(bright upbeat music) >> Welcome back to Detroit guys and girls. Lisa Martin here with John Furrier. We've been on the floor at KubeCon + CloudNativeCon North America for about two days now. We've been breaking news, we would have a great conversations, John. We love talking with CUBE alumni whose companies are just taking off. And we get to do that next again. >> Well, this next segment's awesome. We have former CUBE host, Brian Gracely, here who's an executive in this company. And then the entrepreneur who we're going to talk with. She was on theCUBE when it just started now they're extremely successful. It's going to be a great conversation. >> It is, Idit Levine is here, the founder and CEO of solo.io. And as John mentioned, Brian Gracely. You know Brian. He's the VP of Product Marketing and Product Strategy now at solo.io. Guys, welcome to theCUBE, great to have you here. >> Thanks for having us. >> Idit: Thank so much for having us. >> Talk about what's going on. This is a rocket ship that you're riding. I was looking at your webpage, you have some amazing customers. T-Mobile, BMW, Amex, for a marketing guy it must be like, this is just- >> Brian: Yeah, you can't beat it. >> Kid in a candy store. >> Brian: Can't beat it. >> You can't beat it. >> For giant companies like that, giant brands, global, to trust a company of our size it's trust, it's great engineering, it's trust, it's fantastic. >> Idit, talk about the fast trajectory of this company and how you've been able to garner trust with such mass organizations in such a short time period. >> Yes, I think that mainly is just being the best. Honestly, that's the best approach I can say. The team that we build, honestly, and this is a great example of one of them, right? And we're basically getting the best people in the industry. So that's helpful a lot. We are very, very active on the open source community. So basically it building it, anyway, and by doing this they see us everywhere. They see our success. You're starting with a few customers, they're extremely successful and then you're just creating this amazing partnership with them. So we have a very, very unique way we're working with them. >> So hard work, good code. >> Yes. >> Smart people, experience. >> That's all you need. >> It's simple, why doesn't everyone do it? >> It's really easy. (all laughing) >> All good, congratulations. It's been fun to watch you guys grow. Brian, great to see you kicking butt in this great company. I got to ask about the landscape because I love the ServiceMeshCon you guys had on a co-located event on day zero here as part of that program, pretty packed house. >> Brian: Yep. >> A lot of great feedback. This whole ServiceMesh and where it fits in. You got Kubernetes. What's the update? Because everything's kind of coming together- >> Brian: Right. >> It's like jello in the refrigerator it kind of comes together at the same time. Where are we? >> I think the easiest way to think about it is, and it kind of mirrors this event perfectly. So the last four or five years, all about Kubernetes, built Kubernetes. So every one of our customers are the ones who have said, look, for the last two or three years, we've been building Kubernetes, we've had a certain amount of success with it, they're building applications faster, they're deploying and then that success leads to new challenges, right? So we sort of call that first Kubernetes part sort of CloudNative 1.0, this and this show is really CloudNative 2.0. What happens after Kubernetes service mesh? Is that what happens after Kubernetes? And for us, Istio now being part of the CNCF, huge, standardized, people are excited about it. And then we think we are the best at doing Istio from a service mesh perspective. So it's kind of perfect, perfect equation. >> Well, I'll turn it on, listen to your great Cloud cast podcast, plug there for you. You always say what is it and what isn't it? >> Brian: Yeah. >> What is your product and what isn't it? >> Yeah, so our product is, from a purely product perspective it's service mesh and API gateway. We integrate them in a way that nobody else does. So we make it easier to deploy, easier to manage, easier to secure. I mean, those two things ultimately are, if it's an internal API or it's an external API, we secure it, we route it, we can observe it. So if anybody's, you're building modern applications, you need this stuff in order to be able to go to market, deploy at scale all those sort of things. >> Idit, talk about some of your customer conversations. What are the big barriers that they've had, or the challenges, that solo.io comes in and just wipes off the table? >> Yeah, so I think that a lot of them, as Brian described it, very, rarely they had a success with Kubernetes, maybe a few clusters, but then they basically started to on-ramp more application on those clusters. They need more cluster maybe they want multi-class, multi-cloud. And they mainly wanted to enable the team, right? This is why we all here, right? What we wanted to eventually is to take a piece of the infrastructure and delegate it to our customers which is basically the application team. So I think that that's where they started to see the problem because it's one thing to take some open source project and deploy it very little bit but the scale, it's all about the scale. How do you enable all those millions of developers basically working on your platform? How do you scale multi-cloud? What's going on if one of them is down, how do you fill over? So that's exactly the problem that they have >> Lisa: Which is critical for- >> As bad as COVID was as a global thing, it was an amazing enabler for us because so many companies had to say... If you're a retail company, your front door was closed, but you still wanted to do business. So you had to figure out, how do I do mobile? How do I be agile? If you were a company that was dealing with like used cars your number of hits were through the roof because regular cars weren't available. So we have all these examples of companies who literally overnight, COVID was their digital transformation enabler. >> Lisa: Yes. Yes. >> And the scale that they had to deal with, the agility they had to deal with, and we sort of fit perfectly in that. They re-looked at what's our infrastructure look like? What's our security look like? We just happened to be right place in the right time. >> And they had skillset issues- >> Skillsets. >> Yeah. >> And the remote work- >> Right, right. >> Combined with- >> Exactly. >> Modern upgrade gun-to-the-head, almost, kind of mentality. >> And we're really an interesting company. Most of the interactions we do with customers is through Slack, obviously it was remote. We would probably be a great Slack case study in terms of how to do business because our customers engage with us, with engineers all over the world, they look like one team. But we can get them up and running in a POC, in a demo, get them through their things really, really fast. It's almost like going to the public cloud, but at whatever complexity they want. >> John: Nice workflow. >> So a lot of momentum for you guys silver linings during COVID, which is awesome we do hear a lot of those stories of positive things, the acceleration of digital transformation, and how much, as consumers, we've all benefited from that. Do you have one example, Brian, as the VP of product marketing, of a customer that you really think in the last two years just is solo.io's value proposition on a platter? >> I'll give you one that I think everybody can understand. So most people, at least in the United States, you've heard of Chick-fil-A, retail, everybody likes the chicken. 2,600 stores in the US, they all shut down and their business model, it's good food but great personal customer experience. That customer experience went away literally overnight. So they went from barely anybody using the mobile application, and hence APIs in the backend, half their business now goes through that to the point where, A, they shifted their business, they shifted their customer experience, and they physically rebuilt 2,600 stores. They have two drive-throughs now that instead of one, because now they have an entire one dedicated to that mobile experience. So something like that happening overnight, you could never do the ROI for it, but it's changed who they are. >> Lisa: Absolutely transformative. >> So, things like that, that's an example I think everybody can kind of relate to. Stuff like that happened. >> Yeah. >> And I think that's also what's special is, honestly, you're probably using a product every day. You just don't know that, right? When you're swiping your credit card or when you are ordering food, or when you using your phone, honestly the amount of customer they were having, the space, it's like so, every industry- >> John: How many customers do you have? >> I think close to 200 right now. >> Brian: Yeah. >> Yeah. >> How many employees, can you gimme some stats? Funding, employees? What's the latest statistics? >> We recently found a year ago $135 million for a billion dollar valuation. >> Nice. >> So we are a unicorn. I think when you took it we were around like 50 ish people. Right now we probably around 180, and we are growing, we probably be 200 really, really quick. And I think that what's really, really special as I said the interaction that we're doing with our customers, we're basically extending their team. So for each customer is basically a Slack channel. And then there is a lot of people, we are totally global. So we have people in APAC, in Australia, New Zealand, in Singapore we have in AMEA, in UK and in Spain and Paris, and other places, and of course all over US. >> So your use case on how to run a startup, scale up, during the pandemic, complete clean sheet of paper. >> Idit: We had to. >> And what happens, you got Slack channels as your customer service collaboration slash productivity. What else did you guys do differently that you could point to that's, I would call, a modern technique for an entrepreneurial scale? >> So I think that there's a few things that we are doing different. So first of all, in Solo, honestly, there is a few things that differentiated from, in my opinion, most of the companies here. Number one is look, you see this, this is a lot, a lot of new technology and one of the things that the customer is nervous the most is choosing the wrong one because we saw what happened, right? I don't know the orchestration world, right? >> John: So choosing and also integrating multiple things at the same time. >> Idit: Exactly. >> It's hard. >> And this is, I think, where Solo is expeditious coming to place. So I mean we have one team that is dedicated like open source contribution and working with all the open source community and I think we're really good at picking the right product and basically we're usually right, which is great. So if you're looking at Kubernetes, we went there for the beginning. If you're looking at something like service mesh Istio, we were all envoy proxy and out of process. So I think that by choosing these things, and now Cilium is something that we're also focusing on. I think that by using the right technology, first of all you know that it's very expensive to migrate from one to the other if you get it wrong. So I think that's one thing that is always really good at. But then once we actually getting those portal we basically very good at going and leading those community. So we are basically bringing the customers to the community itself. So we are leading this by being in the TOC members, right? The Technical Oversight Committee. And we are leading by actually contributing a lot. So if the customer needs something immediately, we will patch it for him and walk upstream. So that's kind of like the second thing. And the third one is innovation. And that's really important to us. So we pushing the boundaries. Ambient, that we announced a month ago with Google- >> And STO, the book that's out. >> Yes, the Ambient, it's basically a modern STO which is the future of SDL. We worked on it with Google and their NDA and we were listed last month. This is exactly an example of us basically saying we can do it better. We learn from our customers, which is huge. And now we know that we can do better. So this is the third thing, and the last one is the partnership. I mean honestly we are the extension team of the customer. We are there on Slack if they need something. Honestly, there is a reason why our renewal rate is 98.9 and our net extension is 135%. I mean customers are very, very happy. >> You deploy it, you make it right. >> Idit: Exactly, exactly. >> The other thing we did, and again this was during COVID, we didn't want to be a shell-for company. We didn't want to drop stuff off and you didn't know what to do with it. We trained nearly 10,000 people. We have something called Solo Academy, which is free, online workshops, they run all the time, people can come and get hands on training. So we're building an army of people that are those specialists that have that skill set. So we don't have to walk into shops and go like, well okay, I hope six months from now you guys can figure this stuff out. They're like, they've been doing that. >> And if their friends sees their friend, sees their friend. >> The other thing, and I got to figure out as a marketing person how to do this, we have more than a few handfuls of people that they've got promoted, they got promoted, they got promoted. We keep seeing people who deploy our technologies, who, because of this stuff they're doing- >> John: That's a good sign. They're doing it at at scale, >> John: That promoter score. >> They keep getting promoted. >> Yeah, that's amazing. >> That's a powerful sort of side benefit. >> Absolutely, that's a great thing to have for marketing. Last question before we ran out of time. You and I, Idit, were talking before we went live, your sessions here are overflowing. What's your overall sentiment of KubeCon 2022 and what feedback have you gotten from all the customers bursting at the seam to come talk to you guys? >> I think first of all, there was the pre-event which we had and it was a lot of fun. We talked to a lot of customer, most of them is 500, global successful company. So I think that people definitely... I will say that much. We definitely have the market feed, people interested in this. Brian described very well what we see here which is people try to figure out the CloudNative 2.0. So that's number one. The second thing is that there is a consolidation, which I like, I mean STO becoming right now a CNCF project I think it's a huge, huge thing for all the community. I mean, we're talking about all the big tweak cloud, we partner with them. I mean I think this is a big sign of we agree which I think is extremely important in this community. >> Congratulations on all your success. >> Thank you so much. >> And where can customers go to get their hands on this, solo.io? >> Solo.io? Yeah, absolutely. >> Awesome guys, this has been great. Congratulations on the momentum. >> Thank you. >> The rocket ship that you're riding. We know you got to get to the airport we're going to let you go. But we appreciate your insights and your time so much, thank you. >> Thank you so much. >> Thanks guys, we appreciate it. >> A pleasure. >> Thanks. >> For our guests and John Furrier, This is Lisa Martin live in Detroit, had to think about that for a second, at KubeCon 2022 CloudNativeCon. We'll be right back with our final guests of the day and then the show wraps, so stick around. (gentle music)

>>And welcome to this cube conversation here in Palo Alto, California. I'm John furrier, host of the cube. We have a great guest coming in remotely from LA Christian Hernandez developer experienced lead at code fresh code fresh IO. Recently they were on our feature at a startup showcase series, season two episode one cloud data innovations, open source innovations, all good stuff, Christian. Thanks for coming on this cube conversation. >>Thank you. Thank you, John. Thank you for having me on, >>You know, I'm I was really impressed with code fresh. My met with the founders on here on the cube because GI ops AI, everything's something ops devs dev sec ops. You've got AI ops. You've got now GI ops, essentially operationalizing the software future is here and software's eating the world is, was written many years ago, but it's open source is now all. So all things software's open source and that's kind of a done deal. It's only getting better and better. Mainstream companies are contributing. You guys are on this wave of, of this open source tsunami and you got cloud scale. Automation's right there, machine learning, all this stuff is now the next gen of, of, of code, right? So you, your code fresh and your title is developer experience lead. What does that mean right now? What does it mean to be a developer experience lead? Like you make sure people having a good experience. Are you developing you figuring out the product? What does that mean? >>Yeah. That's and it's also part of the, the whole Debre explosion that's happening right now. I believe it's, you know, everyone's always asking, well, what, you know, what is developer advocate? What does that mean developer experience? What does that mean? So, so you, you kind of hit the nail on the head a little bit up there in, in the beginning, is that the, the experience of the developer when using a particular platform, right? Especially the code flash platform. That is my responsibility there at code fresh to enable, to enable end users, to enable partners, to enable, you know, anyone that wants to use the code fresh platform for their C I C D and get ops square flows. So that's, that's really my, my corner of the world is to make sure their experience is great. So that's, it's really what, what I'm here to do >>At food fresh. You know, one of the things I can say of my career, you've been kind of become a historian over time. When I was a developer back in the old days, it was simply you compiled stuff, you did QA on it. You packaged it out. You wanted out the door and you know, that was a workflow right now with the cloud. I was talking with your founders, you got new abstraction layers. Cloud has changed again again, open source. So newer things are coming, right? Like, like, like Kubernetes for instance is a great example that came out of the open source kind of the innovations. But that, and Hadoop, we were mentioning before he came on camera from a storage standpoint, kind of didn't make it because it was just too hard. Right. And it made the developer's job harder. And then it made the developer's requirements to be specialized. >>So you had kind of two problems. You had hard to use a lot of friction and then it required certain expertise when the developers just want to code. Right. So, so you have now the motion of, with GI ops, you guys are in the middle of kinda this idea of frictionless based software delivery with the cloud. So what's different now, can you talk about that specific point because no one wants to be, do hard work and have to redo things. Yeah. Shift left and all that good stuff. What's hard now, what do you guys solve? What's the, what's the friction that you're taking out what's to become frictionless. >>Yeah. Yeah. And you, you, you mentioned a very interesting point about how, you know, things that are coming out almost makes it seem harder nowadays to develop an application. You used to have it to where, you know, kind of a, sort of a waterfall sort of workflow where, you know, you develop your code, you know, you compile it. Right. You know, I guess back in the day, Java was king. I think Java still is, has a, is a large footprint out there where you would just compile it, deploy it. If it works, it works. Alright cool. And you have it and you kind of just move it along in its process. Whereas I think the, the whole idea of, I think Netflix came out with like the, the fail often fail fast release often, you know, the whole Atlassian C I C D thing, agile thing came into play. >>Where now it's, it's a little bit more complex to get your code out there delivered to get your code from one environment to the other environment, especially with the, the Avan of Kubernetes and cloud native architecture, where you can deploy and have this imutable infrastructure where you can just