me about the BMC partner program. Why become a BMC partner? I think there's a couple of answers to that. First of all, what Greg was talking about in terms of this you know massive I'll call it reinvention of the amount of time it takes to perform some of these tasks. Some of these tasks that are done in every migration from you know months to days or hours that in and of itself can help the AWS consulting partners massively you know in their efforts. So that's one but I think more importantly than that is the culture of BMC and the importance of partners and the focus that it's getting whether or not it be from our board or CEO or down the management rank. So the channel has become massively important to our success and we're committed to helping our partners be successful right, we're committing to help them make money, right. We're actually, as a part of AWS re;Invent here were going to offer an incentive to partners to come and join our family. Traditionally there's enablement and costs associated with that and we're going to refund that cost. Plus we're going to invest our monies and refund any costs associated with the first co-marketing effort together that we can go out to the market and help them. So I think you know, it's sort of the three legs of the stool. The technology itself is you know, impressive the commitment of our leadership and we're also willing to make it you know, very economically attractive so that would be the reasons >> Everybody likes that, especially economically attractive. So in terms of what you're offering you said that around re;Invent with respect to interested perspective partners, how do they move forward with BMC to become an AWS consulting partner? What's that process like? >> Well, we have you know an onboarding team that Susan DuRoff she reports in to me and helps me with that process. But the best way to do it would be to contact me directly. My email address is simon_blanks@bmc.com and if you reach out to me directly, I'll make sure we get back to you promptly. We can have further discussions and you know, facilitate it and we really look forward to making that happen. >> That's pretty excellent personal service I like that. So Greg talk to me as we get towards the wrap here as field CTO, looking forward into 2021 which we all hope is going to be trim significantly better than 2020. What are some of the opportunities that you see that this time has uncovered for the IT folks and the business folks to get even stronger alignment? >> Yeah, I think this is a great opportunity for customers to realize that bringing together the IT organizations in alignment with their business organizations is a great opportunity from the Revolut to accelerate their adoption of technology accelerate their migrations into adoption of cloud services. But then also look for the opportunities to take advantage of, to grow revenue streams. Right I mean, challenges present opportunities and opportunities present growth, right? That's how customers grow when they recognize those opportunities and become agile enough to adopt them and go after them. >> That's a great mindset because it's absolutely true. It's not matter of how we look at it and look at what's being uncovered to then kind of exploit for good new products, new services, competitive differentiators all sorts of things going on. Well gentlemen, it's been a pleasure having you on theCUBE virtual today. Thank you for joining me. >> Thank you so much appreciate the time and thank you. >> All right. For my guests. I'm Lisa Martin. You're watching theCUBE. (upbeat music)

Published Date : Dec 3 2020

SUMMARY :

Narrator: From around the globe. Gentlemen it's great to So guys, I'd like to and I bring their message to our customers little bit about your role So I get to work both Talk to me about how that and moving those to AWS, and every business had to and you know the complexity and to make things tick. So Greg, talk to me about and to move into that cloud space So Greg have you and being able to having go something that sounds to me and lines it back to of the amount of time it takes to perform So in terms of what you're offering back to you promptly. and the business folks to and become agile enough to to then kind of exploit for good appreciate the time and thank you. I'm Lisa Martin.

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Drug Discovery and How AI Makes a Difference Panel | Exascale Day


 

