(light airy music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase, AI and machine learning. "Top Startups Building Generative AI on AWS." This is season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talking about AI machine learning. We have three great guests Bratin Saha, VP, Vice President of Machine Learning and AI Services at Amazon Web Services. Tom Mason, the CTO of Stability AI, and Aidan Gomez, CEO and co-founder of Cohere. Two practitioners doing startups and AWS. Gentlemen, thank you for opening up this session, this episode. Thanks for coming on. >> Thank you. >> Thank you. >> Thank you. >> So the topic is hype versus reality. So I think we're all on the reality is great, hype is great, but the reality's here. I want to get into it. Generative AI's got all the momentum, it's going mainstream, it's kind of come out of the behind the ropes, it's now mainstream. We saw the success of ChatGPT, opens up everyone's eyes, but there's so much more going on. Let's jump in and get your early perspectives on what should people be talking about right now? What are you guys working on? We'll start with AWS. What's the big focus right now for you guys as you come into this market that's highly active, highly hyped up, but people see value right out of the gate? >> You know, we have been working on generative AI for some time. In fact, last year we released Code Whisperer, which is about using generative AI for software development and a number of customers are using it and getting real value out of it. So generative AI is now something that's mainstream that can be used by enterprise users. And we have also been partnering with a number of other companies. So, you know, stability.ai, we've been partnering with them a lot. We want to be partnering with other companies as well. In seeing how we do three things, you know, first is providing the most efficient infrastructure for generative AI. And that is where, you know, things like Trainium, things like Inferentia, things like SageMaker come in. And then next is the set of models and then the third is the kind of applications like Code Whisperer and so on. So, you know, it's early days yet, but clearly there's a lot of amazing capabilities that will come out and something that, you know, our customers are starting to pay a lot of attention to. >> Tom, talk about your company and what your focus is and why the Amazon Web Services relationship's important for you? >> So yeah, we're primarily committed to making incredible open source foundation models and obviously stable effusions been our kind of first big model there, which we trained all on AWS. We've been working with them over the last year and a half to develop, obviously a big cluster, and bring all that compute to training these models at scale, which has been a really successful partnership. And we're excited to take it further this year as we develop commercial strategy of the business and build out, you know, the ability for enterprise customers to come and get all the value from these models that we think they can get. So we're really excited about the future. We got hugely exciting pipeline for this year with new modalities and video models and wonderful things and trying to solve images for once and for all and get the kind of general value and value proposition correct for customers. So it's a really exciting time and very honored to be part of it. >> It's great to see some of your customers doing so well out there. Congratulations to your team. Appreciate that. Aidan, let's get into what you guys do. What does Cohere do? What are you excited about right now? >> Yeah, so Cohere builds large language models, which are the backbone of applications like ChatGPT and GPT-3. We're extremely focused on solving the issues with adoption for enterprise. So it's great that you can make a super flashy demo for consumers, but it takes a lot to actually get it into billion user products and large global enterprises. So about six months ago, we released our command models, which are some of the best that exist for large language models. And in December, we released our multilingual text understanding models and that's on over a hundred different languages and it's trained on, you know, authentic data directly from native speakers. And so we're super excited to continue pushing this into enterprise and solving those barriers for adoption, making this transformation a reality. >> Just real quick, while I got you there on the new products coming out. Where are we in the progress? People see some of the new stuff out there right now. There's so much more headroom. Can you just scope out in your mind what that looks like? Like from a headroom standpoint? Okay, we see ChatGPT. "Oh yeah, it writes my papers for me, does some homework for me." I mean okay, yawn, maybe people say that, (Aidan chuckles) people excited or people are blown away. I mean, it's helped theCUBE out, it helps me, you know, feed up a little bit from my write-ups but it's not always perfect. >> Yeah, at the moment it's like a writing assistant, right? And it's still super early in the technologies trajectory. I think it's fascinating and it's interesting but its impact is still really limited. I think in the next year, like within the next eight months, we're going to see some major changes. You've already seen the very first hints of that with stuff like Bing Chat, where you augment these dialogue models with an external knowledge base. So now the models can be kept up to date to the millisecond, right? Because they can search the web and they can see events that happened a millisecond ago. But that's still limited in the sense that when you ask the question, what can these models actually do? Well they can just write text back at you. That's the extent of what they can do. And so the real project, the real effort, that I think we're all working towards is actually taking action. So what happens when you give these models the ability to use tools, to use APIs? What can they do when they can actually affect change out in the real world, beyond just streaming text back at the user? I think that's the really exciting piece. >> Okay, so I wanted to tee that up early in the segment 'cause I want to get into the customer applications. We're seeing early adopters come in, using the technology because they have a lot of data, they have a lot of large language model opportunities and then there's a big fast follower wave coming behind it. I call that the people who are going to jump in the pool early and get into it. They might not be advanced. Can you guys share what customer applications are being used with large language and vision models today and how they're using it to transform on the early adopter side, and how is that a tell sign of what's to come? >> You know, one of the things we have been seeing both with the text models that Aidan talked about as well as the vision models that stability.ai does, Tom, is customers are really using it to change the way you interact with information. You know, one example of a customer that we have, is someone who's kind of using that to query customer conversations and ask questions like, you know, "What was the customer issue? How did we solve it?" And trying to get those kinds of insights that was previously much harder to do. And then of course software is a big area. You know, generating software, making that, you know, just deploying it in production. Those have been really big areas that we have seen customers start to do. You know, looking at documentation, like instead of you know, searching for stuff and so on, you know, you just have an interactive way, in which you can just look at the documentation for a product. You know, all of this goes to where we need to take the technology. One of which is, you know, the models have to be there but they have to work reliably in a production setting at scale, with privacy, with security, and you know, making sure all of this is happening, is going to be really key. That is what, you know, we at AWS are looking to do, which is work with partners like stability and others and in the open source and really take all of these and make them available at scale to customers, where they work reliably. >> Tom, Aidan, what's your thoughts on this? Where are customers landing on this first use cases or set of low-hanging fruit use cases or applications? >> Yeah, so I think like the first group of adopters that really found product market fit were the copywriting companies. So one great example of that is HyperWrite. Another one is Jasper. And so for Cohere, that's the tip of the iceberg, like there's a very long tail of usage from a bunch of different applications. HyperWrite is one of our customers, they help beat writer's block by drafting blog posts, emails, and marketing copy. We also have a global audio streaming platform, which is using us the power of search engine that can comb through podcast transcripts, in a bunch of different languages. Then a global apparel brand, which is using us to transform how they interact with their customers through a virtual assistant, two dozen global news outlets who are using us for news summarization. So really like, these large language models, they can be deployed all over the place into every single industry sector, language is everywhere. It's hard to think of any company on Earth that doesn't use language. So it's, very, very- >> We're doing it right now. We got the language coming in. >> Exactly. >> We'll transcribe this puppy. All right. Tom, on your side, what do you see the- >> Yeah, we're seeing some amazing applications of it and you know, I guess that's partly been, because of the growth in the open source community and some of these applications have come from there that are then triggering this secondary wave of innovation, which is coming a lot from, you know, controllability and explainability of the model. But we've got companies like, you know, Jasper, which Aidan mentioned, who are using stable diffusion for image generation in block creation, content creation. We've got Lensa, you know, which exploded, and is built on top of stable diffusion for fine tuning so people can bring themselves and their pets and you know, everything into the models. So we've now got fine tuned stable diffusion at scale, which is democratized, you know, that process, which is really fun to see your Lensa, you know, exploded. You know, I think it was the largest growing app in the App Store at one point. And lots of other examples like NightCafe and Lexica and Playground. So seeing lots of cool applications. >> So much applications, we'll probably be a customer for all you guys. We'll definitely talk after. But the challenges are there for people adopting, they want to get into what you guys see as the challenges that turn into opportunities. How do you see the customers adopting generative AI applications? For example, we have massive amounts of transcripts, timed up to all the videos. I don't even know what to do. Do I just, do I code my API there. So, everyone has this problem, every vertical has these use cases. What are the challenges for people getting into this and adopting these applications? Is it figuring out what to do first? Or is it a technical setup? Do they stand up stuff, they just go to Amazon? What do you guys see as the challenges? >> I think, you know, the first thing is coming up with where you think you're going to reimagine your customer experience by using generative AI. You know, we talked about Ada, and Tom talked about a number of these ones and you know, you pick up one or two of these, to get that robust. And then once you have them, you know, we have models and we'll have more models on AWS, these large language models that Aidan was talking about. Then you go in and start using these models and testing them out and seeing whether they fit in use case or not. In many situations, like you said, John, our customers want to say, "You know, I know you've trained these models on a lot of publicly available data, but I want to be able to customize it for my use cases. Because, you know, there's some knowledge that I have created and I want to be able to use that." And then in many cases, and I think Aidan mentioned this. You know, you need these models to be up to date. Like you can't have it staying. And in those cases, you augmented with a knowledge base, you know you have to make sure that these models are not hallucinating. And so you need to be able to do the right kind of responsible AI checks. So, you know, you start with a particular use case, and there are a lot of them. Then, you know, you can come to AWS, and then look at one of the many models we have and you know, we are going to have more models for other modalities as well. And then, you know, play around with the models. We have a playground kind of thing where you can test these models on some data and then you can probably, you will probably want to bring your own data, customize it to your own needs, do some of the testing to make sure that the model is giving the right output and then just deploy it. And you know, we have a lot of tools. >> Yeah. >> To make this easy for our customers. >> How should people think about large language models? Because do they think about it as something that they tap into with their IP or their data? Or is it a large language model that they apply into their system? Is the interface that way? What's the interaction look like? >> In many situations, you can use these models out of the box. But in typical, in most of the other situations, you will want to customize it with your own data or with your own expectations. So the typical use case would be, you know, these are models are exposed through APIs. So the typical use case would be, you know you're using these APIs a little bit for testing and getting familiar and then there will be an API that will allow you to train this model further on your data. So you use that AI, you know, make sure you augmented the knowledge base. So then you use those APIs to customize the model and then just deploy it in an application. You know, like Tom was mentioning, a number of companies that are using these models. So once you have it, then you know, you again, use an endpoint API and use it in an application. >> All right, I love the example. I want to ask Tom and Aidan, because like most my experience with Amazon Web Service in 2007, I would stand up in EC2, put my code on there, play around, if it didn't work out, I'd shut it down. Is that a similar dynamic we're going to see with the machine learning where developers just kind of log in and stand up infrastructure and play around and then have a cloud-like experience? >> So I can go first. So I mean, we obviously, with AWS working really closely with the SageMaker team, do fantastic platform there for ML training and inference. And you know, going back to your point earlier, you know, where the data is, is hugely important for companies. Many companies bringing their models to their data in AWS on-premise for them is hugely important. Having the models to be, you know, open sources, makes them explainable and transparent to the adopters of those models. So, you know, we are really excited to work with the SageMaker team over the coming year to bring companies to that platform and make the most of our models. >> Aidan, what's your take on developers? Do they just need to have a team in place, if we want to interface with you guys? Let's say, can they start learning? What do they got to do to set up? >> Yeah, so I think for Cohere, our product makes it much, much easier to people, for people to get started and start building, it solves a lot of the productionization problems. But of course with SageMaker, like Tom was saying, I think that lowers a barrier even further because it solves problems like data privacy. So I want to underline what Bratin was saying earlier around when you're fine tuning or when you're using these models, you don't want your data being incorporated into someone else's model. You don't want it being used for training elsewhere. And so the ability to solve for enterprises, that data privacy and that security guarantee has been hugely important for Cohere, and that's very easy to do through SageMaker. >> Yeah. >> But the barriers for using this technology are coming down super quickly. And so for developers, it's just becoming completely intuitive. I love this, there's this quote from Andrej Karpathy. He was saying like, "It really wasn't on my 2022 list of things to happen that English would become, you know, the most popular programming language." And so the barrier is coming down- >> Yeah. >> Super quickly and it's exciting to see. >> It's going to be awesome for all the companies here, and then we'll do more, we're probably going to see explosion of startups, already seeing that, the maps, ecosystem maps, the landscape maps are happening. So this is happening and I'm convinced it's not yesterday's chat bot, it's not yesterday's AI Ops. It's a whole another ballgame. So I have to ask you guys for the final question before we kick off the company's showcasing here. How do you guys gauge success of generative AI applications? Is there a lens to look through and say, okay, how do I see success? It could be just getting a win or is it a bigger picture? Bratin we'll start with you. How do you gauge success for generative AI? >> You know, ultimately it's about bringing business value to our customers. And making sure that those customers are able to reimagine their experiences by using generative AI. Now the way to get their ease, of course to deploy those models in a safe, effective manner, and ensuring that all of the robustness and the security guarantees and the privacy guarantees are all there. And we want to make sure that this transitions from something that's great demos to actual at scale products, which means making them work reliably all of the time not just some of the time. >> Tom, what's your gauge for success? >> Look, I think this, we're seeing a completely new form of ways to interact with data, to make data intelligent, and directly to bring in new revenue streams into business. So if businesses can use our models to leverage that and generate completely new revenue streams and ultimately bring incredible new value to their customers, then that's fantastic. And we hope we can power that revolution. >> Aidan, what's your take? >> Yeah, reiterating Bratin and Tom's point, I think that value in the enterprise and value in market is like a huge, you know, it's the goal that we're striving towards. I also think that, you know, the value to consumers and actual users and the transformation of the surface area of technology to create experiences like ChatGPT that are magical and it's the first time in human history we've been able to talk to something compelling that's not a human. I think that in itself is just extraordinary and so exciting to see. >> It really brings up a whole another category of markets. B2B, B2C, it's B2D, business to developer. Because I think this is kind of the big trend the consumers have to win. The developers coding the apps, it's a whole another sea change. Reminds me everyone use the "Moneyball" movie as example during the big data wave. Then you know, the value of data. There's a scene in "Moneyball" at the end, where Billy Beane's getting the offer from the Red Sox, then the owner says to the Red Sox, "If every team's not rebuilding their teams based upon your model, there'll be dinosaurs." I think that's the same with AI here. Every company will have to need to think about their business model and how they operate with AI. So it'll be a great run. >> Completely Agree >> It'll be a great run. >> Yeah. >> Aidan, Tom, thank you so much for sharing about your experiences at your companies and congratulations on your success and it's just the beginning. And Bratin, thanks for coming on representing AWS. And thank you, appreciate for what you do. Thank you. >> Thank you, John. Thank you, Aidan. >> Thank you John. >> Thanks so much. >> Okay, let's kick off season three, episode one. I'm John Furrier, your host. Thanks for watching. (light airy music)

foreign to the AWS re invent Cube coverage I'm John Furrier here with thecube got a great guest line up here talking about computer vision at the edge and saramba product lead AWS events mobile app and Steven White solution architect for Edge ml thanks for joining me today computer vision at the edge with adios Panorama thanks for coming on happy to be here so what is Ada's Panorama let's get that out there right away what's the focus of that let's define what that is and we'll get into this computer vision at the Edge Story yeah so thanks Sean uh AWS Panorama is our managed uh computer vision at the Ed service and so to put that perspective you know imagine with me the last time that you've been into a restaurant or maybe your favorite retail store or even office building and didn't notice a camera and so we were talking to customers and trying to understand you know what is it that they do with all of this uh video content that they're collecting and surprisingly we found out that large part of this data just sits on a hard drive somewhere and never gets used and so as we dug in a little deeper to better understand you know why this data is just sitting there I think there were three main themes that continue to come up across the board uh one is you know around privacy right privacy security a lot of the data that's being captured with these cameras tend to be either intellectual property that is you know focused on kind of the Manifest factoring process or maybe about their products that they don't want to get out there you know or and or it could just be a private pii data privacy data related to their employee Workforce and and maybe even customers so you know privacy is is a big concern second was just the amount of bandwidth that cameras create and produce tend to be uh prohibitive from for you know sending back to a centralized location for processing uh each camera stream tends to generate about a couple of megabytes of data so it could get very voluminous as you've got tons of cameras at your location and the other issue was around just the latency required to take action on the data so a lot of times especially in the manufacturing space um you know as as you've got a manufacturing line of products that are coming through and you need to take action in milliseconds and so latency is extremely important from process processing time to taking action so those three uh main drivers you know we ended up developing this AWS service called Panorama that addressed these three main challenges with uh you know with analyzing video content and database Panorama in particular there's there's two main components right we've got the compute platform that is about the size of a sheet of paper your standard you know eight and a half by eleven size sheet of paper so the platform itself is extremely compact it's a it's a video and and deep learning algorithms it sits at the customer premise and directly interfaces with video cameras using the standard IP protocols collects that data uh processes it and then immediately deletes the data so there isn't any any information that's actually stored at the location and you know basically the only thing that's left over is just metadata that describes that data and then the other key component here is the cloud um you know service component which helps manage the fleet of devices that are existing so all of these Panorama appliances that are sitting at your premise there's a cloud component that helps you configure you know operationalize check the health as well as deploy applications and configure cameras so that's uh basically you know the the service is really hopefully optimal or you know is focused on um helping customers really make use of all of their video data at the edge you know the theme here at re invent this year is applications we've seen things like connect add value to customers this is one of those situations where everyone's got cameras it's easy to connect to an IP address and Cloud kind of gives you all those Services there are a lot of real world applications that people can can Implement with this because with the cloud you kind of have this ability to kind of stand it up and get value out of that data what are some of the real world applications that it was because they're implementing with the camera because I mean I can see a lot of use cases here where I can you don't have to build the clouds there for me I can stand it up and start getting value what kind of use cases do you see implementing from your customers yeah so our customers are really amazing with the different types of problems um and opportunities that they bring to us for uh using computer vision at the edge in their data um you know we've got everything from animal Warfare use cases to being able to use you know video to uh to to make sure that you know food processing and just you know the health of animals is uh is uh sufficient we've got cases in manufacturing doing visual inspection and anomaly detection so looking at products that are on the conveyor belt as they're being manufactured and put together to make sure that obviously they're they're put together in the right in the right way um and then we've got different port authority and airports that use uh for you know security and cargo tracking to make sure that the products get to where they're supposed to go in a timely and efficient manner manager manage and then finally one of the use cases that really show facing a re invent this year is a part of our retail analytics portfolio which is line counting and so in particular we see a lot of customers in the retail space such as quick service restaurants even you know Peril retail and convenience stores where they want to better understand um you know whether their product is being made to the customer specification we've got like french fry use cases to see how the quality of that french fry is um you know over time and if they need to make a new batch when they've got a influx of customers coming in and to understanding employee to customer ratio maybe they need to put somebody on the cash register you know at busy time so there's really just a big number of customers you know opportunities that we've really solving with the computer vision service looks like a great service Panorama looking good and I want to get your thoughts you have the events happy the product lead take us through with your app I know you have decided to use it was Panorama I was a fit for you this year at re invent 2022 but you know you've been doing this event app for a while now take us through the app when it started how it's evolved and kind of what's the focus this year of course Sean app started in 26 4 re invent and since we've really expanded this year we've actually supported up to 34 events for AWS and continue to expand that for future years for this year though specifically we wanted to contribute to the overall event experience at re invent by helping people go through the process of checking in and picking up their badge in a more formed and efficient way so we decided that the AWS Panorama team and their computer vision and Edge capabilities were the best fit to analyze the lines and the registration kiosks that we have on site at both the Venetian and MGM at the airport we'll have digital signage showcasing our bad pickup wait times that will help attendees select which badge pickup location that they want to go to and see the current wait times live on those signs as well as through the mobile app so I can basically um get the feel for the line size when to come in does it give me a little recognition of who I am and kind of when I get there there's a TIA pull up my records as I do a little intelligence behind the scenes give us a little peek under the covers what's the solution look like so you do have to sign into the mobile app with your registration and so with that we will have your QR code specific for your check-in experience available to you you'll see that at the top of the screen and we'll know once you've checked in that will disappear but if you haven't checked in that Banner is at the top of the event screen and when you tap that that's when you can see all the different options where you can go and pick up your badge we do have five locations this year for badge pickup and the app will help you kind of navigate which one of those options will be best for you given you know maybe you want to pick it up right away at the airport or you may want to go even to one of your other Hotel options that we'll have um to pick it up at foreign okay now I gotta get I got to ask you on the app what's the coolest thing you got going on this year what's new every year there seems to be a new feature what's the focus this year so can you share a a peek on some of the key features yeah so our biggest and most popular features are always around the session catalog and calendar as you can utilize both to of course organize your event schedule and really stay on top of what you want to do on site and get the most out of your reinvent experience this year we have a few new exciting features of course badge pickup line counting is is one of our biggest but we also will have a one-way calendar sync so you can sync all of your calendar activities to your native device calendar as well as pure talk which is our newest feature that we launched at the start of November where you can interact with other attendees who have opted in and even set up time on site to meet one-on-one with them we've also filled that experience with peer talk experts that include AWS experts that are ready to meet and interact with attendees who have interest on site you know I love this topic it's a very cool video we love video we're doing this remote video I'm getting ready for you know all the action and and analyzing it video's cool and so to me if we could look at the video and say hey we haven't soon that might have body cams in the future um video is great people love videos very engaging but always people that say what about my privacy so how do you guys put in place uh mechanisms to preserve attendee privacy yeah I think so I'm not I think you know you and our customers share the same concern and so we have built uh foundationally that AWS Panorama to address you know both privacy and security concerns with uh associated with all this video content and so in particular the AWS Panorama Appliance is something that sits at the customer premise it interface directly with video cameras uh the data all the video that's processed is immediately deleted nothing stored um and you know the outcome of the processing is just simple metadata so it's Text data that you know as an example in the case of the AWS uh line counting solution that we're demoing this year at Panorama along with you know the events team uh it's simply a count of the number of people in the video at any given time so so you know we we do take privacy uh at heart and have made every effort to address them and what are some of the things that you're doing at the event app I mean I'm imagining you're probably looking at space I mean there's a fire marshal issues around you know people do you take it to that level I mean what's how far are you pushing the envelope on on Panorama what are some of the things that you guys are doing besides check-ins or anything you can share on what's Happening the area where we're utilizing you know Anonymous attendee data otherwise other things in the app are very Anonymous just in nature I mean you do sign in but besides that everything we collect is anonymous and we don't collect unless you consent with the cookie consent that appears right when you first launch the app experience besides that we do have as I mentioned peer talk and and that's just where you're sharing information that you want to share with other attendees on site and then we do have session surveys where you can provide information that you wish about how this survey or how the sessions rather went that you attended on-site yeah Stephen you're you're uh your title has you the solution architect for Edge ml this is the Ultimate Edge use case you're seeing here I mean it's a big part of the future of how companies are going to use video and data just what's your reaction to all this I mean we're at a time it's very kind of an interesting time in the history of the industry as you look at this this is a really big part of of the future with video and Edge like I mentioned users are involved people are involved spaces are involved kind of a fun area what's your reaction to where this is right now so personally I'm very passionate about this uh particular solution and service I've been doing computer vision now for 12 years I started doing in the cloud but when I heard about you know customers really looking for an edge component solution and this you know AWS was still in the early stages I knew I had to be a part of it and so I I you know work with some amazing talented engineers and scientists putting this solution together and of course you know our customers continue to bring us these amazing use cases that you know that just I wouldn't get an opportunity to um you know witness without without you know the support of our customers and so we've got some amazing opportunity amazing projects and you know I just love the love to uh experience that with our customers and partners yeah and and Stephen this is like one of those times where the industry has always had this everyone's scratching the niche somewhere but then you get cloud and scale and data come in and just it accelerates some of these areas that were you know I won't say not growing fast but very interesting like computer vision video events technology in the cloud is changing in a good way some of these areas uh and we're seeing that like computer vision as you mentioned Stephen so Ann event same thing I can imagine this event app will blow up to probably be all things Amazon events and and be the touch Touchstone for all customers and attendees I'm probably thinking the road map there's looking pretty interesting with all the vision you have there what's your what's your reaction to the cloud scale meets events absolutely yeah I know we we have a lot of events that happen at AWS and our goal is to have as many of them in the app as possible where it makes sense right we have a lot of partial Day events to multi-day events and the multi-day events are definitely the area where it's harder for an attendee to organize all that they have to do going on on site as well as everything surrounding the event pre-event uh topics and sessions looking up what they want to do to make sure that they're getting the most of their time on site so we really want to make sure that that's something that an attendee can do with our app as well as it showcase as many of the AWS Services as we have like we are doing here with Panorama we have a few other services in the app as well Amazon location service and Amazon connect to name a couple and we hope to just include more and more with each year as well as more events as the time goes on I'm sure your roadmaps looking great the computer vision is awesome I mean this is a mashup integration apis are going to come around the corner so much excitement after re invent love to follow up with you guys and find out more I think this is a super interesting area the convergence of what you guys are working on to kind of wrap up where do you guys see um AWS Panorama going and where can people learn more about how to get involved how to use the service how to test it out where's this going and how do people learn more but first off you can get customers can get more information about panorama from our website aws.amazon.com Panorama and you know I think where we're going is super exciting you know we continue to improve the product to add support for as an example containers we've added support for Hardware acceleration to improve the number of cameras that we can support so we've you know we've got um you know we can support now with a single device up to 30 40 cameras we've got the ability now to support many different uh we continue to expand the interface types that we support um you know and the different types of even adding sensors and you know expanding to Sensor Fusion so not just computer vision but we've learned from customers that they actually want to incorporate other uh other sensor types and other interfaces so we're bringing in the ability to handle you know computer vision and video but also many other data types as well all right and and Stephen thank you for sharing great stuff computer vision at the edge with Panorama thanks for coming on thecube appreciate it thanks for coming on thank you okay AWS coverage here in the cube I'm John for your host thanks for watching