deploy and automate so quickly. So often that there needs to be some sort of new process now into place where to have a new process, like GI ops to where it'll, it it's frictionless, meaning that it's, it, it makes it that process a little easier makes that little, that comp that complex process of deploying onto like a cloud native architecture easier. So that way, as you said before, returning the developers to back to what they care about, mot, the most is just code. I just want to code. >>Yeah. You know, the other thing, cool thing, Christian, I wanna bring up and we'll get into some of the specifics around Argo specifically CD is that the community is responding as a kind of, it takes a village kind of mindset. People are getting into this just saying, Hey, if we can get our act together around some de facto workflows and de facto capabilities, everyone wins. It's a rising tide, floats all boats, kind of concept. CNCF certainly has been a big part of that. Even seen some of the big hyper scales getting behind it. But you guys are part of the founding members of the open get ups working group, Amazon Azure, GitHub, red hat Weaveworks and then a ton of contributors. Okay. So this is kind of cool. This means that there's like people behind this thing. Look, we gotta get here faster. What happened at co con this year? You guys had some news around Argo and you had some news around the hosted solution. Can you take a minute to explain two things, one the open community vibe, and then two, what you guys announced at Coon in Spain. >>Yeah. Yeah. So as far as open get ups, that was, you know, as you said before, code fresh was part of that, that founding committee. Right. Of, of group of people trying to figure out, define what get ups is. Right. We're trying to bring it beyond the, you know, the, the hype word, right beyond just like a marketing term to where we actually define what it actually is, because it is actually something that's out there that people are doing. Right. A lot of people, you know, remember that the, the Chick-fil-A story where it's like, they, they are completely doing, you know, this get ops thing, we're just now wanting, putting definition around it. So that was just amazing to see out at there in, in Cuban. And, but like you said, in QAN, we, you know, we're, we're, we're taking some of that, that acceleration that we see in the community to, and we, we announce our, our hosted get ops offering. >>Right. So hosted get ops is something that our customers have been asking for for a while. Many times when, you know, someone wants to use something like Argo CD, the, in, they install it on their cluster, they get up and running. And, but with, with all that comes like the feed and care of that platform, and, you know, not only just keeping the lights on, but also management security, you know, general maintenance, you know, all the things that, that come along with managing a system. And on top of that comes like the scale aspect of it. Right. And so with scale, so a lot of people go with like a hub and spoke others, go with like a fleet design in, in either case, right. There's, there's a challenge for the feet and care of it. Right. And so with code fresh coast of get ups, we take that management headache away. >>Right? So we, we take the, the, the management of, of Argo CD, the management of, of all of that, and kind of just offer Argo CD as a surface, right. Which offers, you know, allows users to, you know, let us take care of all the, of the get offs, runtime. And so they can concentrate on, you know, their application deployments. Right. And you also get things like Dora metrics, right. Integrated with the platform, you have the ability to integrate multiple CI providers, you know, like get hub actions or whatever, existing Jenkins pipelines. And really that, that code fresh platform becomes like your get ops platform becomes like, you know, your, your central view of the world of, of your, you know, get ups processes. >>Yeah. I mean, that whole single source of truth concept is really kind of needed. I gotta ask you though, with the popularity of the Argo CD on get ups internally, right. That's been clear, right. Kubernetes, the way that's going, it's accelerating fast. People want simple it's scaling, you got automation built in all that good stuff. What was the driver behind the hosted get up solution? Was it customer needs? Was it efficiency all the above? What was specifically and, and why would someone want to have the hosted versus say internal? >>Yeah. So it's, it was really driven by, you know, customer need been something that the customers have been asking for. And it's also been something that, you know, you, you, you have a process of developing an application to, you know, you know, a fleet of clusters in a traditional, you know, I keep saying traditional, get outs practice as if get outs are so old. And, you know, in, you know, when, when, when people first start out, they'll start, you know, installing Argo city on all these clusters and trying to manage that at scale it's, it's, it, it seemed like there was, you know, it it'd be nice if we can just like, be able to consume this as a service. So we don't have to like, worry about, you know, you know, best practices. We don't have to worry about security. We don't just, all of that is taken care of and managed by us at code fresh. So this is like something that, you know, has been asked for and, and something that, you know, we believe will accelerate, you know, developers into actually developing their, their applications. They don't have to worry about managing >>The platform. So just getting this right. Hosted, managed service by you guys on this one, >>Correct? Yes. >>Okay. Got it. All right. So let me, let me get in the Argo real quick, just to kind of just level set for the folks that are, are leaning into this and then kicking the tires. Where are we with Argo? What, why was it so popular? What did it do specifically? Did it just make it easier for developers to manage and monitor Kubernetes, keep 'em updated? What was the specific value behind Argo? Where, where, where did it come from and why is it so popular? >>Yeah, so Argo the Argo project, which is made up of, of a few tools, usually when people say Argo, they meet, they they're talking about Argo CD, but there's also Argo workflows, Argo events, Argo notifications. And, and like I said before, CD with that, and that is something that was developed internally at Intuit. Right? So for those of who don't know, Intuit is the company behind turbo tax. So for those, those of us in the us, we, we know, you know, we know that season all too well, the tax season. And so that was a tool that was developed internally. >>And by the way, Intuit we've done many years. They're very huge cloud adopters. They've been on that train from the day one. They've been, they've been driving a lot of cloud scale too. Sorry >>To interrupt. Yeah. And, and, and yeah, no, and, and, and also, you know, they, they were always open source first, right. So they've always had, you know, they developed something internally. They always had the, the intention of opensourcing it. And so it was really a tool that was born internally, and it was a tool that helped them, you know, get stuff done with Kubernetes. And that's kind of like the tagline they use for, for the Argo project is you need to get stuff done. They wanted their developers to focus less on deploying the application and more right. More than on writing the application itself. And so the, and so the Argo project is a suite of tools essentially that helps deploy onto Kubernetes, you know, using get ups as that, you know, that cornerstone in design, right in the design philosophy, it's so popular because of the ease of use and developer friendliness aspect of it. It's, it's, it's, it's meant to be simple right. In and simple in a, in a good sense of getting up and running, which attracted, you know, developers from, you know, all around the world. You know, other companies like red hat got into it as well. BlackRock also is, is a, is a big contributor, thousands of other independent contributors as well to the Argo project. >>Yeah. Christian, if you bring up a good point and I'm gonna go on a little tangent here, but I wanna get your reaction to something that Dave ante and I, and our cube team has been kind of riffing on lately. You mentioned, you know, Netflix earlier, you mentioned Intuit. There's a kind of a story that's been developing and, and with traction and momentum and trajectory over the past, say 10 years, the companies that went on the cloud, like Netflix into it, snowflake, snowflake, not so much now, but in terms of open source, they're all contributing lift. They're all contributing back to open source, but they're not cloud providers. Right. So you're seeing that kind of first generation, I's a massive contribution to open source. So open source been around for a while, remember the early days, and we'd all participate on projects, but now you have real companies building IP going open source first because they're on a hyperscale cloud, but they're not the cloud themselves. They took advantage of that. So there's kind of this cycle of flywheel of cloud to open source, not from the vendors themselves like Amazon, which services or Azure, but the people who rode their CapEx and built on that scale, feeding into the open source. And then coming back, this is kind of an interesting dynamic. What's your reaction to that? Do you see that? Yeah. Super cloud kind of vibe there. >>Yeah. Yeah. Well, and, and also it, it, I think it's, it's a, it's indicative that, you know, open source is not only, you know, a way to develop, you know, applications, a way to engineer, you know, your project, but also kind of like a strategic advantage in, in, in such a way. Right. You know, you, you see, you see companies like, like, like even like Microsoft has been going into, you know, open source, right. They they've been going to open source first. They made a, a huge pivot to, you know, using open source as, you know, like, like a, like a strategic direction for, for the company. And I think that goes back to, you know, a little bit for my roots, you know, I, I, I always, I always talk about, you know, I always talk about red hat, right. I always talk about, you know, I was, I was, I was in red hat previously and, you know, you know, red hat being, you know, the first billion dollar open source company. >>Right. I, we always joke is like, well, you know, internally, like we know you were a billion dollar company that sold free software. How, you know, how, how does that happen? But it's, it's, it's really, you know, built into the, built into being able to tap into those expert resources. Yeah. You know, people love using software. People love the software they love using, and they wanna improve it. Companies are now just getting out of their way. Yeah. You know, companies now, essentially, it's just like, let's just get out of the way. Let's let people work on, you know, what they wanna work on. They love the software. They wanna improve it. Let's let them, >>It's interesting. A lot of people love the clouds have all this power. If you think about what we are just riffing on and what you just said, the economics and the organic self-governing has always been the open source way where commercial value is enabled. If you play ball, right. Like, oh, red hat, for instance. And now you're seeing the community kind of be that arbiter of the cloud. So, Hey, if everyone can create value on say AWS or Azure, bring it to open source, everyone benefits across all clouds hope eventually. So the choice aspect comes in. So this community angle is huge. And I think it's changing a lot for the better. And I think this is where we're seeing a lot of that growth. And you guys have been the middle level with the Argo project and get ups specifically in that, in that sector. How have you seen that growth? What some dynamics have you seen power dynamics, organic? Is it governed well, whats some of the, the successes, what are some of the challenges? Can you share your thoughts on the community's growth around get ops and Argo project? >>Yeah, yeah. Yeah. So I've been, you know, part of some of these communities, right? Like the, the open, get, get ops community, the Argos community pretty much from the beginning and, and seeing it developed from an idea to, you know, having all these contributors, having, you know, the, the, the buzzword come out of it, you know, the get ups and it be that being the, you know, having it, you know, all over the, you know, social media, all over LinkedIn, all over all, all these, all these different channels, you know, I I've seen things like get ops con, right. So, you know, being part of the, get ops open, get ops community, you know, one of the things we did was we did get ops con it started as a meetup, you know, couple years ago. And now, you know, it was a, you know, we had an actual event at Cuan in Los Angeles. >>You know, we had like, you know, about 50 people there, but then, you know, Cuan in Valencia this past Cuan we had over 200 people, it was a second largest co-located events in, at Cuan. So that just, just seeing that community and, you know, from a personal standpoint, you know, be being part of that, that the, the community being the, the event chair, right. Yeah. Being, being one of the co-chairs was a, was a moment of pride for me being able to stand up there and just seeing a sea of people was like, wow, we just started with a handful of people at a meetup. And now, you know, we're actually having conferences and, and, and speaking of conference, like the Argo community as well, we put in, you know, we put on a virtual only event on Argo con last year. We're gonna do it in person today. You know, this year. >>Do you have a date on that? Do you have a date on that Argo con 22? >>Two? Yeah, yeah, yeah. Argo con September 19th, 2022. So, you know, mark your calendars, it it's, you know, it's a multi-day event, you know, it's, it's part of something else that I've seen in the community where, you know, first we're talk talking about these meetups. Now we're doing multi-day events. We're, you know, in talks of the open, get ups, you know, get ups can also make that a multi-day event. There's just so many talks in so many people that want to be involved in network that, you know, we're saying, well, we're gonna need more days because there's just so many people coming to these events, you know, in, in, you know, seeing these communities grow, not just from like the engineering standpoint, but also from the end user standpoint, but also from the people that are actually doing these things. And, you know, seeing some of these use cases, seeing some of the success, seeing some of the failures, right? Like people love listening to those talks about postmortems, I think are part of my favorite talks as well. So seeing that community grow is, is, you know, on a personal level, it's, it's a point >>It's like CSI for software developers. You want to curious about >>Exactly >>What happened. You know, you know, it's interesting, you mentioned about the, the multiple events at Coon. You know, the vibe that's going on is a very festival vibe, right? You have organic groups coming together. I remember when they had just started doing the day zero programs. Now you have like, almost like multiple stages of content at these events. It feels like, like a Coachella vibe or some sort of like festival vibe, like a lot of things going on and you, and if you pick your kind of area, but you can move around, I find that the kind of the format de Azure I think is going well these days. What do you think about that? >>Yeah, yeah. No, for sure. It's and, and, and I love that that analogy of Coachella, it does feel like, you know, it's, there's something for everyone and you can find what you like, and you'll find a little, you know, a little group, right. A little click of, of, of people that's probably the wrong term to use, but you know, you, you find, you know, you, you know, like-minded people and, you know, passionate about the same thing, right? Like the security guys, they, you know, you see them all clump together, right? Like you see like the, the developer C I CD get ops guys, we all kind of clump together and start talking, you know, about everything that we're doing. And it's, that's, that's, I think that's really something special that coupon, you know, some, you know, it's gotten so big that it's almost impossible to fit everything in a, in a week, because unless there's just so much to do. And there's so much that that interests, you know, someone, but it's >>A code, a code party is what we call it. It's a code party. Yeah. >>It's, it's a code party for sure. For >>Sure. Nerd nerd Fest on, on steroids. Hey, I gotta get, I wanna wrap this up and give you the final word, Christian. Thanks for coming on. Great insight, great conversation. There's a huge, you guys are in the middle of a hot area, obviously large scale data growth. Kubernetes is scaling beautifully and making it easier at managed services. What people want machine learning's kicking in and, and you get automation building in all favoring, the developer and C I CD pipeline and all that good stuff. People want to learn more. Can you take a minute to put the plug in for code fresh on the certification? How do I get involved? Where are you? Is there levels if I want to jump in and get trained and get fluent on code fresh, can you share commentary and, and, and what the status is? >>Yeah, yeah, for sure. So code fresh is offering a free certification, right? For get ups or Argo CD and get ops. The first of it's kind for Argo CD, first of it's kind for get ops is you can actually go get certified with Argo CD and get ops. You know, we there level one is out right now. You can go take that code, fresh.io/certification. It's out there, sign up, you know, you, you don't, you don't need to pay anything, right. It's, it's something it's a, of a free course. You could take level two is coming soon. Right? So level two is coming soon in the next few months, I believe I don't wanna quote a specific day, but soon because I, but soon I, it it's soon, soon as in, as in months. Right? So, you know, we're, we're counting that down where you can not only level one cert level certification, but a level, two more advanced certification for those who have been using Argo for a while, they can still, you know, take that and be, you know, be able to get, you know, another level of certification for that. So also, you know, Argo con will be there. We're, we're part of the programming committee for Argo con, right? This is a community driven event, but, you know, code fresh is a proud diamond sponsor. So we'll be there. >>Where's it located up to us except for eptember 19th multiday or one day >>It's a, it's a multi-day event. So Argo con from 19, 19 20 and 21 in a mountain view. So it'll be in mountain view in the bay area. So for those of you who are local, you can just drive in. Great. >>I'm write that down. I'll plug it. I'll put in the show notes. >>Awesome. Awesome. Yeah. And you will be there so you can talk to me, you can talk to anyone else at code, fresh talking about Argo CD, you know, find, find out more about hosted, get ups code, fresh.io. You know, you can find us in the Argo project, open, get ups community, you know, we're, we're, we're deep in the community for both Argo and get ups. So, you know, you can find us there as well. >>Well, let's do a follow up in when you're in town, so's only a couple months away and getting through the summer, it's already, I can't believe events are back. So it's really great to see face to face in the community. And there was responding. I mean, co con in October, I think that was kind of on the, that was a tough call and then get to see your own in Spain. I couldn't make it. Unfortunately, I had got COVID came down with it, but our team was there. Open sources, booming continues to go. The next level, new power dynamics are developing in a great way. Christian. Thanks for coming on, sharing your insights as the developer experience lead at code fresh. Thanks so much. >>Thank you, John. I appreciate it. >>Okay. This is a cube conversation. I'm John feer, host of the cube. Thanks for watching.