>> Hello everyone. On today's panel, the theme is Drug Discovery and how Artificial Intelligence can make a difference. On the panel today, we are honored to have Dr. Ryan Yates, principal scientist at The National Center for Natural Products Research, with a focus on botanicals specifically the pharmacokinetics, which is essentially how the drug changes over time in our body and pharmacodynamics which is essentially how drugs affects our body. And of particular interest to him is the use of AI in preclinical screening models to identify chemical combinations that can target chronic inflammatory processes such as fatty liver disease, cognitive impairment and aging. Welcome, Ryan. Thank you for coming. >> Good morning. Thank you for having me. >> The other distinguished panelist is Dr. Rangan Sukumar, our very own, is a distinguished technologist at the CTO office for High Performance Computing and Artificial Intelligence with a PHD in AI and 70 publications that can be applied in drug discovery, autonomous vehicles and social network analysis. Hey Rangan, welcome. Thank you for coming, by sparing the time. We have also our distinguished Chris Davidson. He is leader of our HPC and AI Application and Performance Engineering team. His job is to tune and benchmark applications, particularly in the applications of weather, energy, financial services and life sciences. Yes so particular interest is life sciences he spent 10 years in biotech and medical diagnostics. Hi Chris, welcome. Thank you for coming. >> Nice to see you. >> Well let's start with your Chris, yes, you're regularly interfaced with pharmaceutical companies and worked also on the COVID-19 White House Consortium. You know tell us, let's kick this off and tell us a little bit about your engagement in the drug discovery process. >> Right and that's a good question I think really setting the framework for what we're talking about here is to understand what is the drug discovery process. And that can be kind of broken down into I would say four different areas, there's the research and development space, the preclinical studies space, clinical trial and regulatory review. And if you're lucky, hopefully approval. Traditionally this is a slow arduous process it costs a lot of money and there's a high amount of error. Right, however this process by its very nature is highly iterate and has just huge amounts of data, right it's very data intensive, right and it's these characteristics that make this process a great target for kind of new approaches in different ways of doing things. Right, so for the sake of discussion, right, go ahead. >> Oh yes, so you mentioned data intensive brings to mind Artificial Intelligence, you know, so Artificial Intelligence making the difference here in this process, is that so? >> Right, and some of those novel approaches are actually based on Artificial Intelligence whether it's deep learning and machine learning, et cetera, you know, prime example would say, let's just say for the sake of discussion, let's say there's a brand new virus, causes flu-like symptoms, shall not be named if we focus kind of on the R and D phase, right our goal is really to identify target for the treatment and then screen compounds against it see which, you know, which ones we take forward right to this end, technologies like cryo-electron, cryogenic electron microscopy, just a form of microscopy can provide us a near atomic biomolecular map of the samples that we're studying, right whether that's a virus, a microbe, the cell that it's attaching to and so on, right AI, for instance, has been used in the particle picking aspect of this process. When you take all these images, you know, there are only certain particles that we want to take and study, right whether they have good resolution or not whether it's in the field of the frame and image recognition is a huge part of this, it's massive amounts of data in AI can be very easily, you know, used to approach that. Right, so with docking, you can take the biomolecular maps that you achieved from cryo-electron microscopy and you can take those and input that into the docking application and then run multiple iterations to figure out which will give you the best fit. AI again, right, this is iterative process it's extremely data intensive, it's an easy way to just apply AI and get that best fit doing something in a very, you know, analog manner that would just take humans very long time to do or traditional computing a very long time to do. >> Oh, Ryan, Ryan, you work at the NCNPR, you know, very exciting, you know after all, you know, at some point in history just about all drugs were from natural products yeah, so it's great to have you here today. Please tell us a little bit about your work with the pharmaceutical companies, especially when it is often that drug cocktails or what they call Polypharmacology, is the answer to complete drug therapy. Please tell us a bit more with your work there. >> Yeah thank you again for having me here this morning Dr. Goh, it's a pleasure to be here and as you said, I'm from the National Center for Natural Products Research you'll hear me refer to it as the NCNPR here in Oxford, Mississippi on the Ole Miss Campus, beautiful setting here in the South and so, what, as you said historically, what the drug discovery process has been, and it's really not a drug discovery process is really a therapy process, traditional medicine is we've looked at natural products from medicinal plants okay, in these extracts and so where I'd like to begin is really sort of talking about the assets that we have here at the NCNPR one of those prime assets, unique assets is our medicinal plant repository which comprises approximately 15,000 different medicinal plants. And what that allows us to do, right is to screen mine, that repository for activities so whether you have a disease of interest or whether you have a target of interest then you can use this medicinal plant repository to look for actives, in this case active plants. It's really important in today's environment of drug discovery to really understand what are the actives in these different medicinal plants which leads me to the second unique asset here at the NCNPR and that is our what I'll call a plant deconstruction laboratory so without going into great detail, but what that allows us to do is through a how to put workstation, right, is to facilitate rapid isolation and identification of phytochemicals in these different medicinal plants right, and so things that have historically taken us weeks and sometimes months, think acetylsalicylic acid from salicylic acid as a pain reliever in the willow bark or Taxol, right as an anti-cancer drug, right now we can do that with this system on the matter of days or weeks so now we're talking about activity from a plant and extract down to phytochemical characterization on a timescale, which starts to make sense in modern drug discovery, alright and so now if you look at these phytochemicals, right, and you ask yourself, well sort of who is interested in that and why, right what are traditional pharmaceutical companies, right which I've been working with for 20, over 25 years now, right, typically uses these natural products where historically has used these natural products as starting points for new drugs. Right, so in other words, take this phytochemical and make chemicals synthetic modifications in order to achieve a potential drug. But in the context of natural products, unlike the pharmaceutical realm, there is often times a big knowledge gap between a disease and a plant in other words I have a plant that has activity, but how to connect those dots has been really laborious time consuming so it took us probably 50 years to go from salicylic acid and willow bark to synthesize acetylsalicylic acid or