(upbeat music) >> Hello, everyone. Welcome to the theCUBE's presentation of the AWS Startup Showcase. The theme, this showcase is MarTech, the emerging cloud scale customer experiences. Season two of episode three, the ongoing series covering the startups, the hot startups, talking about analytics, data, all things MarTech. I'm your host, John Furrier, here joined by Christian Wiklund, founder and CEO of unitQ here, talk about harnessing the power of user feedback to empower marketing. Thanks for joining us today. >> Thank you so much, John. Happy to be here. >> In these new shifts in the market, when you got cloud scale, open source software is completely changing the software business. We know that. There's no longer a software category. It's cloud, integration, data. That's the new normal. That's the new category, right? So as companies are building their products, and want to do a good job, it used to be, you send out surveys, you try to get the product market fit. And if you were smart, you got it right the third, fourth, 10th time. If you were lucky, like some companies, you get it right the first time. But the holy grail is to get it right the first time. And now, this new data acquisition opportunities that you guys in the middle of that can tap customers or prospects or end users to get data before things are shipped, or built, or to iterate on products. This is the customer feedback loop or data, voice of the customer journey. It's a gold mine. And it's you guys, it's your secret weapon. Take us through what this is about now. I mean, it's not just surveys. What's different? >> So yeah, if we go back to why are we building unitQ? Which is we want to build a quality company. Which is basically, how do we enable other companies to build higher quality experiences by tapping into all of the existing data assets? And the one we are in particularly excited about is user feedback. So me and my co-founder, Nik, and we're doing now the second company together. We spent 14 years. So we're like an old married couple. We accept each other, and we don't fight anymore, which is great. We did a consumer company called Skout, which was sold five years ago. And Skout was kind of early in the whole mobile first. I guess, we were actually mobile first company. And when we launched this one, we immediately had the entire world as our marketplace, right? Like any modern company. We launch a product, we have support for many languages. It's multiple platforms. We have Android, iOS, web, big screens, small screens, and that brings some complexities as it relates to staying on top of the quality of the experience because how do I test everything? >> John: Yeah. >> Pre-production. How do I make sure that our Polish Android users are having a good day? And we found at Skout, personally, like I could discover million dollar bugs by just drinking coffee and reading feedback. And we're like, "Well, there's got to be a better way to actually harness the end user feedback. That they are leaving in so many different places." So, you know what, what unitQ does is that we basically aggregate all different sources of user feedback, which can be app store reviews, Reddit posts, Tweets, comments on your Facebook ads. It can be better Business Bureau Reports. We don't like to get to many of those, of course. But really, anything on the public domain that mentions or refers to your product, we want to ingest that data in this machine, and then all the private sources. So you probably have a support system deployed, a Zendesk, or an Intercom. You might have a chatbot like an Ada, or and so forth. And your end user is going to leave a lot of feedback there as well. So we take all of these channels, plug it into the machine, and then we're able to take this qualitative data. Which and I actually think like, when an end user leaves a piece of feedback, it's an act of love. They took time out of the day, and they're going to tell you, "Hey, this is not working for me," or, "Hey, this is working for me," and they're giving you feedback. But how do we package these very messy, multi-channel, multiple languages, all over the place data? How can we distill it into something that's quantifiable? Because I want to be able to monitor these different signals. So I want to turn user feedback into time series. 'Cause with time series, I can now treat this the same way as Datadog treats machine logs. I want to be able to see anomalies, and I want to know when something breaks. So what we do here is that we break down your data in something called quality monitors, which is basically machine learning models that can aggregate the same type of feedback data in this very fine grained and discrete buckets. And we deploy up to a thousand of these quality monitors per product. And so we can get down to the root cause. Let's say, passive reset link is not working. And it's in that root cause, the granularity that we see that companies take action on the data. And I think historically, there has been like the workflow between marketing and support, and engineering and product has been a bit broken. They've been siloed from a data perspective. They've been siloed from a workflow perspective, where support will get a bunch of tickets around some issue in production. And they're trained to copy and paste some examples, and throw it over the wall, file a Jira ticket, and then they don't know what happens. So what we see with the platform we built is that these teams are able to rally around the single source of troop or like, yes, passive recent link seems to have broken. This is not a user error. It's not a fix later, or I can't reproduce. We're looking at the data, and yes, something broke. We need to fix it. >> I mean, the data silos a huge issue. Different channels, omnichannel. Now, there's more and more channels that people are talking in. So that's huge. I want to get to that. But also, you said that it's a labor of love to leave a comment or a feedback. But also, I remember from my early days, breaking into the business at IBM and Hewlett-Packard, where I worked. People who complain are the most loyal customers, if you service them. So it's complaints. >> Christian: Yeah. >> It's leaving feedback. And then, there's also reading between the lines with app errors or potentially what's going on under the covers that people may not be complaining about, but they're leaving maybe gesture data or some sort of digital trail. >> Yeah. >> So this is the confluence of the multitude of data sources. And then you got the siloed locations. >> Siloed locations. >> It's complicated problem. >> It's very complicated. And when you think about, so I started, I came to Bay Area in 2005. My dream was to be a quant analyst on Wall Street, and I ended up in QA at VMware. So I started at VMware in Palo Alto, and didn't have a driver's license. I had to bike around, which was super exciting. And we were shipping box software, right? This was literally a box with a DVD that's been burned, and if that DVD had bugs in it, guess what it'll be very costly to then have to ship out, and everything. So I love the VMware example because the test cycles were long and brutal. It was like a six month deal to get through all these different cases, and they couldn't be any bugs. But then as the industry moved into the cloud, CI/CD, ship at will. And if you look at the modern company, you'll have at least 20 plus integrations into your product. Analytics, add that's the case, authentication, that's the case, and so forth. And these integrations, they morph, and they break. And you have connectivity issues. Is your product working as well on Caltrain, when you're driving up and down, versus wifi? You have language specific bugs that happen. Android is also quite a fragmented market. The binary may not perform as well on that device, or is that device. So how do we make sure that we test everything before we ship? The answer is, we can't. There's no company today that can test everything before the ship. In particular, in consumer. And the epiphany we had at our last company, Skout, was that, "Hey, wait a minute. The end user, they're testing every configuration." They're sitting on the latest device, the oldest device. They're sitting on Japanese language, on Swedish language. >> John: Yeah. >> They are in different code paths because our product executed differently, depending on if you were a paid user, or a freemium user, or if you were certain demographical data. There's so many ways that you would have to test. And PagerDuty actually had a study they came out with recently, where they said 51% of all end user impacting issues are discovered first by the end user, when they serve with a bunch of customers. And again, like the cool part is, they will tell you what's not working. So now, how do we tap into that? >> Yeah. >> So what I'd like to say is, "Hey, your end user is like your ultimate test group, and unitQ is the layer that converts them into your extended test team." Now, the signals they're producing, it's making it through to the different teams in the organization. >> I think that's the script that you guys are flipping. If I could just interject. Because to me, when I hear you talking, I hear, "Okay, you're letting the customers be an input into the product development process." And there's many different pipelines of that development. And that could be whether you're iterating, or geography, releases, all kinds of different pipelines to get to the market. But in the old days, it was like just customer satisfaction. Complain in a call center. >> Christian: Yeah. >> Or I'm complaining, how do I get support? Nothing made itself into the product improvement, except for slow moving, waterfall-based processes. And then, maybe six months later, a small tweak could be improved. >> Yes. >> Here, you're taking direct input from collective intelligence. Okay. >> Is that have input and on timing is very important here, right? So how do you know if the product is working as it should in all these different flavors and configurations right now? How do you know if it's working well? And how do you know if you're improving or not improving over time? And I think the industry, what can we look at, as far as when it relates to quality? So I can look at star ratings, right? So what's the star rating in the app store? Well, star ratings, that's an average over time. So that's something that you may have a lot of issues in production today, and you're going to get dinged on star ratings over the next few months. And then, it brings down the score. NPS is another one, where we're not going to run NPS surveys every day. We're going to run it once a quarter, maybe once a month, if we're really, really aggressive. That's also a snapshot in time. And we need to have the finger on the pulse of product quality today. I need to know if this release is good or not good. I need to know if anything broke. And I think that real time aspect, what we see as stuff sort of bubbles up the stack, and not into production, we see up to a 50% reduction in time to fix these end user impacting issues. And I think, we also need to appreciate when someone takes time out of the day to write an app review, or email support, or write that Reddit post, it's pretty serious. It's not going to be like, "Oh, I don't like the shade of blue on this button." It's going to be something like, "I got double billed," or "Hey, someone took over my account," or, "I can't reset my password anymore. The CAPTCHA, I'm solving it, but I can't get through to the next phase." And we see a lot of these trajectory impacting bugs and quality issues in these work, these flows in the product that you're not testing every day. So if you work at Snapchat, your employees probably going to use Snapchat every day. Are they going to sign up every day? No. Are they going to do passive reset every day? No. And these things are very hard to instrument, lower in the stack. >> Yeah, I think this is, and again, back to these big problems. It's smoke before fire, and you're essentially seeing it early with your process. Can you give an example of how this new focus or new mindset of user feedback data can help customers increase their experience? Can you give some examples, 'cause folks watching and be like, "Okay, I love this value. Sell me on this idea, I'm sold. Okay, I want to tap into my prospects, and my customers, my end users to help me improve my product." 'Cause again, we can measure everything now with data. >> Yeah. We can measure everything. we can even measure quality these days. So when we started this company, I went out to talk to a bunch of friends, who are entrepreneurs, and VCs, and board members, and I asked them this very simple question. So in your board meetings, or on all hands, how do you talk about quality of the product? Do you have a metric? And everyone said, no. Okay. So are you data driven company? Yes, we're very data driven. >> John: Yeah. Go data driven. >> But you're not really sure if quality, how do you compare against competition? Are you doing as good as them, worse, better? Are you improving over time, and how do you measure it? And they're like, "Well, it's kind of like a blind spot of the company." And then you ask, "Well, do you think quality of experience is important?" And they say, "Yeah." "Well, why?" "Well, top of fund and growth. Higher quality products going to spread faster organically, we're going to make better store ratings. We're going to have the storefronts going to look better." And of course, more importantly, they said the different conversion cycles in the product box itself. That if you have bugs and friction, or an interface that's hard to use, then the inputs, the signups, it's not going to convert as well. So you're going to get dinged on retention, engagement, conversion to paid, and so forth. And that's what we've seen with the companies we work with. It is that poor quality acts as a filter function for the entire business, if you're a product led company. So if you think about product led company, where the product is really the centerpiece. And if it performs really, really well, then it allows you to hire more engineers, you can spend more on marketing. Everything is fed by this product at them in the middle, and then quality can make that thing perform worse or better. And we developed a metric actually called the unitQ Score. So if you go to our website, unitq.com, we have indexed the 5,000 largest apps in the world. And we're able to then, on a daily basis, update the score. Because the score is not something you do once a month or once a quarter. It's something that changes continuously. So now, you can get a score between zero and 100. If you get the score 100, that means that our AI doesn't find any quality issues reported in that data set. And if your score is 90, that means that 10% will be a quality issue. So now you can do a lot of fun stuff. You can start benchmarking against competition. So you can see, "Well, I'm Spotify. How do I rank against Deezer, or SoundCloud, or others in my space?" And what we've seen is that as the score goes up, we see this real big impact on KPI, such as conversion, organic growth, retention, ultimately, revenue, right? And so that was very satisfying for us, when we launched it. quality actually still really, really matters. >> Yeah. >> And I think we all agree at test, but how do we make a science out of it? And that's so what we've done. And when we were very lucky early on to get some incredible brands that we work with. So Pinterest is a big customer of ours. We have Spotify. We just signed new bank, Chime. So like we even signed BetterHelp recently, and the world's largest Bible app. So when you look at the types of businesses that we work with, it's truly a universal, very broad field, where if you have a digital exhaust or feedback, I can guarantee you, there are insights in there that are being neglected. >> John: So Chris, I got to. >> So these manual workflows. Yeah, please go ahead. >> I got to ask you, because this is a really great example of this new shift, right? The new shift of leveraging data, flipping the script. Everything's flipping the script here, right? >> Yeah. >> So you're talking about, what the value proposition is? "Hey, board example's a good one. How do you measure quality? There's no KPI for that." So it's almost category creating in its own way. In that, this net new things, it's okay to be new, it's just new. So the question is, if I'm a customer, I buy it. I can see my product teams engaging with this. I can see how it can changes my marketing, and customer experience teams. How do I operationalize this? Okay. So what do I do? So do I reorganize my marketing team? So take me through the impact to the customer that you're seeing. What are they resonating towards? Obviously, getting that data is key, and that's holy gray, we all know that. But what do I got to do to change my environment? What's my operationalization piece of it? >> Yeah, and that's one of the coolest parts I think, and that is, let's start with your user base. We're not going to ask your users to ask your users to do something differently. They're already producing this data every day. They are tweeting about it. They're putting in app produce. They're emailing support. They're engaging with your support chatbot. They're already doing it. And every day that you're not leveraging that data, the data that was produced today is less valuable tomorrow. And in 30 days, I would argue, it's probably useless. >> John: Unless it's same guy commenting. >> Yeah. (Christian and John laughing) The first, we need to make everyone understand. Well, yeah, the data is there, and we don't need to do anything differently with the end user. And then, what we do is we ask the customer to tell us, "Where should we listen in the public domain? So do you want the Reddit post, the Trustpilot? What channels should we listen to?" And then, our machine basically starts ingesting that data. So we have integration with all these different sites. And then, to get access to private data, it'll be, if you're on Zendesk, you have to issue a Zendesk token, right? So you don't need any engineering hours, except your IT person will have to grant us access to the data source. And then, when we go live. We basically build up this taxonomy with the customers. So we don't we don't want to try and impose our view of the world, of how do you describe the product with these buckets, these quality monitors? So we work with the company to then build out this taxonomy. So it's almost like a bespoke solution that we can bootstrap with previous work we've done, where you don't have these very, very fine buckets of where stuff could go wrong. And then what we do is there are different ways to hook this into the workflow. So one is just to use our products. It's a SaaS product as anything else. So you log in, and you can then get this overview of how is quality trending in different markets, on different platforms, different languages, and what is impacting them? What is driving this unitQ Score that's not good enough? And all of these different signals, we can then hook into Jira for instance. We have a Jira integration. We have a PagerDuty integration. We can wake up engineers if certain things break. We also tag tickets in your support system, which is actually quite cool. Where, let's say, you have 200 people, who wrote into support, saying, "I got double billed on Android." It turns out, there are some bugs that double billed them. Well, now we can tag all of these users in Zendesk, and then the support team can then reach out to that segment of users and say, "Hey, we heard that you had this bug with double billing. We're so sorry. We're working on it." And then when we push fix, we can then email the same group again, and maybe give them a little gift card or something, for the thank you. So you can have, even big companies can have that small company experience. So, so it's groups that use us, like at Pinterest, we have 800 accounts. So it's really through marketing has vested interest because they want to know what is impacting the end user. Because brand and product, the lines are basically gone, right? >> John: Yeah. >> So if the product is not working, then my spend into this machine is going to be less efficient. The reputation of our company is going to be worse. And the challenge for marketers before unitQ was, how do I engage with engineering and product? I'm dealing with anecdotal data, and my own experience of like, "Hey, I've never seen these type of complaints before. I think something is going on." >> John: Yeah. >> And then engineering will be like, "Ah, you know, well, I have 5,000 bugs in Jira. Why does this one matter? When did it start? Is this a growing issue?" >> John: You have to replicate the problem, right? >> Replicate it then. >> And then it goes on and on and on. >> And a lot of times, reproducing bugs, it's really hard because it works on my device. Because you don't sit on that device that it happened on. >> Yup. >> So now, when marketing can come with indisputable data, and say, "Hey, something broke here." And we see the same with support. Product engineering, of course, for them, we talk about, "Hey, listen, you you've invested a lot in observability of your stack, haven't you?" "Yeah, yeah, yeah." "So you have a Datadog in the bottom?" "Absolutely." "And you have an APP D on the client?" "Absolutely." "Well, what about the last mile? How the product manifests itself? Shouldn't you monitor that as well using machines?" They're like, "Yeah, that'd be really cool." (John laughs) And we see this. There's no way to instrument everything, lowering the stack to capture these bugs that leak out. So it resonates really well there. And even for the engineers who's going to fix it. >> Yeah. >> I call it like empathy data. >> Yup. >> Where I get assigned a bug to fix. Well, now, I can read all the feedback. I can actually see, and I can see the feedback coming in. >> Yeah. >> Oh, there's users out there, suffering from this bug. And then when I fix it and I deploy the fix, and I see the trend go down to zero, and then I can celebrate it. So that whole feedback loop is (indistinct). >> And that's real time. It's usually missed too. This is the power of user feedback. You guys got a great product, unitQ. Great to have you on. Founder and CEO, Christian Wiklund. Thanks for coming on and sharing, and showcase. >> Thank you, John. For the last 30 seconds, the minute we have left, put a plug in for the company. What are you guys looking for? Give a quick pitch for the company, real quick, for the folks out there. Looking for more people, funding status, number of employees. Give a quick plug. >> Yes. So we raised our A Round from Google, and then we raised our B from Excel that we closed late last year. So we're not raising money. We are hiring across go-to-markets, engineering. And we love to work with people, who are passionate about quality and data. We're always, of course, looking for customers, who are interested in upping their game. And hey, listen, competing with features is really hard because you can copy features very quickly. Competing with content. Content is commodity. You're going to get the same movies more or less on all these different providers. And competing on price, we're not willing to do. You're going to pay 10 bucks a month for music. So how do you compete today? And if your competitor has a better fine tuned piano than your competitor will have better efficiencies, and they're going to retain customers and users better. And you don't want to lose on quality because it is actually a deterministic and fixable problem. So yeah, come talk to us if you want to up the game there. >> Great stuff. The iteration lean startup model, some say took craft out of building the product. But this is now bringing the craftsmanship into the product cycle, when you can get that data from customers and users. >> Yeah. >> Who are going to be happy that you fixed it, that you're listening. >> Yeah. >> And that the product got better. So it's a flywheel of loyalty, quality, brand, all off you can figure it out. It's the holy grail. >> I think it is. It's a gold mine. And every day you're not leveraging this assets, your use of feedback that's there, is a missed opportunity. >> Christian, thanks so much for coming on. Congratulations to you and your startup. You guys back together. The band is back together, up into the right, doing well. >> Yeah. We we'll check in with you later. Thanks for coming on this showcase. Appreciate it. >> Thank you, John. Appreciate it very much. >> Okay. AWS Startup Showcase. This is season two, episode three, the ongoing series. This one's about MarTech, cloud experiences are scaling. I'm John Furrier, your host. Thanks for watching. (upbeat music)

[Music] thecube's coverage of red hat summit 2022 thecube has been covering red hat summit for a number of years of course the last two years were virtual coverage now the red hat summit is one of the industry's most premier events and and typically red hat summits are many thousands of people i think the last one i went to was eight or nine thousand people very heavy developer conference this year red hat has taken a different approach it's a hybrid event it's kind of a vip event at the westin in boston with a lot more executives here than we would normally expect versus developers but a huge virtual audience my name is dave vellante i'm here with my co-host paul gillin paul this is a location that you and i have broadcast from many times and um of course 2019 the summer of 2019 ibm acquired red hat and um we of course we did red hat summit that year but now we're seeing a completely new red hat and a new ibm and you wouldn't know ibm owned red hat for what they've been talking about at this conference we just came out of the keynote where uh in the in the hour-long keynote ibm was not mentioned once and only appeared the logo only appeared once on the screen in fact so this is uh very much red hat being red hat not being a subsidiary at ibm and perhaps that's justified given that ibm's track record with acquisitions is that they gradually envelop the acquired company and and it becomes part of the ibm board yeah they blue wash the whole thing right it's ironic because ibm think is going on right across the street arvin krishna is here but no presence here and i think that's by design i mean it reminds me of when you know emc owned vmware you know the vmware team didn't want to publicize that they had an ecosystem of partners that they wanted to cater to and they wanted to treat everybody equally even though perhaps behind the scenes they were forced to do certain things that they might not have necessarily wanted to because they were owned by another company and i think that you know certainly ibm's done a good job of leaving the brand separate but when they talk about the con the conference calls ibm's earnings calls you certainly get a heavy dose of red hat when red hat was acquired by ibm it was just north of three billion dollars in revenue obviously ibm paid 34 billion dollars for the company actually by today's valuations probably a bargain you know despite the market sell-off in the last several months uh but now we've heard public statements from arvind kushner that that red hat is a 5 billion plus revenue company it's a little unclear what's in there of course when you listen to ibm earnings you know consulting is their big business red hat's growing at 21 but when i remember paul when red hat was acquired stu miniman and i did a session and i said this is not about cloud this is about consulting and modernizing applications and sure there's some cloud in there with openshift but from a financial standpoint ibm was able to take red hat and jam it right into its application modernization initiatives so it's hard to tell how much of that 5 billion is actually you know legacy red hat but i guess it doesn't matter anymore it's working ibm mathematics is notoriously opaque they if the business isn't going well it'll tend to be absorbed into another number in the in the earnings report that that does show some growth so we've heard uh certainly ibm talks a lot about red hat on its earnings calls it's very clear that red hat is the growth engine within ibm i'd say it's a bit of the tail wagging the dog right now where red hat really is dictating where ibm goes with its hypercloud strategy which is the foundation not only of its technology portfolio but of its consulting business and so red hat is really in the driver's seat of of hybrid cloud and that's the future for ibm and you see that very much at this conference where uh red hat is putting out its uh series of announcements today about improvements to his hybrid cloud the new release of route 9 red hat enterprise linux 9 improvements to its hybrid cloud portfolio it very much is going its own way with that and i sense that ibm is going to go along with wherever red hat chooses to go yeah i think you're absolutely right if by the way if you go to siliconangle.com paul just published a piece on red hat reds hats their roll out of their parade which of course is as you pointed out led by enterprise linux but to your point about hybrid cloud it is the linchpin of of certainly ibm strategy but many companies hybrid cloud strategies if you think about it openshift in particular it's it's the modern application development environment for kubernetes you can get kubernetes you can buy eks you can get that for free in a lot of places but you have to do dozens and dozens of things and acquire dozens of services to do what openshift does to get the reliability the recoverability the security and that's really red hat's play and they're the the thing about red hat combining with linux their linux heritage they're doing that everywhere it's going to open shift everywhere red hat everywhere whether it's on-prem in aws azure google out to the edge you heard paul cormier today saying he expects that in the next several years hardware is going to become one of the most important you know factors i agree i think we're going to enter a hardware renaissance you've seen the work that we've done on arm i think 2017 was when red hat and arm announced kind of their initial collaboration could have even been before that today we're hearing a lot about intel and nvidia and so affinity with all of these alternative processes i think they did throw in today in the keynote power and so i think i heard that that was the other ibm branding they sort of tucked that in there but the point is red hat runs everywhere so it's fundamental to building out hybrid cloud and that is fundamental to a lot of company strategies and red hat has been all over kubernetes with openshift it's i mean it's a drum beat here uh the openshift strategy is what really makes hybrid cloud possible because kubernetes is what makes it possible to shift workloads seamlessly from platform to platform you make an interesting point about hardware we have seen kind of a renaissance in hardware these last couple of years as these specific chipsets and uh and even full-scale processors have come to market we're seeing several in the ai area right now where startups are developing full-blown chipsets and and systems uh just for ai processing and nvidia of course that's that's really kind of their stock and trade these days so uh a a company that can run across all of those different platforms a platform like like rel which can run all across those different platforms is going to have a leg up on on anybody else and the implications for application development are considerable when you when you think about we talk about a lot about these alternative processes when flash replaced the spinning disk that had a huge impact on how applications are developed developers now didn't have to wait for that that disc to spin even though it's spinning very fast it's mechanical compared to electrons forget it and and the second big piece here is how memory is actually utilized the x86 you know traditional x86 you know memory everything goes through that core processor intel for years grabbed more and more function and you're seeing now that function become dispersed in fact a lot of people think we're moving from a processor-centric world to a connect centric world meaning connecting all these piece parts alternative processors memory controllers you know storage controllers io network interface cards smartnics and things like that where the communication across those resources is now where a lot of the innovation is going you see you're seeing a lot of that and now of course applications can take advantage of that especially now at the edge which is just a whole new frontier the edge certainly is part of that equation when you look at machine learning at training machine learning models the cpu actually does relatively little work most of it is happening in gpus in these parallel processes that are going on and the cpu is kind of acting as a traffic cop and you see that in the edge as well it's the same model at the edge where more of the intelligence is going to be out in discrete devices spread across the network and the cpu is going to be less of a uh you know less of a engine of intelligence at the same time though we've got cpus with we've got 100 core cpus are on the horizon and there are even 200 and 300 core cpus that we may see in the next uh in the next couple of years so cpus aren't standing still they are evolving to become really kind of super traffic cops for all of these other processors out in the network and on the edge so it's a very exciting time to be in hardware because so much innovation is happening really at the microprocessor level well we saw this you and i lived through the pc era and we saw a whole raft of applications come about as a result of the microprocessor the shift of the microprocessor-based economy we're going to see so we are seeing something similar with mobile and the edge you know just think about some of the numbers if you think about the traditional moore's law doubling a number of transistors every let's call it two years 18 to 24 months pat gelsinger at intel promises that intel is on that pace still but if you look at the apple m1 ultra they increased the transistor density 6x in the last 15 months okay so where is this another data point is the historical moore's law curve is 40 that's moderating to somewhere down you know down in the low 30s if you look at the apple a series i mean that thing is on average increasing performance at 110 a year when you add up into the combinatorial factors of the cpu the neural processing unit the gpu all the accelerators so we are seeing a new era the thing i i i wanted to bring up paul is you mentioned ai much of the ai work that's done today is modeling that's done in the cloud and when we talk about edge we think that the future of ai is ai inferencing in real time at the edge so you may not even be persisting that data but you're going to create a lot of data you're going to be operating on that data in streams and it's going to require a whole new new architectural thinking of hardware very low cost very low power very high performance to drive all that intelligence at the edge and a lot of that data is going to stay at the edge and and that's we're going to talk about some of that today with some of the ev innovations and the vehicle innovations and the intelligence in these vehicles yeah and in talking in its edge strategy which it outlined today and the announcements that are made today red hat very much uh playing to the importance of being able to run red hat enterprise linux at the edge the idea is you do these big machine learning models centrally and then you you take the you take what results from that and you move it out to smaller processors it's the only way we can cope with it with the explosion of data that will be uh that these sensors and other devices will be generating so some of the themes we're hearing in the uh announcements today that you wrote about paul obviously rel9 is huge uh red hat enterprise linux version nine uh new capabilities a lot of edge a lot of security uh new cross portfolio capabilities for the edge security in the software supply chain that's a big conversation especially post solar winds managed ansible when you think about red hat you really i think anyway about three things rel which is such as linux it powers the internet powers everything uh you think of openshift which is application development you think about ansible which is automation so itops so that's one of the announcements ansible on azure and then a lot of hybrid cloud talk and you're gonna hear a lot of talk this week about red hat's cloud services portfolio packaging red hat as services as managed services that's you know a much more popular delivery mechanism with clients because they're trying to make it easy and this is complicated stuff and it gets more complicated the more features they add and the more the more components of the red hat portfolio are are available it's it's gonna be complex to build these hybrid clouds so like many of these so thecube started doing physical events last summer by the way and so this is this is new to a lot of people uh they're here for the first time people are really excited we've definitely noticed a trend people are excited to be back together paul cormier talked about that he talked about the new normal you can define the new normal any way you want so paul cormier gave the uh the the intro keynote bidani interviewed amex stephanie cheris interviewed accenture both those firms are coming out stephanie's coming on with the in accenture as well matt hicks talked about product innovation i loved his reference to ada lovelace that was very cool he talked about uh serena uh ramyanajan a famous mathematician who nobody knew about when he was just a kid these were ignored individuals in the 1800s for years and years and years in the case of ada lovelace for a century even he asked the question what if we had discovered them earlier and acted on them and been able to iterate on them earlier and his point tied that to open source very brilliantly i thought and um keynotes which i appreciate are much shorter much shorter intimate they did a keynote in the round this time uh which i haven't seen before there's maybe a thousand people in there so a much smaller group much more intimate setting not a lot of back and forth but uh but there is there is a feeling of a more personal feel to this event than i've seen it past red hat summits yeah and i think that's a trend that we're going to see more of where the live audience is kind of the on the ground it's going to the vip audience but still catering to the virtual audience you don't want to lose them so that's why the keynotes are a lot tighter okay paul thank you for setting up red hat summit 2022 you're watching the cube's coverage we'll be right back wall-to-wall coverage for two days right after this short break [Music] you