>>Oh, welcome back to the cubes coverage of coop con cloud native con 2021. I'm John is the Cuba, David Nicholson, our cloud host analyst, and it's exciting to be back in person in event. So we're back. It's been two years with the cube con and Linux foundation. So scrape, it was a hybrid event and we have a great guest here, Cuban London, Nick Dirk, and CT field CTO of harness and harness.io. The URL love the.io. Good to see you. >>Thank you guys for having me on. I genuinely appreciate >>It. Thanks for coming on. You were a part of our AWS startup showcase, which you guys were featured as a fast growing mature company, uh, as cloud scales, you guys have been doing extremely well. So congratulations. But now we're in reality now, right? So, okay. Cloud native has kind of like, okay, we don't have to sell it anymore. People buying into it. Um, and now operationalizing it with cloud operations, which means you're running stuff, applications and infrastructure is code and it costs money. Yeah. Martine Casada at Andreessen Horowitz. Oh, repatriated from the cloud. So there's a lot of, there's some cost conversations starting to happen. This is what you guys are in the middle of. >>Yeah, absolutely. What's interesting is when you think about it today, we want to shift left. When you want to empower all the engineers, we want to empower people. We're not giving them the data they need, right. They get a call from the CFO 30 days later, as opposed to actually being able to look at what change I did and how it actually affected. And this is what we're bringing in. Allowing people to have is now really empowering. So throughout the whole software delivery life cycle from CGI continuous integration, continuous delivery feature flagging, and even bringing cost modeling and in cloud cost management. And even then being able to shut down, shut down the services that you're not using, how much of that is waste. We talk about it. Every single cloud conference it's how much is waste. And so being able to actually turn those on, use those accordingly and then take advantage of even the cheapest instances when you should. That's really what >>It's so funny. People almost trip over dollars to pick up pennies in the cloud business because they're so focused on innovation that they think, okay, we've got to just innovate at all costs, but at some point you can make it productive for the developers in process in the pipeline to actually manage that. >>That's exactly it. I mean, if you think about it to me in order to breach state continuous delivery, we have to automate everything. Right. But that doesn't mean stop at just delivering, you know, to production. That means to customer, which means we've got to make them happy, but then ultimately all of those resources in dev and QA and staging and UAT, we've sticker those as well. And if we're not being mindful of it, the costs are astronomical, right. And we've seen it time and time again with every company you see, you've seen every article about how they've blown through all their budgets. So bring it to the people that can affect change. That's really the difference, making it visible, looking at it. In-depth not just at the cloud level and all the spend there, but also even at the, uh, thinking about it, the Kubernetes level down to the containers, the pods and understanding where are the resources even inside of the clusters and bringing that as an aggregate, not just for visibility and, and giving recommendations, but now more importantly, because part of a pipeline start taking action. That's where it's interesting. It's not just about being able to see it and understand it and hope, right? Hope is not a strategy acting upon it is what makes it valuable. And that's part of the automate everything. >>Yeah. We'll let that at the Dawn of the age of DevOps, uh, there was a huge incentive for a developer just to get their job done, to seize control of infrastructure, the idea of infrastructure as code, you know, and it's, it's, you know, w when it was being born, it's a fantastic, I've always wondered though, you know, be careful what you wish for. Do you really want all of that responsibility? So we've got responsibility from a compliance and security perspective and of course cost. So, so where do we, where do we go from here, I guess is the question. Yeah. So >>When we look at building this all together, I think when we think about software delivery, everybody wants to go fast. We start with velocity, right? Everybody says, that's where I want to go. And to your point with governance compliance, the next roadblock to hit is weight. In order to go fast, I have to do it appropriately. I've got governing bodies that tell me how this has to work. And that becomes a challenge. >>It slows it down too. It doesn't, I mean, basically people are getting pissed off, right? This is, this general sentiment is, is that developers are moving fast with their code. And then they have to stop. Compliance has to give the green light sometimes days, correct? Uh, it used to be weeks now. It's days, it's still unacceptable. So there's like this always been that tension to the security groups or say it, or finance was like slow down and they actually want to go faster. So that has to be policy-based something. Yep. This is the future. What is your take on that? >>Take on, this is pretty simple. When everybody talks about people, process and technology, it's kind of bogus, right? It's all about confidence. If you're confident that your developers can deploy appropriately and they're not going to do something wrong, you'll let them to play all the time. Well, that requires process. But if you have tooling that literally guarantees your governance, make sure that at no point in time, can any of your developers actually do something wrong. Now you have, >>That's the key. That's the key. That's the key because you're giving them a policy-based guardrails to execute in their programs >>And that's it. So now you can free up all those pieces. So all those bottlenecks, all those waiting all those time, and this is how all of our customers, they move from, you know, change advisory boards that approve deployments. >>Can you give us some, give us some, give us some, uh, customer anecdotal examples of this inaction and kind of the love letters you get, or, or the customer you take us through a use case of how it all. >>So this is one of my favorites. So NCR national cash register. If you slide a credit card at like a Chick-fil-A or a Safeway, right? Um, traditional technology. But what was interesting is they went from doing PCI audit, which would take seven days to go to a PCI audit right now with harness, because, >>And by the way, when you and the seventh, six day, the things that you did on day one change. >>Exactly, exactly. And so now, because of using harness and everything's audited, and all the changes are, are controlled to make sure that developers again, can only do what they're allowed. They only get to broadcast two per production. If they've met all their security requirements, all their compliance, permits, all their quality checks. Now, because of that, they literally gave a re read only view of harness to their auditor. And in three hours it was over. And it's because now we're that evidence file from code commit through to production. Yeah. It's there for point of sale compliant. >>So what is the benefits to them? What's the result saves them time, saves the money. What's the good, the free up more times. I'll see the chops it down. That's the key. >>Yeah. It's actually something we didn't build in like our ROI calculators, which was, we talked to their engineers and we gave them their nights and their weekends back, which I thought was amazing. But Thursday night, when we're doing that deploy, they don't have to be up. Harness is actually managing and understanding, using machine learning to understand what normal looks like. So they don't have to, they don't have to sit and look at the knock or sit in the war room and eat the free pizza. Yeah. Right. And then when those things break, same concept rates aren't as good. So >>I got to ask you, I got you here. You know, as the software development delivery lifecycle is radically being overhauled right now, which people generally agree that that's the case, the old models are, are different. How do you see your vision around AI and automation playing into this? Because you could say, okay, we're going to have different kinds of coding styles. This batch has got an AI block here. It's very Lego block. Like yep. Okay. Services and higher level services in the cloud. What's your reaction to how this impacts automation and >>Sure. So throughout our entire platform, we've designed our AI to take care of the worst parts of anyone's job as Guinea dev ops person. If they love babysitting deployments, they don't harness handles that for them, ask your engineers that they love sitting there waiting for their tests to run. Every time they build, they go get coffee, right. Because we're waiting for all of our tests to run. Y yeah. Right. The reality >>Is sometimes they have to wait days and >>That's it. But like, if I change the gas cap on, uh, on your car, would you expect me to check every light switch and every electronic piece? No. Well, why do we do that with code? And so our AI, our ML is designed to remove all the things that people hate. It's not to remove people's jobs. It's actually to make their jobs much better. >>How do you guys feed the data? What's the training algorithm for that? How does that work? Yeah, >>Actually, it's interesting. A lot of people think it's going to take a ton of time to figure this out. The good news is we start seeing this on the second deployment. On the second bill, we have to have a baseline of what good looks like, and that's where it starts. And it goes from there. And by the way, this isn't a lot of people say AI, and this AML, I teach a class on this because ML is not standard deviation. It's not some checks. So we use a massive amount of machine learning, but we have neural networks to think about things like engineers do. Like if we looked at a log and I saw the same log with two different user IDs, you and I would know, well, it's the same thing. It's just different users, but machine learning models. Don't so we've got to build neural networks to actually think like humans. So that, >>So that's the whole expectation maximization kind of concept of people talk about, >>Well, and that's it because at the end of the day, we're like I said, I'm not trying to take people's jobs. I want to meet. >>Yeah. You want to do the crap work out of the way. And I had to do other redundant, heavy lifting that they have to do every single time we use the cloud way. We've >>Built mechanical muscle in, in the early 19 hundreds. Right. And it made everyone's jobs easier, allowed them to do more with their time. That's exactly what we're doing here. >>I mean, we've seen the big old guys in the industry trying to evolve. You got the hot startups coming out. So you got, you know, adapt or die as classic thing. We've been saying for many years, David on the cube, you know that. So it's like, this is a moment of truth. We're going to see who comes out the other side. How do you, Nick, what would you be your, your kind of guess of when that other side is, when are we gonna know the winners and the losers truly in the sense of where we are now? >>So I think what I've found is that in this space specifically, there's a constant shift and this is something with software. And the problem is, is that we see them come in ebbs and flows, right. And very few times are there businesses that actually carry the model? And what you find is that when they focus on one specific problem, it solves it. Now, if I was working on VMs a few years ago, great, but now we're, we're here at coop con, right? And that's because it's eaten, uh, that side of the world. And so I think it's the companies that can actually grow the test of time and continue to expand to where the problems are. Right. And that's one of the things that I traditionally think about harness and we've done it. We cover our customers where they were, I think the old mainframes, if you had to, where they were, where they are at their traditional, their VM. >>I mean, if you think about it, Nick, it's one of those things where it's like, that's such a common sense way to look at it evolves with a problem. So I ride the right with tech ways. But if you think about the high order bit, here is just applications. We ended the day. Companies have applications that they want to write modern. The applications of their business is going to be codified so that you just work backwards from there. Then you say, okay, what is the infrastructure as code working for me? That's an ethos of dev ops. And that's where we're at. So that's why I think that the cloud need is kind of one already, but we still have the edge devices, more complexity. This is a huge next level conversation at one point is that we just put a hard and top on the complexity. When is that coming? Because the developers are clear. They want to go fast. They want to go shift left and have all that data, get the right analytics, the telemetry and the AI. But it's too complicated still. That is a big problem. >>It's too complicated. You ask for a full-stack developer to also know infrastructure, to also know edge computing. Like it's impossible, right? And this is where tooling helps, right? Because if you can actually parameterize that and make it to the engineers and have to care, they can do what they're best at. Hey, I'm great at turning code in artifact, let them do that and have tooling take care of the rest. This is where our goal is. Again, allow people >>We'll do what they love. And this is kind of the new roles that are changing. What SRE has done. Everyone talks about the SRE and some states just as he had dev ops guy, but it's not just that there's also, uh, different roles emerging. It's, it's an architectural game. At this point, we would say, >>I'd say a hundred percent. And this is where the decisions that you make on are architecturally. If you don't know how to then roll them out, this is what we've seen. Time and time again, you go to these large companies, I've got these great architectures on planning four years later, we haven't reached it because to that point process, >>The process killed them four >>Different new tools throughout the process. Well, yeah. >>So when do we hit peak Kubernetes peak >>Kubernetes? I think we have a bit to go in and I'm excited about the networking space and really what we're doing there and, and bringing that holistic portion of the network, like when Istio was originally released, I thought that was one of the most amazing things, uh, to truly come to it. And I think there's a vast space in networking. Um, and, and so I think in the next few years, we're going to see this, you know, turn into that a hundred percent utilized across the board. This will be that where everyone's workloads continue to exist. Um, somewhat like VMs we're in >>And, and, and no, no fear of developers as code in the very near future. You're talking about automating the mundane. Correct. Uh, there have been stories recently about the three-day workweek, you know, as a, as a fan of, um, utopian science fiction, myself, as opposed to dystopian. Absolutely. I think that, you know, technology does have the opportunity to lift all boats and, uh, and it's, it's not nothing to be afraid of. You know, the fact that I put my dishes in the dishwasher and they run by themselves for three hours. It's a good thing. It's a great thing. >>I don't need to deal with that. Yeah, I agree. No, I think that's, and that's what I said in the beginning. Right. That's really where we can start empowering people. So allow them to do what they're good at and do what they're best at. And if you look at why do people quit? We don't have to go so hard to find. Yeah. Why? Because they're secondary to babysit and implement and they're told everywhere they go, they're not going to have to >>That's the line. And that's all right. We got a break, but it's great insight to have you on the Q one final question for you. Um, I got to ask about the whole data as code something that I've been riffing on for a bunch of years now. And as infrastructures could we get that, but data is now the resource everyone needs, and everyone's trying to, okay, I have the control plane for this and that, but ultimately data cannot be siloed. This is a critical architectural element. How does that get resolved in the land of the competitive advantage and lock in and whatnot? What's your take on that? >>So data's an interesting one because it has, it has gravity and this is the problem. And as we move, as I think you guys know, as you move to the edge as remove, move it places there's insights to be taken at the edge there's insights to be taken as it moves through. And I think what you'll see honestly, going forward is you'll see compute done differently to your point. It needs to be aggregated. It needs to be able to be used together, but I think you'll see people computing it on its way through it. So now even in transport, you'll start seeing insights gained in real time before you can have the larger insights. And I see that happening more and more. Um, and I think ultimately we just want to empower that >>Nick, great to have you on CTO of field CTO of harness and harness.io is a URL. Check it out. Thanks for the insight. Thank you so much. Great comments. Appreciate it. Natural cube analysts right here, Nick, of course, we've got our, our analysts right here, David Nicholson. You're good on your own. I'm John for a, you know, we have the host. Thanks for watching. Stay with two more days of coverage. We'll be back after this short break.