aspirin it just doesn't work in today's environment. So casting about trying to figure out how we expedite that process that's when about four years ago, I read a really fascinating article in the Los Angeles Times about my colleague and business partner, Dr. Rangan Sukumar, describing all the interesting things that he was doing in the area of Artificial Intelligence. And one of my favorite parts of this story is basically, unannounced, I arrived at his doorstep in Oak Ridge, he was working Oak Ridge National Labs at the time, and I introduced myself to him didn't know what was coming, didn't know who I was, right and I said, hey, you don't know me you don't know why I'm here, I said, but let me tell you what I want to do with your system, right and so that kicked off a very fruitful collaboration and friendship over the last four years using Artificial Intelligence and it's culminated most recently in our COVID-19 project collaborative research between the NCNPR and HP in this case. >> From what I can understand also as Chris has mentioned highly iterative, especially with these combination mixture of chemicals right, in plants that could affect a disease. We need to put in effort to figure out what are the active components in that, that affects it yeah, the combination and given the layman's way of understanding it you know and therefore iterative and highly data intensive. And I can see why Rangan can play a huge significant role here, Rangan, thank you for joining us So it's just a nice segue to bring you in here, you know, given your work with Ryan over so many years now, tell I think I'm also quite interested in knowing a little about how it developed the first time you met and the process and the things you all work together on that culminated into the progress at the advanced level today. Please tell us a little bit about that history and also the current work. Rangan. >> So, Ryan, like he mentioned, walked into my office about four years ago and he was like hey, I'm working on this Omega-3 fatty acid, what can your system tell me about this Omega-3 fatty acid and I didn't even know how to spell Omega-3 fatty acids that's the disconnect between the technologist and the pharmacologist, they have terms of their own right since then we've come a long way I think I understand his terminologies now and he understands that I throw words like knowledge graphs and page rank and then all kinds of weird stuff that he's probably never heard in his life before right, so it's been on my mind off to different domains and terminologies in trying to accept each other's expertise in trying to work together on a collaborative project. I think the core of what Ryan's work and collaboration has led me to understanding is what happens with the drug discovery process, right so when we think about the discovery itself, we're looking at companies that are trying to accelerate the process to market, right an average drug is taking 12 years to get to market the process that Chris just mentioned, Right and so companies are trying to adopt what's called the in silico simulation techniques and in silico modeling techniques into what was predominantly an in vitro, in silico, in vivo environment, right. And so the in silico techniques could include things like molecular docking, could include Artificial Intelligence, could include other data-driven discovery methods and so forth, and the essential component of all the things that you know the discovery workflows have is the ability to augment human experts to do the best by assisting them with what computers do really really well. So, in terms of what we've done as examples is Ryan walks in and he's asking me a bunch of questions and few that come to mind immediately, the first few are, hey, you are an Artificial Intelligence expert can you sift through a database of molecules the 15,000 compounds that he described to prioritize a few for next lab experiments? So that's question number one. And he's come back into my office and asked me about hey, there's 30 million publications in PubMag and I don't have the time to read everything can you create an Artificial Intelligence system that once I've picked these few molecules will tell me everything about the molecule or everything about the virus, the unknown virus that shows up, right. Just trying to understand what are some ways in which he can augment his expertise, right. And then the third question, I think he described better than I'm going to was how can technology connect these dots. And typically it's not that the answer to a drug discovery problem sits in one database, right he probably has to think about uniproduct protein he has to think about phytochemical, chemical or informatics properties, data and so forth. Then he talked about the phytochemical interaction that's probably in another database. So when he is trying to answer other question and specifically in the context of an unknown virus that showed up in late last year, the question was, hey, do we know what happened in this particular virus compared to all the previous viruses? Do we know of any substructure that was studied or a different disease that's part of this unknown virus and can I use that information to go mine these databases to find out if these interactions can actually be used as a repurpose saying, hook, say this drug does not interact with this subsequence of a known virus that also seems to be part of this new virus, right? So to be able to connect that dot I think the abstraction that we are learning from working with pharma companies is that this drug discovery process is complex, it's iterative, and it's a sequence of needle in the haystack search problems, right and so one day, Ryan would be like, hey, I need to match genome, I need to match protein sequences between two different viruses. Another day it would be like, you know, I need to sift through a database of potential compounds, identified side effects and whatnot other day it could be, hey, I need to design a new molecule that never existed in the world before I'll figure out how to synthesize it later on, but I need a completely new molecule because of patentability reasons, right so it goes through the entire spectrum. And I think where HP has differentiated multiple times even the recent weeks is that the technology infusion into drug discovery, leads to several aha! Moments. And, aha moments typically happened in the other few seconds, and not the hours, days, months that Ryan has to laboriously work through. And what we've learned is pharma researchers love their aha moments and it leads to a sound valid, well founded hypothesis. Isn't that true Ryan? >> Absolutely. Absolutely. >> Yeah, at some point I would like to have a look at your, peak the list of your aha moments, yeah perhaps there's something quite interesting in there for other industries too, but we'll do it at another time. Chris, you know, with your regular work with pharmaceutical companies especially the big pharmas, right, do you see botanicals, coming, being talked about more and more there? >> Yeah, we do, right. Looking at kind of biosimilars and drugs that are already really in existence is kind of an important point and Dr. Yates and Rangan, with your work with databases this is something important to bring up and much of the drug discovery in today's world, isn't from going out and finding a brand new molecule per se. It's really looking at all the different databases, right all the different compounds that already exist and sifting through those, right of course data is mind, and it is gold essentially, right so a lot of companies don't want to share their data. A lot of those botanicals data sets are actually open to the public to use in many cases and people are wanting to have more collaborative efforts around those databases