(upbeat music) >> Welcome to theCUBE coverage of women in tech. International Women's Day 2022. I'm your host, Lisa Martin. Karla Wong joins me next. Country Sales Leader for the Commercial Sector in Peru at AWS. Karla, welcome to theCUBE. >> Thank you so much Lisa and thank you for having me. It's a pleasure to be with you today. >> I'm looking forward to chatting with you. You've been in the tech industry for more than 20 years, you've been a leader in tech and sales and customer service, partners, organizations. Talk to me a little bit about your background. >> I am a system engineer. I have some studies from enterprise direction with a university in Savannah, Columbia and I have a digital transformation certified with MIT in Boston. >> Fantastic, were you always interested in technology or STEM or was it something that you pivoted into somewhere during your career? >> Yes, you know what? Since I was little, I was just fascinated with the technology and all the time I was just trying to figure out how to do things and how to build that things and I remember once I was just, of course many time long ago, I was with this BHS, right? An equipment and I tried to do and tried to understand how this works and just figure out I was with many parts of that equipment and then I didn't realize how to join that parts but it was really funny because all the time I was trying to understand what is behind that kind of equipment, how this works and all the time I was asking and my dad said, I was just feeling so curiosity about that and asking many questions and I have uncles that they are engineers. So I was just all the time asking about that and they said, you know what? You are good in math, maybe you can just decide for an engineering career. They were encouraged me for doing that. So I guess that was my first clue that I'm interested in technology. >> Well, you sounds like you have a natural curiosity that you had great role models in your parents and probably others along your educational route and your career route that kind of encouraged that curiosity and being curious is one of the things that's important to being at AWS. Am I right? >> Yes, it's really important because we promote, you know, our, one of the main leadership principles that you read is learn to be curious and they promote that one, right? They're encouraging you to innovate, to learn more, to try to understand more about our solutions, our customers, how to make the things better and you have the space to propose new things, to do the things better. So they encourage you and they empower you to do that and you feel like your curiosity that you have very natural here's improved and they just promote that you continue to do that. >> That curiosity is so important. I mean, when we think about women in technology and we think about bringing in more thought diversity and DEI, it's important to be curious, to be able to bring different thoughts in so that the organization can be more well rounded, it can learn, you also not only do you lead the sales organization, but you are someone that's very active in volunteering. Tell me a little bit about that and how do you balance leading a sales organization and volunteering at the same time? >> You know, when you talk about this is more like work life balance, right? And when we talk about that you can feel like you need it, right? You need to work on that. It's more like an attitude of it's extremely important to think about mental health for everyone because that of course have impact in your physical health and when you talk about this, it not only matters in terms of attitude, it's action and disciplines as well and you have to keep in mind that. The first thing I believe and all the time I do it give the right value for this balance because it's something that a lot of people want more than anything and I have more than some professional decision thinking about this precisely and I have to thinking of me as a person, my family, how to help the community and you cannot imagine the impact when you decide to go for a volunteering activities how can benefit you and not in only the personal way, in your professional way. Even though you didn't start a volunteering, trying to figure out how this help you in your professional life, you receive a lot of benefits from the volunteering activities and it's amazing how that one's impacting your professional life also. When you are a volunteer, you'll receive new and meaningful experiences. Volunteering can be an excellent getaway to find unique and valuable experiences that you are very difficult to find in a day to day basis, right? And you develop your real life skills, openness to criticism, responsibility, humility, commitment, service, attitude, many things that you can proactively include in your job with your team and you can join with them in teamwork and try to figure out how to engage with them in your activities. This is another way to motivate your team, to build your team, right? Talking with this very valuable experiences and also I find out that that improves your health and mood. >> Sounds very-- >> We talk having-- >> Sorry. >> I'm sorry, no don't worry. >> That's very complimentary, that the volunteer work with leading the sales organization that there's so much value that you're bringing into your sales leadership role from the volunteering that you do. I'm just curious, can you describe some of the volunteer organizations that you work with? I think it's pretty impressive. >> Yes, I started my volunteering 14 years ago I guess but I was in the volunteering activities from the school and my dad was a really strong influence for that because I joined, I remember joining with him and go to do some volunteering activities that he led and I start 14 years I went with Operation and Smile group and then in the last two or three years I start with Project of Love. We are focused on kids with cancer and try to help them to build the last wishes they have because they pass away and at the end of this, this two years ago, I start with local activity that we do for patients with rare diseases and we just try to join two great passion that I have. One is the dance that we have here. The name of our national dance is Marinera Norteña and we are just doing this with a group that they are passion at the same time with this volunteering activities and the dance and we just trying to be the ambassador for and the voice for these patients, try to share with the community, the hard health journey that they have trying to obtain a fair treatment, a fair diagnostic, because they are rare disease and here is very difficult that they investigate about that. So that's why we are just doing this using dance as a way to broadcast our voice and just share happiness and hope and health. >> Happiness and hope. Those are two great things. So as the female leader in the tech industry, what are some of the main challenges that you have found regarding cultural aspects, regarding geographical aspects and LATAM? Talk to me about some of those challenges. >> Let me share with you my personal journey. My challenges started with the moment I decided to start engineering. A career that is traditional considered for men only, although this changes over the time, you will realize that the stereotype remains in many people minds right? It happens not only in Peru I can see it in Latin America. Someone once asked me if I wouldn't like to study something easier for a woman, right? And I just, when I received that question, that helping me to reaffirm that it was taking the right decision and I have the fortune to work with companies that believe in female leadership and the importance of our contribution and empower me to do things differently. Although I must confess that this was not always like this. I experienced the situation when I have to show that I'm so much and more capable and prepared than a man to take a major challenge. So despite the fact in the recent years you have had the great advances in integration of women in the field of science and technology, the gap in equality in equality in this sector still continues and many times the attitude towards women is discriminatory considering that we don't have enough knowledge and we don't have enough strength to overcome challenge without the ability to give the extra mile that is often required, or simply because of a gender issue. And generally speaking, opportunities that they're not equal. Neither in salaries. Several studies have revealed that in the same position since at position level within company, men's salary or benefits are higher than the woman. In addition, sometimes the position for a woman is not necessarily for merit it's just to feel fulfill a gender quota and when it's fulfilled, there's no more opportunities. So it's still a long way to go. We are working in that, we are trying to inspire more women to be part of this world. This is an amazing world and this world needs our leadership, judgment, ambition, as a woman. So that's why we try to inspire and try to be a role model for some young ladies that they are thinking about this career in technology. >> Right, you bring up a great point though about one of the things in terms of hiring for quotas. And as we think about this International Women's Day, this year's theme is Breaking the Bias. Where do you think we are with that? >> I think we have a lot long, long way to go to. Today we don't see that we have more women in some leadership roles in technology. We see more young ladies studying engineering but you know what, when you talk about stereotypes we need to understand, or the bias, the bias is not only what the society it's giving you, it's also your own bias because we need to understand that technology careers is not only for men it's also for a woman. And we need to understand and change the perspective that we see the challenges that we have in our life because sometimes that could be a really stopper in your professional life. And for me, we don't, we really need to understand that it's important. We cannot stop believing in ourself and we can achieve whatever we want. So we never stop pursuing our goals and achieve what you really need to achieve and as I said all the time, get inspired by women with great achievements who have changed this world technology. We have many examples of that for many years. We have Eva Maria Kiesler, the core inventor of Wi-Fi, Radia Joy Perlman, known as the the mother of the internet and Ada Lovelace who became the first female computer programmer. So we have many examples in this story to understand that the limit is on you. So the bias we need to break the first one is the bias that you have of yourself. >> That's a good point. That's a really good point there. I'm curious, what would your recommendation be? You obviously had, you had that natural curiosity that we talked about. You also seems like you had great parents who were very encouraging of all of the different things that you were interested in. What do you recommend for women maybe starting out in the STEM area or in tech in particular? How do they get that courage to just try? >> You know what, the main thing I guess as I mentioned before, is to put aside the stereotypes, right? And get out of your head, the standing out career like science, technology and engineering is only for a man. All the time I have this list for me, that is lesson learned. And my lesson learned is please don't think that you cannot do it. Try it. If you go and the things do not work well, try it again and try it again. So don't feel stopped because you face your first challenge and the challenge it's very difficult, because we have the courage to do that and you know what? It is very and interesting to understand that women has resilience, we have the courage to do anything, we are multi tasking all the time they say women can do many things at the same time and we have this particular way to communicate. We are very inclusive. We make empathy. We're just leading with a cohesion concept of a team. So we need to explore more about our strengths and try to encourage from them. And one of the main things for me is don't feel afraid and transform, you know, when you feel like that, transfer that as your power, you're encouraged to continue. So we need to transform our fears in our, I always said our gasoline to continue and then your motive to be successful. So transform your fears. >> I love that. >> That's my main focus. >> Transform your fear. That's great advice there is. And I will say no, don't be afraid to raise your hand and ask a question 'cause I guarantee you, many people in the room whether it's a physical room these days or it's a virtual video conferencing room, probably have the same question. Be the one to raise your hand and ask. But I love how you're saying transform that fear 'cause it's there. Don't be afraid to fail but also we need to have those female role models, mentors and sponsors that we can see that can have help us kind of in that transformation process, that mentorship is really critical to help guide that along. >> Yes, yes, yes, that's correct and I will, I am, I was really fortunate because I have real role models in my life not only, as I mentioned my dad and also one of the things that I recognize in this company that I work for that empower leadership from women and I identify some role models I want to follow and I ask her in each particular company to be my coach and to be my mentor, because of course you are starting in the technology side and you need more from others that they can share with you her wisdom, right? And try to give you advice, how to work on that. And I always said, and I will always repeat because I sometimes I have the opportunity to mentor young ladies that they are very curious about the technology side and I share with them my experience, my lesson learned so they can build their own story to do this and I share all the time don't compete in a male environment in a gray suit. You have your own personality, you have your own strengths, you're a woman and you have your strength as a woman. Show that, be, you know, the black point in the middle of the white environment because you're different, your leadership is different. You have to understand that, value that and explore more about that so you can inspire others and you can inspire yourself and it's fair to say, please identify your achievements and value them because you deserve that, you fight for them and you have to be celebrate for that. >> Right. >> So that's the main, you know, the main idea when I share with these ladies but it's right, it's fair to be recognized for that. It's your effort, it's your way to do the things differently and it's very appreciated. >> Very appreciated and very inspiring. Thank you so much Karla for sharing your story, how you are balancing work life volunteerism, how it's complimentary. I found this conversation very inspiring so thank you so much for joining me today. >> Thank you. No, thank you so much Lisa. It was really a pleasure for me to be with you today. >> Excellent, likewise. For Karla Wong, I'm Lisa Martin. You're watching theCUBE's coverage of women in tech, International Women's Day 2022. (upbeat music)

>>Welcome back to the cubes coverage of ADA reinvent 2021 here, the cube coverage. I'm Judd for a, your host we're on the ground with two sets on the floor, real event. Of course, it's hybrid. It's online as well. You can check it out there. All the on-demand replays are there. We're here with Sandy Carter, worldwide vice president, public sector partners and programs. And we've got Fred Swanick, her founder, and chief curator of the room. We're talking about getting the best talent programming and in the cloud, doing great things, innovation all happening, Sandy. Great to see you. Thanks for coming on the cube, but appreciate it. Thanks for halfway to see. Okay. So tell us about the room. What is the room what's going on? >>Um, well, I mentioned in the room is to help the world's most extraordinary do us to fulfill their potential. So, um, it's a community of exceptional talent that we are building throughout the world, um, and connecting this talent to each other and connecting them to the organizations that are looking for people who can really move the needle for those organizations. >>So what kind of results are you guys seeing right now? Give us some stats. >>Well, it's a, it's a relatively new concept. So we're about 5,000 members so far, um, from 77 different countries. Um, and this is, you know, we're talking about sort of the top two to 3% of talent in different fields. Um, and, um, as we go forward, you know, we're really looking, seeing this as an opportunity to curate, um, exceptional talent. Um, and it feels like software engineering, data science, UX, UI design, cloud computing, um, and, uh, it really helped to, um, identify diverse talent as well from pockets that have typically been untapped for technology. Okay. >>I want to ask you kind of, what's the, how you read the tea leaves. How do I spot the talent, but first talk about the relationship with Amazon. What's the program together? How you guys working together? It's a great mission. I mean, we need more people anyway, coding everywhere, globally. What's the AWS connection. >>So Fred and I met and, uh, he had this, I mean the brilliant concept of the room. And so, uh, obviously you need to run that on the cloud. And so he's got organizations he's working at connecting them through the room and kind of that piece that he was needing was the technology. So we stepped in to help him with the technology piece because he's got all the subject matter expertise to train 3 million Africans, um, coming up on tech, we also were able to provide him some of the classwork as well for the cloud computing models. So some of those certs and things that we want to get out into the marketplace as well, we're also helping Fred with that as well. So >>I mean, want to, just to add onto that, you know, one of the things that's unique about the room is that we're trying to really build a long-term relationship with talent. So imagine joining the room as a 20 year old and being part of it until you're 60. So you're going to have a lot of that. You collect on someone as they progress through different stages of their career and the ability for us to leverage that data, um, and continuously learn about someone's, you know, skills and values and use, um, predictive algorithms to be able to match them to the right opportunities at the right time of their lives. And this is where the machine learning comes in and the, you know, the data lake that we're building to build to really store this massive data that we're going to be building on the top talent to the world. >>You know, that's a really good point. It's a list that's like big trend in tech where it's, it's still it's over the life's life of the horizon of the person. And it's also blends community, exactly nurturing, identifying, and assisting. But at the same day, not just giving people the answer, they got to grow on their own, but some people grow differently. So again, progressions are nonlinear sometimes and creativity can come out of nowhere. Got it. Uh, which brings me up to my number one question, because this always was on my mind is how do you spot talent? What's the secret sauce? >>Well, there is no real secret source because every person is unique. So what we look for are people who have an extra dose of five things, courage, passion, resilience, imagination, and good values, right? And this is what we're looking for. And you will someone who is unusually driven to achieve great things. Um, so of course, you know, you look at it from a combination of their, their training, you know, what they, what they've learned, but also what they've actually done in the workplace and feedback that you get from previous employers and data that we collect through our own interactions with this person. Um, and so we screened them through, you know, with the town that we had, didn't fly, we take them through really rigorous selection process. So, um, it takes, uh, for example, people go through an online assessments and then they go through an in-person interview and then we'll take them through a one to three month bootcamp to really identify, you know, people who are exceptional and of course get data from different sources about the person as well. >>Sandy, how do you see this collaboration helping, uh, your other clients? I mean, obviously talent, cross pollinates, um, learnings, what's your, you see this level of >>It has, uh, you know, AWS grows, obviously we're going to need more talent, especially in Africa because we're growing so rapidly there and there's going to be so much talent available in Africa here in just a few short years. Most of the tech talent will be in Africa. I think that that's really essential, but also as looking after my partners, I had Fred today on the keynote explaining to all my partners around the world, 55,000 streaming folks, how they can also leverage the room to fill some of their roles as well. Because if you think about it, you know, we heard from Presidio there's 3 million open cyber security roles. Um, you know, we're training 20 of mine million cloud folks because we have a gap. We see a gap around the world. And part of my responsibility with partners is making sure that they can get access to the right skills. And we're counting on the room and what Fred has produced to produce some of those great skills. You have AI, AML and dev ops. Tell us some of the areas you haven't. >>You know, we're looking at, uh, business intelligence, data science, um, full-stack software engineering, cybersecurity, um, you know, IOT talent. So fields that, um, the world needs a lot more talented. And I think today, a lot of technology, um, talent is moving from one place to another and what we need is new supply. And so what the room is doing is not only a community of top 10, but we're actually producing and training a lot more new talent. And that was going to hopefully, uh, remove a key bottleneck that a lot of companies are facing today as they try to undergo the digital trends. >>Well, maybe you can add some hosts on there. We need some cube hosts, come on, always looking for more talent on the set. You could be there. >>Yeah. The other interesting thing, John, Fred and I on stage today, he was talking about how easy to the first narrative written for easy to was written by a gentleman out of South Africa. So think about that right. ECE to talent. And he was talking about Ian Musk is based, you know, south African, right? So think about all the great talent that exists. There. There you go. There you go. So how do you get access to that talent? And that's why we're so excited to partner with Fred. Not only is he wicked impressive when a time's most influential people, but his mission, his life purpose has really been to develop this great talent. And for us, that gets us really excited because we, yeah, >>I think there's plenty of opportunities to around new business models in the U S for instance, um, my friends started upstart, which they were betting on people almost like a stock market. You know, almost like currency will fund you and you pay us back. And there's all kinds of gamification techniques that you can start to weave into the system. Exactly. As you get the flywheel going, exactly, you can look at it holistically and say, Hey, how do we get more people in and harvest the value of knowledge? >>That's exactly. I mean, one of the elements of the technology platform that we developed to the Amazon with AWS is the room intelligence platform. And in there is something called legacy points. So every time you, as a member of the room, give someone else an opportunity. You invest in their venture, you hire them, you mentor them, you get points and you can leverage those points for some really cool experiences, right? So you want to game-ify um, this community that is, uh, you know, essentially crowdsourcing opportunities. And you're not only getting things from the room, but you're also giving to others to enable everyone to grow. >>Yeah, what's the coolest thing you've seen. And this is a great initiative. First of all, it's a great model. I think it's, this is the future. Cause I'm a big believer that communities groups, as we get into this hybrid world is going to open up the virtualization. What the virtual world has shown us is virtualization, which is a cloud technology when Amazon started with Zen, which is virtualization technology, but virtualization, conceptually is replicating things. So if you think hybrid world, you can blend the connect people together. So now you have this social construct, this connective tissue between relationships, and it's always evolving, you know, this and you've been involved in community from, from, from the early days when you have that social evolution, it's not software as a mechanism. It's a human thing. Exactly. It's organism, it evolves. And so if you can get the software to think like that and the group to drive the behavior, it's not community software. >>Exactly. I mean, we say that the room is not an online community. It's really an offline community powered by technology. So our vision is to actually have physical rooms in different cities around the world, whether it's talent gathers, but imagine showing up at a, at a room space and we've got the technology to know what your interests are. We know that you're working on a new venture and there's this, there's a venture capitalists in that area, investing that venture, we can connect you right then that space powered by the, >>And then you can have watch parties. For instance, there's an event going on in us. You can do some watch parties and time shifted and then re replicated online and create a localization, but yet have that connection in >>Present. Exactly, exactly. Exactly. So what are the >>Learnings, what's your big learning share with the audience? What you've learned, because this is really kind of on the front edge of the new kind of innovation we're seeing, being enabled with software. >>I mean, one thing we're learning is that, uh, talent is truly, uh, evenly distribute around the world, but what is not as opportunity. And so, um, there's some truly exceptional talent that is hidden and on tap today. And if we can, you know, and, and today with the COVID pandemic companies or around the world, a lot more open to hiring more talent. So there's a huge opportunity to access new talent from, from sources that haven't been tapped before. Well, but also learnings the power of blending, the online and offline world. So, um, you know, the room is, as I mentioned, brings people together, normally in line, but also offline. And so when you're able to meet talent and actually see someone's personality and get a sense of the culture fit the 360 degree for your foot, some of that, you can't just get on a LinkedIn. Yes. That I built it to make a decision, to hire someone who is much better. And finally, we're also learning about the importance of long-term relationships. One of my motives in the room is relationships not transactions where, um, you actually get to meet someone in an environment where they're not pretending in an interview and you get to really see who they are and build relationships with them before you need to hide them. And these are some really unique ways that we think we can redefine how talent finds opportunity in the 21st. So >>You can put a cube in every room, we pick >>You up because, >>And the cube, what we do here is that when people collaborate, whether they're doing an interview together, riffing and sharing content is creating knowledge, but that shared experience creates a bonding. So when you have that kind of mindset and this room concept where it's not just resume, get a job, see you later, it's learning, having peers and colleagues and people around you, and then seeing them in a journey, multiple laps around the track of humans >>And going through a career, not just a job. >>Yes, exactly. And then, and then celebrating the ups and downs in learning. It's not always roses, as you know, it's always pain before you accelerate. >>Exactly. And you never quite arrive at your destination. You're always growing, and this is where technology can really play. >>Okay. So super exciting. Where's this go next, Sandy. And next couple of minutes left in. >>So, um, one of the things that we've envisioned, so this is not done yet, but, um, Fred and I imagined like, what if you could have an Alexa set up and you could say, Hey, you know, Alexa, what should be my next job? Or how should I go train? Or I'm really interested in being on a Ted talk. What could I do having an Alexa skill might be a really cool thing to do. And with the great funding that Fred Scott and you should talk about the $400 million to that, he's already raised $400 million. I mean, there, I think the sky's the limit on platforms. Like >>That's a nice chunk of change. There it is. We've got some fat financing as they say, >>But, well, it's a big mission. So to request significant resources, >>Who's backing you guys. What's the, who's the, where's the money coming from? >>It's coming from, um, the MasterCard foundation. They, our biggest funder, um, as well as, um, some philanthropists, um, and essentially these are people who truly see the potential, uh, to unlock, um, opportunity for millions of people global >>For Glen, a global scale. The vision has global >>Executive starting in Africa, but truly global. Our vision is eventually to have a community of about 10 to 20 million of the most extraordinary doers in the world, in this community, and to connect them to opportunity >>Angela and diverse John. I mean, this is the other thing that gets me excited because innovation comes from diversity of thought and given the community, we'll have so many diverse individuals in it that are going to get trained and mentored to create something that is amazing for their career as well. That really gets me excited too, as well as Amazon website, >>Smart people, and yet identifying the fresh voices and the fresh minds that come with it, all that that comes together, >>The social capital that they need to really accelerate their impact. >>Then you read the room and then you get wherever you need. Thanks so much. Congratulations on your great mission. Love the room. Um, you need to be the in Cuban, every room, you gotta get those fresh voices out there. See any graduates on a great project, super exciting. And SageMaker, AI's all part of, it's all kind of, it's a cool wave. It's fun. Can I join? Can I play? I tell you I need a room. >>I think he's top talent. >>Thanks so much for coming. I really appreciate your insight. Great stuff here, bringing you all the action and knowledge and insight here at re-invent with the cube two sets on the floor. It's a hybrid event. We're in person in Las Vegas for a real event. I'm John ferry with the cube, the leader in global tech coverage. Thanks for watching.