>>Well, good day. And thank you for joining us here on the cube, John Walls here, uh, bringing you to this conversation as part of the AWS startup showcase. And we're joined by Justin bough, who is the SVP of product for amplitude and Justin. Good to see you today. How are you? >>I'm doing great. Thank you for having me, John. >>No pleasure. Looking forward to it. Um, you know, personalization that everybody's talking about these days and then how do we better personalize our, our digital presence, our digital products, um, you know, how do we get much more acutely aware of the end user at the end of the day and grow? I know that's what Amplitude's all about. So maybe if you just give us a 30,000 foot, um, perspective on that, about your thoughts about personalization today and how amplitude tries to affect >>For sure. Yeah. So I think first off personalization matters because it actually works. I think we live in a world where, as you know, we're drowning in content and distraction, uh, and it's been proven that customers respond better to digital experiences that are more personalized, that are more relevant for them. And frankly just save them time. Um, and the nice thing about this is not only the customers benefit, but companies do too. Uh, we actually see that a big impact on a company's bottom line, if they're able to, uh, deliver a more relevant customer experience to them because that leads to better engagement, better return, higher loyalty and lifetime value, uh, for those customers. >>So, um, well, let's, let's just go right to an example then, uh, I know you worked with a lot of different people, um, but there's anybody in particular that stands out, um, maybe give us an idea of a case study here about what practices you put into place, the kind of evaluations that you do, and ultimately the service that you're providing that allows them to increase sales and, and get a little more stickiness with them. >>Yeah, that's great. That's great. So I think one, uh, company customer of ours we're working with right now on this is actually Chick-fil-A. Uh, so people probably familiar with Chick-fil-A. Their mission is to be the most customer caring company in the world, uh, which I love in personalization is critical to that strategy because it helps them create a more relevant and seamless experience for their customers. Um, and the experience itself, and the app is actually pretty simple, which is the magic of personalization. So you open the Chick-fil-A app, uh, you see a list of menu items and those items are relevant to you based on your previous behavior. Um, after you order your entree, you're then offered a list of personalized sides. And then after that Alyssa personalized drinks, um, and the great thing is that as new items, uh, get introduced to the menu by Chick-fil-A you see the ones that are most relevant to you based on predicted affinity and all of the machine learning that we're doing in the background. And so really now Chick-fil-A is actually they're able to deliver a customized menu for everyone that automatically updates based on your behavior and your preferences. Um, and I think the real beauty of this is that they're able to configure all of this by a marketer through a simple UI. This did not require an army of data scientists or engineers. Uh, they're able to use the amplitude platform, uh, to build out this entire experience for their customers. >>Right. Cause I mean, it seems like there'd be an enormous amount of analytics that you have to apply here, right. Um, because you got all this structured and unstructured data, uh, you know, it's, it's all over the place, right. And a lot of times people don't even know what they have on hand. Um, and so you gotta, you gotta help them sift through all this. Right. So let's talk about that process a little bit for somebody who's watching and thinking about, well, that's all sounds well and good, but, but how do you kind of automate this? How do you make it so that we don't have to invest a lot in a team dedicated solely to, you know, sipping through our data and making it valuable for us? >>Yeah. I mean, I think that's the beauty of, uh, of amplitude actually offering this in that that's actually our original first product product analytics. That's what we've done. Um, so we've actually made an out of the box system that can read from all your different data sources. Um, so whether those be your product sources, marketing channels, data that sits in your data warehouse, um, but it's not just piping that data. Uh, we then combine that into a unique identity, uh, profile for that customer, um, across all those different touch points, um, and also have out of the box data governance, um, so that you can make sure you maintain, uh, the quality of that data profile, uh, over time. And then that gets fed into, um, our, what we call our behavioral graph. It's our database, uh, that's actually built to both understand and predict future behavior. And so all of this happens effectively out of the box for our customer. They don't need to do any of this, uh, themselves. Uh, we're managing all this for them. And then what they experience is, uh, an analytics application. So they can analyze that user behavior understand kind of what the drivers of different things like engage in retention are, and then use that to actually personalize the product experience. >>And, and you mentioned machine learning, um, talk about that aspect of this. I mean, how much more capability you have now because of what I know can deliver and, and, um, in some ways it adds some complexity, um, but also obviously it delivers exponentially, I would think in benefit at the end of the day. >>Yeah, for sure. I mean, it's just not possible to do one to one personalization without machine learning. I think that's actually, when we talk about the benefits and the advantages of personalization, it's probably even worth taking a step back. Like there's a lot of different types of personalization. Um, I think when you want to do behavioral personalization where you truly getting to one-to-one experiences, you have to use machine learning. Now you compare that to maybe like demographic personalization, which is actually, I think when most companies talk about when they're doing personalization, they're actually doing demographic personalization. That's like, are you a male or female? Um, what's your, you live in a city or a suburb. Um, uh, but the reality is like that light segmentation, it's not really that effective. Like do all women who live in a city behave the same, obviously not. Uh, and so, uh, we want instead to use behavior because your past behavior is the best predictor of your future behavior. >>Um, and, uh, and you need machine learning to be able to actually come up with, for an individual. What is their likelihood propensity to actually engage on any piece of content of which think about for you think about Chick-fil-A, how many different items they have in a menu. Um, you can think about like, we work with, um, a content company that has millions of different articles and they want to figure out what's the right article to put in front of you. Like, that's just not possible to actually analyze that by hand, uh, nor actually work working straight that, uh, uh, in real time without actually leveraging machine learning. Um, and so that's the exciting thing that's happened with, uh, new advances in, uh, supervisor and supervised learning models that we can actually do those in generalizable ways, uh, for our customers, >>Wait, we've talked a lot about behavioral, so that's obviously metrics you've been tracked. Right. I saw something and I clicked on something and I acted on something or watch something. These are all very measurable activities. On the other hand, though, as you know, in the consumer space, a lot of it's emotion too, you know, I make decisions based on, on my feelings or my thoughts or whatever. Can you, can you do any kind of unpeeling of my motivation in this almost like empathetic, uh, investigation so that you have an idea of what social cues on emanating or sending off? So, Hey, yeah, we can, we can get John this way too. >>Yeah. So I think a lot of it is, I mean, we're talking a lot about the science of, uh, product development, uh, for sure. And how do you bring personalization leveraging data? There is then the art of actually understanding, like what are the emotional States that users are in and like this isn't to say that the ability to personalize the product means that you're not actually bringing the heart as well. Like you act, it actually is a, both about the art and the science coming together. Um, and so you still need to, like, you're still gonna talk to your customers. You're still going to understand, uh, them and kind of what their, uh, different need States are, but this is then taking what you have, which you've built as a great product, then how do you optimize that? So we call it an optimization system, um, and actually deliver, uh, the best experience, uh, based on that customer's behavior. >>So just to kind of flip this a little bit, then what are you doing? Amplitude? What are you doing that, um, that hasn't been done before? I couldn't, I didn't understand that a lot of people think personalization just hasn't has a great horizon, has a lot of great promise. Well, but we're not there yet. I mean, what haven't we delivered on yet that you think amplitude is improving on and refining this capability? >>Yeah. So I think there are a couple of things there as to why we haven't fully seen the promise of personalization deliver no way. And I would say we're really starting to see that chasm emerge, where there are some companies that, you know, you think of, um, you know, Netflix, like obviously Amazon and others, who've done, who've been really successful here, but they've done it through armies of people. Um, what hasn't happened is a self-serve way of doing this so that it does not require massive investments, uh, in technical resources. Um, and so what we've solved for three things, um, one we've already talked about it, but it's just so true. Like this actually in and of itself is not an ML problem. First, it's actually a trustworthy data problem. Do you actually have the behavioral data that you can trust? Can you actually capture that across the entire customer journey because you can't personalize a journey if you don't even know what your users are doing to begin with. >>So you have to start there at that foundational level. Um, and that is a big part of our secret sauce is that we've built a database specifically catered to helping you understand that journey of that customer across all the different platforms and channels that they do. That's not easy to actually unify behavior in that fashion and allow you to analyze that in real time. Um, so that's the first thing that we did, um, is build that, uh, that database. So that's number one. And that's just the foundation. You have to have that, like, I, I think so many companies fail because they think we can go hire ML engineers, but if you don't have the foundation, it's not going to work. Um, the second thing isn't necessarily technological. It's more cultural, but it is really critical. And I think our analytics applications helped, uh, helped a lot here, which is you gotta break down the silos between marketing product engineering and data science. >>You actually have, you have to have all of them working together, um, to really be able to fulfill the promise of personalization because you have to be aligned and what's the outcome we're trying to drive, but that's actually how I literally can walk you through like the, how the, how the actual product works. But the first starting point is what are we trying to accomplish? Like in the Chick-fil-A example, it is, we want people to buy more than one item. Okay. So that's your goal. Like you have to get alignment that that is the goal. Cause if everyone's arguing about different goals, it doesn't matter what ammo model, like the model needs to know what we're trying to actually focus in on. Uh, and so how do you bring people together? And you do that through shared understanding of data. You do that through, we call it a North star, like we're aligned in what is the North star that we're focused on. >>And can you measure that? And that's analytics is focused in on that. And then when you have both of those, you've got behavioral data, you understand the journey of a customer you're aligned in the goals and outcomes you care about. Then you can leverage machine learning to actually deliver that personalized experience. And the advances that we're making there are actually doing that in a generalizable fashion. And so that does not have to be custom built for every single use case. Um, and our models are now able that we can run a model basically, uh, every hour to update for a customer. Um, and that scales horizontally, >>Well, I know of Chick-fil-A certainly has a track record that, um, is an arguable, right? And, and, and you've had a lot to do with satisfying that appetite for success. So, uh, Justin, uh, congratulations to amplitude. It's been a real pleasure speaking with you and thanks for the time today. >>Of course. >>Excellent speaking with Justin Bauer, the senior vice president of product at amplitude, and you've been watching the AWS startup showcase here on the cube.

(upbeat techno music) >> Well, good day. And thank you for joining us here on theCUBE. John Walls here, bringing you this conversation as part of the AWS Startup Showcase. And we're joined by Justin Bauer, who is the SVP of Product for Amplitude. And Justin, good to see you today. How are you doin? >> I'm doing great. Thank you for having me, John. >> Oh, you beat, no, a pleasure. Looking forward to it. You know, personalization. That's what everybody's talking about these days, and how do we better personalize our our digital presence, our digital products, you know, how do we get much more acutely aware of the end-user at the end of the day and grow? I know that's what Amplitude's all about. So maybe if you'd just give us a 30,000 foot perspective on that, about your thoughts about personalization today and how Amplitude tries to affect that. >> For sure, yeah. So I think, first-off, personalization matters because it actually works. I think we live in a world where, as you know we're drowning in content and distraction and it's been proven that customers respond better to digital experiences that are more personalized, that are more relevant for them. And frankly just save them time. And the nice thing about this is not only the customers benefit, but companies do too. We actually see that a big impact on a company's bottom line, if they're able to deliver a more relevant customer experience to them, because that leads to better engagement, better return (audio crackling drowns out speaker) and higher loyalty and lifetime value for those customers. >> So, well, let's just go right to an example then. I know you worked with a lot of different people. If there's anybody in particular that stands out, maybe give us an idea of a case study here about what practices you put into place, the kind of evaluations that you do, and ultimately, the service that you're providing that allows them to increase sales and get a little more stickiness with their customer. >> Yeah, that's great, that's great. So I think one company, a customer of ours we're working with right now on this, is actually Chick-fil-A. So people probably familiar with Chick-fil-A. Their mission is to be the most customer-caring company in the world, which I love. In personalization, it's critical to that strategy because it helps them create a more relevant and seamless experience for their customers. And the experience itself in the app is actually pretty simple, which is the magic of personalization. So you open the Chick-fil-A app, you see a list of menu items, and those items are relevant to you based on your previous behavior. After you order your entree, you're then offered a list of personalized sides. And then after that, a list of personalized drinks. And the great thing is that as new items get introduced to the menu by Chick-fil-A, you see the ones that are most relevant to you, based on predicted affinity, and all of the machine learning that we're doing in the background. And so really now Chick-fil-A is actually, they're able to deliver a customized menu for everyone that automatically updates based on your behavior, your preferences. And I think the real beauty of this is that they're able to configure all of this by a marketer through a simple UI. This did not require an army of data scientists or engineers. They're able to use the Amplitude platform to build out this entire experience for their customers. >> Right? Cause I mean, it seems like there'd be an enormous amount of analytics that you have to apply here, right? That because you got all this structured and unstructured data, ya know, it's all over the place, right? And a lot of times people don't even know what they have on hand. And so you got to help them sift through all this, right? So let's talk about that process a little bit for somebody who's watching and thinking about, "Well, that's all sounds well and good, "but how do you, kind of, automate this? "How do you make it so "that we don't have to invest a lot "in a team dedicated solely to, ya know, "sifting through our data "and making it valuable for us?" >> Yeah. I mean, I think that's the beauty of of Amplitude actually offering this in that that's actually our original first product, Product Analytics. That's what we've done. So we've actually made an out-of-the-box system that can read from all your different data sources. So whether those be your product sources, marketing channels, data that sits in your data warehouse. But it's not just piping that data. We then combine that into a unique identity, a profile for that customer, across all those different touch points, and also have out-of-the-box data governance so that you can make sure you maintain the quality of that data profile over time. And then that gets fed into our, what we call our behavioral graph. It's our database that's actually built to both understand and predict future behavior. And so all of this happens effectively out of the box for our customer. They don't need to do any of this themselves. We're managing all this for them. And then what they experience is an analytics application. So they can analyze that user behavior, understand kind of what the drivers of different things like engagement retention are, and then use that to actually personalize the product experience. >> And you mentioned machine learning. Talk about that aspect of this. I mean, how much more capability you have now because of what ML can deliver. And in some ways it adds some complexity but also, obviously, delivers exponentially, I would think, in benefit and value at the end of the day. >> Yeah, for sure. I mean, you, it's just not possible to do one-to-one personalization without machine learning. I think that's actually, when we talk about the benefits and the advantages of personalization, it's probably even worth taking a step back. Like, there's a lot of different types of personalization. I think when you want to do behavioral personalization, where you're truly getting to one-to-one experiences, you have to use machine learning. Now, you compare that to maybe like demographic personalization, which is actually, I think, when most companies talk about when they're doing personalization, they're actually doing demographic personalization. That's like, "Are you a male or female? "What's, do you live in a city or a suburb?" But the reality is like, that light segmentation, it's not really that effective. Like, do all women who live in a city behave the same? Like, obviously not. (laughs) And so we want instead to use behavior, because your past behavior is the best predictor of your future behavior, and you need machine learning to be able to actually come up with, for an individual, what is their likelihood, propensity, to actually engage on any piece of content? Of which, think about, for, you can think about Chick-fil-A, how many different items they have in a menu? You can think about, like, we work with a content company that has millions of different articles, and they want to figure out what's the right article to put in front of you. Like, that's just not possible to actually analyze that by hand nor actually orchestrate that in real time without actually leveraging machine learning. And so that's the exciting thing that's happened with new advances in supervised and unsupervised learning models. That we can actually do those in generalizable ways for our customers. >> We've talked a lot about behavioral, so that's obviously metrics you can track, right?. I saw something, I clicked on something. I acted on something and watched something. These are all very measurable activities. On the other hand, though, as you know in the consumer space, a lot of it's emotionally driven too. Ya know, I make decisions based on my feelings or my thoughts or whatever. Can you, can you do any kind of unpeeling of my motivation in this? Almost like empathetic investigation so that you have an idea of what social cues I'm emanating, or I'm sending it off, say, "Hey, yeah, we can "we can get John this way too." >> Yeah. So I think a lot of it is, I mean, we're talking a lot about the science of product development, for sure, and how you bring personalization leveraging data. There is then the art of actually understanding. Like, what are the emotional states that users are in? And like, this isn't to say that the ability to personalize the product means that you're not actually bringing the art as well. Like you act, it actually is about both the art and the science coming together. And so you still need to, like, you're still going to talk to your customers. You're still going to understand them and kind of what their different need-states are, but this is then taking what you have, which you've built as a great product, then how do you optimize that? That's why we call it an optimization system. And actually deliver the best experience, based on that customer's behavior. >> So just to kind of flip this a little bit then, what are you doing, Amplitude, what are you doing that hasn't been done before? I can, I understand that a lot of people think personalization just hasn't, has a great horizon, has a lot of great promise. Well, but we're not there yet. I mean, what haven't we delivered on yet that you think Amplitude is improving on and refining this capability? >> Yeah. So I think there are a couple things there as to why we haven't fully seen the promise of personalization deliver. Though we, and I would say, we're really starting to see that chasm emerge, where there are some companies that you know, you think of, you know, Netflix, like, obviously, Amazon and others, who've done, who've been really successful here. But they've done it through armies of people. What hasn't happened is a self-serve way of doing this so that it does not require massive investments in technical resources. And so what we've solved for are three things. One, we've already talked about it, but it's just so true. Like, this actually in and of itself is not an ML problem first, it's actually a trustworthy data problem. (chuckles) Do you actually have the behavioral data that you can trust? Can you actually capture that across the entire customer journey? Cause you can't personalize a journey if you don't even know what your users are doing to begin with. So you have to start there at that foundational level. And that is a big part of our secret sauce is that we've built a database specifically catered to helping you understand that journey of that customer across all the different platforms and channels that they do. That's not easy to actually unify behavior in that fashion and allow you to analyze that in real time. So that's the first thing that we did, is build that database. So that's number one. And that's just the foundation. You have to have that, like I said I think so many companies fail because they think, "We can go hire ML engineers." But if you don't have the foundation, it's not going to work. The second thing isn't necessarily technological, it's more cultural, but it is really critical. And I think our analytics application has helped a lot here, which is you've got to break down the silos between marketing, product, engineering, and data science. You actually have, you have to have all of them working together to really be able to fulfill the promise of personalization because you have to be aligned on, "What's the outcome we're trying to drive?" Like, that's actually how, I literally can walk you through like the, how the actual product works. But the first starting point is, "What are we trying to accomplish?" (chuckles) Like, in the Chick-fil-A example, it is, "We want people to buy more than one item." Okay, so that's your goal. Like, you have to get alignment that that is the goal. Cause if everyone's arguing about different goals, it doesn't matter what ML model, like the model needs to know what we're trying to actually focus in on. And so how do you bring people together? And you do that through shared understanding of data. Like you do that through, we call it a North Star. Like, "We're aligned and what is the North Star that we're focused on?" And can you measure that? And that's analytics, is focused in on that. And then when you have both of those, you've got behavioral data, you understand the journey of a customer, you're aligned on the goals and outcomes you care about. Then you can leverage machine learning to actually deliver that personalized experience. And the advances that we're making there are in actually doing that in a generalizable fashion. So that does not have to be custom built for every single use case. And our models are now able, that we can run a model, basically, every hour to update for a customer, and that scales horizontally. >> Well, I know Chick-fil-A certainly has a track record. That is inarguable, right? And, and you've had a lot to do with satisfying that appetite for success. So Justin, congratulations to Amplitude. It's been a real pleasure speaking with you and thanks for the time today. >> Of course, no, it's been great, thank you for having me. >> Excellent, speaking with Justin Bauer, the Senior Vice President of Product at Amplitude. And you've been watching the AWS Startup Showcase here on theCUBE. (soft marimba-techno music)