so that's really interesting to kind of see that being picked up more and more. >> Mm, well and Ryan that's where NCNPR hosts much of those datasets, yeah right and it's interesting to me, right you know, you were describing the traditional way of drug discovery where you have a target and a compound, right that can affect that target, very very specific. But from a botanical point of view, you really say for example, I have an extract from a plant that has combination of chemicals and somehow you know, it affects this disease but then you have to reverse engineer what those chemicals are and what the active ones are. Is that very much the issue, the work that has to be put in for botanicals in this area? >> Yes Doctor Goh, you hit it exactly. >> Now I can understand why a highly iterative intensive and data intensive, and perhaps that's why Rangan, you're highly valuable here, right. So tell us about the challenge, right the many to many intersection to try and find what the targets are, right given these botanicals that seem to affect the disease here what methods do you use, right in AI, to help with this? >> Fantastic question, I'm going to go a little bit deeper and speak like Ryan in terminology, but here we go. So with going back to about starting of our conversation right, so let's say we have a database of molecules on one side, and then we've got the database of potential targets in a particular, could be a virus, could be bacteria, could be whatever, a disease target that you've identified, right >> Oh this process so, for example, on a virus, you can have a number of targets on the virus itself some have the spike protein, some have the other proteins on the surface so there are about three different targets and others on a virus itself, yeah so a lot of people focus on the spike protein, right but there are other targets too on that virus, correct? >> That is exactly right. So for example, so the work that we did with Ryan we realized that, you know, COVID-19 protein sequence has an overlap, a significant overlap with previous SARS-CoV-1 virus, not only that, but it overlap with MERS, that's overlapped with some bad coronavirus that was studied before and so forth, right so knowing that and it's actually broken down into multiple and Ryan I'm going to steal your words, non-structural proteins, envelope proteins, S proteins, there's a whole substructure that you can associate an amino acid sequence with, right so on the one hand, you have different targets and again, since we did the work it's 160 different targets even on the COVID-19 mark, right and so you find a match, that we say around 36, 37 million molecules that are potentially synthesizable and try to figure it out which one of those or which few of those is actually going to be mapping to which one of these targets and actually have a mechanism of action that Ryan's looking for, that'll inhibit the symptoms on a human body, right so that's the challenge there. And so I think the techniques that we can unrule go back to how much do we know about the target and how much do we know about the molecule, alright. And if you start off a problem with I don't know anything about the molecule and I don't know anything about the target, you go with the traditional approaches of docking and molecular dynamics simulations and whatnot, right. But then, you've done so much docking before on the same database for different targets, you'll learn some new things about the ligands, the molecules that Ryan's talking about that can predict potential targets. So can you use that information of previous protein interactions or previous binding to known existing targets with some of the structures and so forth to build a model that will capture that essence of what we have learnt from the docking before? And so that's the second level of how do we infuse Artificial Intelligence. The third level, is to say okay, I can do this for a database of molecules, but then what if the protein-protein interactions are all over the literature study for millions of other viruses? How do I connect the dots across different mechanisms of actions too? Right and so this is where the knowledge graph component that Ryan was talking about comes in. So we've put together a database of about 150 billion medical facts from literature that Ryan is able to connect the dots and say okay, I'm starting with this molecule, what interactions do I know about the molecule? Is there a pretty intruding interaction that affects the mechanism of pathway for the symptoms that a disease is causing? And then he can go and figure out which protein and protein in the virus could potentially be working with this drug so that inhibiting certain activities would stop that progression of the disease from happening, right so like I said, your method of options, the options you've got is going to be, how much do you know about the target? How much do you know the drug database that you have and how much information can you leverage from previous research as you go down this pipeline, right so in that sense, I think we mix and match different methods and we've actually found that, you know mixing and matching different methods produces better synergies for people like Ryan. So. >> Well, the synergies I think is really important concept, Rangan, in additivities, synergistic, however you want to catch that. Right. But it goes back to your initial question Dr. Goh, which is this idea of polypharmacology and historically what we've done with traditional medicines there's more than one active, more than one network that's impacted, okay. You remember how I sort of put you on both ends of the spectrum which is the traditional sort of approach where we really don't know much about target ligand interaction to the completely interpretal side of it, right where now we are all, we're focused on is, in a single molecule interacting with a target. And so where I'm going with this is interesting enough, pharma has sort of migrate, started to migrate back toward the middle and what I mean by that, right, is we had these in a concept of polypharmacology, we had this idea, a regulatory pathway of so-called, fixed drug combinations. Okay, so now you start to see over the last 20 years pharmaceutical companies taking known, approved drugs and putting them in different combinations to impact different diseases. Okay. And so I think there's a really unique opportunity here for Artificial Intelligence or as Rangan has taught me, Augmented Intelligence, right to give you insight into how to combine those approved drugs to come up with unique indications. So is that patentability right, getting back to right how is it that it becomes commercially viable for entities like pharmaceutical companies but I think at the end of the day what's most interesting to me is sort of that, almost movement back toward that complex mixture of fixed drug combination as opposed to single drug entity, single target approach. I think that opens up some really neat avenues for us. As far as the expansion, the applicability of Artificial Intelligence is I'd like to talk to, briefly about one other aspect, right so what Rang and I have talked about is how do we take this concept of an active phytochemical and work backwards. In other words, let's say you identify a phytochemical from an in silico screening process, right, which was done for COVID-19 one of the first publications out of a group, Dr. Jeremy Smith's group at Oak Ridge National Lab, right, identified a natural product as one of the interesting actives, right and so it raises the question to our botanical guy, says, okay, where in nature do we find that phytochemical? What plants do I go after to try and source botanical drugs to achieve that particular end point right? And so, what Rangan's system allows us to do is