>>Hello, and welcome back to the cubes. Continuous coverage of AWS 2021. We're here live real people, and we're pleased to bring you this hybrid event. The most important hybrid event of the year to wrap up really 20, 21 and kick off next year, we're going to dig into the intersection of machine learning and business intelligence, business intelligence, Innomar, and Corian is here as the senior vice president of technology alliances at click and costy Wasilla caucus is the head of product growth for low code, no code machine learning at AWS gentlemen. Welcome to the >>Cube. Thanks for having us. >>I think the first time you were on at reinvent Sev definitely early last decade of >>My life. I >>Had black hair and it was maybe a 2013, I want to say. So it's been quite a run >>And it's definitely been a, been a privilege. I had a, had a chance to attend pretty much all all reinvents from the first one, eh, with a much fewer people and say this growth year over year. And what's amazing about it. This is beyond the scale, how much you grow, the number of people. It's just the face of innovation. Keeps, keeps accelerating as an it's, just this phenomenal. >>We're lucky that we chose data as sort of a, our business passion. But, um, so speaking of data, what are you hearing from customers about what they want to do with their data and bringing together business intelligence and machine learning it's being injected in, but what are they telling you that they, that they want, that they need? What's the opportunity that you're hearing now? >>So, uh, I think first of all, this is a fascinating, fascinating topic because we're talking kind of about the intersection of, uh, what everybody wants to look to do as the next frontier of, uh, of data with predictive data, because descriptive analytics have been around for a long time, but what coconut use predictive analytics, prescriptive analytics to enrich what we've had with descriptive analytics to be the end of the day, improve the business and what, what I love talking to people around here and just listening to customers, express the, you know, their needs is how can they get more value out of data? So they have the data, they don't use. A lot of the data are in Applegate and they want to use it in more ways. And that's what exciting to discuss those new ways. They want to bring it together >>Because anything you'd add to that from AWS perspective, >>I'll tell you what we don't hear from our customers and that we've stopped hearing what is AI and machine learning. And on the contrary we are hearing, how can we make the teams that already AI and ML a lot more productive and make a lot more of it, for example, how can they iterate a lot faster across the ML workflow, how they can train and build really large state of the art, natural language processing models like DDB DBT three, how can we help customers build, train and tune customer specific models for all their, to be able to bring in hyper personalization to their products? And the other thing we're hearing is how can we help the teams that are not tapping into AI and ML get the most power of it in a way, how could you actually potentially either democratize the building and development of machine learning models? Or how can you, in another way, expose machine learning into applications that analytics users are already using? >>Yeah. So in my, when we first met success was measured in, yeah, I got the Hadoop cluster, the work technically, but to your point, they customers want to get more value out of that data now. And so they want to operationalize machine intelligence. Is that what active intelligence is? >>Um, so active intelligence is something that you have here click started to talk about, but we believe it really represents what customers are trying to achieve. And the reason we use the word active intelligence is if you're going to think about active, not being passive. So, uh, traditional BI, uh, kind of relied on pre-configured historical data sets, which were great for what they did, but today they're kind of out of gas in terms of supporting real time decisioning and action. So what active intelligence is all about is really enabling customers to make it take informed, informed action, not just informed decision informed action in the moment. So when that action needs needs to happen. So in order to accommodate that again, this is really the difference between active and passive. Is it active intelligence is all about innovations to bring real-time data. So it's all just historical data. >>I need real time data that's relevant to what's happening. Now. I need a way to get an intelligent data pipeline. And I lead this data pipeline that makes it real-time data available in the forum and the structure that allows me to make a decision or to take action. And finally, it's really to be designed to drive action, right? So whether it's a manual action or whether it's even completely automated, but it's intelligent, it's informed. So that's, that's what active intelligence is all about that by the way, predictive data fits really well into that entire paradigm. Right. >>I mean, we've been talking for years about real-time and it's like, okay, what is real time? Well, it's real time is before you lose the customer before you lose the patient before the machine explodes. Right? So your point about predictive. Yeah. Now you guys made an announcement yesterday, uh, ADA, which stands for AI, for data analytics, what what's that all about? Well, >>Ate them tries to aims to address the very point I mentioned before our customers that are asking us, how can we give access to our business teams? There are a lot more business needs to machine learning. An AI for data analytics is a set of partner solutions that are ML powered. And they're focusing across the spectrum of analytics from data warehousing, business intelligence, business process automation, and other business application. And the idea is to help our partners bring to our customers a lot of those more ways. And for example, we've built integrations with clique Tableau, snowflake, Workato Pegasystems. And through those, those usually take two flavors. Either we help our partners build a mail and embedded into their applications and in a way, make them more intelligent as Mr. Wright mentioned, or we help our partners expose machine learning capability from AWS, right within the UI. >>So for example, yes, they will launch snowflake integration with SageMaker. Now snowflake user can use the same user experience in three-year the same use, the SQL query that they love and trigger an auto ML process insights maker, right from the same UI and get ML into the same UI. And I'm quite excited to also discuss today about the integration we announced today with click SageMaker integration or that was about it. No, no, no other, so I think, um, what a setups, yeah. You mentioned customers want to create more machine learning. They, they want to build faster, new, more machine learning capabilities, which is whereby the way the, the, uh, no code local, you know, comes into mind. How can you use the autopilot, which is a SageMaker product for enabling faster creation of models. So I want to create models faster. They also want to be able to use models in a sense, monetize them, turn them into value to make them available to more users where they're you there's users are. >>Eh, so, you know, BI environments or experiences like as we started to think about him. So I says, well, be provided with Gleevec. And again, with our active intelligence platform is all about weaving the data into the applications, into the environments, either the analytic workflows that, uh, that users have. So we introduced and are super excited. Uh, we've announced, uh, two integrations. So very robust integration between cloud and Amazon SageMaker. And that includes both our new analytic connector for, uh, uh, Amazon SageMaker and our integration with Amazon SageMaker autopilot. So with integration with SageMaker, we now have ClixSense interacting directly and seamlessly with any model deployed within SageMaker. So again, very much like cost dimension in your experience as a user seamlessly, you now also have predictive predictive data. So as you working in application, as you're interacting with your data, dynamically data is interchanged between click and SageMaker in reaching your decision, making your actions with predictive datasets. And that's, what's so cool about it. So again, the clinic environment, we bring real-time data in, prepare it for analytics, and then feed that real-time data to SageMaker to get the real-time prediction back in the same experience for the user. So we're really, really excited about that. So >>Translate what that means for customers is that everything happens faster. Is it unlocked new capabilities? Can we unpack >>A little bit? Absolutely. So aware in a way, bridging the chasm between the data science world and the business teams. So the data science teams are building machine learning models to make predictions. And now with the first integration that Myra mentioned, we actually expose those machine learning models in an application that the business team uses click and with the same dashboards that they are very familiar with can now trigger those machine learning models and get real time predictions in the dashboards themselves powered by machine learning. So in a way, this chasm between the two worlds of data science and business users is completely bruised. And the second integration we built with autopilot, she helps data engineers use completely their own machine learning technology powered by AWS pacemaker. So a data engineers creating different pipelines and through those pipelines, they can now with a building block, add auto ML capabilities in that pipeline without them really knowing machine learning. So we bridge the gap of the business teams, getting access to the data science teams and also bringing the skillset gap for the data engineers to tap into machine learning. You mentioned >>Monitor monetization before. So this to me is key because who's going to do with doing the monetization. It's the business lines that are going to do that, not the data scientists data they're going to enable that, but ultimately it's those data consumers that are building those, I call them data products that they can ultimately monetize. And that's, I'm interested in low-code no-code who sits in your title too, so that all plays in doesn't it? >>Yeah, you guys, and we're heavily invested into that whole space. So for example, today we just launched SageMaker canvas. That is a low-code no-code capability for analysts and business users, but we realized we don't need to only innovate on the technology side. We need to also innovate on the partnerships that we built and those integrations help expose those, our technology to wherever our customers want to be the one to be in clique. So be it, let them use the machine learning technology that we are innovating on exactly where they wanted to be. >>Can you give us some customer examples and use cases, maybe make it real for us, >>Uh, for sure. And I, and I think as you, as you think about these use cases, one of the other things I want to do to kind of envision is the fact that all this predictive data and all this integration that we're talking about is not, can actually express itself in a lot of different experiences for the user. It can be a dashboard. It can also be a conversation analytics, which is part of what we offer in the cloud. So you can actually, he can arrive and interact with the data. You don't have to actually look at it. It can be alerts that actually look automatically and inform you that you need to take action. So you don't actually look at the data. The data will come to you when it, when it needs you including base on, on predictive data. So there's a lot of, uh, a lot of options about how you're going to do it. >>Then give me, let me give you, let me give you an example. I'll let me try and maybe pick one that is intuitive. I think for, for many, for many people sales, right? So you have sales, you have a lot of orders. You want to try to close to closing a quarter, you have a forecast, the deals you expect to close. Uh, and then you can use machine learning for example, to forecast or to try to project which, which deals you're going to lose. So now again, that can look at a lot of different aspects of the deal, the timing, the folder, the volume, the amounts, a lot of other parameters, right. Then predict if you're going to lose a deal. So now, if there's a deal that I, that my sales person is telling me, he's going to win, but the mall is telling me you may lose, well, I probably want to double click on that one. >>Right? So I cannot bring that information right in again, in the moment it is to the seller or to the management, so they can identify it and take action. Now, not only can I bring it to them, but I can also, you know, from the machine learning, you know, what is the likely reason that they lose? And if I know the likely reason, it also become prescriptive, I now can know what to do to try and fix it, right. So I can either do it again manually, or it can also integrate it, uh, again, you know, click cloud. We also also click on application automation, which is again, also kind of a low-code no-code environment to orchestrate processes. I can also take that automatically, also update back Salesforce or the CRM. Okay. So that the metadata management system gets updated. So you got an example, exactly. The example of active intelligence. It allows me to take informed action in the now in the moment about making the best example. >>And if Salesforce salesperson, maybe I prioritize and the machines helping me direct my resources. Is this available today? Is it in general availability >>Available right now? Right? Anyone can go start it right now and click LA >>Congratulations. Um, last question. So what's the future hold for this partnership? Where are you guys headed? Give us a little >>Direction. First of all, would love to scale those integrations. So if you're a customer of Blake, please go ahead and test them and do sir, the feedback. And second for us, we really want to learn from our customers and improve those integrations. We bring to them, we really want to hear what technologies they want to expose to a lot more users. And we are aspiring to build that partnership and get a lot more tight aligned with, uh, with Glick. And, uh, thank you costly. And, uh, we, we see tremendous additional opportunities. I think Amazon tells it where I would say is, well, we're in day one. That that's how we kind of feel about it. There's only so much we put into it, but the market is so dynamic. There's so many new needs that are coming up. So we kind of think about it that way. >>So first of all, we want to journey to expand Lee cloud, adding more services. It's actually a platform where we're bringing both data services. They integration data management, everything related to the analytics pipeline, and of course the analytic services. So it all comes together in one environment that makes it more agile, faster to build these new modern, active intelligence type experiences. So as we do that, we're going to be adding more services, creating more opportunities to integrate with more services from the AWS side. So we're really excited to look at that and just like close to, you mentioned with canvas, you know, Amazon keeps coming up with new new services and new capabilities. So there's gonna be a lot of more opportunity. Eh, we're gonna keep, uh, again, within spirit of our partnership where we want to, you know, jump first innovate quickly and, uh, you know, create is integration, adds value to customer >>Often the flywheel that's. I love it. Great. Great to have you guys awesome to reconnect. All right. Appreciate it. Thank you for watching. This is the queue and we're covering AWS reinvent 2021. We're the leader in high tech coverage, right back

>>Oh, well, the back to the cubes coverage of ADA bus reinvent, 2021 executive seminar, I'm John ferry hosts of the cube. We've got a great segment here on the modernization. We were ringing in the success with Amazon web services, Vodafone digital in the UK, an example of modern engineering examples using Amazon, the cloud, looking at where we're cloud native is actually changing the game two great guests, Ben Collie, head, head of digital engineering, Vodafone UK, and Maynard Williams, managing director of center. Gentlemen, thank you for coming on the cube and sharing the story. >>Thanks, John. Appreciate it. So >>I gotta, I gotta ask you guys one of the main themes that we've been covering all year and even even pre pandemic, we, we saw the cloud native wave coming pretty hard containers. Great for modernization sets the table. You seeing things like Kubernetes and now serverless changing the game on all aspects of how modernization is happening. And everyone's talking about application modernization shift left all great for business, but you have to, you have to kind of take care of things under the, under the covers a little bit, the infrastructure, making sure the engineering teams are all set. So this has been a top topic. This is kind of what you guys are doing. Can you guys explain to me the needs that Vodafone has, um, that brought about this transformation? >>Yeah, sure. Um, so we we've been on this transformation for around four years, but you're absolutely right. The, uh, the pandemic has been a real catalyst for, for all kinds of organizations like ours around the world. Uh, so we were really driving a digital first agenda for quite a long time. Uh, and that, that came as, as you just said, John, it, it really did start with the, uh, the cloud hosted, uh, and then, uh, and then moving and realizing the difference between that and become native to the, to the cloud and really leveraging the services, uh, like AWS, um, in order to really drive pace, uh, and, and the outcomes that we needed for the business. Uh, we've seen a huge change over the last, uh, purely over the last 18 months, really. Um, our daily traffic, uh, these days is as it was on our highest ever, uh, uh, like an iPhone launch day, for example, um, before the pandemic, is I a daily traffic these days. And so that scalability and flexibility and that leveraging those services has been absolutely fundamental to supporting the, the changing needs and expectations of our customers. >>You know, back in the old days, uh, Maynard, you know, it's oh yeah, black Friday surge, you need the cloud to scale up and be flexible. Agile elastic, you know, scale is definitely now table stakes. And if you're not dealing with scale and some sort of either SRE fashion or whatever, you, you really ain't going to be behind the curve, but the next level that's being discussed is how do you leverage the scale for not just customer experience and business value, but we're talking about system architecture, kind of thinking there's kind of, this is our system design is now a big part of it. Can you talk about how this kind of threads together? Because we always talk about consumer experience, customer experience CX, but now there's a new system was mindset out there. Can you kind of share your vision on that >>Thing that stands out for me is if I look at digital, we've designed it to a point where the scale is just as you say, it's the table stakes, and only for launch with something that two years ago needed to be planned and thought about. And it's now absolutely routine. We think about the business side of it, but a big increase in scale really is seamless. But if I look at the full stack, we're still connected into some of the older backend systems, um, where any production, uh, they were on prime actually tasks. This is on AWS now, which is a big step forward, but when you've got to manage scaling in a way that translates from backend systems that are on premises on prime, and therefore we can't lastingly scale through to the front tab where we have to be able to scale up very seamlessly and balancing that across with, uh, an architecture that supports that level of scale and makes it so seamless on something like, as you say, iPhone launches or back Friday, any product coming out is actually key to the way we've architected that. >>So you're saying that essentially AWS combined with Vodafone worked on this solution that was more of a cloud native solutions that the innovation here, can you just summarize and unpack a little bit of what is the innovation, what problems did you solve together with essentially those and Vodafone? What was the core challenge? Yes. >>I think that the core is actually, how do you get to the point where, um, at the scaling is seamless, where you can move from being on the cloud to cloud native has been, just touched on what the same time you're actually connected into an enterprise state where the production systems are all on prem and don't have that ability to scale in the same fraction. So you can't, for example, push you to load into, uh, an on-prem backend system and, and simply expected to scale in the same fashion. So between our three organizations architecting something that is robust scales, we usable and takes away a load of pieces that actually were quite complex two years ago. And turns them into just routine has been a big step forward. >>And I want to get your reaction to this because, you know, you're, you're the you're on the, on the front line saying, Hey, be more agile at Basel saying, be agile, do different left, take that hill. Um, it's, it's easier said than done. Talk about what goes on when you have to implement and the stakes involved. Again, there's always the old way, new way. Can you just kind of give some color on what's going on? What's your perspective showing? >>And as I just said, that the real benefits and the story behind this was the ability to launch an iPhone. For example, as a event for Vodafone previously was weeks and months of preparation and design and testing and confidence building. And now it really is, it just happens. Uh, and we watched things scale and, and, and then down again, gracefully, um, and really do celebrate the, the another level up, if you like the leveling up of us as an organization, allowing our commercial colleagues to, to launch propositions or to launch campaigns without needing us to be involved anymore, because they're confident, we're all that things will, will flex like that. But you're absolutely right, that, that the changes and the demands of us as a, as a team, but also the, the expectations of our stakeholders, uh, have been changing for quite a long time now. Uh, and we're really excited now to be able to meet them by leveraging the services that we're discussing. >>Yeah. So the guys say said launched the iPhone, no big deal routine, hit the pub. Everyone's happy having a good day. >>Uh, >>Let's get into the solution, how it works. Talk about what's going on with the covers. How does this all work? Can you take us through, what's the state of the art of the, of the solution? Sure. >>Well, uh, as you mentioned earlier, we were very much inclined to serverless these days. So we rolled out fire gate, um, a few, uh, uh, started about 18 months ago. Um, and that really has, um, freed us up in, into all kinds of, um, uh, scalability, uh, measures, but also really about, about reusing and applying this across much more than just the, the engineering or the digital part of Vodafone, where we, where we began. So that's been a really big part of our agenda, uh, and that's, that's informed all kinds of things, the ability to scale and flex like that, and the architecture beneath us, um, and the containerization and orchestration that that goes along with that has really enabled us to, um, to flex that, uh, ability to, to reuse it across other areas. And because of that, now it's driven our hiring policy or tooling and, uh, technical, uh, our procedural approaches, uh, it all now leverages that ability to move a patient, to be able to scale, uh, not just in, um, uh, infrastructure or ability to serve customers, but in ability to deliver for the business commercially as well. Uh, and this is all now informed on our direction. I think, as an organization, >>It's interesting, you mentioned far you far gate than a trigger of events happens. People get excited, opens up new doors of opportunities as a chain reaction from that. Um, talk about the impact to the staff and the operations, because you almost, it's motivating at some level you get new things happening, but you're actually making things go better and faster, cheaper. >>Yeah. Uh, well, the, the impact is one, uh, because we're on a journey at Vodafone of this transformation, really becoming a technology business first and foremost, rather than a telco classically like our competitors, uh, we're able to really drive cultural change as well. So the impact on our people is a really, it's been particularly engaging. One with, we've also been part of, uh, a real recruitment drive. We've just announced 7,000 new, uh, roles, uh, joining our team across Europe and that these are engineering roles, um, driving more of the same, uh, behaviors and principles of a modern software engineering business like ours. Uh, and that really is fueled by our, our ability to experiment and try, but become cloud native and, and, uh, employ these services in the way that they're designed to be >>Maynard. I'd like to get your take on this and, and, and shift to a topic around how, what this all means. Um, if you zoom out and you say, okay, with the pandemic, it's become a mobile virtual hybrid. Now world around work play, all those lines are kind of blurring. It's not as clean as it used to be. Oh, the network segmented over here. This is over here. These legacy systems were built around the notion of things when nicely segmented. Um, now you have this whole kind of mashup, if you will, of how you just want to work, right. There's mobilization is a huge thing. So access identity, these are things that we're all kind of set up nicely before the pandemic, or at least, you know, not as, uh, stable, maybe not scalable, but what's your take on this? What's the big picture what's all happening. >>I think, I mean, the pandemic has accelerated a set of changes that were already happening anyway. And I'd say the other particles is under the covers. A lot of the work's been done has been to create the microservices that stitch together to produce those journeys, but, you know, running the containers. And so that, that opens up an omni-channel future that starts to move away from saying actually businesses are organized around the environment in which they're serving. Is it a retail store? Is it, is it online that additional and so on, and actually into much more of a space where you're building the best journeys and those journeys come and are served through digital or through a call center or through a store and so on. And that makes a huge difference because the focus on improving the customer's experience has been enormous. And I think that's one of the other parts that come out of the whole cloud native setup. >>And the ability to experiment has been iteratively and endlessly improving the experience for the customer. And that's, that's a, that's a massive step forward. So we can talk about the fact that we deploy a huge number of times more frequently than we did even a year ago, uh, or the, you know, our quality has improved by a massive percentage and so on. And I think the thing that's really interesting is the improvement in the experience and the endless improvement and iteration of that, because we can make lots and lots of small changes and do every day. That's a big one, >>You know, what's interesting Ben, and let's get your reaction on this. And if you don't mind to just add a little color to this, this is just another example of reports that we've been talking with folks on where it's not about just replatforming to the cloud. It's refactoring the business, uh, with, with the engineering, the modernization. And so there's two things that go on one, you see the efficiencies and new doors open up new things are happening. People are getting excited, good, some good Mo morale boosting things are becoming clear, but then there's actually new business, new business value being created or new propositions engineering propositions. Can you share from a digital standpoint, because this seems to be the new role of the digital person, whether it's engineering or on the business side, make things run faster, cheaper, and better, and then create new opportunities, new propositions, what's your >>Absolutely. Yeah. Yeah. It's fundamentally around pace of delivery. Uh, being able to, as, as may not says, uh, moving from a world, uh, two or three years ago where we were deploying once every two or three months, uh, this is a website once every two or three months where we were, uh, to now it's happening all the time every day. Uh, it's, it's, it's a skill that we've given us as an organization that we couldn't have leveraged before. And what we're able to do with that now is experiment our way and iterate our way to new value streams, as you say, but also trial and error. What we already know, uh, or expects to be true with our customers much, much more easily and much, much more frequently, very little a barrier to production or friction between us and the customer these days, and the almost instant response and feedback we get from customers. Um, we, we learn constantly about because of that. And it's, uh, it's become much less of a stab in the dark with large business cases where they work well, they worked and are much more experimental initiative. Uh, we, most of the propositions we know about, but also to the experiments, um, and unknowns in our future. Um, that also now unlocked, >>That's a great point. You mentioned about the whole timing of, you know, the old way, months, weeks, just for website stuff, uh, Maynard. And if you guys can share this new world order is actually pretty exciting, but also daunting if you're not like in the water, so to speak, right? So, you know, some people are actually, you know, putting their toe in the water, they're experimenting, but it's a game changer. I mean, a significant step up of value. What's your advice about solutions and they're not easy. I mean, you just got to get your hands around the sensor. You guys have been doing a lot more of these projects is seeing more and more of these, these kinds of partnerships, uh, and the value is there. Can you guys share your, your, uh, opinion and advice to folks out there watching saying, how do I do this and is it going to be worth it? Is that bridge to the future there? >>I mean, I think there's a mechanical piece. How do I enable this? And we can talk about dev ops and moving to cloud native, and actually some of the, some of the process side of as an organization, how do I get really comfortable with deploying very frequently and it being low risk and routine. And so the other part for me, which we sort of haven't touched on is as much as we talk about experimentation, it's about the data and the analytics and the knowledge that we create of that. So the, the, the small changes we're making are highly scientific. And when we think about actually understanding how we're optimizing experiences, that's all about the whole set of data points that I'm pinning up. And so I'll take two parts is know the, the journey we've been on here is, is about enablement. It's about moving the architecture. It's about moving the ways of working so that a lot of things that were hard or required thinking about two years ago on that quality team. But the other part of it is understanding the data and having the analytics capability and being able to make a very scientific experiment where you can see the result in the day-to-day >>Ben, what's your reaction advice to folks watching as they modernize exciting, challenging. It's a lot of hard work, but what's it look, it's the end game, >>All of those things, yes. I'd say it's, um, more than anything, it's a necessity these days we have to embark on this journey. It is, it is daunting. And, and of course, a lot of large organizations like ours, we were successful for doing things in a particular way, uh, have built up a lot of, uh, protection mechanisms for doing, for making sure we protect that. And so to come at it from a new angle is, is obviously daunting. And it's very challenging as well. There is an immune system in all of our organizations that is real, but I'll deal with it. Um, but the, the real, um, success behind, uh, the real, I think the reasons behind a lot of our success has been beat by being able to quickly prove value to quickly prove that outcomes are deliverable and achievable. Um, and then to build on those and iterate on it. And as, as I said, it's, it's about being able to move at pace for us in Vodafone. It's about leveraging our scale. We're a huge organization. Um, and we're, we're now coming together as one to really make sure that we do just lean on that scale more than we have them. Yeah, that's really about iterating, as I said, and, and, um, finding things that work, keep doing it, finding things that hold you back and get rid of them as quickly as you can, uh, is what I would say for us. >>It's interesting. You mentioned the scale. The thing about the cloud is when I hear the common pattern is it takes advantage of the strengths of your environment. You know, so every environment is a bit different, but you guys have the scale. I have to ask you while you're here. What are some of the anecdotal comments that kind of, you hear from folks that make you happy? When about the results? I think saying, Hey man, I'm not even seeing this anymore, or, wow. This is faster. What's some of the sound bites that you guys take as proof points of the success of this project. >>Yeah. It's, uh, I'd say it's mainly an R there's two things I would say, uh, the ability to rely less on it delivery if you like. So empowering our commercial business to make changes for themselves in a safe and secure manner. So providing these self-service capabilities, we've started to see a real pace about our commercial business, as well as our technology business. Uh, but also the, the time it takes to get things out is probably one of the biggest, uh, really tangible results and outcomes for us at the moment. Um, just the sheer amount of things we can release to production, uh, in, in sorts of short space, space of time really does bring to life, our ability to now trial and error, to AB test a Canary deploy. Things like that is really, um, it's been a real superpower for our, um, transformation, I think yes. >>Kind of kidding about can't make time to go to the pub, but in reality, it's free time freeing up people from doing those tasks that were slower shifting that value. >>Yeah. Whereas as you mentioned, Johnny, it really is much more than a technical journey. This is a cultural one as well for a lot of organizations and, um, by being more connected, by being more connected to the outcomes or the value that you add into production, uh, it really does drive a new culture and engagement across our teams. You know, if it's six months between writing a line of code and seeing it in production by up no sense of ownership or pride in what I've done there, but if I can deploy code immediately see an impact good or bad, um, then, uh, I really do feel connected to the outcomes and the value that I'm driving to, to the business and to our customers. So there really is a great cultural, >>Yeah. I remember Andy Jassy last year when he was a sea of AWS on stage and talked about that dynamic of the teamwork, people rowing in the right direction. Um, feeling part of it may know this is a cultural shift on how companies do business. I know center I've covered probably a dozen or so killer projects that have just been awesomely new and kind of different, but successful built on the cloud. So a lot of replatforming refactoring you're in the front lines, working with, uh, companies that essentially what's the pattern that you see that's that's happening right now. What's the, what's your view of the current market? >>Um, I mean, I think there's a huge shift to this, that this journey too has been part of the move from being on the cloud to being proud nature. I'm really getting that value because there's a, um, a kind of, almost a example. I see there's a light bulb moment where ownership of what you put in production means that you move away from a model of we change code because either the business tell us too, because they have a functional requirement or because something's broken. When we get into the model of that, I want to improve the thing that I feel ownership of. That's not leave. And you suddenly see how much difference that makes to the experience of it, the quality of it, the stability, all of those things improving. And so if, if I look more generally that cultural shift is it is an evolution that organizations go through and it starts with actually delivering it in a more agile way. At some large scale, you see agility moving up into kind of business agility and starting to affect things like budgeting cycles and the kind of corporate functions. If you like that tend to sit around, uh, you know, supporting Pete pieces of delivery. And there's a lot more of that happening at the moment, a load with more organizations pushing into being properly cloud native and transforming rather than the kind of first wave, which was the shift onto the cloud. Now it's actually, that's really leveraged what we've got with the, >>Yeah. And you guys essentially have been riding on the wave of AWS and the cloud for many, many years. We've been covering it. Ben great success story. Thanks for coming on the cube, a head of digital engineering, Vodafone UK, great example of modern engineering at work using AWS in Europe. Uh, thanks for coming on the Cuban, sharing your story. Maynor thank you for also coming on and the work you're doing at Accenture and AWS. Thank you. Thanks John. The cube coverage of AWS reinvent 2021 executive summit. I'm John furry, your host. Thanks for watching.