>>Yeah, yeah. Welcome back to the third session in our building, A vibrant data ecosystem track. This session is unleash the power of your cloud data warehouse. So what comes after you've moved your data to the cloud in this session will explore White Enterprise Analytics is finally ready for the cloud, and we'll discuss how you can consume Enterprise Analytics in the very same way he would cloud services. We'll also explore where analytics meets cloud and see firsthand how thought spot is open for everyone. Let's get going. I'm happy to say we'll be hearing from two folks from thought spot today, Michael said Cassie, VP of strategic partnerships, and Vika Valentina, senior product marketing manager. And I'm very excited to welcome from our partner at AWS Gal Bar MIA, product engineering manager with Red Shift. We'll also be sharing a live demo of thought spot for BTC Marketing Analytics directly on Red Shift data. Gal, please kick us off. >>Thank you, Military. And thanks. The talks about team and everyone attending today for joining us. When we talk about data driven organizations, we hear that 85% of businesses want to be data driven. However, on Lee. 37% have been successful in We ask ourselves, Why is that and believe it or not, Ah, lot of customers tell us that they struggled with live in defining what being data driven it even means, and in particular aligning that definition between the business and the technology stakeholders. Let's talk a little bit. Let's look at our own definition. A data driven organization is an organization that harnesses data is an asset. The drive sustained innovation and create actionable insights. The super charge, the experience of their customers so they demand more. Let's focus on a few things here. One is data is an asset. Data is very much like a product needs to evolve sustained innovation. It's not just innovation innovation, it's sustained. We need to continuously innovate when it comes to data actionable insights. It's not just interesting insights these air actionable that the business can take and act upon, and obviously the actual experience we. Whether whether the customers are internal or external, we want them to request Mawr insights and as such, drive mawr innovation, and we call this the for the flywheel. We use the flywheel metaphor here where we created that data set. Okay, Our first product. Any focused on a specific use case? We build an initial NDP around that we provided with that with our customers, internal or external. They provide feedback, the request, more features. They want mawr insights that enables us to learn bringing more data and reach that actual data. And again we create MAWR insights. And as the flywheel spins faster, we improve on operational efficiencies, supporting greater data richness, and we reduce the cost of experimentation and legacy environments were never built for this kind of agility. In many cases, customers have struggled to keep momentum in their fleet, flywheel in particular around operational efficiency and experimentation. This is where Richie fits in and helps customer make the transition to a true data driven organization. Red Shift is the most widely used data warehouse with tens of thousands of customers. It allows you to analyze all your data. It is the only cloud data warehouse that sits, allows you to analyze data that sits in your data lake on Amazon, a street with no loading duplication or CTL required. It is also allows you to scale with the business with its hybrid architectures it also accelerates performance. It's a shared storage that provides the ability to scale toe unlimited concurrency. While the UN instant storage provides low late and say access to data it also provides three. Key asks that customers consistently tell us that matter the most when it comes to cost. One is usage based pricing Instead of license based pricing. Great value as you scale your data warehouse using, for example, reserved instances they can save up to 75% compared to on the mind demand prices. And as your data grows, infrequently accessed data can be stored. Cost effectively in S three encouraged through Amazon spectrum, and the third aspect is predictable. Month to month spend with no hitting charges and surprises. Unlike and unlike other cloud data warehouses, where you need premium versions for additional enterprise capabilities. Wretched spicing include building security compression and data transfer. >>Great Thanks. Scout um, eso. As you can see, everybody wins with the cloud data warehouses. Um, there's this evolution of movement of users and data and organizations to get value with these cloud data warehouses. And the key is the data has to be accessible by the users, and this data and the ability to make business decisions on the data. It ranges from users on the front line all the way up to the boardroom. So while we've seen this evolution to the Cloud Data Warehouse, as you can see from the statistic from Forrester, we're still struggling with how much of that data actually gets used for analytics. And so what is holding us back? One of the main reasons is old technology really trying to work with today's modern cloud data warehouses? They weren't built for it. So you run into issues of trying to do data replication, getting the data out of the cloud data warehouse. You can do analysis and then maintaining these middle layers of data so that you can access it quickly and get the answers you need. Another issue that's holding us back is this idea that you have to have your data in perfect shape with the perfect pipeline based on the exact dashboard unique. Um, this isn't true. Now, with Cloud data warehouse and the speed of important business data getting into those cloud data warehouses, you need a solution that allows you to access it right away without having everything to be perfect from the start, and I think this is a great opportunity for GAL and I have a little further discussion on what we're seeing in the marketplace. Um, one of the primary ones is like, What are the limiting factors, your Siegel of legacy technologies in the market when it comes to this cloud transformation we're talking about >>here? It's a great question, Michael and the variety of aspect when it comes to legacy, the other warehouses that are slowing down innovation for companies and businesses. I'll focus on 21 is performance right? We want faster insights. Companies want the ability to analyze MAWR data faster. And when it comes to on prem or legacy data warehouses, that's hard to achieve because the second aspect comes into display, which is the lack of flexibility, right. If you want to increase your capacity of your warehouse, you need to ensure request someone needs to go and bring an actual machine and install it and expand your data warehouse. When it comes to the cloud, it's literally a click of a button, which allows you to increase the capacity of your data warehouse and enable your internal and external users to perform analytics at scale and much faster. >>It falls right into the explanation you provided there, right as the speed of the data warehouses and the data gets faster and faster as it scales, older solutions aren't built toe leverage that, um, you know, they're either they're having to make technical, you know, technical cuts there, either looking at smaller amounts of data so that they can get to the data quicker. Um, or it's taking longer to get to the data when the data warehouse is ready, when it could just be live career to get the answers you need. And that's definitely an issue that we're seeing in the marketplace. I think the other one that you're looking at is things like governance, lineage, regulatory requirements. How is the cloud you know, making it easier? >>That's That's again an area where I think the cloud shines. Because AWS AWS scale allows significantly more investment in securing security policies and compliance, it allows customers. So, for example, Amazon redshift comes by default with suck 1 to 3 p. C. I. Aiso fared rampant HIPPA compliance, all of them out of the box and at our scale. We have the capacity to implement those by default for all of our customers and allow them to focus. Their very expensive, valuable ICTY resource is on actual applications that differentiate their business and transform the customer experience. >>That's a great point, gal. So we've talked about the, you know, limiting factors. Technology wise, we've mentioned things like governance. But what about the cultural aspect? Right? So what do you see? What do you see in team struggling in meeting? You know, their cloud data warehouse strategy today. >>And and that's true. One of the biggest challenges for large large organizations when they moved to the cloud is not about the technology. It's about people, process and culture, and we see differences between organizations that talk about moving to the cloud and ones that actually do it. And first of all, you wanna have senior leadership, drive and be aligned and committed to making the move to the cloud. But it's not just that you want. We see organizations sometimes Carol get paralyzed. If they can't figure out how to move each and every last work clothes, there's no need to boil the ocean, so we often work with organizations to find that iterative motion that relative process off identifying the use cases are date identifying workloads in migrating them one at a time and and through that allowed organization to grow its knowledge from a cloud perspective as well as adopt its tooling and learn about the new capabilities. >>And from an analytics perspective, we see the same right. You don't need a pixel perfect dashboard every single time to get value from your data. You don't need to wait until the data warehouse is perfect or the pipeline to the data warehouse is perfect. With today's technology, you should be able to look at the data in your cloud data warehouse immediately and get value from it. And that's the you know, that's that change that we're pushing and starting to see today. Thanks. God, that was That was really interesting. Um, you know, as we look through that, you know, this transformation we're seeing in analytics, um, isn't really that old? 20 years ago, data warehouses were primarily on Prem and the applications the B I tools used for analytics around them were on premise well, and so you saw things like applications like Salesforce. That live in the cloud. You start having to pull data from the cloud on Prem in order to do analytics with it. Um, you know, then we saw the shift about 10 years ago in the explosion of Cloud Data Warehouse Because of their scale, cost reduced, reduce shin reduction and speed. You know, we're seeing cloud data. Warehouses like Amazon Red Shift really take place, take hold of the marketplace and are the predominant ways of storing data moving forward. What we haven't seen is the B I tools catch up. And so when you have this new cloud data warehouse technology, you really need tools that were custom built for it to take advantage of it, to be able to query the cloud data warehouse directly and get results very quickly without having to worry about creating, you know, a middle layer of data or pipelines in order to manage it. And, you know, one company captures that really Well, um, chick fil A. I'm sure everybody has heard of is one of the largest food chains in America. And, you know, they made a huge investment in red shift and one of the purposes of that investment is they wanted to get access to the data mawr quickly, and they really wanted to give their business users, um, the ability to do some ad hoc analysis on the data that they were capturing. They found that with their older tools, the problems that they were finding was that all the data when they're trying to do this analysis was staying at the analyst level. So somebody needed to create a dashboard in order to share that data with a user. And if the user's requirements changed, the analysts were starting to become burdened with requests for changes and the time it took to reflect those changes. So they wanted to move to fought spot with embrace to connect to Red Shift so they could start giving business users that capability. Query the database right away. And with this, um, they were able to find, you know, very common things in in the supply chain analysis around the ability to figure out what store should get, what product that was selling better. The other part was they didn't have to wait for the data to get settled into some sort of repository or second level database. They were able to query it quickly. And then with that, they're able to make changes right in the red shift database that were then reflected to customers and the business users right away. So what they found from this is by adopting thought spot, they were actually able to arm business users with the ability to make decisions very quickly. And they cleared up the backlog that they were having and the delay with their analysts. And they're also putting their analysts toe work on different projects where they could get better value from. So when you look at the way we work with a cloud data warehouse, um, you have to think of thoughts about embrace as the tool that access that layer. The perfect analytic partner for the Cloud Data Warehouse. We will do the live query for the business user. You don't need to know how to script and sequel, um Thio access, you know, red shift. You can type the question that you want the answer to and thought spot will take care of that query. We will do the indexing so that the results come back faster for you and we will also do the analysis on. This is one of the things I wanted to cover, which is our spot i. Q. This is new for our ability to use this with embrace and our partners at Red Shift is now. We can give you the ability to do auto analysis to look at things like leading indicators, trends and anomalies. So to put this in perspective amount imagine somebody was doing forecasting for you know Q three in the western region. And they looked at how their stores were doing. And they saw that, you know, one store was performing well, Spot like, you might be able to look at that analysis and see if there's a leading product that is underperforming based on perhaps the last few quarters of data. And bring that up to the business user for analysis right away. They don't need to have to figure that out. And, um, you know, slice and dice to find that issue on their own. And then finally, all the work you do in data management and governance in your cloud data warehouse gets reflected in the results in embrace right away. So I've done a lot of talking about embrace, and I could do more, but I think it would be far better toe. Have Vika actually show you how the product works, Vika. >>Thanks, Michael. We learned a lot today about the power of leveraging your red shift data and thought spot. But now let me show you how it works. The coronavirus pandemic has presented extraordinary challenges for many businesses, and some industries have fared better than others. One industry that seems to weather the storm pretty well actually is streaming media. So companies like Netflix and who Lou. And in this demo, we're going to be looking at data from B to C marketing efforts. First streaming media company in 2020 lately, we've been running campaigns for comedy, drama, kids and family and reality content. Each of our campaigns last four weeks, and they're staggered on a weekly basis. Therefore, we always have four campaigns running, and we can focus on one campaign launch per >>week, >>and today we'll be digging into how our campaigns are performing. We'll be looking at things like impressions, conversions and users demographic data. So let's go ahead and look at that data. We'll see what we can learn from what's happened this year so far, and how we can apply those learnings to future decision making. As you can already see on the thoughts about homepage, I've created a few pin boards that I use for reporting purposes. The homepage also includes what others on my team and I have been looking at most recently. Now, before we dive into a search, will first take a look at how to make a direct connection to the customer database and red shift to save time. I've already pre built the connection Red Shift, but I'll show you how easy it is to make that connection in just three steps. So first we give the connection name and we select our connection type and was on red Shift. Then we enter our red shift credentials, and finally, we select the tables that we want to use Great now ready to start searching. So let's start in this data to get a better idea of how our marketing efforts have been affected either positively or negatively by this really challenging situation. When we think of ad based online marketing campaigns, we think of impressions, clicks and conversions. Let's >>look at those >>on a daily basis for our purposes. So all this data is available to us in Thought spot, and we can easily you search to create a nice line chart like this that shows US trends over the last few months and based on experience. We understand that we're going to have more clicks than impressions and more impressions and conversions. If we started the chart for a minute, we could see that while impressions appear to be pretty steady over the course of the year, clicks and especially conversions both get a nice boost in mid to late March, right around the time that pandemic related policies were being implemented. So right off the bat, we found something interesting, and we can come back to this now. There are few metrics that we're gonna focus on as we analyze our marketing data. Our overall goal is obviously to drive conversions, meaning that we bring new users into our streaming service. And in order to get a visitor to sign up in the first place, we need them to get into our sign up page. A compelling campaign is going to generate clicks, so if someone is interested in our ad, they're more likely to click on it, so we'll search for Click through Rape 5% and we'll look this up by campaign name. Now even compare all the campaigns that we've launched this year to see which have been most effective and bring visitors star site. And I mentioned earlier that we have four different types of campaign content, each one aligned with one of our most popular genres. So by adding campaign content, yeah, >>and I >>just want to see the top 10. I could limit my church. Just these top 10 campaigns automatically sorted by click through rate and assigned a color for each category so we could see right away that comedy and drama each of three of the top 10 campaigns by click through rate reality is, too, including the top spot and kids and family makes one appearance as well. Without spot. We know that any non technical user can ask a question and get an answer. They can explore the answer and ask another question. When you get an answer that you want to share, keep an eye on moving forward, you pin the answer to pin board. So the BBC Marketing Campaign Statistics PIN board gives us a solid overview of our campaign related activities and metrics throughout 2020. The visuals here keep us up to date on click through rate and cost per click, but also another really important metrics that conversions or cost proposition. Now it's important to our business that we evaluate the effectiveness of our spending. Let's do another search. We're going to look at how many new customers were getting so conversions and the price cost per acquisition that we're spending to get each of these by the campaign contact category. So >>this is a >>really telling chart. We can basically see how much each new users costing us, based on the content that they see prior to signing up to the service. Drama and reality users are actually relatively expensive compared to those who joined based on comedy and kids and family content that they saw. And if all the genres kids and family is actually giving us the best bang for our marketing >>buck. >>And that's good news because the genres providing the best value are also providing the most customers. We mentioned earlier that we actually saw a sizable uptick in conversions as stay at home policies were implemented across much of the country. So we're gonna remove cost per acquisition, and we're gonna take a daily look how our campaign content has trended over the years so far. Eso By doing this now, we can see a comparison of the different genres daily. Some campaigns have been more successful than others. Obviously, for example, kids and family contact has always fared pretty well Azaz comedy. But as we moved into the stay at home area of the line chart, we really saw these two genres begin to separate from the rest. And even here in June, as some states started to reopen, we're seeing that they're still trending up, and we're also seeing reality start to catch up around that time. And while the first pin board that we looked at included all sorts of campaign metrics, this is another PIN board that we've created so solely to focus on conversions. So not only can we see which campaigns drug significant conversions, we could also dig into the demographics of new users, like which campaigns and what content brought users from different parts of the country or from different age groups. And all this is just a quick search away without spot search directly on a red shift. Data Mhm. All right, Thank you. And back to you, Michael. >>Great. Thanks, Vika. That was excellent. Um, so as you can see, you can very quickly go from zero to search with thought Spot, um, connected to any cloud data warehouse. And I think it's important to understand that we mentioned it before. Not everything has to be perfect. In your doubt, in your cloud data warehouse, um, you can use thought spot as your initial for your initial tool. It's for investigatory purposes, A Z you can see here with star, Gento, imax and anthem. And a lot of these cases we were looking at billions of rows of data within minutes. And as you as your data warehouse maturity grows, you can start to add more and more thoughts about users to leverage the data and get better analysis from it. So we hope that you've enjoyed what you see today and take the step to either do one of two things. We have a free trial of thoughts about cloud. If you go to the website that you see below and register, we can get you access the thought spots so you can start searching today. Another option, by contacting our team, is to do a zero to search workshop where 90 minutes will work with you to connect your data source and start to build some insights and exactly what you're trying to find for your business. Um thanks, everybody. I would especially like to thank golf from AWS for joining us on this today. We appreciate your participation, and I hope everybody enjoyed what they saw. I think we have a few questions now. >>Thank you, Vika, Gal and Michael. It's always exciting to see a live demo. I know that I'm one of those comedy numbers. We have just a few minutes left, but I would love to ask a couple of last questions Before we go. Michael will give you the first question. Do I need to have all of my data cleaned and ready in my cloud data warehouse before I begin with thought spot? >>That's a great question, Mallory. No, you don't. You can really start using thought spot for search right away and start getting analysis and start understanding the data through the automatic search analysis and the way that we query the data and we've seen customers do that. Chick fil a example that we talked about earlier is where they were able to use thoughts bought to notice an anomaly in the Cloud Data Warehouse linking between product and store. They were able to fix that very quickly. Then that gets reflected across all of the users because our product queries the Cloud Data Warehouse directly so you can get started right away without it having to be perfect. And >>that's awesome. And gal will leave a fun one for you. What can we look forward to from Amazon Red Shift next year? >>That's a great question. And you know, the team has been innovating extremely fast. We released more than 200 features in the last year and a half, and we continue innovating. Um, one thing that stands out is aqua, which is a innovative new technology. Um, in fact, lovely stands for Advanced Square Accelerator, and it allows customers to achieve performance that up to 10 times faster, uh, than what they've seen really outstanding and and the way we've achieved that is through a shift in paradigm in the actual technological implementation section. Uh, aqua is a new distributed and hardware accelerated processing layer, which effectively allows us to push down operations analytics operations like compression, encryption, filtering and aggregations to the storage there layer and allow the aqua nodes that are built with custom. AWS designed analytics processors to perform these operations faster than traditional soup use. And we no longer need to bring, you know, scan the data and bring it all the way to the computational notes were able to apply these these predicates filtering and encourage encryption and compression and aggregations at the storage level. And likewise is going to be available for every are a three, um, customer out of the box with no changes to come. So I apologize for being getting out a little bit, but this is really exciting. >>No, that's why we invited you. Call. Thank you on. Thank you. Also to Michael and Vika. That was excellent. We really appreciate it. For all of you tuning in at home. The final session of this track is coming up shortly. You aren't gonna want to miss it. We're gonna end strong, come back and hear directly from our customer a T mobile on how T Mobile is building a data driven organization with thought spot in which >>pro, It's >>up next, see you then.