to say, okay, let's take this phytochemical in this case, a phytochemical flavanone called eriodictyol and say, where else in nature is this found, right that's a trivial question for an Artificial Intelligence system. But for a guy like me left to my own devices without AI, I spend weeks combing the literature. >> Wow. So, this is brilliant I've learned something here today, right, If you find a chemical that actually, you know, affects and addresses a disease, right you can actually try and go the reverse way to figure out what botanicals can give you those chemicals as opposed to trying to synthesize them. >> Well, there's that and there's the other, I'm going to steal Rangan's thunder here, right he always teach me, Ryan, don't forget everything we talk about has properties, plants have properties, chemicals have properties, et cetera it's really understanding those properties and using those properties to make those connections, those edges, those sort of interfaces, right. And so, yes, we can take something like an eriodictyol right, that example I gave before and say, okay, now, based upon the properties of eriodictyol, tell me other phytochemicals, other flavonoid in this case, such as that phytochemical class of eriodictyols part right, now tell me how, what other phytochemicals match that profile, have the same properties. It might be more economically viable, right in other words, this particular phytochemical is found in a unique Himalayan plant that I've never been able to source, but can we find something similar or same thing growing in, you know a bush found all throughout the Southeast for example, like. >> Wow. So, Chris, on the pharmaceutical companies, right are they looking at this approach of getting, building drugs yeah, developing drugs? >> Yeah, absolutely Dr. Goh, really what Dr. Yates is talking about, right it doesn't help us if we find a plant and that plant lives on one mountain only on the North side in the Himalayas, we're never going to be able to create enough of a drug to manufacture and to provide to the masses, right assuming that the disease is widespread or affects a large enough portion of the population, right so understanding, you know, not only where is that botanical or that compound but understanding the chemical nature of the chemical interaction and the physics of it as well where which aspect affects the binding site, which aspect of the compound actually does the work, if you will and then being able to make that at scale, right. If you go to these pharmaceutical companies today, many of them look like breweries to be honest with you, it's large scale, it's large back everybody's clean room and it's, they're making the microbes do the work for them or they have these, you know, unique processes, right. So. >> So they're not brewing beer okay, but drugs instead. (Christopher laughs) >> Not quite, although there are pharmaceutical companies out there that have had a foray into the brewery business and vice versa, so. >> We should, we should visit one of those, yeah (chuckles) Right, so what's next, right? So you've described to us the process and how you develop your relationship with Dr. Yates Ryan over the years right, five years, was it? And culminating in today's, the many to many fast screening methods, yeah what would you think would be the next exciting things you would do other than letting me peek at your aha moments, right what would you say are the next exciting steps you're hoping to take? >> Thinking long term, again this is where Ryan and I are working on this long-term project about, we don't know enough about botanicals as much as we know about the synthetic molecules, right and so this is a story that's inspired from Simon Sinek's "Infinite Game" book, trying to figure it out if human population has to survive for a long time which we've done so far with natural products we are going to need natural products, right. So what can we do to help organizations like NCNPR to stage genomes of natural products to stage and understand the evolution as we go to understand the evolution to map the drugs and so forth. So the vision is huge, right so it's not something that we want to do on a one off project and go away but in the process, just like you are learning today, Dr. Goh I'm going to be learning quite a bit, having fun with life. So, Ryan what do you think? >> Ryan, we're learning from you. >> So my paternal grandfather lived to be 104 years of age. I've got a few years to get there, but back to "The Infinite Game" concept that Rang had mentioned he and I discussed that quite frequently, I'd like to throw out a vision for you that's well beyond that sort of time horizon that we have as humans, right and that's this right, is our current strategy and it's understandable is really treatment centric. In other words, we have a disease we develop a treatment for that disease. But we all recognize, whether you're a healthcare practitioner, whether you're a scientist, whether you're a business person, right or whatever occupation you realize that prevention, right the old ounce, prevention worth a pound of cure, right is how can we use something like Artificial Intelligence to develop preventive sorts of strategies that we are able to predict with time, right that's why we don't have preventive treatment approach right, we can't do a traditional clinical trial and say, did we prevent type two diabetes in an 18 year old? Well, we can't do that on a timescale that is reasonable, okay. And then the other part of that is why focus on botanicals? Is because, for the most part and there are exceptions I want to be very clear, I don't want to paint the picture that botanicals are all safe, you should just take botanicals dietary supplements and you'll be safe, right there are exceptions, but for the most part botanicals, natural products are in fact safe and have undergone testing, human testing for thousands of years, right. So how do we connect those dots? A preventive strategy with existing extent botanicals to really develop a healthcare system that becomes preventive centric as opposed to treatment centric. If I could wave a magic wand, that's the vision that I would figure out how we could achieve, right and I do think with guys like Rangan and Chris and folks like yourself, Eng Lim, that that's possible. Maybe it's in my lifetime I got 50 years to go to get to my grandfather's age, but you never know, right? >> You bring really, up two really good points there Ryan, it's really a systems approach, right understanding that things aren't just linear, right? And as you go through it, there's no impact to anything else, right taking that systems approach to understand every aspect of how things are being impacted. And then number two was really kind of the downstream, really we've been discussing the drug discovery process a lot and kind of the kind of preclinical in vitro studies and in vivo models, but once you get to the clinical trial there are many drugs that just fail, just fail miserably and the botanicals, right known to be safe, right, in many instances you can have a much higher success rate and that would be really interesting to see, you know, more of at least growing in the market. >> Well, these are very visionary statements from each of you, especially Dr. Yates, right, prevention better than cure, right, being proactive better than being reactive. Reactive is important, but we also need to focus on being proactive. Yes. Well, thank you very much, right this has been a brilliant panel with brilliant panelists, Dr. Ryan Yates, Dr. Rangan Sukumar and Chris Davidson. Thank you very much for joining us on this panel and highly illuminating conversation. Yeah. All for the future of drug discovery, that includes botanicals. Thank you very much. >> Thank you. >> Thank you.