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Okay. Welcome back to the cubes coverage of 80 us. Re-invent 2020 virtual ecentric executive summit. The two great guests here to break down the analysis of the relationship with cloud and essential. Brian bowhead director ahead of Accenture. 80 was a business group at Amazon web services. And Andy T a B G the M is essentially Amazon business group lead managing director at Accenture. Uh, I'm sure you're super busy and dealing with all the action, Brian. Great to see you. Thanks for coming on. So thank you. You guys essentially has been in the spotlight this week and all through the conference around this whole digital transformation, essentially as business group is celebrating its 50th anniversary. What's new, obviously the emphasis of next gen post COVID generation, highly accelerated digital transformation, a lot happening. You got your five-year anniversary, what's new. >>Yeah, it, you know, so if you look back it's exciting. Um, you know, so it was five years ago. Uh, it was actually October where we, where we launched the Accenture AWS business group. And if we think back five years, I think we're still at the point where a lot of customers were making that transition from, you know, should I move to cloud to how do I move to cloud? Right? And so that was one of the reasons why we launched the business group. And since, since then, certainly we've seen that transition, right? Our conversations today are very much around how do I move to cloud, help me move, help me figure out the business case and then pull together all the different pieces so I can move more quickly, uh, you know, with less risk and really achieve my business outcomes. And I would say, you know, one of the things too, that's, that's really changed over the five years. >>And what we're seeing now is when we started, right, we were focused on migration data and IOT as the big three pillars that we launched with. And those are still incredibly important to us, but just the breadth of capability and frankly, the, the, the breadth of need that we're seeing from customers. And obviously as AWS has matured over the years and launched our new capabilities, we're Eva with Accenture. Um, and in the business group, we've broadened our capabilities and deepened our capabilities over the, over the last five years as well. For instance, this year with, with COVID, especially, it's really forced our customers to think differently about their own customers or their citizens, and how do they serve as those citizens. So we've seen a huge acceleration around customer engagement, right? And we powered that with Accenture customer engagement platform powered by ADA, Amazon connect. And so that's been a really big trend this year. And then, you know, that broadens our capability from just a technical discussion to one where we're now really reaching out and, and, um, and helping transform and modernize that customer and citizen experience as well, which has been exciting to say, Andy want to get your thoughts here. We've >>Been reporting and covering essential for years. It's not like it's new to you guys. I mean, five years is a great anniversary. You know, check is good relationship, but you guys have been doing the work you've been on the trend line. And then this hits and Andy said on his keynote, and I thought he said it beautifully. And he even said it to me, my one-on-one interview with them was it's on full display right now, the whole digital transformation, everything about it is on full display and you're either were prepared for it or you kind of word, and you can see who's there. You guys have been prepared. This is not new. So give us the update from your perspective, how you're taking advantage of this, of this massive shift, highly accelerated digital transformation. >>Well, I think, I think you can be prepared, but you've also got to be prepared to always sort of, I think what we're seeing in, in, um, in, in, in, in recent times and particularly in two 20, what, what is it I think today there are, um, 4% of the enterprise workloads sits at the cloud. Um, you know, that leaves 96% out there on prem. Um, and I think over the next four to five years, um, we're going to see that sort of, uh, acceleration to the, to the cloud pick up, um, this year as Andy touched on, I think, uh, uh, on Tuesday in his, I think the pandemic is a forcing function, uh, for companies to, to, to really pause and think about everything from, from, you know, how they, um, manage that technology, their infrastructure, to, to clarity to where that data sets to what insights and intelligence that getting from that data. >>And then eventually even to, to the talent, the talent they have in the organization and how they can be competitive, um, that culture, that culture of innovation, of invention and reinvention. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, it forces us, it forces AWS's forces, AEG to come together and think through how can we help create value for them? How can we help help them move from sort of just causing and rethinking to having real plans in action and that taking them, uh, into, into implementation. And so that's, that's what we're working on. Um, I think over the next five years, we're looking to just continue to come together and, and help these companies get to the cloud and get the value from the cloud. Cause it's, it's beyond just getting to the cloud attached to me and living in the cloud and getting the value from it. >>It's interesting. Andy was saying, don't just put your toe in the water. You've got to go beyond the toe in the water kind of approach. Um, I want to get to that large scale cause that's the big pickup this week that I kind of walked away with was it's large scale. Acceleration's not just toe in the water experimentation. Can you guys share, what's causing this large scale end to end enterprise transformation and what are some of the success criteria have you seen for the folks who have done that? Yeah. And I'll, I'll start in the end. >>You can buy a lawn. So you, it's interesting if I look >>Back a year ago at reinvent and when I did the cube interview, then we were talking about how ABG we're >>Starting to see that shift of customers. You know, we've been working with customers for years on a single of what I call a single-threaded programs, right? We can do a migration, we can do SAP, we can do a data program. And then even last year we were really starting to see customers ask. The question is like, what kind of synergies and what kind of economies of scale do I get when I start bringing these different threads together and also realizing that it's, you know, to innovate for the business and build new applications, new capabilities, well, that, that is going to inform what data you need to, to hydrate those applications, right? Which then informs your data strategy while a lot of that data is then also embedded in your underlying applications that sit on premises. So you should be thinking through how do you get those applications into the cloud? >>So you need to draw that line through all of those layers. And that was already starting last year. And so last year we launched the joint transformation program with AEG. And then, so we were ready when this year happened and then it was just an acceleration. So things have been happening faster than we anticipated, but we knew this was going to be happening. And luckily we've been in a really good position to help some of our customers really think through all those different layers of kind of the pyramid as we've been calling it along with the talent and change pieces, which are also so important as you make this transformation to cloud >>Andy, what's the success factors. Andy Jassy came on stage during the partner day, a surprise fireside chat with Doug Hume and talking about this is really an opportunity for partners to, to change the business landscape with enablement from Amazon. You guys are in a pole position to do that in the marketplace. What's the success factors that you see, >>Um, really from three, three fronts, I'd say, um, w you know, one is the, the people. Um, and, and I, I, again, I think Andy touched on sort of a, uh, success factors, uh, early in the week. And for me, it's these three areas that it sort of boils down to, to these three areas. Um, one is the, the, the, the people, uh, from the leaders that it's really important to set those big, bold visions point the way. And then, and then, you know, set top down goals. How are we going to measure you almost do get what you measure, um, to be, you know, beyond the leaders, to, to the right people in the right position across the company. We're finding a key success factor for these end to end transformations is not just the leaders, but you haven't poached across the company, working in a, in a collaborative, shared, shared success model, um, and people who are not afraid to, to invent and fail. >>And so that takes me to perhaps the second point, which is the culture. Um, it's important, uh, with finding food for the right conditions to be set in the company, not enable people to move at pace, move at speed, be able to fail fast, um, keep things very, very simple, and just keep iterating and that sort of culture of iteration, um, and improvement versus seeking perfection is, is super important for, for success. And then the third part of maybe touch on is, is partners. Um, I think, you know, as we move forward over the next five years, we're going to see an increasing number of players in the ecosystem in the enterprises state. Um, you're going to see more and more SAS providers. And so it's important for companies and our joint clients out there to pick partners like, um, like AWS or, or Accenture or others, but to pick partners who have all worked together and built solutions together. And that allows them to get speed to value quicker. It allows them to bring in pre-assembled solutions, um, and really just drive that transformation in a quicker, it sorts of manner. >>Yeah, that's a great point worth calling out, having that partnership model that's additive and has synergy in the cloud, because one of the things that came out of this this week, this year is reinvented, is there's new things going on in the public cloud, even though hybrid is an operating model, outpost and super relevant. There, there are benefits for being in the cloud and you've got partners, APIs, for instance, and have microservices working together. This is all new, but I got, I got to ask that on that thread, Andy, where did you see your customers going? Because I think, you know, as you work backwards from the customers, you guys do, what's their needs, how do you see them? You know, where's the puck going? Where can they skate to where the puck's going? Because you can almost look forward and say, okay, I've got to build modern apps. I got to do the digital transformation. Everything is a service. I get that, but what do they, what, what solutions are you building for them right now to get there? >>Yeah. And, and of course, with, with, you know, industries blurring and multiple companies, it's always hard to boil down to the exact situations, but you can probably look at it from a sort of a thematic lens. And what we're seeing is as the cloud transformation journey picks up from us perspective, we've seen a material shift in the solutions and problems that we're trying to address with clients that they are asking for us, uh, to, to help, uh, address is no longer just the back office where you're sort of looking at cost and efficiency and, um, uh, driving gains from that perspective. It's beyond that, it's now materially the top line. It's, how'd you get the driving to the, you know, speed to insights, how'd you get them decomposing, uh, their application set in order to derive those insights. Um, how'd you get them, um, to, to, um, uh, sort of adopt leading edge industry solutions that give them that jump start, uh, and that accelerant to winning the customers, winning the eyeballs. >>Um, and then, and then how'd you help drive the customer experience. We're seeing a lot of push from clients, um, or ask for help on how do I optimize my customer experience in order to retain my eyeballs. And then how do I make sure I've got a soft self-learning ecosystem at play, um, where I, you know, it's not just a practical experience, but I can sort of keep learning and iterating, um, how treat my, eat, my customers, um, and a lot of that, um, that's still self-learning that comes from, you know, putting in, uh, intelligence into your, into your systems, getting an AI and ML, uh, in that. And so as a result of that, where it was seeing a lot of push and a lot of what we're doing, uh, is pouring investments into those areas. And then finally, maybe beyond the bottom line and the top line is how do you harden that and protect that with, um, security and resilience? Uh, so I'll probably say those are the three areas. John >>Brian on the business model side, obviously the enablement is what Amazon has. Um, we see things like SAS factory coming on board and the partner network I've see a, is a big, huge partner of you guys. Um, the business models there. You've got I, as, as doing great with chips, you have this data modeling this data opportunity to enable these modern apps. We heard about the partner strategy from Andy. I'm talking about yesterday now about how can partners within even a center. What's the business model side on your side that you're enabling this. Can you just share your thoughts on that? >>Yeah. And so it's, it's interesting. And again, I'm kind of build it in a build a little bit on some of the things that Andy really talked about there, right? And that we, if you think of that from the partnership, we are absolutely helping our customers with kind of that it modernization piece and we're investing a lot and that there's hard work that needs to get done there. And we're investing a lot as a partnership around the tools, the assets and the methodology. So in AWS and Accenture show up together as AEG, we are executing off a single blueprint with a single set of assets so we can move fast. So we're going to continue to do that with all the hybrid announcements from this past week, those get baked into that, that migration modernization theme, but the other really important piece here as we go up the stack, Andy mentioned it, right? >>The data piece, like so much of what we're talking about here is around data and insights. Right? I did a cube interview last week with, uh, Carl hick. Um, who's the CIO from Takeda. And if you hear Christophe Weber from Takeda talk, he talks about Takeda being a data company, data and insights company. So how do we, as a partnership, again, build the capabilities and the platforms like with Accenture's applied insights platform so that we can bootstrap and really accelerate our client's journey. And then finally, on the innovation on the business front, and Andy was touching on some of these, we are investing in industry solutions and accelerators, right? Because we know that at the end of the day, a lot of these are very similar. We're talking about ingesting data, using machine learning to provide insights and then taking action. So for instance, the cognitive insurance platform that we're working together on with Accenture, if they get about property and casualty claims and think about how do we enable touchless claims using machine learning and computer vision that can assess based on an image damage, and then be able to triage that and process it accordingly, right? >>Using all the latest machine learning capabilities from AWS >>With that deep, um, AI machine learning data science capability from Accenture, who knows all those algorithms that need to get built and build that library by doing that, we can really help these insurance companies accelerate their transformation around how they think about claims and how they can speed those claims on behalf of their policy holder. So that's, what's an example of a, kind of like a bottom to top view of what we're doing in the partnership to address these new needs. >>That's awesome. Andy, I want to get back to your point about culture. You mentioned it twice now. Um, challenge is a big part of the game here. Andy Jassy referenced Lambda. Next generation developers were using Lambda. He talked about CIO stories around, they didn't move fast enough. They lost three years. A new person came in and made it go faster. This is a new, this is a time for a certain kind of, um, uh, professional and individual, um, to, to be part of, um, this next generation. What's the talent strategy you guys have to attract and attain the best and retain the best people. How do you do it? >>Um, you know, it's, it's, um, it's an interesting one. It's, it's, it's oftentimes a, it's, it's a significant point and often overlooked. Um, you know, people, people really matter and getting the right people, um, in not just in AWS or, but then on our customers is super important. We often find that much of our discussions with, with our clients is centered around that. And it's really a key ingredient. As you touched on, you need people who are willing to embrace change, but also people who are willing to create new, um, to invent new, to reinvent, um, and to keep it very simple. Um, w we're we're we're seeing increasingly that you need people who have a sort of deep learning and a deep, uh, or deep desire to keep learning and to be very curious as, as they go along. Most of all, though, I find that, um, having people who are not willing or not afraid to fail is critical, absolutely critical. Um, and I think that that's, that's, uh, a necessary ingredient that we're seeing, um, our clients needing more off, um, because if you can't start and, and, and you can't iterate, um, you know, for fear of failure, you're in trouble. And I think Andy touched on that you, you know, where that CIO, that you referred to last three years, um, and so you really do need people who are willing to start not afraid to start, um, and, uh, and not afraid to lead. Yeah. >>It takes a gut-check there. I just said, you guys have a great team over there. Everyone at the center I've interviewed strong, talented, and not afraid to lean in and, and into the trends. Um, I got to ask on that front cloud first was something that was a big strategic focus for Accenture. How does that fit into your business group? That's, uh, Amazon focus, obviously their cloud, and now hybrid everywhere, as I say, um, how does that all work it out? >>We're super excited about our cloud first initiative, and I think it fits it, um, really, uh, perfectly it's it's, it's what we needed. It's, it's, it's a, it's another accelerant. Um, if you think of first, what we're doing is we're, we're putting together, um, a capability set that will help enable him to and translations as Brian touched on your help companies move, you know, from just, you know, migrating to, to, to modernizing, to driving insights, to bringing in change, um, and, and, and helping on that, on that talent. So that's sort of component number one is how does Accenture bring the best, uh, end to end transformation capabilities to our clients? Number two is perhaps, you know, how do we, um, uh, bring together pre-assembled as Brian touched on preassembled industry offerings to help as an accelerant, uh, for our, for our customers three, as, as we touched on earlier, is, is that sort of partnership with the ecosystem. >>We're going to see an increasing number of SAS providers in an estate in the enterprises States out there. And so, you know, parts of our cloud first and our AEG strategy is to increase our touchpoints and our integrations and our solutions and our offerings where the ecosystem partners out there, the ISV partners out there, and the SAS providers out there. And then number four is really about, you know, how do we, um, extend the definition of the cloud? I think oftentimes people thought of the cloud just as sort of on-prem and prem. Um, but, but as Andy touched on earlier this week, you know, you've, you've got this, the concept of hybrid cloud and that in itself, um, uh, is, is, is, uh, you know, being redefined as well, you know, where you've got the intelligent edge and you've got various forms of the edge. Um, so that's the fourth part of, of our, of our cloud first strategy. And, and, and for us was super excited because all of that is highly relevant for ABG, as we look to build those capabilities as industry solutions and others, and as we look to enable our customers, but also how we, you know, as we, as we look to extend how we go to market, uh, I joined tally PS, uh, in, uh, in our respective skews and products. >>Well, what's clear now is that people now realize that if you contain that complexity, the upside is massive. And that's great opportunity for you guys. We got to get to the final question for you guys to weigh in on, as we wrap up next five years, Brian, Andy weigh in, how do you see that playing out? What do you see this exciting, um, for the partnership and the cloud first cloud, everywhere cloud opportunities share some perspective. >>Yeah, I, I, they, you know, just kinda building on that cloud first, right? What cloud first. And we were super excited when cloud first was announced and you know, what it signals to the market and what we're seeing in our customers, which is cloud really permeates everything that we're doing now. Um, and, and so all aspects of the business will get infused with cloud in some ways, you know, it, it touches on all pieces. And I think what we're going to see is just a continued acceleration and getting much more efficient about pulling together the disparate, what had been disparate pieces of these transformations, and then using automation using machine learning to go faster. Right? And so, as we start thinking about the stack, right, well, we're going to get, I know we are, as a partnership is we're already investing there and getting better and more efficient every day as the migration pieces and the moving assets, the cloud are just going to continue to get more automated, more efficient, and those will become the economic engines that allow us to fund the differentiated, innovative app activities up the stack. >>So I'm excited to see us, you know, kind of invest to make those, those, um, those bits accelerated for customers so that we can free up capital and resources to invest where it's going to drive the most outcome for their end customers. Um, and I think that's going to be a big focus and that's going to have the industry, um, you know, focus. It's going to be making sure that we can consume the latest and greatest of AWS has capabilities and, you know, in the areas of machine learning and analytics, but then Andy's also touched on it bringing in ecosystem partners, right? I mean, one of the most exciting wins we had this year, and this year of COVID is looking at the universe, uh, looking at Massachusetts, the COVID track and trace solution that we put in place is a partnership between Accenture, AWS, and Salesforce, right? So again, bringing together three really leading partners who can deliver value for our customers. I think we're going to see a lot more of that. As customers look to partnerships like this, to help them figure out how to bring together the best of the ecosystem to drive solutions. So I think we're going to see more of that as well. >>All right, Andy final word, your take >>Of innovation is, is picking up. Um, the split things are just going faster and faster. I'm just super excited and looking forward to the next five years as, as you know, the technology invention, um, comes out and continues to sort of set new standards from AWS. Um, and as we, as Accenture bringing our industry capabilities, we marry the two, we, we go and help our customers super exciting times. >>Well, congratulations on the partnership. I want to say thank you to you guys, because I've reported a few times some stories around real successes around this COVID pandemic that you guys worked together on with Amazon that really changed people's lives. Uh, so congratulations on that too as well. I want to call that out. Thanks for coming >>Up. Thank you. Thanks for coming on. >>Okay. This is the cubes coverage, Accenture AWS partnership, part of the center's executive summit at Avis reinvent 2020. I'm John for your host. Thanks for watching.

>>Well, thank you, everyone. And welcome to winning the roadmap race. How? Toe work with tech vendors to get the features that you need. We're here today with representatives or RBC Capital Markets. We will share some of their best practices for collaborating with technology vendors. I am Ada Mancini, solution architect here at Mirant us. And we're joined by Tina Bustamante, senior production manager, RBC Capital Markets and Minnows Agarwal, head of capital markets. Compute and data fabric. Um, RBC has been using docker since about 2016 and you've been closely involved with that effort. What moved you to begin, contain arising applications. >>Okay, uh, higher that. Thank you for having us. Um, back in 2016 when we started our journey one off our major focus, Syria was measuring develops capabilities And what we, uh what we found was it was challenging. Toe adopt develops across applications with different shapes and sizes, different text tax. And as the financial industry, we do have, um, a large presence of rental applications. So making it making that work was challenging. This is where containers were appealing. Tow us. In those early days, we started looking at containers as a possible solution to create a standardization across across different applications to have a consistent format. Other than that, we also saw containers as a potential technology that could be adopted across across enterprise, not just a small subset of applications. Uh, so that that was very interesting. Interesting. Tow us. In addition to that, uh, containers came with schedulers like kubernetes or swarm, which were, uh, which we're doing a lot more than all, which would do a lot more than the traditional traditional schedulers. As an example, resource management fell over management or scaling up and down, depending on a application or business requirements. So all those things were very appealing. It looked like a solutions to a number of problems that are number of challenges that we're facing. So that's when we got started with containers. >>So what subsequently motivated you to start utilizing swarm and then kubernetes? >>Yeah, other than resource management, the follower Management Aziz, you can imagine managing followers. D are Those are never difficult, Never easy on with containers. We saw that, as the container schedule is, we saw that it's a kind of becomes a manage manage service for us. Um, other aspect We are heavily regulated industry in capital markets, especially so creating an audit trail off events. Who did what? When? Uh, that's important. And containers seem to provide all those all those aspects tow us out of the box. Um, the another thing that we saw with containers under the schedulers, we could simplify our risk management. We could control what, what application on which container gets deployed, where, how they run on when they run. So all all those aspects of schedule er they simplify are seen to simplify at that time a lot off a lot off the traditional challenges, and that that's what was very appealing to us. >>Eso what kind of changes were required in the development culture and in operations in order to enable these new this new platform in this new delivery method? >>Yeah, that that's a good question, and any change obviously requires a lot of education. And this was not just a change across our developers or operations, but it was the change across throughout the change, starting with project managers, business analyst developers, Q A, uh, Cuba and our support personal. In addition, I talked about the risk and security Management so it it is. It is a change across the organization. It's, uh it's a cultural change. So the collaboration other than education collaboration was extremely, extremely important. So across those two, we started first with internal education, using something like internal lunch and learns. We did some external workshops or some hands on workshops. So a lot of those exercises were done in collaboration across all those all those things. The next item that we focused on is how do we get our high end developers the awareness of this technology on, uh, make sure they can. They can see, uh, the use cases. Or they can identify the use cases that can benefit from this technology. So we picked high end developers, noticed application and kind of try before you buy type of scenarios. So we ran through some applications to make sure they get their hands study. They feel comfortable with it on. Then they can broadcast that message. The broader organization, the next thing we did it waas getting the management buying. So obviously any change is going to require investment on uh, making sure there's a value proposition that's clear to our management as well as our business was critical very early on in in container option face. So that that that was that was another item that we focused heavily on. And the last thing I would say is a clearly defining strategy benefits so defining a roadmap off how we will proceed, How do we go from our low risk to high risk application or low risk medium risk applications? And what other strategy benefits are these purely operational? Are these purely cause best benefit? Or it's a modernization of the underlying technical facts. So if the containers do check all those three boxes So that that was that was our fourth item on the left that, uh, that, I would say, changed, um, in a container adoption journey. >>So as as people are getting onto the container ization process and as this is starting to gain traction, what things did your developers embrace as the real tangible benefits, um, of moving the containers of container platforms? >>It's interesting. The benefits are not just for developers. And the way I will answer this question is not from development operations. But let me answer it from the operations to developers. So operationally the moment developers saw that application can be deployed with containers relatively quickly without without having them on the collar without them writing a long release notes. They started seeing that benefit right away, but I don't need to be there late in the evening. I don't need to be there on call to create the environment or deploying, uh, deploying Q A versus production versus the are to them because, like do it right one on then repeat that success factor of different environments. So that was that. That was a big eye opening, um, eye opening for them. And they started realizing that Say, Look, I can free up my time now I can focus. I can focus on my core development, and I don't need to deal with the traditional traditional operational operational issues. So that's what that what? That was quite eye opening for all of us, not just for developers. And we started seeing those, uh, that are very early on. Another thing, I would say the developers talked about waas. Hey, I can validate this application on my laptop. I don't need to be I don't need to be on, uh, on on servers. I don't need all these servers. I don't need to share my service. I don't need to depend on infrastructure teams or other teams to get their check is done. Before I kept start my work, I can validate on my on my laptop. That was that was another very powerful feature. Um, that that empowered them. The last thing I would say is that the software defined aspect, uh, aspect off, um, off technology as an example, Network or storage. Although a lot of these traditional things that something Democrats have to call someone they have to wait on, then they have to deal with tickets. Now, they can do a lot of these things themselves. They can define it themselves, and that's very empowering. So they are perspective. Our move towards left, Um, s o the more control developers have, the better the product is. The better the quality of the product. The time to market improves on just the overall experience on the business benefits. They also start to They all start toe, um improved last part. One extra point. I would like to make here the success success of this waas so interesting, uh, to the development community even our developers from business. They they came along and they have shown interest in adopting containers. Whether it's, uh, the development developers from the quartz are the data science developers. They all started realizing the value value proposition of containers. So it was It was quite eye opening, I would have to say. >>And so while this while this process is happening while you're moving to container platforms, um, you started looking for new ways to try and deliver some of the benefits of containers and distributed systems orchestration more widely across the organization. And I think you identified a couple areas where, um, the doctor Enterprise kubernetes service wasn't meeting the features that you anticipated or it hadn't planned on integrating the features that you required. Um, can you tell us about that situation? >>Certainly. Haida. Thanks for having us again. Um, from the product management perspective, I would say products are always evolving and the capabilities can We have different stages of maturity. So when we reviewed what our application teams what are businesses looking to dio? One area that stood out was definitely the state of science space. Um, are quantum data science is really wanted to expand our risk analysis models. Um, they were looking for larger scales, uh, to compute like a lot more computing power. And we tried to see, um, come up with a way to be ableto facilitate their needs. Um, one thing, and it really, really came from like an early concept was the idea of being able to leverage GPU. Um, we stood up like a small R and D team, trying to see if there was something that would be feasible for our on our end. Um, but based on different factors and considerations and, you know, technical thinking involved in this we just realized that the complexity that it would bring to our you know, our overall technical back is not something, um that we would be, um, best suitable, I would say to do it on our own. So we reached out Thio Tim Aransas and brought forth, like, the concept of being able to scale the kubernetes pods on GPS. We relied on there authorities on their engineers Thio, you know, think about being able to expand, uh, kubernetes there kubernetes offering to be able to scale and potentially support running the pods and GPS um, definitely was not something that came from one day to the next that it did involve a number of conversations. Um, but, you know, I'm happy to say I was saying the recent months it has become part of the KUBERNETES product offering. >>Yeah, I believe that that effort, um, did take ah, while took a ah lot of engineering effort. Um, and I think initially all had done some internal r and D to try to work on those features, but ultimately, you decided to go with a different strategy and rely on the vendor to produce those assed part of the vendors product. Um, can you elaborate on the things that you found in that internal R and D? >>Well, we definitely saw the potential for there was definitely potential there. But, you know, the longevity of actually maintaining that GPU, uh, scaling using communities on our own was just not 100% like, in our expertise, expertise of something that we wanted to collaborate more closely with the vendor. Um, you know, technology is always evolving, So it's just the longevity of keeping up with, like, the the up to date features or capabilities testing que involved was just not something that we thought it would be. Something that we should be taking on on our own. >>Okay, So, like spending the time and engineering effort, focusing on the data science, the quantity of analysis parts I see. Um, and then ultimately, um, working with the vendor produced a release and where these features are now available. Um, how what did that engagement look like? Um, with RBC s involvement, >>I would say the engagement started off with, you know, discussing bringing it forth, being very open, you know, having transparency. So that delivery was always a little bit was the focus. Um, but it definitely, um, started office, you know, discussing what it would be like the business case. Why we would require the feature. Definitely the representative. Those and others engaged from them. A ransom side had their own, Um, you know, thoughts and opinions. Um, it had to be being able to run the work clothes, um, on GPU would be something that they would ultimately, as I mentioned, have to support on their end. Um, so we did work with them very closely. There was a very much a willingness collaborate we held a number of meetings. We discuss how the CPU support would would actually evolved. So it wasn't something that came about within like one sprint. No, that was never like our expectation. It did take a couple weeks to be able to see, like a beta product opine on it, see a demo, review it, discuss it further. Um, as you know, sometimes there might be a relief where this capability maybe offered, but there are delays. It's just, you know, part of off of our industry in a cent. Um, we're very much risk versus the nose mentioned, you know, >>when >>you are a financial institution. So we just wanted to make sure it was a viable product, that it was definitely available off the shelf, and then we would be able to leverage it. Um, but yeah, the key point, I would say, in terms of being able to bring the feature forward with definitely constant communication with Miranda, >>that's excellent. I'm glad that were ableto help bring that feature forward. I think that it's something that a lot of people have been asking for and like you said, it enables ah, whole new class of uh, problem solving. Okay. Uh, Meno je Tina, Thank you for your time today. It's been wonderful talking to you again. Uh, that is our session on working with your vendors. I want to thank everyone who's watching this for taking the time Thio contribute to our conference. Uh, awesome. Thank you, kitty.