>> Announcer: Live from San Diego, California, it's theCUBE covering KubeCon and CloudNativeCon. Brought to you by RedHat, the CloudNative Computing Foundation, and its ecosystem partners. >> Stu: Welcome back to theCUBE, I'm Stu Miniman. My cohost for three days of coverage is John Troyer. We're here at KubeCon CloudNativeCon in San Diego, over 12,000 in attendance and happy to welcome back a CUBE alumni and veteran of generations of the stacks that we've seen come together and change over the time, Sheng Liang, who is the co-founder and CEO of Rancher Labs. Thanks so much, great to see you. >> Shang: Thank you Stuart, is very glad to be here. >> All right, so you know Kubernetes, flash to the pan nobody's all that excited about it. I mean, we've seen all these things come and go over the years, Sheng. No but seriously, the excitement is palpable. Every year, you know, so many more people, so many more projects, so much more going on. Help set the stage for you, as to what you see and the importance today of kind of CloudNative in general and you know, this ecosystem specifically. >> Yeah you're so right though, Stuart. Community as a whole and Kubernetes has really come a long way. In the early days, Kubernetes was a uh, you know, somewhat of a technical community, lot of Linux people. But not a whole lot of end users. Not a whole lot of Enterprise customers. I walk in today and just the kind of people I've met, I've probably talked to fifty people already who are just really at the beginning of the show and uh there's a very very large number Enterprise customers. And this does feel like Kubernetes has crossed the chasm and headed in to the mainstream Enterprise market. >> Yeah it's interesting you know I've talked to you know plenty of the people here probably if you brought up things like OpenStack and CloudStack they wouldn't even know what we were talking about. The wave of containerization really seemed to spread far and wide. At Rancher you've done some surveys, give us some of the insight. What are you seeing? You've talked to plenty of customers. Give us where we are with the maturity. >> Definitely, definitely. Enterprise Kubernetes adoption is ready for prime time. You know the So what we're really seeing is some of the early challenges a few years ago a lot of people were having problems with just installing Kubernetes. They were literally just making sure to get people educated about container as a concept. Those have been overcome. Now, uh, we're really facing next generation of growth. And people solve these days solve problems like how do I get my new applications onboarding to Kubernetes. How do I really integrate Kubernetes into my multicloud and hybrid-Cloud strategy? And as Enterprise's need to perform computing in places beyond just the data centers and the cloud, we're also seeing tremendous amount of interest in running Kubernetes on the Edge. So those are some of the major findings of our survey. >> John: That's great. So Sheng I'd love for you to kind of elaborate or elaborate for us where Rancher fits into this. Right. Rancher is, you've been around, you've a mature stack of technology and also some new announcements today so I'd kind of love for you to kind of tell us how you fit in to that landscape you just described. >> Absolutely. This is very exciting and very very fast changing industry. So one of the things that Rancher is able to play very well is we're really able to take work with the community, take the latest and greatest open source technology and actually develop open source products on top this and make that technology useful and consumable for Enterprise at large. So the way we see it, to make Kubernetes work we really need to solve problems at three levels. At the lowest level, the industry need at lot of compliant and compatible certified Kubernetes distros and services. So that's table stakes now. Rancher is a leader in providing CNCF certified Kubernetes distro. We actually provide two of them. One of them is called RKE - Rancher Kubernetes Engine. Something we've been doing it for years. It's really one of the easiest to use and most widely deployed Kubernetes distributions. But we don't force our customers to only use our Kubernetes distribution. Rancher customers can use whatever CNCF certified Kubernetes distribution or Kubernetes services they want. So a lot of our customers use RKE(Rancher Kubernetes Engine) but they also use, when they go to the cloud, they use cloud hosted Kubernetes Services like GKE and EKS. There are really a lot of advantages in using those because cloud providers will help you run these Kubernetes clusters for free. And in many cases they even throw in the infrastructure it takes to run the Kubernetes masters and etcd databases for free. If you're in the cloud, there's really no reason not to be using these Kubernetes services. Now there's one area that Rancher ended up innovating at the Kubernetes distros, despite having these data center focus and cloud focus Kubernetes distros and services. And that is one of our, one of the two big announcements today. And that's called K3S. K3S is a great open source project. It's probably one of the most exciting open source projects in the Kubernetes ecosystem today. And what we did with K3S is we took Kubernetes that's been proven in data center and cloud and we brought it everywhere. So with K3S you can run Kubernetes on a Raspberry Pi. You can run Kubernetes in a surveillance camera. You can run Kubernetes in an ATM machine. You know, we have customers trying to run now Kubernetes in a uh, factory floor. So it really helps us realize our vision of Kubernetes as a new Linux and you run it everywhere. >> Well that's great 'cause you talk about that simplicity that we need and if you start talking about Edge deployment, I don't have the people, I don't have the skillset, and a lot times I don't have the gear, uh, to run that. So you know, help connect the dots as to you know, what led Rancher to do the K3S piece of it and you know, what did we take out? Or what's the differences between K8S and the K3S? >> That's a great question, you know. Even the name "K3S" is actually somewhat a wordplay on K8S You know we kind of cut half of 8 away and you're left with 3. It really happened with some of our early traction we sawing some customers. I remember, in retrospect it wasn't really that long ago. It was like middle of last year, we saw a blog coming out of Chick-fil-A and a group of technical enthusiasts were experimenting with actually running uh, Kubernetes in very, in like Intel Nook servers. You know, they were talking about potentially running three of those servers in every one of their stores and at the time they were using RKE and Rancher Kubernetes Engine to do that. And they run into a lot of issues. I mean to be honest if you think about running Kubernetes in the cloud in the database center, uh these servers have a lot of resources and you also have a dedicated operations teams. You have an SRE to manage them, right? But when you really bring it out into branch offices and Edge computing locations, now all of the sudden, number one, these uh, the software now has to take a lot less resource but also you don't really have SREs monitoring them every day anymore. And you, since these, Kubernetes distro really has to be zero touch and it has to run just like a, you know like a embedded window or Linux server. And that's what K3S was able to accomplish, we were able to really take away lot of the baggage that came with having all the drivers that were necessary to run Kubernetes in the cloud and we were also able to dramatically simplify what it takes to actually start Kubernetes and operate it. >> So unsolicited, I was doing an event right before this one and I asked some people what they looking forward to here at KubeCon. And independently, two different people said, "The thing I'm most excited about is K3S." And I think it's because it's the right slice through Kubernetes. I can run it in my lab. I can run it on my laptop. I can on a stack of Raspberry Pis or Nooks, but I could also run it in production if I, you know I can scale it up >> Stu: Yeah. >> John: And in fact they both got a twinkle in their eye and said well what if this is the future of Kubernetes, like you could take this and you could run it, you know? They were very excited about it. >> Absolutely! I mean, you know, I really think, you know, as a company we survive by, and thrive by delivering the kind of innovation that pushes the market forward right? I mean, we, otherwise people are not going to look at Rancher and say you guys are the originators of Kubernetes technology. So we're very happy to be able to come up with technologies like K3S that effectively greatly broadened the addressable market for everyone. Imagine you were a security vendor and before like all you really got to do is solving security problems. Or if you were a monitoring vendor you were able to solve monitoring problems for a data center and in the cloud. Now with K3S you end up getting to solve the same problems on the Edge and in branch offices. So that's why so many people are so excited about it. >> All right so Sheng you said K3S is one of the announcements this week, what's the rest of the news? >> Yeah so K3S, RKE, and all the GKE, AKS, EKS, they're really the fundamental layer of Kubernetes everywhere. Then on top of that one of the biggest piece of innovation that Rancher labs created is the idea of multi-cluster management. A few years ago it was pretty much of a revolutionary concept. Now it's widely understood. Of course an organization is not going to have just one cluster, they're going to have many clusters. So Rancher is the industry leader for doing multi-cluster management. And these clusters could span clouds, could span data centers, now all the way out to branch offices and the Edge. So we're exhibiting Rancher on the show floor. Everyone, most people I've met here, they know Rancher because of that flash of product. Now our second announcement though is yet another level above Rancher, so what we've seen is in order to really Kubernetes to achieve the next level of adoption in the Enterprise we're seeing you know some of the development teams and especially the less skilled dev ops teams, they're kind of struggling with the learning curve of Kubernetes and also some of the associated technologies around service mesh around Knative, around, you know, CICD, so we created a project called Rio, as in Rio de Janeiro the city. And the nice thing about Rio is it packaged together all these Cloud Native technologies and then we created very easy to use, very simple to understand user experience for developers and dev ops teams. So they no longer have to start with the training course on Kubernetes, on Istio, on Knative, on Tekton, just to get productive. They can pretty much get productive on day one. So that Rio project has hit a very important milestone today, we shipped the beta release for it and we're exhibiting it at the booth as well. >> Well that's great. You know, the beta release of Rio, pulling together a lot of these projects. Can you talk about some folks that, early adopters that have been using them or some folks that have been working with the project? >> Sheng: Yeah absolutely. So I talk about some of the early adoption we're seeing for both K3S and Rio. Uh, what we see the, first of all just the market reception of K3S, as you said, has been tremendous. Couple of even mentioned to you guys today in your earlier interviews. And it is primarily coming from customers who want to run Kubernetes in places you probably haven't quite anticipated before, so I kind of give you two examples. One is actually appliance manufacture. So if you think they used to ship appliances, then you can imagine these appliances come with Linux and they would image their appliance with an OS image with their applications. But what's happening is these applications are becoming so sophisticated they're now talking about running the entire data analytics stack and AI software. So it actually takes Kubernetes not necessarily, because it's one server in a situation of appliance. Kubernetes is not really managing a cluster, but it's managing all the application components and microservices. So they ended up bundling up K3S into their appliance. This is one example. Another example is actually an ISV, that's a very interesting use case as well. So uh, they ship a micro service based application software stack and again their software involves a lot of different complicated components. And they decided to replatform their software on Kubernetes. We've all heard a lot of that! But in their case they have to also ship, they don't just run the software themselves, they have to ship the software to the end users. And most of their end users are not familiar with Kubernetes yet, right? And they don't really want to say, to install our software you go provision the Kubernetes cluster and then you operate it from now on. So what they did is they took K3S and bundled into their application as if it were an application server, almost like a modern day WebLogic and WebSphere, then they shipped the whole thing to their customers. So I thought both of these use cases are really interesting. It really elevates the reach of Kubernetes from just being almost like a cloud platform in the old days to now being an application server. And then I'll also quickly talk about Rio. A lot of interest inside Rio is around really dev ops teams who've had, I mean, we did a survey early on and we found out that a lot of our customers they deploy Kubernetes in services. But they end up building a custom experience on top of their Kubernetes deployment, just so that most of their internal users wouldn't have to take a course on Kubernetes to start using it. So they can just tell that this thing that, this is where my source code is and then every thing from that point on will be automated. So now with Rio they wouldn't have to do that anymore. Effectively Rio is the direct source to URL type of, one step process. And they are able to adopt Rio for that purpose. >> So Sheng, I want to go back to when we started this conversation. You said, you know, the ecosystem growing. That not only, you know, so many vendors here, 129 end users, members of the CNCF. The theme we've been talking about is to really, you know, it's ready for production and people are all embracing it. But to get the vast majority of people, simplicity really needs to come front and center, I think. K3S really punctuates that. What else do we need to do as an ecosystem, you know, Rancher is looking to take a leadership position and help drive this, but what else do you want to see from your peers, the community, overall to help drive this to the promise that it could deliver. >> We really see the adoption of Kubernetes is probably going to wing at three, I mean. We see most organizations go through this three step journey. The first step is you got to install and operate Kubernetes. You know, day one, day two. And I think we've got it down. With K3S it becomes so easy. With GKE it becomes one API call or one simple UI interaction. And CNCS has really stepped up and created a great, you know, compliance certification program, right? So we're not seeing the kind of fragmentation that we saw with some of the other technologies. This is fantastic. Then the second step we see is, which a lot of our customers are going through now, is now you have all the Kubernetes clusters coming from different clouds, different infrastructure, potentially on the Edge. You have a management problem. Now you all of the sudden because we made Kubernetes clusters so easy to obtain you can potentially have a sprawl. If you are not careful you might leave them misconfigured. That could expose a security issue. So really it takes Rancher, it takes our ecosystem partners, like Twistlock, like Aqua. CICD partners, like CloudBees, GitLab. Just everyone really needs to come together, make that, solve that management problem. So not only, uh, you build this Kubernetes infrastructure but then you actually going to get a lot of users and they can use the cluster securely and reliably. Then I think the third step, which I think a lot of work still remain is we really want to focus on growing the footprint of workload, of enterprise workload, in the enterprise. So there the work is honestly just getting started. Anywhere from uh, if you walk into any enterprise you know what percentage of their total workload is running on Kubernetes today? I mean outside of Google and Uber, that percentage is probably very small, right? They're probably in the minority, maybe even in single digit percentage. So, we really need to do a lot of work. You know, we need to uh, Rancher created this project called LongHorn and we also work with a lot of our ecosystem partners in persistence storage area like Portworx, StorageOS, OpenEBS. Lot of us really need to come together and solve this problem of running persistent workload. I mean there was also a lot of talk about it at the keynote this morning, I was very encouraged to hear that. That could easily double, triple the amount of workload that could bring, that could be onboarded into Kubernetes and even experiences like Rio, you know? Make it further simpler, more accessible. That is really in the DNA of Rancher. Rancher wouldn't be surviving and thriving without our insight into how to make our technology consumable and widely adopted. So a lot of work we're doing is really to drive the adoption of Kubernetes in the enterprise beyond, you know, the current state and into something I really don't see in the future, Kubernetes wouldn't be as actually widely used as say AWS or vSphere. That would be my bar for success. Hopefully in a few years we can be talking about that. >> All right, that is a high bar Sheng. We look forward to more conversations with you going forward. Congratulations on the announcement. Great buzz on K3S, and yeah, thanks so much for joining us. >> Thank you very much. >> For John Troyer, I'm Stu Miniman, back with lots more coverage here from KubeCon CloudNativeCon 2019 in San Diego, you're watching theCUBE. [Upbeat music]