Published Date : Oct 16 2020

SUMMARY :

And of particular interest to him Thank you for having me. technologist at the CTO office in the drug discovery process. is to understand what is and you can take those and input that is the answer to complete drug therapy. and friendship over the last four years and the things you all work together on of all the things that you know Absolutely. especially the big pharmas, right, and much of the drug and somehow you know, the many to many intersection and then we've got the database so on the one hand, you and so it raises the question and go the reverse way that I've never been able to source, approach of getting, and the physics of it as well where okay, but drugs instead. foray into the brewery business the many to many fast and so this is a story that's inspired I'd like to throw out a vision for you and the botanicals, right All for the future of drug discovery,

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Simon Walsh, NTT | Upgrade 2020 The NTT-Research Summit


 

>>from around the globe. It's the Cube covering upgrade twenty twenty, The NTT Research Summit presented by NTT Research. >>Welcome back. I'm stupid a man. And this is the Cubes coverage of Upgrade twenty twenty. Of course, it's the NTT Research Summit and happy to welcome to the program someone that watch the Cube for a long time. But first time on the program. Simon Walsh. He is the new CEO of NTT America's Simon. Great to see you and thanks so much for joining us. >>Thanks very much. Too good to be here. All right. See, >>A Zai mentioned your your previous companies that you've worked for are ones that the Cube and Cube audience are well aware of. Matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could maybe let's start with just a little bit of your background. And as I said, it's only been a few months that you've been the CEO, so you know, what's it like coming into a role like this? You know, during the situation that we're all faced with in twenty twenty. >>Yeah, Thank you. I mean, my background is really in, You know, the platforms that enable the customers Thio run their technologies. Andi, Uh, you know, I spent some of my time in Europe and the media on then latterly the last five plus years in the Americas. I have to say I really enjoy It's a much better environment. If I think about it from a GDP and an economy perspective, it's, ah really dynamic place to work. I worked with companies headquartered from Europe running America's, and I've worked with companies that were headquartered in the Americas, running some of the European businesses. So I've crossed the continent's if you like. I recently joined NTT. I have to say, you know, it was a pretty lengthy process to explore, but that was partly, you know, interviews and due diligence because you want to make sure that, you know, you're you're buying into a company that, you know, number one, you can have ah, cultural compatibility with, but also somebody who you see really investing in technology that consult for, you know, the business agenda of the markets. So that's really a bit about my background and then, you know, joining. I mean, I literally joined last week of June, so my whole time has bean through, locked down in terms of employment. It's been very unique. Taking on a new post, exclusively remote. Andi I was a bit worried, you know, at a human level, just, you know, how do you connect with people? What I would comment is I've actually had the ability to really meet ah, lot more people in person because you can physically get to people's schedules a lot easier. So that's certainly helped, you know. And I've done my, uh, activities of meeting clients. Eso they've been very amenable to connecting talking to our business partners and spending, you know, considerable amount of time with my colleagues, uh, in the Americas and around the world. Andi, it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen and you probably like twenty four inches away from each other. Whereas in a meeting room you'd be the other side of the table. So it's been unique, but so far so good. >>Well, yeah, absolutely. The the new abnormal is we. We have sometimes say what? We're all usedto looking in the screens all day talking to various people there. Uh, the impact on business, though, has been, uh, you know, obviously ah, lot of different things, depending on the company. But that discussion of digital transformation a few years ago it was like, Oh, I don't know if it's really is it a buzzword? But that the spotlight that's been shown here in twenty twenty is what Israel and what is not leveraging cloud services, giving people agility, being able to react fast because, boy in twenty twenty if we needed to react fast, so help bring us inside a little bit. And your time there, the discussion you're having with customers, that adoption moving along that journey for digital transformation, the impact that you're seeing and house NTT helping its customers as they need to accelerate and respond toe the realities that we see today. >>Yeah, so you're right into I mean, digital disruption has been ongoing for multiple years. Way used to call it technology and change, and now we call it digital disruption or digital transformation. So it's not necessarily new. I think the thing that's really accelerated in twenty twenty, You know, as a consequence of the pandemic is really the word distributed, uh, in that customers are undertaking their digital transformations understanding. You know what it is to modernize processes, you know, modernize the customer experience on Then they're finding that actually, they don't need in a board room and discuss, you know, the performance of the business so they now need to have distributed access to data on. I think the topics that we see very prevalent is the distributed nature off the workforce. Andi. Obviously there's always been a filled workforce, and we've had systems, crm systems and other systems that were built for a distributed workforce. But now we have toe think about our supply chain management systems and our HR systems, the P and L. And you know all of the activities that business undertakes with an entirely distributed workforce, and it's quite abnormal. And I think what