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi buddy welcome to this special noob digital event where we're focusing in on data ops data ops in Acton with generous support from friends at IBM let me set up the situation here there's a real problem going on in the industry and that's that people are not getting the most out of their data data is plentiful but insights perhaps aren't what's the reason for that well it's really a pretty complicated situation for a lot of organizations there's data silos there's challenges with skill sets and lack of skills there's tons of tools out there sort of a tools brief the data pipeline is not automated the business lines oftentimes don't feel as though they own the data so that creates some real concerns around data quality and a lot of finger-point quality the opportunity here is to really operationalize the data pipeline and infuse AI into that equation and really attack their cost-cutting and revenue generation opportunities that are there in front of you think about this virtually every application this decade is going to be infused with AI if it's not it's not going to be competitive and so we have organized a panel of great practitioners to really dig in to these issues first I want to introduce Victoria Stassi with who's an industry expert in a top at Northwestern you two'll very great to see you again thanks for coming on excellent nice to see you as well and Caitlin Alfre is the director of AI a vai accelerator and also part of the peak data officers organization at IBM who has actually eaten some of it his own practice what a creep let me say it that way Caitlin great to see you again and Steve Lewis good to see you again see vice president director of management associated a bank and Thompson thanks for coming on thanks Dave make speaker alright guys so you heard my authority with in terms of operationalizing getting the most insight hey data is wonderful insights aren't but getting insight in real time is critical in this decade each of you is a sense as to where you are on that journey or Victoria your taste because you're brand new to Northwestern Mutual but you have a lot of deep expertise in in health care and manufacturing financial services but where you see just the general industry climate and we'll talk about the journeys that you are on both personally and professionally so it's all fair sure I think right now right again just me going is you need to have speech insight right so as I experienced going through many organizations are all facing the same challenges today and a lot of those pounds is hard where do my to live is my data trust meaning has a bank curated has been Clinton's visit qualified has a big a lot of that is ready what we see often happen is businesses right they know their KPIs they know their business metrics but they can't find where that data Linda Barragan asked there's abundant data disparity all over the place but it is replicated because it's not well managed it's a lot of what governance in the platform of pools that governance to speak right offer fact it organizations pay is just that piece of it I can tell you where data is I can tell you what's trusted that when you can quickly access information and bring back answers to business questions that is one answer not many answers leaving the business to question what's the right path right which is the correct answer which which way do I go at the executive level that's the biggest challenge where we want the industry to go moving forward right is one breaking that down along that information to be published quickly and to an emailing data virtualization a lot of what you see today is most businesses right it takes time to build out large warehouses at an enterprise level we need to pivot quicker so a lot of what businesses are doing is we're leaning them towards taking advantage of data virtualization allowing them to connect to these data sources right to bring that information back quickly so they don't have to replicate that information across different systems or different applications right and then to be able to provide that those answers back quickly also allowing for seamless access to from the analysts that are running running full speed right try and find the answers as quickly as they find great okay and I want to get into that sort of how news Steve let me go to you one of the things that we talked about earlier was just infusing this this mindset of a data cult and thinking about data as a service so talk a little bit about how you got started what was the starting NICUs through that sure I think the biggest thing for us there is to change that mindset from data being just for reporting or things that have happened in the past to do some insights on us and some data that already existed well we've tried to shift the mentality there is to start to use data and use that into our actual applications so that we're providing those insight in real time through the applications as they're consumed helping with customer experience helping with our personalization and an optimization of our application the way we've started down that path or kind of the journey that we're still on was to get the foundation laid birch so part of that has been making sure we have access to all that data whether it's through virtualization like vic talked about or whether it's through having more of the the data selected in a data like that that where we have all of that foundational data available as opposed to waiting for people to ask for it that's been the biggest culture shift for us is having that availability of data to be ready to be able to provide those insights as opposed to having to make the businesses or the application or asked for that day Oh Kailyn when I first met into pulp andari the idea wobble he paid up there yeah I was asking him okay where does a what's the role of that at CBO and and he mentioned a number of things but two of the things that stood out is you got to understand how data affect the monetization of your company that doesn't mean you know selling the data what role does it play and help cut cost or ink revenue or productivity or no customer service etc the other thing he said was you've got a align with the lines of piss a little sounded good and this is several years ago and IBM took it upon itself Greek its own champagne I was gonna say you know dogfooding whatever but it's not easy just flip a switch and an infuse a I and automate the data pipeline you guys had to go you know some real of pain to get there and you did you were early on you took some arrows and now you're helping your customers better on thin debt but talk about some of the use cases that where you guys have applied this obviously the biggest organization you know one of the biggest in the world the real challenge is they're sure I'm happy today you know we've been on this journey for about four years now so we stood up our first book to get office 2016 and you're right it was all about getting what data strategy offered and executed internally and we want to be very transparent because as you've mentioned you know a lot of challenges possible think differently about the value and so as we wrote that data strategy at that time about coming to enterprise and then we quickly of pivoted to see the real opportunity and value of infusing AI across all of our needs were close to your question on a couple of specific use cases I'd say you know we invested that time getting that platform built and implemented and then we were able to take advantage of that one particular example that I've been really excited about I have a practitioner on my team who's a supply chain expert and a couple of years ago he started building out supply chain solution so that we can better mitigate our risk in the event of a natural disaster like the earthquake hurricane anywhere around the world and be cuz we invest at the time and getting the date of pipelines right getting that all of that were created and cleaned and the quality of it we were able to recently in recent weeks add the really critical Kovach 19 data and deliver that out to our employees internally for their preparation purposes make that available to our nonprofit partners and now we're starting to see our first customers take advantage too with the health and well-being of their employees mine so that's you know an example I think where and I'm seeing a lot of you know my clients I work with they invest in the data and AI readiness and then they're able to take advantage of all of that work work very quickly in an agile fashion just spin up those out well I think one of the keys there who Kaelin is that you know we can talk about that in a covet 19 contact but it's that's gonna carry through that that notion of of business resiliency is it's gonna live on you know in this post pivot world isn't it absolutely I think for all of us the importance of investing in the business continuity and resiliency type work so that we know what to do in the event of either natural disaster or something beyond you know it'll be grounded in that and I think it'll only become more important for us to be able to act quickly and so the investment in those platforms and approach that we're taking and you know I see many of us taking will really be grounded in that resiliency so Vic and Steve I want to dig into this a little bit because you know we use this concept of data op we're stealing from DevOps and there are similarities but there are also differences now let's talk about the data pipeline if you think about the data pipeline as a sort of quasi linear process where you're investing data and you might be using you know tools but whether it's Kafka or you know we have a favorite who will you have and then you're transforming that that data and then you got a you know discovery you got to do some some exploration you got to figure out your metadata catalog and then you're trying to analyze that data to get some insights and then you ultimately you want to operationalize it so you know and and you could come up with your own data pipeline but generally that sort of concept is is I think well accepted there's different roles and unlike DevOps where it might be the same developer who's actually implementing security policies picking it the operations in in data ops there might be different roles and fact very often are there's data science there's may be an IT role there's data engineering there's analysts etc so Vic I wonder if you could you could talk about the challenges in in managing and automating that data pipeline applying data ops and how practitioners can overcome them yeah I would say a perfect example would be a client that I was just recently working for where we actually took a team and we built up a team using agile methodologies that framework right we're rapidly ingesting data and then proving out data's fit for purpose right so often now we talk a lot about big data and that is really where a lot of industries are going they're trying to add an enrichment to their own data sources so what they're doing is they're purchasing these third-party data sets so in doing so right you make that initial purchase but what many companies are doing today is they have no real way to vet that so they'll purchase the information they aren't going to vet it upfront they're going to bring it into an environment there it's going to take them time to understand if the data is of quality or not and by the time they do typically the sales gone and done and they're not going to ask for anything back but we were able to do it the most recent claim was use an instructure data source right bring that and ingest that with modelers using this agile team right and within two weeks we were able to bring the data in from the third-party vendor what we considered rapid prototyping right be able to profile the data understand if the data is of quality or not and then quickly figure out that you know what the data's not so in doing that we were able to then contact the vendor back tell them you know it sorry the data set up to snuff we'd like our money back we're not gonna go forward with it that's enabling businesses to be smarter with what they're doing with 30 new purchases today as many businesses right now um as much as they want to rely on their own data right they actually want to rely on cross the data from third-party sources and that's really what data Ops is allowing us to do it's allowing us to think at a broader a higher level right what to bring the information what structures can we store them in that they don't necessarily have to be modeled because a modeler is great right but if we have to take time to model all the information before we even know we want to use it that's gonna slow the process now and that's slowing the business down the business is looking for us to speed up all of our processes a lot of what we heard in the past raised that IP tends to slow us down and that's where we're trying to change that perception in the industry is no we're actually here to speed you up we have all the tools and technologies to do so and they're only getting better I would say also on data scientists right that's another piece of the pie for us if we can bring the information in and we can quickly catalog it in a metadata and burn it bring in the information in the backend data data assets right and then supply that information back to scientists gone are the days where scientists are going and asking for connections to all these different data sources waiting days for access requests to be approved just to find out that once they figure out how it with them the relationship diagram right the design looks like in that back-end database how to get to it write the code to get to it and then figure out this is not the information I need that Sally next to me right fold me the wrong information that's where the catalog comes in that's where due to absent data governance having that catalog that metadata management platform available to you they can go into a catalog without having to request access to anything quickly and within five minutes they can see the structures what if the tables look like what did the fields look like are these are these the metrics I need to bring back answers to the business that's data apps it's allowing us to speed up all of that information you know taking stuff that took months now down two weeks down two days down two hours so Steve I wonder if you could pick up on that and just help us understand what data means you we talked about earlier in our previous conversation I mentioned it upfront is this notion of you know the demand for for data access is it was through the roof and and you've gone from that to sort of more of a self-service environment where it's not IT owning the data it's really the businesses owning the data but what what is what is all this data op stuff meaning in your world sure I think it's very similar it's it's how do we enable and get access to that clicker showing the right controls showing the right processes and and building that scalability and agility and into all of it so that we're we're doing this at scale it's much more rapidly available we can discover new data separately determine if it's right or or more importantly if it's wrong similar to what what Vic described it's it's how do we enable the business to make those right decisions on whether or not they're going down the right path whether they're not the catalog is a big part of that we've also introduced a lot of frameworks around scale so just the ability to rapidly ingest data and make that available has been a key for us we've also focused on a prototyping environment so that sandbox mentality of how do we rapidly stand those up for users and and still provide some controls but have provide that ability for people to do that that exploration what we're finding is that by providing the platform and and the foundational layers that were we're getting the use cases to sort of evolve and come out of that as opposed to having the use cases prior to then go build things from we're shifting the mentality within the organization to say we don't know what we need yet let's let's start to explore that's kind of that data scientist mentality and culture it more of a way of thinking as opposed to you know an actual project or implement well I think that that cultural aspect is important of course Caitlin you guys are an AI company or at least that you know part of what you do but you know you've you for four decades maybe centuries you've been organized around different things by factoring plant but sales channel or whatever it is but-but-but-but how has the chief data officer organization within IBM been able to transform itself and and really infuse a data culture across the entire company one of the approaches you know we've taken and we talk about sort of the blueprint to drive AI transformation so that we can achieve and deliver these really high value use cases we talked about the data the technology which we've just pressed on with organizational piece of it duration are so important the change management enabling and equipping our data stewards I'll give one a civic example that I've been really excited about when we were building our platform and starting to pull districting structured unstructured pull it in our ADA stewards are spending a lot of time manually tagging and creating business metadata about that data and we identified that that was a real pain point costing us a lot of money valuable resources so we started to automate the metadata and doing that in partnership with our deep learning practitioners and some of the models that they were able to build that capability we pushed out into our contacts our product last year and one of the really exciting things for me to see is our data stewards who be so value exporters and the skills that they bring have reported that you know it's really changed the way they're able to work it's really sped up their process it's enabled them to then move on to higher value to abilities and and business benefits so they're very happy from an organizational you know completion point of view so I think there's ways to identify those use cases particularly for taste you know we drove some significant productivity savings we also really empowered and hold our data stewards we really value to make their job you know easier more efficient and and help them move on to things that they are more you know excited about doing so I think that's that you know another example of approaching taken yes so the cultural piece the people piece is key we talked a little bit about the process I want to get into a little bit into the tech Steve I wonder if you could tell us you know what's it what's the tech we have this bevy of tools I mentioned a number of them upfront you've got different data stores you've got open source pooling you've got IBM tooling what are the critical components of the technology that people should be thinking about tapping in architecture from ingestion perspective we're trying to do a lot of and a Python framework and scaleable ingestion pipe frameworks on the catalog side I think what we've done is gone with IBM PAC which provides a platform for a lot of these tools to stay integrated together so things from the discovery of data sources the cataloging the documentation of those data sources and then all the way through the actual advanced analytics and Python models and our our models and the open source ID combined with the ability to do some data prep and refinery work having that all in an integrated platform was a key to us for us that the rollout and of more of these tools in bulk as opposed to having the point solutions so that's been a big focus area for us and then on the analytic side and the web versus IDE there's a lot of different components you can go into whether it's meal soft whether it's AWS and some of the native functionalities out there you mentioned before Kafka and Anissa streams and different streaming technologies those are all the ones that are kind of in our Ketil box that we're starting to look at so and one of the keys here is we're trying to make decisions in as close to real time as possible as opposed to the business having to wait you know weeks or months and then by the time they get insights it's late and really rearview mirror so Vic your focus you know in your career has been a lot on data data quality governance master data management data from a data quality standpoint as well what are some of the key tools that you're familiar with that you've used that really have enabled you operationalize that data pipeline you know I would say I'm definitely the IBM tools I have the most experience with that also informatica though as well those are to me the two top players IBM definitely has come to the table with a suite right like Steve said cloud pack for data is really a one-stop shop so that's allowing that quick seamless access for business user versus them having to go into some of the previous versions that IBM had rolled out where you're going into different user interfaces right to find your information and that can become clunky it can add the process it can also create almost like a bad taste and if in most people's mouths because they don't want to navigate from system to system to system just to get their information so cloud pack to me definitely brings everything to the table in one in a one-stop shop type of environment in for me also though is working on the same thing and I would tell you that they haven't come up with a solution that really comes close to what IBM is done with cloud pack for data I'd be interested to see if they can bring that on the horizon but really IBM suite of tools allows for profiling follow the analytics write metadata management access to db2 warehouse on cloud those are the tools that I've worked in my past to implement as well as cloud object store to bring all that together to provide that one stop that at Northwestern right we're working right now with belieber I think calibra is a great set it pool are great garments catalog right but that's really what it's truly made for is it's a governance catalog you have to bring some other pieces to the table in order for it to serve up all the cloud pack does today which is the advanced profiling the data virtualization that cloud pack enables today the machine learning at the level where you can actually work with our and Python code and you put our notebooks inside of pack that's some of this the pieces right that are missing in some of the under vent other vendor schools today so one of the things that you're hearing here is the theme of openness others addition we've talked about a lot of tools and not IBM tools all IBM tools there there are many but but people want to use what they want to use so Kaitlin from an IBM perspective what's your commitment the openness number one but also to you know we talked a lot about cloud packs but to simplify the experience for your client well and I thank Stephen Victoria for you know speaking to their experience I really appreciate feedback and part of our approach has been to really take one the challenges that we've had I mentioned some of the capabilities that we brought forward in our cloud platform data product one being you know automating metadata generation and that was something we had to solve for our own data challenges in need so we will continue to source you know our use cases from and grounded from a practitioner perspective of what we're trying to do and solve and build and the approach we've really been taking is co-creation line and that we roll these capability about the product and work with our customers like Stephen light victorious you really solicit feedback to product route our dev teams push that out and just be very open and transparent I mean we want to deliver a seamless experience we want to do it in partnership and continue to solicit feedback and improve and roll out so no I think that will that has been our approach will continue to be and really appreciate the partnerships that we've been able to foster so we don't have a ton of time but I want to go to practitioners on the panel and ask you about key key performance indicators when I think about DevOps one of the things that we're measuring is the elapsed time the deploy applications start finished where we're measuring the amount of rework that has to be done the the quality of the deliverable what are the KPIs Victoria that are indicators of success in operationalizing date the data pipeline well I would definitely say your ability to deliver quickly right so how fast can you deliver is that is that quicker than what you've been able to do in the past right what is the user experience like right so have you been able to measure what what the amount of time was right that users are spending to bring information to the table in the past versus have you been able to reduce that time to delivery right of information business answers to business questions those are the key performance indicators to me that tell you that the suite that we've put in place today right it's providing information quickly I can get my business answers quickly but quicker than I could before and the information is accurate so being able to measure is it quality that I've been giving that I've given back or is this not is it the wrong information and yet I've got to go back to the table and find where I need to gather that from from somewhere else that to me tells us okay you know what the tools we've put in place today my teams are working quicker they're answering the questions they need to accurately that is when we know we're on the right path Steve anything you add to that I think she covered a lot of the people components the around the data quality scoring right for all the different data attributes coming up with a metric around how to measure that and and then showing that trend over time to show that it's getting better the other one that we're doing is just around overall date availability how how much data are we providing to our users and and showing that trend so when I first started you know we had somewhere in the neighborhood of 500 files that had been brought into the warehouse and and had been published and available in the neighborhood of a couple thousand fields we've grown that into weave we have thousands of cables now available so it's it's been you know hundreds of percent in scale as far as just the availability of that data how much is out there how much is is ready and available for for people to just dig in and put into their their analytics and their models and get those back into the other application so that's another key metric that we're starting to track as well so last question so I said at the top that every application is gonna need to be infused with AI this decade otherwise that application not going to be as competitive as it could be and so for those that are maybe stuck in their journey don't really know where to get started I'll start with with Caitlin and go to Victoria and then and then even bring us home what advice would you give the people that need to get going on this my advice is I think you pull the folks that are either producing or accessing your data and figure out what the rate is between I mentioned some of the data management challenges we were seeing this these processes were taking weeks and prone to error highly manual so part was ripe for AI project so identifying those use cases I think that are really causing you know the most free work and and manual effort you can move really quickly and as you build this platform out you're able to spin those up on an accelerated fashion I think identifying that and figuring out the business impact are able to drive very early on you can get going and start really seeing the value great yeah I would actually say kids I hit it on the head but I would probably add to that right is the first and foremost in my opinion right the importance around this is data governance you need to implement a data governance at an enterprise level many organizations will do it but they'll have silos of governance you really need an interface I did a government's platform that consists of a true framework of an operational model model charters right you have data domain owners data domain stewards data custodians all that needs to be defined and while that may take some work in in the beginning right the payoff down the line is that much more it's it it's allowing your business to truly own the data once they own the data and they take part in classifying the data assets for technologists and for analysts right you can start to eliminate some of the technical debt that most organizations have acquired today they can start to look at what are some of the systems that we can turn off what are some of the systems that we see valium truly build out a capability matrix we can start mapping systems right to capabilities and start to say where do we have wares or redundancy right what can we get rid of that's the first piece of it and then the second piece of it is really leveraging the tools that are out there today the IBM tools some of the other tools out there as well that enable some of the newer next-generation capabilities like unit nai right for example allowing automation for automation which right for all of us means that a lot of the analysts that are in place today they can access the information quicker they can deliver the information accurately like we've been talking about because it's been classified that pre works being done it's never too late to start but once you start that it just really acts as a domino effect to everything else where you start to see everything else fall into place all right thank you and Steve bring us on but advice for your your peers that want to get started sure I think the key for me too is like like those guys have talked about I think all everything they said is valid and accurate thing I would add is is from a starting perspective if you haven't started start right don't don't try to overthink that over plan it it started just do something and and and start the show that progress and value the use cases will come even if you think you're not there yet it's amazing once you have the national components there how some of these things start to come out of the woodwork so so it started it going may have it have that iterative approach to this and an open mindset it's encourage exploration and enablement look your organization in the eye to say why are their silos why do these things like this what are our problem what are the things getting in our way and and focus and tackle those those areas as opposed to trying to put up more rails and more boundaries and kind of encourage that silo mentality really really look at how do you how do you focus on that enablement and then the last comment would just be on scale everything should be focused on scale what you think is a one-time process today you're gonna do it again we've all been there you're gonna do it a thousand times again so prepare for that prepare forever that you're gonna do everything a thousand times and and start to instill that culture within your organization a great advice guys data bringing machine intelligence an AI to really drive insights and scaling with a cloud operating model no matter where that data live it's really great to have have three such knowledgeable practitioners Caitlyn Toria and Steve thanks so much for coming on the cube and helping support this panel all right and thank you for watching everybody now remember this panel was part of the raw material that went into a crowd chat that we hosted on May 27th Crouch at net slash data ops so go check that out this is Dave Volante for the cube thanks for watching [Music]

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Okay. Welcome back everyone. Cube coverage, Las Vegas live action ADA was reinvent 2019 third day of a massive show where our seventh year of the eight years of Ava when documenting the history and the rise and the changing landscape of the business. I'm Jon Favreau, Stu Miniman, my cohost, our next guest, bill McGee, senior vice president, general manager of the hybrid cloud security group within trend micro sold this company, those guys now lead executive of the cloud and hybrid hybrid cloud security. You've got hybrid in there looking through the queue and I've been to every re-invent every single one. Congratulations. Welcome to the cube. Nice to be here. So eight years. What's changed in your mind real quick? >>Ah, wow. The um, yeah, certainly the amount of adop uh, the amount of adoption is now massive mainstream. You don't have the question, should I go to the cloud? It's all about how and how much. Probably the biggest change we've seen is how it's really being embraced all around the world. We're a global company. We saw initially a U S on Australia type focused UK. Now it's all over the place and so really relevant everywhere. Oh Phil. I, you know, at least from my standpoint, and I have enough friends of mine in the security industry when we first started coming to the show, I mean security was here, security is not only is so front and center in the discussion of cloud that they had a whole show for it here. So, you know, give us the 2019 view of security inside that the, the broader hybrid cloud discussion here at Reinventure. >>Let me tell you a couple of things. Kind of what we're seeing within our customer base and then what matters from a security perspective. So we see some organizations doing cloud migration, moving workloads to the cloud. A various farms had a couple of meetings yesterday. One was call it evacuating their data center. The other one was celebrating that two weeks ago they closed their data center. So that's a big step. Windows and Linux workloads moving to the cloud and really changing existing security controls to work better in the cloud. But certainly what a lot of these cloud builders are here for is, uh, you know, developing cloud native applications. And originally, you know, back seven, eight years ago, that was on top of what's now seemed like pretty simple services like S three. Now you've got containers and serverless and other platforms that people are using. >>And then the last thing, a lot of companies are establishing a cloud center of excellence and they're trying to optimize their use of the cloud. They still have compliance requirements that they need to achieve. So these are what we see happening and really the challenge for the customer, okay, how do we secure all this? How do we secure the aggressive, aggressive cloud native application development? How do we help a customer achieve compliance easily from a cloud center of excellence? So that's where we see fitting. And we made a big announcement a couple of weeks ago about a new platform that we've created and you know, I'd love to talk to. >>Yeah, let's dig into that. Let's dig into that. But first when we were at was Amazon's first security conference, Dave latte and I were talking about wow, cloud security versus on prem security. And then what's happening here is I had a conversation with someone who was close to the CIA, can't say his or her name and that, and they said cloud has changed the game for them because their cost line was pretty much flat, but the demand for missions, which we're growing scaling. So we're seeing that same dynamic you were referring to it earlier, that cost in data centers is kind of flat, but the demand for application new stuff's happened. So there's a real increased her demand for apps. This is the real driver of how people are flexing and deploying technology. So the security becomes really the built in conversation. Correct. Comment on that dynamic. And what do you recommend while, so here's a couple of things >>as we've seen really. Uh, you know, again, we've been doing cloud security for about a decade and really it was primarily focused on one service of AWS, which is. Now that's a pretty darn big service. And, uh, you know, widely used within their customer base. There's now 170 services I think is the, you know, the most recent number. Um, so developers are embracing all these new services. We acquired a new capability in October company called cloud conformity based in Sydney, Australia. Very focused on AWS analyzes implementations against the AWS well architected framework. So the first step we see for customers is you got to get visibility into your use of the cloud for the security team. What services are being used? Then can you set up a set of security guard rails to allow those services to be used in a secure manner? Then we help our customers turn to more detailed specialized protection of or containers or serverless. So that's what we've recognized ourselves. We had to create a very modest version of what Amazon has created themselves, which is a platform that allows builders to connect to and choose what security services they want >>to help. Lota how broad is your service base? Is it all the services? Are you guys now pick and choose? I can't. It's hard to do all, but yeah, there's the main ones. What are the highlights? >>Yeah, I'll give you the ones where we provide, uh, a very large breadth of protection. So in the, what we're calling cloud one conformity service, so that's this, uh, technology we acquired a couple months ago. Um, it cuts across about 70 services right now and gives you visibility of potential security configuration errors that you have in your environment. Now, if it's in a dev team, maybe not such a big deal, but if it's in production, it is a big deal. Even better, you can scan your cloud formation templates on the way to, to, to being live. Then we have a set of specialized protection that will, you know, will run on a workload and protect it, protect a containerized environment, a library that can sit within a serverless application. So that's kinda how we look at it. >>They'll want, one of the things of going to the more and more cloud for customers is that there's that shared responsibility model. We know that security is everyone's responsibility. It needs to be built in from the ground up. How are your customers doing with that shift and how are they understanding what they need to do? There've been some pretty visible like, Oh wait, I really had to configure that. I'm not about that. And Amazon's trying to close the gap on some, bring us through some of those. >>We've seen a big positive change over the years. Initially I would say that there was what I would call a naive perception that the cloud was magic and it was perfectly secure and that I don't have to worry about it. Right. Amazon did a, did the industry a real favor by establishing the shared responsibility model and making crystal clear what they've got covered that you don't need to worry about anymore as a customer and then what are the capabilities you still need to worry about? They've delivered a set of security tools that help their customers and then they rely on partners like us to deliver a set of more in depth tools to a, you know, specialized markets. >>You actually used a word that we've been talking about a lot this week. Naive. So we said there's, you know, the one letter difference between being cloud native, I mean cloud naive there. What does it mean to be cloud native in the security world? >>Well, I would say what allows you to be so first the most important thing in every customer's mind. I don't care how good the security capabilities you're helping me with. If you're going to slow down the improvements that I've just made to my development life cycle, I'm not interested. So that is the most important thing is are you able to inject your security technology and allow the customer to deliver at the rate that they're currently or continuing to improve? That is by far the most important thing. Then it's are your controls fitting into an environment in a way that that are as easy as possible for the customer? One part that's been very critical for us. We've been a lead adopter of the AWS marketplace allowing customers to procure security technology easily. They don't actually have to talk to us to buy our product. That's pretty revolutionary. >>Talking about the number of breaches that have gone on and what's changed with you guys over the year because new vectors are coming out, there's more surface area. Obviously it's been been discussed what's changed most in years? I'll tell you what we're worried about and what we expect to see. Although I would say the evidence, it's early. Uh, the reality in our traditional data centers, they were so porous at runtime in terms of the infrastructure and vulnerabilities that it was relatively easy for attackers to get in. The cloud has actually improved the level of security because of automation, less configuration errors. Unfortunately, what we expect as attackers to move to the developers move to the dev pipeline, injecting code, not at runtime, but injecting it earlier in the life cycle. We've seen evidence of container images, uh, up on Docker hub getting infected and then developers just pulling in without thinking about it. >>That's where attackers are going to move to the dev pipeline and we need to move some of our security technology to the dev pipeline to help customers defend themselves. What about international geo geo issues around compliance? How is that changing the game or slowing it down or I'd say doubling it or can you talk about that dynamic? Because I'm sure with regions, I'm sure you know, the U S is the most innovative market and the most risk taking market and therefore people move to the cloud quite bravely. Uh, you know, over this over this decade. Um, and some of the markets, so for example, we're Japanese headquartered company, um, in general Japanese companies, you know, really, uh, take into a lot of considerations before they make that type of big bet. But now we're seeing it, we're seeing auto manufacturers, uh, embrace the cloud. So I think those, it was a struggle for us in the early days, how regional the adoption of cloud was. >>That's not the case anymore. It's really a relevant conversation in every one of our markets. Bill, thank you for coming on the Cuban sharing your insights on hybrid cloud security. I got to ask you to end the segment. Yeah. What is going on for you this year? I see hybrids in your title. That's obviously the, the operating model is clouds and are gravity clouds going to the edge or data center and just operating model. What's on your mind this year? What are you trying to do and accomplish? What's, what are you excited about? What we're really excited about was this a product announcement that we made called cloud one and what cloud one is, is a set of security services which customers can access through, you know, common, uh, common access, common billing infrastructure, common cloud account management, and choose what to use. You know, Andy put it pretty well in his keynote where, you know, he talked about, he doesn't think of AWS as, as a Swiss army knife. >>He thinks of it as a specialized set of tools that builders get to adopt. We want to create a set of security tools in a similar way where customers can choose which of these specialized security services that they want to adopt. Bill, great pleasure to meet you and have this conversation pro and then security area entrepreneur sold this company to trend micro. This is the hybrid world is all about the cloud operating model. So all about agility and getting things done with application developers, just cube bringing you all the data from re-invent. Stay with us for more coverage after this short break.