>> Announcer: From Seattle, Washington, it's theCUBE! Covering AWS IMAGINE Nonprofit. Brought to you by Amazon Web Services. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in the waterfront in Seattle, Washington, it's absolutely gorgeous here the last couple of days. We're here for the AWS IMAGINE Nonprofit event. We were here a couple weeks ago for the education event, now they have a whole separate track for nonprofits, and what's really cool about nonprofits is these people, these companies are attacking very, very big, ugly problems. It's not advertising, it's not click here and get something, these are big things, and one of the biggest issues is human trafficking. You probably hear a lot about it, it's way bigger than I ever thought it was, and we're really excited to have an expert in the field that, again, is using the power of AWS technology as well as their organization to help fight this cause. And we're excited to have Brad Myles, he is the CEO of Polaris and just coming off a keynote, we're hearing all about your keynote. So Brad, first off, welcome. >> Yeah, well thank you, thank you for having me. >> Absolutely, so Polaris, give us a little bit about kind of what's the mission for people that aren't familiar with the company. >> Yeah, so Polaris, we are a nonprofit that works full-time on this issue. We both combat the issue and try to get to long-term solutions, and respond to the issue and restore freedom to survivors by operating the National Human Trafficking Hotline for the United States, so, it's part kind of big data and long-term solutions, and it's part responding to day-to-day cases that break across the country every day. >> Right, in preparing for this interview and spending some time on the site there was just some amazing things that just jump right off the page. 24.9 million people are involved in this. Is that just domestically here in the States, or is that globally? >> That's a global number. So when you're thinking about human trafficking, think about three buckets. The first bucket is any child, 17 or younger, being exploited in the commercial sex trade. The second bucket is any adult, 18 or over, who's in the sex trade by force, fraud, or coercion. And the third bucket is anyone forced to work in some sort of other labor or service industry by force, fraud, or coercion. So you've got the child sex trafficking bucket, you've got the adult sex trafficking bucket, and then you've got all the labor trafficking bucket, right? You add up those three buckets globally, that's the number that the International Labour Organization came out and said 25 million around the world are those three buckets in a given year. >> Right, and I think again, going through the website, some of the just crazy discoveries, it's the child sex trafficking you can kind of understand that that's part of the problem, the adult sex trafficking. But you had like 25 different human trafficking business models, I forget the term that was used, for a whole host of things well beyond just the sex trade. It's a very big and unfortunately mature industry. >> Totally, yeah, so we, so the first thing that we do that we're kind of known for is operating the National Human Trafficking Hotline. The National Human Trafficking Hotline leads to having a giant data set on trafficking, it's 50,000 cases of trafficking that we've worked on. So then we analyzed that data set and came to the breakthrough conclusion that there are these 25 major forms, and almost any single call that we get in to the National Hotline is going to be one of those 25 types. And once you know that then the problem doesn't seem so overwhelming, it's not, you know, thousands of different types, it's these 25 things, so, it's 18 labor trafficking types and seven sex trafficking types. And it enables a little bit more granular analysis than just saying sex trafficking or labor trafficking which is kind of too broad and general. Let's get really specific about it, we're talking about these late night janitors, or we're talking about these people in agriculture, or we're talking about these women in illicit massage businesses. It enables the conversation to get more focused. >> Right, it's so interesting right, that's such a big piece of the big data trend that we see all over the place, right? It used to be, you know, you had old data, a sample of old data that you took an aggregate of and worked off the averages. And now, because of big data, and the other tools that we have today, now actually you can work on individual cases. So as you look at it from a kind of a big data point of view, what are some of the things that you're able to do? And that lead directly to, everyone's talking about the presentation that you just got off of, in terms of training people to look for specific behaviors that fit the patterns, so you can start to break some of these cases. >> Exactly, so, I think that the human trafficking field risks being too generic. So if you're just saying to the populace, "Look for trafficking, look for someone who's scared." People are like, that's not enough, that's too vague, it's kind of slipping through my fingers. But if you say, "In this particular type of trafficking, "with traveling magazine sales crews, "if someone comes to your door "trying to sell you a magazine with these specific signs." So now instead of talking about general red flag indicators across all 25 types, we're coming up with red flag indicators for each of the 25 types. So instead of speaking in aggregate we're getting really specific, it's almost like specific gene therapy. And the data analysis on our data set is enabling that to happen, which makes the trafficking field smarter, we could get smarter about where victims are recruited from, we could get smarter about intervention points, and we could get smarter about where survivors might have a moment to kind of get help and get out. >> Right, so I got to dig into the magazine salesperson, 'cause I think we've all had the kid-- >> Brad: Have you had a kid come to you yet? >> Absolutely, and you know, you think first they're hustlin' but their papers are kind of torn up, and they've got their little certificate, certification. How does that business model work? >> Yeah, so that's one of the 25 types, they're called mag crews. There was a New York Times article written by a journalist named Ian Urbina who really studied this and it came out a number of years ago. Then they made a movie about it called "American Honey," if you watch with a number of stars. But essentially this is a very long-standing business model, it goes back 30 or 40 years of like the door-to-door salesperson, and like trying to win sympathy from people going to door-to-door sales. And then these kind of predatory groups decided to prey on disaffected U.S. citizen youth that are kind of bored, or are kind of working a low-wage job. And so they go up to these kids and they say, "Tired of working at the Waffle House? "Well why don't you join our crew and travel the country, "and party every night, and you'll be outdoors every day, "and it's coed, you get to hang out with girls, "you get to hang out with guys, "we'll drink every night and all you have to do "is sell magazines during the day." And it's kind of this alluring pitch, and then the crews turn violent, and there's sometimes quotas on the crew, there's sometimes coercion on the crew. We get a lot of calls from kids who are abandoned by the crew. Where the crew says, "If you act up "or if you don't adhere to our rules, "we'll just drive away and leave you in this city." >> Wherever. >> Is the crews are very mobile they have this whole language, they call it kind of jumping territory. So they'll drive from like Kansas City to a nearby state, and we'll get this call from this kid, they're like, "I'm totally homeless, my crew just left me behind "because I kind of didn't obey one of the rules." So a lot of people, when they think of human trafficking they're not thinking of like U.S. citizen kids knocking on your door. And we're not saying that every single magazine crew is human trafficking, but we are saying that if there's force, and coercion, and fraud, and lies, and people feel like they can't leave, and people feel like they're being coerced to work, this is actually a form of human trafficking of U.S. citizen youth which is not very well-known but we hear about it on the Hotline quite a lot. >> Right, so then I wonder if you could tell us more about the Delta story 'cause most of the people that are going to be watching this interview weren't here today to hear your keynote. So I wonder if you can explain kind of that whole process where you identified a specific situation, you train people that are in a position to make a difference and in fact they're making a big difference. >> Yeah. So the first big report that we released based on the Hotline data was the 25 types, right? We decided to do a followup to that called Intersections, where we reached out to survivors of trafficking and we said, "Can you tell us about "the legitimate businesses that your trafficker used "while you were being trafficked?" And all these survivors were like, "Yeah, sure, "we'll tell you about social media, "we'll tell you about transportation, "we'll tell you about banks, "we'll tell you about hotels." And so we then identified these six major industries that traffickers use that are using legitimate companies, like rental car companies, and airlines, and ridesharing companies. So then we reached out to a number of those corporate partners and said, "You don't want this stuff on your services, right?" And Delta really just jumped at this, they were just like, "We take this incredibly seriously. "We want our whole workforce trained. "We don't want any trafficker to feel like "they can kind of get away with it on our flights. "We want to be a leader in transportation." And then they began taking all these steps. Their CEO, Ed Bastian, took it very seriously. They launched a whole corporate-wide taskforce across departments, they hosted listening sessions with survivor leaders so survivors could coach them, and then they started launching this whole strategy around training their flight attendants, and then training their whole workforce, and then supporting the National Human Trafficking Hotline, they made some monetary donations to Polaris. We get situations on the Hotline where someone is in a dangerous situation and needs to be flown across the country, like an escape flight almost, and Delta donated SkyMiles for us to give to survivors who are trying to flee a situation, who needs a flight. They can go to an airport and get on a flight for free that will fly them across the country. So it's almost like a modern day Underground Railroad, kind of flying people on planes. >> Jeff: Right, right. >> So they've just been an amazing partner, and they even then took the bold step of saying, "Well let's air a PSA on our flights "so the customer base can see this." So when you're on a Delta flight you'll see this PSA about human trafficking. And it just kept going and going and going. So it's now been about a five-year partnership and lots of great work together. >> And catching bad guys. >> Yeah, I mean, their publicity of the National Human Trafficking Hotline has led to a major increase in calls. Airport signage, more employees looking for it, and I actually do believe that the notion of flying, if you're going to be a trafficker, flying on a Delta flight is now a much more harrowing experience because everyone's kind of trained, and eyes and ears are looking. So you're going to pivot towards another airline that hasn't done that training yet, which now speaks to the need that once one member of an industry steps up, all different members of the industry need to follow suit. So we're encouraging a lot of the other airlines to do similar training and we're seeing some others do that, which is great. >> Yeah, and how much of it was from the CEO, or did he kind of come on after the fact, or was there kind of a champion catalyst that was pushing this through the organization, or is that often the case, or what do you find in terms of adoption of a company to help you on your mission? >> That's a great question. I mean, the bigger picture here is trafficking is a $150 billion industry, right? A group of small nonprofits and cops are not going to solve it on their own. We need the big businesses to enter the fight, because the big businesses have the resources, they have the brand, they have the customer base, they have the scale to make it a fair fight, right? So in the past few years we're seeing big businesses really enter the fight against trafficking, whether or not that's big data companies like AWS, whether or not that's social media companies, Facebook, whether or not that's hotel companies, like Wyndham and Marriott, airlines like Delta. And that's great because now the big hitters are joining the trafficking fight, and it happens in different ways, sometimes it's CEO-led, I think in the case of Delta, Ed Bastian really does take this issue very seriously, he was hosting events on this at his home, he's hosted roundtables of other CEOs in the Atlanta area like UPS, and Chick-fil-A, and Home Depot, and Coca-Cola, all those Atlanta-based CEOs know each other well, he'll host roundtables about that, and I think it was kind of CEO-led. But in other corporations it's one die hard champion who might be like a mid-level employee, or a director, who just says, "We really got to do this," and then they drive more CEO attention. So we've seen it happen both ways, whether or not it's top-down, or kind of middle-driven-up. But the big picture is if we could get some of the biggest corporations in the world to take this issue seriously, to ask questions about who they contract with, to ask questions about what's in their supply chain, to educate their workforce, to talk about this in front of their millions of customers, it just puts the fight against trafficking on steroids than a group of nonprofits would be able to do alone. So I think we're in a whole different realm of the fight now that business is at the table. >> And is that pretty much your strategy in terms of where you get the leverage, do you think? Is to execute via a lot of these well-resourced companies that are at this intersection point, I think that's a really interesting way to address the problem. >> Yeah, well, it's back to the 25 types, right? So the strategies depend on type. Like, I don't think big businesses being at the table are necessarily going to solve magazine sales crews, right? They're not necessarily going to solve begging on the street. But they can solve late night janitors that sometimes are trafficked, where lots of big companies are contracting with late night janitorial crews, and they come at 2:00 a.m., and they buff the floors, and they kind of change out the trash, and no one's there in the office building to see those workers, right? And so asking different questions of who you procure contracts with, to say, "Hey, before we contract with you guys, "we're going to need to ask you a couple questions "about where these workers got here, "and what these workers thought they were coming to do, "and we need to ID these workers." The person holding the purse strings, who's buying that contract, has the power to demand the conditions of that contract. Especially in agriculture and large retail buyers. So I think that big corporations, it's definitely part of the strategy for certain types, it's not going to solve other types of trafficking. But let's say banks and financial institutions, if they start asking different questions of who's banking with them, just like they've done with terrorism financing they could wipe out trafficking financing, could actually play a gigantic role in changing the course of how that type of trafficking exists. >> So we could talk all day, I'm sure, but we don't have time, but I'm just curious, what should people do, A, if they just see something suspicious, you know, reach out to one of these kids selling magazines, or begging on the street, or looking suspicious at an airport, so, A, that's the question. And then two, if people want to get involved more generically, whether in their company, or personally, how do they get involved? >> Yeah, so there are thousands of nonprofit groups across the country, Polaris is in touch with 3,000 of them. We're one of thousands. I would say find an organization in your area that you care about and volunteer, get involved, donate, figure out what they need. Our website is polarisproject.org, we have a national Referral Directory of organizations across the country, and so that's one way. The other way is the National Human Trafficking Hotline, the number, 1-888-373-7888. The Hotline depends on either survivors calling in directly as a lifeline, or community members calling in who saw something suspicious. So we get lots of calls from people who were getting their nails done, and the woman was crying and talking about how she's not being paid, or people who are out to eat as a family and they see something in the restaurant, or people who are traveling and they see something that doesn't make, kind of, quite sense in a hotel or an airport. So we need an army of eyes and ears calling tips into the National Human Trafficking Hotline and identifying these cases, and we need survivors to know the number themselves too so that they can call in on their own behalf. We need to respond to the problem in the short-term, help get these people connected to help, and then we need to do the long-term solutions which involves data, and business, and changing business practice, and all of that. But I do think that if people want to kind of educate themselves, polarisproject.org, there are some kind of meta-organizations, there's a group called Freedom United that's kind of starting a grassroots movement against trafficking, freedomunited.org. So lots of great organizations to look into, and this is a bipartisan issue, this is an issue that most people care about, it's one of the top headlines in the newspapers every day these days. And it's something that I think people in this country naturally care about because it references kind of the history of chattel slavery, and some of those forms of slavery that morphed but never really went away, and we're still fighting that same fight today. >> In terms of, you know, we're here at AWS IMAGINE, and they're obviously putting a lot of resources behind this, Teresa Carlson and the team. How are you using them, have you always been on AWS? Has that platform enabled you to accomplish your mission better? >> Yeah, oh for sure, I mean, Polaris crunches over 60 terabytes of data per day, of just like the computing that we're doing, right? >> Jeff: And what types of data are you crunching? >> It's the data associated with Hotline calls, we collect up to 150 variables on each Hotline call. The Hotline calls come in, we have this data set of 50,000 cases of trafficking with very sensitive data, and the protections of that data, the cybersecurity associated with that data, the storage of that data. So since 2017, Polaris has been in existence since 2002, so we're in our 17th year now, but starting three years ago in 2017 we started really partnering with AWS, where we're migrating more of our data onto AWS, building some AI tools with AWS to help us process Hotline calls more efficiently. And then talking about potentially moving our, all of our data storage onto AWS so