we've learned is where is the data on how doe I amalgamate data from distributed systems. And so I see. And we're doing a lot of work with our clients relating to digital transformation, but really about how doe I join data from system a two system F in a distributed manner, most importantly, securely timely on in A in an interface that is usable on it sounds really easy is like Oh, great, yeah, it's just two different data points. Connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms Very expensive and significant historical investments on those things Don't modernize themselves overnight. Quite often. The dollars to modernize them don't justify themselves. So we then end up layering on, you know, new technology. So you know what I'm seeing on in digital transformation is really about. How do we handle distributed data Distributed decision making on how we do that in a secure manner on through an interface that is, uh, user friendly? >>Yeah, way. Obviously know that there's had to be some prioritization. You know, the joke. I've had everybody came into twenty twenty with Okay, here. Here's what I'm gonna do for the first half of the year. Here's the objectives that I have, and we kind of throw those in the shredder rather early on Number one priority. I still hear it was probably that the number one priority coming into the year and it stays there, and you've mentioned it multiple times. Its security, you know, is absolutely front and center Still. How overall, though, How are your customers? You know, the c X So sweet. How are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center? Obviously, you know, that distributed work from anywhere. Telemedicine, uh, you know, teach and learn from anywhere have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are gonna probably stay with us. Uh, you know, for the long term, >>Absolutely. We've definitely seems Thio customers re prioritizing. And I think there is obviously an inevitability to this, a za consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen is a prioritization has been How do we get our information to our users? Whether the user is a customer or whether the user is an employee, you know, there's examples where there's lots of companies who are saying they've got, like, online detail, right. But now they've got to do curbside pickup because they've actually got inventory in the stores. But the stores couldn't open. So what you've seen is a re prioritization to say, Well, when we look out inventory management and the supply chain systems, are we factoring in that the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale, ready for distribution on. Then we've got inventory in a store retail ready for consumer consumption. What? We don't want that to be separate Infantry. We want that to be holistic on. Then how do we enable any any consumer anywhere to be able to arrange for curbside pickup, which we didn't used to do because we would come into the store or arrange for mail order? But the inventory may come from, you know, I may send something from San Francisco to somebody in Boston because it was in a storied inventory in San Francisco. Now, sure, it's got it's got some freight cost, but I've also got some other efficiency savings, and I'm reducing my working capital in my inventory expense. So we've seen prioritization for really how to take advantage of this. I come back to it. This word distributed is very simple in principle, but everything is now working on a new dynamic. So that's some of the prioritization we've seen. >>Um, you mentioned one of the things that might get put on hold is wait. If I was doing a corporate network update, that might not be the first thing. You know, we we Absolutely. We've gotten some great data on just the changing traffic patterns of the Internet, but the network is so critically important, everybody from home is, you know, dealing with Children doing their zoom classrooms while we're trying to dio video meetings. Um, NTT obviously has a strong, uh, you know, network component to what? Its businesses help us understand the services that are important there. What? What? You're working with customers. And how has this kind of transformed, uh, some of those activities? >>Yeah, Yeah, sure. Thank you. You're so right. I mean, I have to say I just like thio, pay my respects to colleagues and fellow workers around the world who are not just working from home but also home schooling in parallel. Uh, kids are fled the nest, you know, they're working for themselves now, so we don't have the extra activity of home schooling. But I can really have a lot of respect her colleagues who are trying to do both. It's a real fine art on. We've seen a lot of actually just talking of re prioritization. We've seen a lot of companies, including ourselves. You know, say to our colleagues, Look after your Children home, school them do everything you can to support your families on, then get to your work So that re prioritization. Justin behavior has been a key change that we've seen a lot of people do that flexibility to. You know, work is something you do not somewhere you go on. Therefore, as long as the work is done, we can flex around. You know your needs is a family, so that's one prioritization we've seen at, actually. But to your point on the network, it is quite amusing to me that we've been for years now talking about cloud on demand subscription services on Actually, the one asset that you need to really enable cloud is the network and its historically been the least cloudlike that you could possibly imagine Because you still need to specify a physical connection. You still need to specify a band with value you still need to specify. You know, the number of devices you get too attached to it. I think this is really a monstrous change that we're going to experience and really are experiencing the network as a service. I mean, we talk about I as has SAS. But what happened toe now, as I mean really, did we just think that everything was about computing software? The network is the underpin er on DSO. Really? We see a big change and this is where we've been very busy in the network as a service enabling customers tohave dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events, you