la from Las Vegas it's the cube covering AWS reinvent 2019 brought to you by Amazon Web Services and Vinum care along with its ecosystem partners Oh welcome back to the sands here we are live here in Las Vegas along with Justin Warren I'm John wall's you're watching the Cuban our coverage here of AWS rain vut 2019 day one off in Rowan and EJ on the keynote stage this morning for a couple of hours and now a jam-packed show for Chris Wright joins us the CTO and Red Hat waking his way toward Cube Hall of Fame status we're getting there this is probably worth 50 of the parents I think good to see you good to see you yeah always a pleasure first off let's just let's just talk about kind of the broad landscape right now the pace of innovation that's going on what's happening in the open cloud you know catching up to that acceleration if you're if you're a legacy enterprise you know you got all these guys that are born over here and they're moving at warp speed you got to be you've got to play catch-up and and talk about maybe that friction if you will and and what people are learning about that in terms of trying to get caught up to the folks that have two head start well I think number one the way I like to frame it is open source is the source of innovation for the industry and part of that is you look at the collaborative model bringing different people together across industry to build technology together it's hard to compete with that pace and speed the challenge of course is as you describe how do you how do you consume that how do you bring it into the enterprise which is you know got a whole business that's running off of infrastructure that has been sustaining their business for potentially decades so there's that impedance mismatch of needing to go quickly to keep abreast of of the technology changes while honoring the fact that your core business is running already on key technology so I think looking at how you bring platforms in that support the newer technologies as well as create connections or even support existing applications is a great way to kind of bridge that gap and then partnering with people who can build a bridge like an impedance match between your speed and the speed of innovation is a great way to kind of you know harness the power without exposing yourself to the ragged edges as much sure yeah talk to us a bit more about it about enterprise experience with open source a Red Hat has a long heritage of providing open source to enterprise and couldn't pretty much sits out as a unique example of how you make money with open source so enterprises have lots of open source that they're using every day now you know Linux has come into the enterprise left right and center but there's a lot more open source technologies that enterprises are using today so give us a bit of a flavor of how enterprises are coming to grips with how open source helps sustain their business well in one sense it's that innovation engine so it's bringing new technology and in another sense it's what we've experienced in the in the Linux space is post driving a kind of commoditization of infrastructure so switching away from the traditional vertically integrated stack of a RISC UNIX environment to providing choice so you have a common platform that you can target all your applications do that creates independence from the underlying hardware that's that's something that provide a real value to the enterprise that notion continues to play out today as infrastructure changes it's not just hardware it's virtualized data centers it's public clouds how do you create that consistency for developers to target their applications too as well as the operation seems to manage well you know it's through leveraging open source and bringing a common platform in into your environment as you go up the stack I think you get more and more proliferation of ideas and choices from developer tools and modules and dependencies you know most software stacks today have some open source even included inside whether you're building exclusively on top of a platform that's open source based you're probably also including open source into your application so it's a whole variety from building your key infrastructure to supporting your your enterprise applications and you mentioned openness which y'all know is a big very important thing to Red Hat and one thing that red has been speaking of lately is open hybrid cloud so maybe you can explain that to us what what he is open hybrid cloud what does red head mean by that sure so open hybrid cloud for us start with open that's our platforms are built from open source project so we work across like literally thousands of open source projects bring those together into products that build our platform also we create an open ecosystem so you know we're really fostering partnerships and collaboration at every level from the developer level up through our commercial partnerships the hybrid piece is talking about where you deploy this infrastructure inside your data center on bare metal servers inside your data center virtualized in a private cloud across multiple public clouds and increasingly out to the edge so that that notion of what is the data center - to me it really encompasses all those different footprints so the hybrid cloud cloud meaning give a cloud like experience from an Operations point of view simple to operate meaning you know we're doing everything we can to help operators manage that infrastructure from a developer point of view surface scene functionality as services Nate the eyes and you know how do you give a self-service environment to developers like you know like a cloud so it's across all that first you talk about data in the edge which you know the fact that there's so much the computing that's going on out there and staying closer to the source right we're not bringing it back in you're leaving it out there that adds a whole new level of complexity - I would think and scale you know massive amounts what everything is happening out there so what are you seeing in that in that in terms of handling that complexity and addressing challenges that you see coming as this growth is tremendous growth continues well one it's how do you manage all of that infrastructure so I think having some consistency is a great way to manage that so using the same platform across all of those different environments including the edge that's really going to give you a direct benefit to targeting your applications to that same common platform having the ability to recognize some dependencies so maybe you have a dependency on a data set and that data sets supplied from sources that are in an edge location we can codify that and then enable developers to build applications you know do test dev Prada cross a variety of environments pushing all the way out to an edge deployment where you know thinking you're taking in a lot of data you may be building models in a scale out environment internally in your private cloud or out in the public cloud taking those models deploying those to the edge for inference in real time to make real-time decisions based on data flows through the system and that's that's the world that we live in today so managing that complexity is critical automation for managing that consistency common platforms I think are key tools that we can use to to help build up that that rich in person just from an industry perspective so who does who's that applied to in your mind right what kind of industry is looking at this and saying all right this is this is a an opportunity but also a challenge for us and something we really need to address what's the array there do you think honestly I see it across almost all market verticals so we look at the world or a platform centric view from from a RedHat perspective so we look at the world across industries what I find interesting in the edge use cases is they tend to get more vertically specific so in a manufacturing case you know maybe you're dealing with a manufacturing line which is a set of applications and a set of devices which looks quite different from a retail office or branch office environment some similar problems but very different environments and then you take the service providers networks the telco network out of the edge and that looks quite different from a manufacturing floor so you know it's a it's a wide variety of vertically oriented solutions drawing from some common platform technologies containers Linux you know how do you do automation across all of those environments that machine learning tools those are the things that I think are consistent but you get all a lot of very vertically focused use cases yeah I'm now in the canine today that that Andy was mentioning that they love open source and when we're here at Amazon and and he likes to talk about the compatibility that and customer choice is also very important to Amazon's wit tell us a little bit about how openness interacts with somewhere like ADA we're actually we're here at reinvent which is an ADA where show so how does Red Hat and AWS work together how do you coexist in this ecosystem and get the benefits of open source technologies we could exist in a number of different ways one would be as engineers working together in open source communities building technology another is we have commercial partnerships so we run our platforms on top of AWS so we bring customers to AWS which is a shared you know we have a shared benefit there and then there's also areas where we have competitive offerings so it's you know it's a full spectrum kind of the modern world of the buzzword co-op petitioner or whatever you know it I really think when you look in the open source communities engineers thrive on building great technologies together independent of any kind of corporate boundaries commercially people develop relationships that are complicated today and we have a great working relationship we've run a lot of our cloud customers on Amazon but again there's there's areas where we're both invested in kubernetes ours is openshift there's a zk s so customers have a choice in that context yeah sorry is that in that context that there are some in the open-source community who view cloud as possibly a bit of a villain and certain things we've seen some some dynamics around some particular providers around the debt the database face I went I went name 50 particular players but we've seen some competitive moves in in that place so do you see cloud is it the villain or is it an enabler of open-source technologies well it's definitely an enabler now there's a complicated scenario and this like is it a villain which is how do we create sustainable communities and in the context where a technology is developed largely by one vendor and it's monetized largely by another vendor it's not going to be a very sustainable model so we just have to focus on how are we building technology together and building it in a sustainable way and part of that is making the contributions back into the community to help the project's themselves grow and thrive part of it is having a great diversity of contributors into the into the project and recognizing that business models change and you know the world evolves yeah that doesn't introduce an element of risk it's been around for a while that enterprise are a little bit concerned about open source oh well who's really behind this will this project or software still be here in six months that seems to be decreasing as as the commercial support for particular open source projects and initiatives come to me and we see the rise of foundations and so on that try to give a little bit of an underpinning to some of these projects particularly ones that are critical for the supportive of enterprise technologies do you see enterprises maturing in their view of open source do they do they see it as no no that we understand that this is definitely a sustainable technology whereas these other ones like yeah that one's not quite there yet or do they still need a lot of assistance in making that kind of decision I've been at it for a couple of decades so in the beginning there was a lot of evangelism that this is safe it's consumable by the enterprise it's not some kind of crazy idea to bring open-source you're not gonna lose your intellectual property or things like that those days I mean I'm sure you could find an exception but those days are largely over in this in the sense that open source has gone mainstream so I would say open source is one most large enterprises have an open-source strategy they consider open source as critical to not only how they source software from vendors but also how they build their own applications so the world has really really evolved and now it's really a question of where are you partnering with vendors to build infrastructure that's critical to your business but not your differentiator and where are you leveraging open source internally for your to differentiate your business I think that's a more sophisticated view it's not the safety question it's not is it is it legally you know that you're bringing legal concerns into the picture it's really a much different conversation and people in the enterprise are looking how can we contribute to these projects so that's really it's pretty exciting actually so so what do you think it is then in the maturation process then as it did is it in the adolescent years is it growing into young adulthood you said you've been at it for a long time and it's more acceptable but where are we you think on that in that arc you know what in terms of adapting or or adopting if you will that philosophy probably depends on where you are in the layer of the stack and so the lower you get into the infrastructure the more commonplace it is the closer you get to differentiated value and something that's really unique there's less reason to even build those applications as open source if it's only you consuming it you know pretty pretty broad spectrum there I think that in general we're in some level of adulthood it's a very mature world in the open-source communities and what's interesting today is how we change business models around deploying and consuming open source technologies and then a next generation of technology will be very data-centric data drives a whole set of questions there's policy and governance around data placement there's model training and model exchanging and where models come from data or the models open source is the data shareable you know that it sets a whole new wave of questions that I think in that context it's much earlier so that's our next interview by the way with Chris next time down the road thanks for the time as always really good to see you and I know you're you're awfully busy this week so we really do appreciate you carving out a little slice of time glad to do face press yeah thank this right over Red Hat CTO back with Justin and John live on the cube here at AWS reinvent 2019

>> From the heart of Silicon Valley, it's theCUBE covering Comcast Innovation Day. (smooth music) Brought to you by Comcast. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Comcast Silicon Valley Innovation Center here in Sunnyvale. Very cool facility right off the runway from Moffett. They got a ton of cool toys downstairs which I get to go play with, which I'm looking forward to, but today the conversation was all about CX, customer experience, and you know, Comcast is there. A lot of people like to watch their TVs, interacting with their cable systems for a long, long time, but there's a whole range of new and innovative things that are coming out from Comcast, and we're excited to have an engineer who's kind of down in the bowels here in the engine room building all this stuff. So like to welcome Mike Fine. He's a cable software architect for Comcast. Mike, great to see you. >> Likewise. >> So you had a really cool demo earlier, which is not a demo, right? I think this thing is-- >> Production. >> Now in production, it's called the X1 Eye Control. I think most people know what X1 is. What's X1 Eye Control? >> Yeah. X1 Eye Control is a web application that integrates with off-the-shelf accessibility hardware, so that could be a Tobii eye gaze rig, it could be something called a sip-and-puff, which let's users use their inhalation and exhalation to control the application, or any other off-the-shelf accessibility hardware that can mimic a mouse to a piece of software. >> Too, it's-- >> Yeah. The goal of the project was pretty simple. It was to let people with ALS and other conditions control their TVs independently. >> That's amazing, and you showed a great video. The gentleman on the video is using I think an eye gaze method, but you said you've got integrations to a number of different, you know, kind of ADA-approved interface devices. >> That's right, the journey that this project has taken has been interesting. We started with just the ALS use case, which was the eye gaze, but it turned out that one of our early users had control over his voice, which is somewhat unusual for ALS patients, and so he asked whether he could control it with his voice, so we did that work through he had Dragon NaturallySpeaking, which was nice, so we did that work, and then of course given that we have the voice remote we decided could we make voice work for everybody, which we did, so now the application is on par with a physical remote, and then we even went further and let people type in voice commands, so in case somebody who's perhaps mute or had a speech impediment, or some sort of speech pathology issue that prevented them from using a voice, they could do that as well. >> It's really interesting, I mean you guys have so many kind of interface points to an ecosystem broader than simply what's available at Comcast, whether it's on the front end, as you said, with some of these interfaces with ADA devices, or on the backend if I want to watch my Netflix or I want to watch YouTube, or I want to watch, you know, a different service. You guys have really taken, you know, kind of an open, integrated approach to all these, one might argue, competitive threats to really bring it in as the customer wants to experience. Why did you do that, what's kind of the philosophy driving that? >> Yeah, well, the first thought that comes to mind is that none of it's possible without the right cloud APIs, so somebody very visionary years ago made the decision that everything you can do on your TV or on the mobile app you can do through the cloud, and so a project like this couldn't happen unless it was possible for a piece of software that somebody invented well after the fact to cause a TV to change channels unless there was that underpinning, so like any other piece of software it's a bit of an iceberg. There's a lot of stuff underneath that you don't realize as a user-- >> Right. >> But it's there and that's what makes it possible. >> Right, I'm just curious about some of the challenges in terms of moving UI and UX forward into places that people are not familiar with. And I've joked about it on a number of these interviews that, you know, I still get an email, not only from Comcast, but from Google and from Alexa, suggesting to me ways in which I might use voice. You know, as you sit back from a technologist what are some of the challenges you guys, you know, kind of anticipate, what are some of the ones you didn't anticipate, and how do you help us old people, you know, find new ways to interact with the technology? >> Yeah, it's a great question. I mean there's a lot of us here that spend our days solving that exact problem, right? Part of it is is notifying you of interesting things through SMS or through mobile push, or the messages on the TV, so your team is playing in a game that you want to see, a movie that you've declared interest in has become cheaper, become free, or maybe even buyable if you wanted to do that. Obviously there's lots of AI and ML in terms of putting recommendations in front of you based on your viewing habits, based on broader trends across, you know, because you watch this, other people watch this, so we know this is probably a good solution for you as well, but yeah, we're all, there's a large number of us trying to optimize what we call "time to joy," from the time you pick up your remote to think about what you want to watch to the time you're actually watching something you want to watch; make that as seamless as possible. >> Preston said you guys get like a billion voice commands, what was the period of time? >> A month. >> A month. >> A month, yeah. (chuckles) >> So obviously a big, giant new dataset for you guys now to have at your disposal. >> What are some of the things that you're learning from that inbound, what can you do with it, how do you, you know, now use this direct touch with the customer to, again, kind of recycle and have another iteration on improved experience? >> Right, so voice is a lot like a text chat, like a bot interface in that it's an experience where users are telling you exactly what they want to do, so if a user sits in front of a traditional web application or mobile application and has trouble finding what they want to do, they can't figure out what button to press, what screen to go to, you have no idea, right? You can't infer that they're having a problem, but with voice or somebody interacting with a bot, they type exactly what they mean, or they say exactly what they mean, so we can mine those voice commands and find the popular ones that we don't at that point have implemented, and if we can iterate on that cycle fast enough we can quickly introduce new voice commands that our users are literally asking for as quickly as possible. >> Right. What about the stuff that customers are not asking for, because right? There's one line of thought, which is the customer knows best, but the customer doesn't know-- >> That's right. >> What they don't know. So how do you guys continue to look for more kind of cutting edge stuff that isn't necessarily coming back through a feedback loop? >> Right, yeah, so it's an interesting question. So we're trying to add other non-TV use cases into the mix, right, so controlling your IoT devices at home, controlling your security, seeing your cameras through the Set-Top Box, and so on. So you know, until those use cases exist nobody's asking for them, and so you do have to be a bit visionary in terms of what you want to put out there as voice commands. You know, luckily we have people who, well, we're all customers of the platform generally, so we know what it means to be a user, but you know, we have people that talk with users and have a general sense of what they want to do, and then we figure out what the right commands are. >> Right, not voice specifically, but let's unpack a little bit deeper into the impact of IoT. You know, Nest probably was the first kind of broadly accepted kind of IoT device in the home, and now you got Ring, which everybody loves to take pictures of people stealing their boxes from the front porch, but that puts you guys with the internet connectivity in a very different place than simply providing a football game or the entertainment. So as you think of your role changing in the house, specifically with now these connected devices, how do you think about new opportunities, new challenges that being the person in the middle of that is different than just sending a TV signal? >> Yeah, there's a lot of talk about trying to be the home OS. Certainly we are in a unique position being in the home, both in terms of the router and the internet, but also, you know, often frankly you know when your system's setup a human being came in and helps you understand how to best position the physical devices in your house, and so on, that other companies don't have, right? Those vendors just don't have that builtin advantage. Clearly security has become a big thing for us. Home automation, I sit very close to that group. They're doing amazing things with automating rules like, you know, "Tell me when my door's been open too long," and these sort of things, and so more and more the use cases start to converge, that, for example, when you say, "Good morning," we have this idea of scenes, all right. So when your morning starts you not only want to tune the TV, but you also want to crank up the lights and unlock the door and open the windows, or whatever, and when you go to bed, so the actions that are involved in those use cases span not just TV and not just internet, but all of it. >> Right, it's just funny because I don't think Comcast would be the first name that people would say when they're talking about voice technology and the transformational impact of voice technology, right? They're probably going to say Siri was the first and Alexa's probably the most popular, and you know-- >> Right. >> Google's got Lord knows how many inputs they have, but you guys are really sitting at a central place, and I might argue it's one of the more used voice applications-- >> Absolutely. >> Out there, so from kind of a technology leadership perspective you guys have a bunch of really unique assets in terms of where you are, what you control, what you're sitting on in terms of that internet. You know, how does that really help you and the team think about Comcast as an innovation company, Comcast as a cool tech company, not necessarily Comcast as what used to be just a cable company? >> Right, right. Well you know, as somebody in the valley with friends in the valley it's always interesting to try to differentiate reality from the view that many people have. You know, this is definitely much more than your dad's cable company. It's a consumer and electronic company as much as anything else. We very much position ourselves with all the, you know, with the FAANG companies, et cetera, so you know, when we talked about CX it's no longer the case that whatever's passable for a stodgy cable company passes as CX anymore. Now you're being compared to a set of customers, companies that are providing fantastic user experiences for their customers, and you're being held to that standard, so you know, there's a lot of pressure on us, which is great; we like that. We want to produce fantastic products, and yeah, I don't know if I have a great answer in terms of how to move forward in terms of melding it all together, but we have a lot of smart people in the hallways making that happen. (chuckles) >> So last question is really the impact of AI, because you know, we cover a lot of tech events and a lot of talk about AI, but you know, I think those of us around know that really where AI shines is applied AI in specific applications for specific U cases. So how are you guys, you know, kind of implementing AI, where are some of the opportunities that you see that you can do in the future that you couldn't do the past, whether it be just with much better datasets, whether it be with much faster connectivity and much better compute so that you can ultimately deliver a better customer experience using some of these really modern tools? >> Right, so some of the work is just making what you already do or experience better, so for example showing you recommendations, right? Just make that algorithm better, and so there's a great deal of effort, as you might expect, at a company like this on that problem, but there's also work being done to just take any interactivity between you and the system out of the picture completely. We talked a little bit about this earlier, that, for example, we're working on technology that when you turn your TV on in the morning it should probably tune to the channel that you normally tune to in the morning. That's a pretty simple problem, in a sense, but you know, if I watch your viewing patterns and I see that you turn on a particular news show in the morning, why should you have to pick up the remote and change it from what you watched the night before to that channel? It should just happen. We talked about the Smart Resume stuff, that's obviously a fantastic use case for end users, so there's, you know, it's not surprising it's being used all over the technology set. It's in the home automation world. You know, it's in A/B testing, so trying to figure out the right cohorts to try different things in front of, so it's everywhere as you would expect. >> Right, right, it's pretty amazing. I mean there's just so many things going on, you know, kind of under the covers, some that we can see, some that we can't see where you guys are really kind of progressing, you know kind of the leading edge, cutting edge customer experience with something that people interact with every single day. >> That's right. >> Yeah, cool stuff. Well Mike, thanks for taking a few minutes. Congratulations on the Eye Control; really a cool story, and look forward to more publicity around that because that's a really important piece of technology. >> Thank you very much. It's been a pleasure. >> All right. He's Mike, I'm Jeff, you're watching theCUBE. We're at Comcast Silicon Valley Innovation Center. Thanks for watching, we'll see you next time. (smooth music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Welcome back, everyone. Day three Q coverage here in San Francisco for V emerald. 2019. I'm just for a student, Um, in here with David Lan. Take days free kick off. We have two sets wall to wall coverage. Guys, this is the time where we get to take a deep breath two days under our belts look and reflect on all the news we've covered in a dark to last analysis sessions but also kind of riff on. We got two nights in hallway conversations we learned a lot of the party means do. I learned a lot last night. Dave. I know you. You learned a lots, do you, Thomas? When things that the chatter Certainly twittersphere hashtag the emerald. A lot of action on there, but it's the hallway conversations. It's the party that people have a few cocktails in them day that you start to hear the truth. The real deal comes out, >> No doubt. And and again Jon Stewart, there's real concern over from the from the practitioners we talked to about this acquisition spree. Are they going to be integrated? Are they going to just throw all this stuff at us and keep jamming products and service is down our throats? Or is this going to be a coherent set of solutions that solves our problem? We also had a little little interesting side conversation about, you know, Snowflake, Frank's lumens new company and how basically Frank is bringing back the Pirates from Data Domain and from service. Now Mike Scarpelli is over there. He's a rock star. CFO Beth White is eventually is back over there. And Frank's Lupin. He's the guy who takes companies from, you know, 100 million to a billion, so that's gonna be >> very serious money making him going on there. >> We have been following his career for a number of years now. We watched him take data domain. We watched him pull that that rabbit out of his hat with the sale with net app, and then the emcee swooped in. And then we saw what he did service. Now we've documented this is an individual to watch, you know, >> he's a world class management team member I mean, he's executes. >> Oh, yeah, no doubt. And >> he has >> a formula that's been proven and in time and time again. And to me, the biggest testament salute Min is the success of the continued success of Data Domain. After he left Hey, he really helped clean up the emcees data protection mess. Um, and then the second thing is, look at service now is performance after he left, I haven't missed a beat. And, yeah, John Donahoe, great executive and all, but it's because Frank's Lubin had everything in place and that was a really well run >> dry. And they got a nice little oracle like business model. >> Yeah. No, you're right. They kind of, you know, the big complaint now as well. Your price is too high that Oracle. >> What have you learned? What you hear in the hallways? I mean, a lot of chatter. >> Yes, John, we We've been reflecting back a lot. It's 10 years in 10th year of the Cube here and back here in San Francisco. The new Mosconi, our third show that I've been at this year in Mosconi and we always track year to year. But since it's been what 45 years since we were here for VM World. When I talked to the average vendor. When I talk to you know, the analysts here were like, Oh, thank goodness we're not in Vegas. When I talked to the average attendee, they're like, Oh my God, what happened to San Francisco since last time we were here? It is too expensive. And the experience walking around San Francisco has really not nearly as nice as it might have been five or 10 years ago. And many of them we were talking to, Ah, woman that runs an event that has been Vegas in San Francisco. And she said, Oh, we did in San Francisco and got tremendous feedback. Don't do it there again. Brings back to Vegas both for costs and the enjoyment of being around the environment. >> Where was a shit show here in San Francisco is horrible right now, I got to say to your right eye was walking this morning from my hotel. Literally. A homeless person passed out the middle of the sidewalk. Um, your smells like urine. It's P, and it's It's just I mean, it's really bad this tense now. I mean City of San Francisco is gonna do some. Mosconi, by the way, has been rebuilt. Awesome. So, you know, in terms of the new Mosconi stew, that's a serious upgrade. Hotel rooms are scarce and just the homeless problem. It's just ridiculous. I don't know what they're >> doing. So one of the other big things when I was reflecting coming into here two years ago when VM wear really started down right before the war on AWS announcement, they made a big announcement. IBM because they had sold off the cloud air toe Oh, VH And for two years Oh, VH was a big partner, Talked about that transition, said we handed off this great asset over h isn't here at the show. I was like, Oh, my gosh, you know, that was, you know, such a big story and other companies like New >> 12. That's good. One lets someone who's not at the show and why. Yeah, oh, VH wired to hear >> They aren't here because, well, they've got customers. More of them are in Europe That was supposed to be a big entry into the United States. Obviously, it wasn't as valuable for them to be here, even though I'm sure they're still part of that service provider ecosystem. They have other big one for us, and we've had on the Cube Nutanix. You know, we've had Dheeraj Pandey. First time we had him on was that this show is still the majority of Nutanix. Customers are VM where customers I've talked to lots of Nutanix customers at the event, even part of the analyst event. Some of the customers I talked to were like, Oh, yeah, my hardware stacks Nutanix and amusing NSX. And I'm using other things there. But they are not here. They're not allowed to be at the show. And I >> mean, they were blatantly told they can't come. >> They can't come here. They can't come to the regional things. They can't do the partner things. So that that that relationship is definitely >> from red hat. What kind of presence have you seen from Red s? >> So their number companies like red Hat that they're kept at a lower level of sponsorship. So they're here. They participate, you know. Open shift, of course, is you know, big enemy for cloud native. Lots of open shift runs on V sphere. So many of those companies that are part of the ecosystem, but not the ones that they want to celebrate and put front and forward. So it's always interesting kind of walk around on those. Even Microsoft is an interesting relationship for, you know, decades with the M wear. You know, of course, azure they partner with. But hyper V was long a competitors. So, you know, we understand those competitive relationships >> could be interesting. Stew and Dave on the ecosystem Jerry Chan Day when we just doing my interview yesterday on the other set mentioned that the ecosystem reinvents itself the community. The question now is with Delhi emceeing Del Technologies obviously heard Michael Dell essentially laying out his plan, which is he's got. He's trying to keep people distracted, but the bottom line is going to top people putting together the