know, a lot of customers are now doing activities such as hosting their own event, their own digital conference on. Do you want to prioritize what the user experience is when you host one of those events over perhaps a back office process that, quite frankly, wait a few days so we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network of the service solutions. You know, the Cloud Network. And I think the whole software defined network agenda has materially accelerated. That's one major area on then. The other area has just been the phenomenal ship to I p voice on soft bone, actually almost the deletion of the phone in its entirety. Everybody using you know, teams or Skype or Google hangouts to really use as their collaboration mechanism on. Then you know, we're providing all the underlying transportation layer. But as I p voice, you know, that creates a much more integrated collaboration. Experience on git creates a cost saving because you're taking away classic voice services. >>Yeah, Simon Boy, I'm excited for that. I I remember when I got my first BlackBerry and they were trying to sell me some things. I'm like, Wait, this is an Internet endpoint. I can do all of these things there and of course you know it's taking taking it. The last dozen years. If If Ghana certain far, but and we always joke, it's like smartphones. We don't use them for phones anymore. We use them for all the messaging and all those services. So, uh, the the data and the network are so critically important, something I want to turn Thio, you know, upgrade twenty twenty. You know what? I'm excited about this. You know, we've talked about, you know, the major impacts of what's happened in twenty twenty, and we're looking at the here and now. But it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So we'd love to hear from your standpoint, some of the areas. What's exciting? You what's exciting? That we can look forward to some of the areas and pockets of research that we see at the event. >>Yeah. Thank you. Strewn E. I think what I like about Aravind is the investment that we make to work with, You know, scientific community, academia, really invest in, you know, forward looking future proofing, how physics and different technologies might play a role in the future. And, you know, some of these investments and some of this research yields commercial products, and some of it doesn't. But it's still a very valuable opportunity for us to really look at you know where technology is going. I think the areas that particularly appealing to me on a personal level, just the whole thing of quantum computing. This is, uh, you know, I know we're already exploring the capabilities of quantum computing in, you know, some labs and Cem academia centers on really to understand, how can we take advantage of that? But I think if you then say and you take another area that we're exploring through the event Biosciences, if you then take the two together and you think Okay, how do we take quantum computing on? We take Biosciences on you think about health care, and then you think about the pandemic. You know? Are there things that we can do with simulations and technologies in the future that really would give us a greater comprehension and ability to accelerate understanding, understand, accelerate testing, and then really contribute to, you know, the health and welfare of society. Andi, I think that's really quite an exciting area for us. So that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space quantum computing as well as you know, Biosciences. And I'd say, you know, one other area where I still think we're all trying to ascertain how it serves the business is really the area of Blockchain. I think this is, um, intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed Thio overcome the topic of my brain yet, So I'm still working on it on. Then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology. Now, on our data is available how we secure it, How we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally on globally to ensure that there is, you know, security of data on. I think the subject of cryptography and how we go forward with, you know, beyond one hundred and twenty eight bit is gonna be a very difficult and critical subjects. So these are the areas I'm very impressed with. >>Wonderful. Simon, I wanna give you the final word from update. Great. Twenty twenty. >>Yeah, thanks to you. Just thanks very much, Thio. Anybody that's attending what you'll find through various workshops. There's lots of insight from our strategic partners from research scientists from academia from ourselves. So thank you very much for participating. You know, we always value your feedback. So please tell us what we could do to improve the content to help you with your businesses. Onda, We look forward and hope that everybody stays safe. Thank you for connecting with us virtually >>well. Simon Walsh, Thank you so much. Great. Having a conversation and glad to have you in our cube alumni now, >>thank you very much to have a good day. >>Alright, Stay tuned. More coverage from upgrade twenty twenty. I'm still minimum. And thanks. As always, for watching the cube. Yeah,

Published Date : Sep 29 2020

SUMMARY :

It's the Cube covering upgrade Great to see you and thanks so much for joining us. Too good to be here. NTT is one of the large global companies that I had the pleasure to interact with over I have to say, you know, it was a pretty lengthy process to explore, Uh, the impact on business, though, has been, uh, you know, You know what it is to modernize processes, you know, modernize the customer Uh, you know, for the long term, But the inventory may come from, you know, I may send something from San a strong, uh, you know, network component to what? kids are fled the nest, you know, they're working for themselves now, so we don't have the You know, we've talked about, you know, the major impacts of what's happened in twenty twenty, I think the subject of cryptography and how we go forward with, you know, Twenty twenty. what we could do to improve the content to help you with your businesses. Having a conversation and glad to have you in our cube alumni now, And thanks.

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