cloud right well service provider model. So you know, that's what he's gonna be a big impact. VM wear the crown jewel of Del Technologies certainly is looking more and more like It's >> well and yesterday remember the first VM world we did in 2010? It was It was del I mean course and see only the time Who's Del? It was H p Yes, the emcee was there, but it was net app. I mean, everybody could've had equal standing yesterday at the keynotes. It was Project Dimension of V M, where cloud on Delhi emcee and long keynotes >> data protection into the VM were >> also it's It's all very heavily, you know, Jeff Clarke has his his thumb on, you know, the the deli emcee folks pushing that through Veum where Michael is orchestrating the whole thing. Pat obviously is allowing it. I was sitting in the audience Next next, Some folks from Netapp they're like, you know, this kind of a bummer. Calvin Sito from h p e tweeted Wow how to stick it in the face of your ecosystem partners. He then later went on Facebook saying, Hey, I love this ecosystem, so sort of balancing it out because, you know, he wants to be a good, good citizen, but clearly the ecosystem partners who basically brought VM where you know, to the the position where it's in through distribution, our little ruffled. Right now you can't blame him, But at the same time, the mandate is clear. Michael Dell is driving his products and his solutions through VM were period the end. And, you know, if you don't like it, leave >> right. They had such great success with V San and VX rail in that joint product development and go to market. If they can replicate that with a number of other solutions, they get that the synergies. If >> you don't like it, don't leave. That leave is worse than that. They say you don't like it, you know, invited you. But >> how about what Pat said yesterday in the Cube about when they announced on Gwen heavily leaned into V san. He said publicly that Joe Tucci was pissed and I hate her. They were going at it so that so that shows you the change, right? I mean, so so so e m. C. When it owned VM where was very cautious about allowing Veum wears a software company to drive value somewhere Now is just acting like a software company. >> Well, I think I mean, I learned last night's do, um and you can appreciate this. I learned that the top executives of'em where are looking heavily and working hard at understanding and drive them kubernetes cloud native thing because this is not a throwaway deal. This is not a you know, far anything that they are investing. They get their top brass tech execs on kubernetes fto. Two big players job. Ada, Craig McCaw calumnies. We know interviews since day one, but I think the cloud native thing is going to be interesting. And I think it's gonna be evolution. I think there's gonna be a very dynamic road thing's gonna be a series, of course, corrections, but directionally they're all in on. They're going for it, they're not. >> And actually, I had a, you know, good discussion with Chad Attack. It's a good friend of the program now working at GM, where for the first time, but came from AMC worked at Pivotal. He said, culturally, such a gap between VM wear don't have to touch your app, you know, move everything along lifted shift is nice and easy versus pivotal, you know must go completely You know, dual programming, you know, agile everything there, so bridging those because there's multiple paths and the rail pharaoh announcement is that would be cloud native stuff that won't necessarily go to the EMS. We're going to retool V EMS to now be a platform for kubernetes so that they have a few passed to bridge or to build towards the future. Here's the >> answer strategy. Discussion That and Rayo Farrell was now running Cloud native. Think this is just really >> ties in the interesting discussion that I had with some folks was that you've essentially got well, Jerry Chen brought this up last time we had him on it and reinventing because >> we have >> a conversation all the time about this Amazon have to go up the stack. And Jerry Chen made a really he said, Look, it they're not They're not gonna become an e r peace offer company. What they're gonna do is give tools to the builders so that they can disrupt Europea. They can disrupt service. Now they can disrupt Oracle. That's their strategy, at least for now. Okay, so what does that say? I think the strategy discussion inside of'em were and and l is about by whatever clouds gonna be 35 to 50% of the market. Fine. And the cloud native abs. Great. But you got this mission critical. E r p is an example. Database saps that are on Prem. What we have to do is keep them there. So we're going to sell to the incumbents and we're going to give them cloud native tools, toe modernize. Those APS have build new acts on Prem, and that's the that is the collision course that's coming. So the big question is, can the cloud native guys and AWS disrupt that >> huge? I've always said I'm is on and like the way they're coming in, a tsunami is coming in. And who's gonna build that sea wall to stop it right? And that's essentially only hope that these guys have. You look at all the competitive strategy. Was Oracle. Whoever just gotta stop it? You can't like >> the sea >> wall. That's a great building. A sea wall I was, I would say, is Is that you know, they're only hope at this point is to, you know, get in the game because see Amazon is the stack. They're not really moving up the stack. You hear that from Cisco and Dale and other people? That's where it's a game of musical chairs. Right now, the music's you know, there's still a lot of shares left, but soon chairs getting pulled away and Cisco Deli emcee VM, where they're all fighting for these big chairs. And one >> thing >> we talked about yesterday is that VM wears very directional, product driven. Otherwise they pick a direction, is a statement of direction and don't really have a lot of meat on the bone. In the product side, Sister is actually in market with service providers there in market with NETWORKINGS to this no vapor there that's installed basis and incumbent business. You have developers Esso Baton talks about suffered to find data center, suffer defined networking. I mean, come on, Really. I mean, they're getting there, but it didn't have the complete solution. Cisco >> Coming into this week, I expected here a bit more about the progress and all the customers of'em wear on AWS and feel like Vienna actually downplayed the AWS. We know what a strong partnership it is at every Amazon show we go to, and we got a lot of them Now there's a big presence there, and I can talk to customers that are starting to roll out and move there, but it felt like it was David's. You pointed out there are some messaging differences when you talk about multi cloud and how they're positioning it. So, you know, put those >> here Amazon. If your Amazon you're not happy with Microsoft Dell Technologies World The big announcement that was positioned a cloud foundation Although it wasn't a joint engineering, But the press picked it up as though the Amazon deal has been replicated with Microsoft and Google. I mean, you gotta be gotta be hurt if your Amazon >> So I've I've just been taking notes this this event, there's I've noted at least five major points of difference between a W s what they're saying and their philosophy and the anywhere so eight of us. We know they they don't talk multi cloud. They've told their partners, If you're doing joint marketing with us, you cannot say multi cloud aws that reinforce John. We saw this. Steven Schmidt said that this narrative that security is broken doesn't help the industry. Security's not broken, you know, we're doing great. The state of the nation is wonderful. Aws Matt. Not really. I agree. By the way. Uh, that's not the case. I agree with Pat saying Security's broken. It's a do over VM where wants to be the best infrastructure and developer software company. Who's the best infrastructure and software development platform. Eight of us. The M one wants to be the security cloud. Who's the security cloud? Eight of us. And then, uh, they talked about 10,000 cloud data Listeners are those really cloud data centers at Vienna. And the last one was this was a little nuanced Veum was talking about We know about migrating, modernize, lifted ship shift and then modernize The empire's not talking about modernize and then migrate. If you want to. I totally in conflict >> as a collision course. That's got Look, look, look at the data center was Look, it looks like we're going. We're going away, right to the data center. Staying. That's music to Michael Dell's VM. Where's years they live in the Data City? Do you pointed out yesterday? Data Senate goes away. So does begin. Where's business? >> One of things. I'm surprised. I'm wondering you both have talked to some of the service fighter telco pieces of'em, where they're doing that project dimension, which is the VM where stack on del that looks just like outposts on. And I know they had deployments on this for months. If I was them, you know, it's everybody's hearing about Outpost to talk about it, being more like we're already doing it in. This has you in that Amazon ecosystem. It might be a little strong for the Amazon story, but have you been hearing any about that this week? >> I think they keep a lot of cards close to the chest, but it's clear from the announces that they're doing certainly del the VM, where on Delhi Emcee Cloud or whatever it's called, it's not a cloud but their their infrastructure that is essentially a managed service. That's gonna be really strong for I t. People, because I think that the value proposition of going toe i t and saying we have this, you don't need to do anything. It's very strong, I mean, because I didn't want him >> and justified because this the project to mention it is that single, that thinner stack like what we saw on Outpost in the Amazon video, as opposed to Veum, where cloud on AWS, which is the full C i r h d. I stack. >> I haven't heard anything still on >> well, but the conversation I had from from Vienna, where standpoint, they could make money on that manage service. That's why it's the preferred partnership, right? And so that's their part of their cloud play. If you don't have a public cloud, I said this yesterday, you have to redefine Cloud and you have to get into cloud service. And that's what's happening. And that's exactly what's happening. And what I like about what V M where is doing is they are transitioning their model to a sass based model. Now it's only 12 and 1/2 percent of the revenues today. But both pivotal and carbon black are gonna add, you know, ah, $1,000,000,000 next year to that subscription based $3 billion in year two. Um, and so you know, Pat said the other day, I think we could get to 50 50. I don't necessarily think in the near term we're gonna go beyond that. It's not the Adobe >> way could be critical. Critical of'em were in some areas, but I gotta tell you their core strength that they went to a software operators on the data center friend of prices. That's been a great strategy. Focusing on their core building from there is Jerry 10 point out adding other products so their software company, So I think they're really got a good solution. And you? The data shows that people are increasing their spending, John. Just one based on >> that. Because I had a couple of really good conversation with customers, customers that would deploy VCF So they've got the full stack on there. So using H C I, but not necessarily on Dell hardware, could be Cisco Hardware. Could be HB hardware in the like or they're buying NSX. But the virtual ization team owns it, and they get kind of put in. A box storage team says That's not the array I'm used to buy. Well, maybe I'll put a pure storage box and put it in between. The networking team says I'm refreshing my Cisco hardware. You know, we're like, but we have NSX, and it's great. Well, you can use NSX over there. We're going to use a C I over here. So the term I heard from a number of customers is organizations still have hardware to find roles, and they're trying to figure out how to move to that software world. Which hurts me, cause I spent years trying to get beyond silos and helping people you know, move through those environments. And still, in 2019 it's a big challenge. That organizational shift is we know how tough that is. >> So just couple points in the data, because you're right. There are some countervailing trends, though. So, yes, people are spending Maurin VM where in the second half. But at the same time, the data shows that cloud is hurting VM wear spend. So this that's kind of gets interesting. Our containers gonna kill VM where? No, there's no evidence that container's air hurting VM where spend. But there's clearly risks there, you know, as we've talked about who's best position of multi cloud. Well, it turns out three guys with the public cloud are best positioned in multi Google and Microsoft on, and so and then the pivotal thing is interesting, and ties ties all this in so that the data is actually really interesting. It's like you're seeing tugs at both sides, and I think your your notion about the seawall is dead on. That's exactly what they're doing. >> You see that with Oracle's trying to stop jet. I just want they can't win this one to stop Amazon just on the tracks gave great data. Great reporting, Stoop. Good observations. Get all the day that night and parties we're gonna certainly keep doing that. Day three of wall to wall coverage here. You bringing to the insights and interviews here live from the Emerald Twin 19. Stay with us for more after this short break.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by IBM Wear and its ecosystem partners. >> Welcome to our live coverage here in Mosconi North Lobby, Of'em World 2019. I'm John for a Student and a Volante celebrating our 10th VM World or 10 years of covering the M world. Dave's stew. What a run been Go back across Mosconi South 10 years ago with the green set. This is 10 years later. 10:10 p.m. World BMC Rule No longer the show, so that kind of folds in the Dell Technologies Man, The world's changed. Pat Nelson had just delivered his keynote as CEO Sanjay Poon and a CEO came on talk to customers stew. A lot of acquisitions, a lot of cloud native, a lot of cloud. 2.0, this is turning into VM. Wear 2.0, where vm zehr kind of only one part of the equation. So let's jump into the analysis, Dave. I mean, you put out some killer research on silken angle dot com, and we keep on dot com around customer spend still, we put out a lot of analysis on all the key trends that Vienna was playing into. Cloud two point. Oh, is what we're calling it. It's enterprise Cloud of fresh scale Day. What? What? What? What do you want? Your analysis, Latino >> John, when you go back. 10 VM Worlds ago, it was all about virtualization, completely changing the deployment dynamics. When when I first saw a VM deployed, I went, Oh, my God, This is gonna change everything. And it did. But while compared to now what's happening with cloud and a I we heard so much about five g. It was also the big, big difference in the ecosystem. Back when e. M. C owned VM wearing 2010 there was that sort of Chinese wall stew. You were working there, you know, just before that. And there wasn't a lot of, you know, swapping of I P, if you will. They were sort of treating them as unequal player to net app and everybody else out there. Tod Nielsen used to say, for every dollar spent on of'em were licensed, 15 spent an ecosystem. You don't hear that kind of narrative anymore, you hear we're crushing the HC. I vendor where number one basically a sort of backhand to Nutanix We heard on the on the keynote Very tight integration VX rail project Dimension So much, much tighter integration since Pat Tell Singer joined VM. Where from the emcee lots has changed >> will be a lot of research on reporting leading up to the show around Cloud two point. Oh, I'll see Dev. Ops is willing to home of the dimension on enterprise scale, the number of acquisitions of'em wears made and then, boom. They dropped two monsters on the table or the 11th hour pivotal for 2.7 billion carbon black for 2.1 billion. Lot of stories in those AK was other acquisitions, your analysis and how that played out today on the >> Kino. As Dave said when we started coming to this event back in 2010 you know, the virtual machine was the center of the universe. What were these servers that it lived on, how to storage and network and get fixed to be ableto live in that environment And the keynote. It was a lot of cloud, you know, John, we brought in a lot of the Cloud camp people that first year and some people were like, Why are we talking about Cloud? This is VM World, and we're like, Well, this is the future. And today we're not talking about V EMS at the center we're talking about containers were talking about cloud native applications, that multi cloud world absolutely something that pack l singer did. Front center actually felt it almost glossed over a little bit of the H C, I and NSX and all these wonderful things. Sure, there was some big del pieces in there. The M word cloud on Delhi emcee the Del Di are, you know, data protection, power protect, you know, into the VM where peace something that you definitely would not have seen under the old emcee Federation model. So Michael Dell, absolutely having his strong footprint here. Dave's done a lot of analysis talking about things like Pivotal getting pulled in and like so many different acquisitions, Pivotal came out of'em wear and, you know, carbon black Boston based companies so many different pieces here to get them talking about applications and where Veum, where the company sits in this multi cloud world where they're trying to be, you know, maintain their relationship with us. >> Let's get into the analysis on the whole ecosystems. I really want to dig into the work. Dave, you didn't and the team did. But let's go through the keynote first. So my personal opinion was it felt like, um, I'll give him a C plus Pat because it just didn't have a lot of meat. In my opinion, it felt like it was too much tech for good, although super important to have that mission driven stuff I think is really valuable as the market tends to look >> at tech >> as bad actors. I thought that was addressing. That was a positive thing, but it felt too much. I didn't see a lot of specifics. It felt do is and David, if they were hiding something, they were putting a lot of it didn't seem like there's a lot of substance coming out specifically around how Kubernetes was going to be impacted. Specifically, how Cooper is going to sit within the VM where ecosystem products specifically I just didn't feel like the product side was there. >> Well, you know what? I'll say it, John and General, I agree with you because Day one usually is here is the company vision. And if the vision is kubernetes, well, we've been hearing kubernetes for a bunch of years. Kubernetes is not the answer. Kubernetes is an enable ionizing technology job. Ada, who we up on stage? You know, we had him on the Cuban. He's like, look committed. This is not a magic layer. It's this thin layer that's gonna help us go between clouds. Getting into some of their future projects is something I usually would expect on Day two, the vision of V. M. Whereas a company, it feels like we're in that transition from who do you want a big tech for? Good? That that's great stuff. You know, Pat has a long history of talking about, you know, that moral compass that he has and wants the company to live. That which is a good change from many of the Silicon Valley companies. But, you know, I didn't get a strong feel for their vision and it was not >> a conservative. They didn't want to actually put a position down there because I think everyone in the hallway that I talked to wants to know how Cooper is gonna impact the sphere for instance, is gonna change the makeup of the sphere. And what's the impact on the product side the head that stat about bare metal being 8%. I was like, a little bit biased. Maybe there, So are they. They tiptoeing. Dave, you think? I mean, the spend numbers show that if you could just hold the line for 24 months and the new trends won't take away from that license, I mean, is it a tactical thing? Or do you think that here's the >> thing? I want to go back? I do want to give'em where? Props on one thing and you've used this term to If you go back to 8 4009 Paul Maritz talked about. We're building the software mainframe and passed them pretty consistent about that they used, they said, Any workload, any app? What's different today than back then is, he said, any workload, any up any cloud. Really. Cloud wasn't as much of a factor back then, but that vision has been fairly consistent it to you. Answer your question, Veum. We're spending remains strong, you know they're spending data that we shared with the GT R on silicon angle yesterday and today is that 41% of the VM were installed. Base is going to spend Maurine the second half of 2019 and only 7% are going to spend less. Okay, that's a real positive. But at the same time, the data clearly shows that cloud is negatively impacting VM wear spend and so that's a real threat. So multi club Pat said today technologists who Master Master Multi Cloud will own the next decade. He's talking to his audience. I'm not sure I agree with that. How much you're mastering Multi Cloud is what's gonna be the determining factor to own the next decade. >> Well, I'm stumped. Stick with my position. That multi cloud is not a reality. I think it's really more overhyped, and our actually just started to be hyped and probably will be then over hypes. And then seven years from now we'll start seeing multiple clouds truly interoperable. But I think multi cloud is we find on the Cuba simply enterprises have multiple vendors and multiple environments that happen to be those vendors have cloud, so I don't think it actually is an operating model yet. But again, just like on the Cube 2012 stew. We talked about hybrid Cloud. I called. I asked, yes. When was it a halfway house of the weigh station? He had a connection. >> So gassy. So, John, here's what I say. Number one is customers today absolutely have multiple clouds. But for multi cloud, to be a reality multi cloud must be greater than the sum of just the piece is that it's made up today and absolutely were not there. Today. VM wear has a strong reason why it should be at the center of that discussion. But they're gonna be right at loggerheads with Red Hat and Microsoft and Google and Cisco in that kind of debate at the multi cloud >> and we had, we had a story on our special report on silicon angle dot com. Check it out. It's called Coping With Multi Cloud. Were coping was by design. Coping as a mechanism used to deal with uncertainty. Coping strategies is what CEOs are going to deal with. But read that post. But in it I kind of see. I mean, I kind of agree and disagree. We have two perspectives, Dave developing. You want to get your thoughts butts do on this C I ose that come from a traditional I t background tend to like multi vendor things because they know they don't want lock. And they're afraid if you then swing to the progressive side si SOS, for instance, who are have a gun to their head in terms of security, they're all saying no, we're betting on one cloud and we'll have backup clouds, but our development staff is gonna build stacks. Have AP eyes, and we'll share those AP ice to our suppliers. Cloud vendors are saying Support our specs. So to spectrums the old school I t. Guys saying Multi vendor equals multi cloud. And then then, on the other end, See says to say, I'm gonna build technology and build a stack, exposed FBI's and let the clouds support my my tooling that not the other way around your thoughts. I >> pulled a quote in my piece That's on Silicon angle as well. From David. If lawyer and he was defining a hybrid multi cloud, he said, any application of application service can run on any note of the hybrid cloud without rewriting re compiling a re testing. My argument would be you're never gonna have that North Star without a high degree of homogeneity. And there's three examples of high degrees of homogeneity in hybrid Cloud. Today it's azure stack. It's clouded customer, and it's outposts. You're so this idea that we're gonna have this diverse set of clouds and yet they're all gonna run is one to me. I ask, Is it technically feasible? And is it Is it practical? >> Well, Steve, Steve Harry was on his Hey had announced the signal. FX has come. Portfolio can be sold on a big deal to split when he was on The Cube with me last week and he said one of them looking back on the 10 years that 1 may be M where great was virtual ization allowed for massive efficiencies and improvements without rewriting the apse. The question today's point is, is that a reality? Can what's next? So that that next gain that's not gonna require people to rewrite their APs >> well and that actually not rewriting the axes where VM or has its strength. Because, you know, I I made a joke during the keynote. It was like you have a V M insert magic. Congratulations. You now have a cloud workload because I just did. VM were cloud and it's the same app. But on the other hand, that's actually been my biggest dig on V M. Where is the long pole? In the tent and modernization is modernizing wraps. And that is that Tom Zoo that Veum were announced. They're taking bit Nami and pivotal because we do need to modernize the application. If you have an application, you've been running long enough that your users are complaining about it. We need to modernize that. VM wear has not been much of enabler of that pivotal. Yes, absolutely. That's what the cloud Foundry Labs, the pivotal Labs has been doing for years. It is a tough thing to do. That's what the developers we hear it Amazon. They're building new abs. I don't hear modern building new app at VM where, but they are moving in that >> direct question for you guys and John you in particular, but also used to as well followed AWS probably more closely than any two people I know, Pat said. Strength, lies and differences, not similarities. I've noted many differences in philosophy between A. W S and V M. where they're both winning in the market place. We know a divorce is growing much faster, but a divorce doesn't believe in multi cloud. A Devil's doesn't believe security is broken. That's that's VM wears narrative VM where says it wants to be the best infrastructure and develop our software company. That's kind of like eight of us is the platform for that. They both want to be the security cloud, and and VM were said today they have 10,000 cloud data centers, and I'm guessing that Andy Jassy wouldn't think that many of those data centers are cloud data centers. Your thoughts on the differences between between A. W S s philosophy and VM wears narrative. And can they both? Is there enough market for them both to win? >> Well, it's strikingly different. I mean, AWS is just in a breed of its own. VM wears hedging and playing there their bets. They're kind of putting, you know, bets on each horse, right? Interesting enough in the cloud thing. There was no mention of Google Cloud. I didn't see that mentioned there. Andi was speculation. Wouldn't Oracle be great partnering with Google? That's not a rumor. I'm just kind of put it out there. That would be a good combination partnership, given the Oracle's cloud is failing miserably, I think v M. Where because of the operating leverage in the enterprise, has that operational layer down to me, Amazon is the model, the future, because they are clearly born with a dev ops mindset. They have an environment where developers can build applications and they could operate. It scale with all the efficiencies of operations. So I think cloud to foreigners were calling. It is all about having developers and operational excellence without a lot of disruption or re platforming. So I think that's where the differences are. You have company that have toe have to work with this world of legacy applications, and that requires first lift and shift, which doesn't become attractive. Then you add containers on the game changes. So I think container ization really was, I think, the seminal moment in the shift where where you got kubernetes and containers. So let the enterprise cloud. Native guys get in and have an operational framework that takes advantage of the horsepower of public cloud, which is computing storage, which is why we think networking and security will be the absolute focus areas for Cloud two point. Oh, and Amazon is just dominating the depth and the ops. And I don't think anyone is coming close. >> I'd love to hear your thoughts, too, but I just got caught. I don't think Oracles Cloud is failing miserably. I think it's I wouldn't say it that way. I think their infrastructures of service is irrelevant and the cloud is all about SAS. But just, you know, that's what I think. Waken debate that somebody >> has been great for the Oracle customers. But in terms of all metrics in terms of public and enterprise, cloud with multiple environments nonstarter. >> So there's a bit of a schism out there if you talk to customers. There are many customers when they deploy in Public Cloud, although uses, you know, compute storage and, like the identity management and that's it. And they'll stop and I talkto you con many customers that are using kubernetes so that if they want to hit the eject button, but they're all on Amazon today, so it's not like they're all fleeing Amazon or doing it. But we talked to lots of developers that are deep in aws they're using those service is they're using Lambda and they're building it. So how deep will they go? And that's where I look at this VM we're offering. And it's if I'm gonna take the sphere and extend that with kubernetes. I saw Cuba. Well, um, actually in the Twitter stream said it is, you know, cloud lock in to Dato is what we get if we do that. Because the whole reason VM were originally created called Foundry. So they didn't have to take that entire V's fear colonel and put it everywhere. So it's a nice bridge. That van, where has the partnership they have with AWS is a great strategy. But I still think it is a bridge to an ultimate solution where they'll still use the M where the embers not going anyway. But that shift of where my application live in what service is I do is going to change a lot over the next 3 to 5. >> Let's not lose sight, Dave, of where we are in the industry. I mean, we're at VM World 2019. We go to reinvents coming up. We kind of live in a tech bubble in the sense that all this stuff is all kind of great skating to where the puck is gonna be. But the reality is in most I tea shops, and again, I use ceases as a proxy in my mind, because they're in the cutting edge of all the real critical nature of security, of the impact that harm that could happen to a company. So I look at sea. So she's more of a canary in the coal mine for trends than the nutritional CEO. At this point, most enterprises are just trying to rationalize kubernetes, generally speaking like never mind, like making a centerpiece of their entire architecture. They're looking at their existing environment saying, Hey, I got V EMS that did great for me. Serve a consolidation enabled more efficiency, not rewriting code. Now what? I gotta do kubernetes and do all this other stuff. How do I suspect my VM with kubernetes? Is it on bare metal? So I think we're way ahead right now. In the narrative, I think the reality is that people catch up. That's where the proof is gonna come into. That's why the customer survey numbers are interesting. >> Keep keep. Townsend is set on the Cube VM, where moves at the speed of the CEO, so they're not moving too far ahead of them, but they are key heating up with them. >> Let me share some data to share some data so you could go to Silicon Angle. Look at the V M World 2019 90 spending survey containers, Cloud NSX and pivotal its data from Enterprise Technology Research that we analyzed. There's no evidence right now that Container's air hurting VM wear. But then that was the narrative that containers are gonna kill the M where but long term. There's real threats there. So that's what the pivotal acquisition, at least in part was about. I want to address the pivotal acquisition cause we haven't dug into it a little bit a cz, Much as I'd like to see. There's really three things there. One pivotal was struggling. You look at the stock price, you look at their buying patterns, you know the stock was down that not even close to their original AIPO price, so they wanted to get out of the public eye right now would not be on that 30 day shot clock. The second is it's a hedge on containers. And the third is it's a financial scheme. I mean, I'll call it that VM wears paying $800 million in cash for an asset that's worth $4 billion. How can that be? Well, they already owned 15% of pivotal there. Give. They're exchanging stock. So their trade trading paper to Adele in exchange for Dell's 70% ownership in Pivotal. So they pick up this asset, and it's basically a forced migration by Michael Del, who controls 96% of the voting shares. So there's all kinds of inside nuance going on there that nobody's really talked about it a >> great deal for Of'em. Where and Michael Dell? It's >> a very good deal for VM wear and Michael Dell. >> Let's unpack that are rapidly. >> Just did the one piece on that, right, because kubernetes it was the elephant, the room that was damaging what Pivotal was doing. VM were made a couple of acquisitions VM where needs to react at, so it made sense to pull out back in. Even if it does go against some of the original mission, that Cloud Foundry and Pivotal had to be able to be that cloud native without that full strong time, >> it's all about building apse, right? It's all about enabling developers. >> Let's on that note. Let's go around the horn and talk about what we expect from the emerald this year. And then we'll kick off three days of wall to wall coverage. I'll start, I expect. And I'm not looking for is how VM wear and its ecosystem and who's really deep in the ecosystem, who's kind of independent and neutral, what they're doing with their containers and kubernetes play. Because I think the container revolution that was started with Dr Absolutely is very relevant to the C i o and the Sea. So so and then how they're using data in that in their applications. So you know how VM Way wants to position themselves on the control plane, how that fits in the NSX. I think containers in the container ization is going to change. I think bare metal is gonna be a super important topic in the next couple of years. Dio I'm kind of swinging back to the my feeling that you know, hyper convergence what it did for server storage networking back when you were calling those those moves. I think that kind of hyper convergence mentality is coming up the stack, and I think Containers and the Kubernetes Chess Board will will play out. >> I think if you my feelings, if you don't own a public cloud, you better convince your customers in your ecosystem that the future is in our definition of cloud, which is multi cloud. And that's what this VM world to me is all about. >> Yeah, you know, Veum wears taking their software state and trying to live in all of those cloud world. So you know, V. Amar has 600,000 customers and they want to be the ones to educate them on the kubernetes containers. You know you're at modernization, but there's a lot of other places customers can learn about this. No one understand where VM wear really adds value beyond all of those pieces, because all the cloud platforms have their kubernetes. >> A lot of other places, like the public cloud. That's where all the action >> exactly comes back down the cloud 2.0 Dev and ops developers and operations all come together with software. Thank you. Breaking it down here for three days. Wall to wall coverage here in Moscow north to set celebrating our 10th year covering VM World. Thanks for watching stay with us from or action after this short break.