that we don't have our own server racks in our office, we still need to go through a number of steps to get there. But having AWS at the table, and then talking about the Impact Computing team and this, like, real big data crunching of like millions of trafficking cases globally, we haven't even started talking about that yet but I think that's like a next stage. So for now, it's getting our data stronger, more secure, building some of those AI bots to help us with our work, and then potentially considering us moving completely serverless, and all of those things are conversations we're having with AWS, and thrilled that AWS is making this an issue to the point that it was prioritized and featured at this conference, which was a big deal, to get in front of the whole audience and do a keynote, and we're very, very grateful for that. >> And you mentioned there's so many organizations involved, are you guys doing data aggregation, data consolidation, sharing, I mean there must be with so many organizations, that adds a lot of complexity, and a lot of data silos, to steal classic kind of IT terms. Are you working towards some kind of unification around that, or how does that look in the future? >> We would love to get to the point where different organizations are sharing their data set. We'd love to get to the point where different organizations are using, like, a shared case management tool, and collecting the same data so it's apples to apples. There are different organizations, like, Thorn is doing some amazing big data-- >> Jeff: Right, we've had Thorn on a couple of times. >> How do we merge Polaris's data set with Thorn's data set? We're not doing that yet, right? I think we're only doing baby steps. But I think the AWS platform could enable potentially a merger of Thorn's data with Polaris's data in some sort of data lake, right? So that's a great idea, we would love to get to that. I think the field isn't there yet. The field has kind of been, like, tech-starved for a number of years, but in the past five years has made a lot of progress. The field is mostly kind of small shelters and groups responding to survivors, and so this notion of like infusing the trafficking field with data is somewhat of a new concept, but it's enabling us to think much bigger about what's possible. >> Well Brad, again, we could go on all day, you know, really thankful for what you're doing for a whole lot of people that we don't see, or maybe we see and we're not noticing, so thank you for that, and uh. >> Absolutely. >> Look forward to catching up when you move the ball a little bit further down the field. >> Yeah, thank you for having me on. It's a pleasure to be here. >> All right, my pleasure. He's Brad, I'm Jeff, you're watching theCUBE. We're at AWS IMAGINE Nonprofits, thanks for watching, we'll see you next time. (futuristic music)

>> From Gillette Stadium in Foxboro, Massachusetts, if the queue covering Vita Winter warmer, twenty nineteen brought to you by Silicon Angle media. >> Hi, I'm stew Minutemen. And this is the Cube Worldwide Leader and live tech coverage. >> We're on the ground here at the V Tug winter warmer, and it is twenty nineteen. It's actually, the thirteenth year of this event was one of the original, if not the original Veum, where user groups covers virtual ization, cloud computing and even Mohr, always great to be able to get back to the community, get some good interviews and no better person helped me start with my first interview at a show of the year. But good friend of the program, Keith Towns and he is the CTO advisor. And he's also now a slew front architect with the M. Where Keith. Thanks for joining >> us. Thanks for having me on the cute. >> Yeah. So, Keith, I mean, you were host of our program for a number of years. You're now, you know, back working on the vendor side. But you know, you know this community. You know what I always say in my career, There, certain communities, an ecosystem where there's just love to be a part of it. And the virtual ization group. You know, I've been part of it for a long time. You know, Veum, wear and beyond, though, you know people that you know, they get excited, They geek out on the technology and they love to share. And that's why we come to events like this. >> Yeah, it is amazing. Just, you know, the every every show is getting smaller, but maybe with the session of a Ws re event, but I don't think the intensity has shrunk at all. You get around friends, you know, we're just at a desk and one of the ten days, actually, how did I get a job doing X? And the community was like, Oh, you just talk to the people at this table. So it is. It is a great, great commute. >> Yeah, it's an interesting dynamic you talk about. You know, we've seen the huge growth in Meetups in user groups and regional shows. You know, vm Where does Veum World but the VM world being where forums around the globe. I'm sure you probably have to go for a few of those they've been doing well. I'm right back in my emcee Daisy M. C. Did a number of those. So we see you. Amazon Reinvent is growing, but oh, my God, they're regional shows are ridiculous. I I've said some of those regional shows either different communities or different localities can actually be even better than some of the big shows on. You know, we love Keith. We're happy to welcome you here to the home of the NFC Championship. New England Patriots ur >> First off, Congratulations. The wait went a little better for you to bare sand and say, You know what? Tom Brady won't play forever, so enjoy it. This is amazing backdrop through him. Little finish that you've not involved. Invited me to a veto before now. >> Oh. Oh, I'm sorry, Keith. It's It's a community thing that absolutely got to come. Absolutely. I've had friends. Most of them. It is local. I'm talking to users from Maine and Massachusetts, Rhode Island and Connecticut and like so you gave a keynote this morning and you didn't True fashion. You did a block post about reality check leading in, and I thought it was a great way for us to start is, You know, there's so much change in the industry, uh, those of us that are technologies that you know, we're super excited because there's so much new stuff. It's not like Oh, jeez, you know, twenty nineteen is probably going to be just like twenty eighteen. It's like, Oh, my gosh, what did I do in twenty eighteen? What do I have to change? How do I keep up? How do I manage it? I would love to get your viewpoint. You know what's going on with Keith? And you're talking about a lot of users, so you know how help share, You know, what is the reality? Check that everybody's going >> to know. We're talking about a pre recording in the banter. Just, you know, whether it's, you know, Vienna where we're hip Theo and all the stuff that Casey Kelsey Hightower is going out with Cooper Netease. Then as you spent spent out to serve earless, uh, infrastructures Cole scripting it centre. There's much to learn that you're a bit overwhelmed and we're seeing this out. You know, as I'm talking to executive CTO CEOs, VP of infrastructure, they're filling the same kind of excitement at the same time. Overwhelmed this Like what? What's what's really You know, we had the big cloud movements over a few years ago where I think we're at the height cycle where organizations are starting to understand that. You know, Cloud isn't the destination is part of a strategy, and everyone seems to be in the throes of figuring out what that means for us. We're just on the crowd chat, talking about multi Cloud and the drivers around. Multi Cloud. You guys did a great job hosting that cloud shit chat, nothing. We saw the gambit off where people are. You know, uh, there's not really a business rationality people who are really in the throes of trying to figure it out. >> Yeah, actually, I love to comment friend of ours that we've had on the program before, Bobby Allen from Cloud General said when he's working with companies, if they ask for a three year strategy plan, he said, I will not do it unless we guarantee that we will go revisit it every six months because I looked back. You know, Clay Christensen, you no way talks about strategy is strategy is a point in time thing, not something that you write it in stone. I've been saying for a couple of years cloud strategies that companies today is, they wrote it in ink and the ink still drying. And, you know, you're probably going to need toe, you know, go through it and change it because it is changing fast and therefore, you know, huge. Out I started Deploy something. Oh, wait, what about the next thing? Or there's some new practice or something to do it. So it is challenging because I need to run my business. Today. I got to set my budget for the year, usually, um and it's I need to be agile. But, you know, I can't constantly be tearing everything up and you're not going to be throwing it out or re training and skills. I mean, there's so many challenges. >> So still, you might remember when when I was on the other side of the the table. I, uh it was meant at somewhat of a D that Veum where moves at the speed of the aisle, and it was picked up as Maury compliment. But >> it was a >> big I'll be honest that it was a dig. And what I've learned the past few months is that Veum, where has to move at the speed of the CIA, is no longer and It's not just being wherever the community has and the CIA always faced with that we could do a few years ago. A cloud strategy, and that thing can sit on the desk for a year, and it would still be valid. But the bobbies point, if you're going to do a strategy and three year strategy, got to revisit that every six months and this agility that were not accustomed to previously in the industry, we have to now become super agile and figure out how do we keep the lights on and innovate at the pace That business, these witches? Pretty good chance. >> Yeah, it's attorney were beginning the year I made a comment personally said, You know, I'm not a big believer in, you know, setting. You know, Resolutions. Mohr. You know, let's set goals Your runner, I do some biking and it's like, Okay, you know, I've got a big race I want to do this year. I'm gonna work myself, you know, towards that goal and raise the money. You've got a certain target and something that you could do over the year. It's and there's no way that you do that, cos you know they've got goals that they need to accomplish and business. And it's great to say, Oh, well, we need to be more efficient. We need to do some down something different. But, you know, reality is, you know, it's not just digital transformation of modernizing. It was, you know. Oh, okay. Do I need to transform my backup? You know, data protection, you know, huge activity going on in the marketplace right now, you know? So, what >> is sixty million noon investment in one >> week? Exactly. You know, the wave of hyper convergence is one that really changed a lot of architectures and had people change. You know, we've talked cloud computing. They're what are some of the, You know, some of the big, you know, movements that you see, you know, will you? Tracking the industry? It was kind of the the intel refunds for a cycle, and, you know, Oh, well, it's the next version of Microsoft or, you know, Veum, where operating system would be one of those big, you know, kind of ticked. Talks of what? What are some of the big commonalities that you're seeing Al? So they're actually moving people to >> new things without a doubt. There is one conversation that customers cannot get the enough of. And I had Ah, on my little vlog. I had game being from Vienna, where V P off the Storch and Business availability unit and I challenged her on the via Where? Vision around this. But customers cannot get enough of having a conversation around data. What they What do they do with data? And how does a move data? How did they get compute closest to data? How did we get data they're closest to? They're re sources. We talked about it on the multi cloud conversation, but by far conversations are around. Howto they extract value from data had really protect data, and howto they make sure their compliant with the data is something that that's driving a lot of innovation and a lot of conversation. A lot of interest. >> Yeah, Keith, it's a great one. When I look at you know, our research team, that wicked bond data is that the center of everything. In many ways, the failings of big data was talking about, You know, the challenges. I have infrastructure. No, the growth and the variety and blah, blah, blah and everything that's not what important to the business they don't care about, You know, it's like, Oh, well, there's a storage problem in a network problem. It's the business says there's data, you know? Do I protect my bird business to make sure that I'm not a risk? You know, all the things like DDP are coming And can I livered value? Do I Can I get new lines of business? Can I generate revenue out of that? And I've seen early signs that we've learned this whole, You know, a I m l movement. You know, data, Really? At the center. All right, we've seen enough storage. We went from talking about storing data to about, you know, that data ecosystem, Andi, even computing and I ot data where data needs to be, how I work it. Absolutely a center. So, yeah, it's great to hear that. Customers are identifying that. We've been doing like, chief data officer events for many years. You know, where does data live? Is that a CEO Thing? Is that a different part of the business? I don't know if you've got anything you're seeing from, you know, your customers is Tau, >> who owns the Data initiative, So it's really interesting. I had a conversation with a major bank, and it was a one on one with the CDO and what I thought was the most tricky part of the conversation is that here, Not only does he report directly into the CIA, which you know is to be expected, but he meets regularly with the board of directors. So data were seen. I've seen these seedy old rolls being popped up, and it's not just about the technology as you mentioned. It's about the whole approach about this asset that we have. It's so critical that worth creating a sea level position that today might reporting to the CEO but is most definitely accountable to the border director. >> Well, yeah, Keith, it's that the trend we've been watching for a while, as it used to be, it was a cost center. And, you know, it's kind of, you know, that's what it was considered today. If it isn't in, you know, direct relationship, working with the business, the business will go find somebody else to do it. The whole stealthy movement. You know, I can go find an answer for what I'm doing. I think about project I've worked on in my career and been like, I wish it was easy. You know, fifteen years ago, it was today to do those. But we see security's a board level discussion data as a board level discussion is excellent. And all of those things that traditionally you would think that own them. Having awareness and visibility and information communication flow between the board in the C suite is great progress. You >> know, it's interesting. I was a big proponent of this prior to coming on The vendor side is that vendors have to start having conversations outside of it. So traditional infrastructure of injustice, his goal. Hurry, right saw and where the whole the Dale emcee Dale Technologies they have to skill up and have conversations with CIA moles. Seo's CEO Ole's H R directors because the these buying centers now have power to go out and buy solutions. You know, talked about in my no keynote this morning. You know how many people have worked day? How many people have salesforce applications? They had nothing to do when I had no nothing to do with the procurement of off these solutions. The ball is moving outside of just traditional for court technology is starting to get to the point where regular users can consume business users can consume these massive, massive solutions based on technology and just happens to be a label. The technology, whether sales Force worked in >> Sochi, thought on this this whole point there want to ask you, In my career, there's often been groups inside a business that didn't get along. And we, you know, built silos. You know, the storage in the network team don't get along cloud and traditional I t You know what we're fighting? You know who owns it? Turf wars Managing that, You know, have we built silos in multi cloud today? Is everybody holding hands and, you know, pointing the business in the same direction, you could kind of give us the good the bad. So what? We need to work on going forward. >> I think the good is that you know that the umbrella of infrastructure starting to work as a single. Uh, you So you have storage, compu networking, even configuration man groups that were kind of confrontational before and territorial. Those groups are starting. Tio. Come on. Their one senior manager or one senior executive looking at? How do you provide services as a group and providing those services? I think we're we're starting to see Silos is actually the developer versus the infrastructure group is developers just wantto FBI, too. A set of services. They want infrastructure to get away. Developers themselves. Haven't you know, kind of katende enough of the scars from heaven have to do operations, So there's a different view off the world. And, uh, today I think developers haven't yet getting the budget power off operations. But the business wants solutions, and they're going out there competing with traditional Teo get the dollars to run the services in the cloud or or wherever, however they consumed them, whether it's, you know, just saw Chick fil a's deploying two thousand ten points to run six thousand containers at the edge. Is that something that's run by tears? That something wrong? Run by developers? I don't know. Check feeling well enough to know about. This is what we're seeing in >> industry. Yeah. All right. Well, keep towns. And always a pleasure to catch up with you. Thanks so much for joining us. Be sure to check him out see Teo advisor on Twitter, check out his blogged. And of course, thank you so much for watching. We'll be back. Uh, lots more coverage here at V tug. Winter warmer, twenty nineteen. Thanks for watching.

>> From Seattle, Washington, it's theCUBE. Covering KubeCon and CloudNativeCon North America 2018. Brought to you by Red Hat. The Cloud Native Computing Foundation and it's ecosystem partners. [techno Music] >> Okay, welcome back everyone. It's theCUBE's live coverage in Seattle for KubeCon and CloudNativeCon 2018. I'm John Furrier with theCUBE. Stu Miniman. Breaking down all the action. Talking to all the thought leaders, all the experts, all the people making it happen. We're here with Aparna Sinha who's the group product manager, Kubernetes, Google Cloud. Also one of the power women of the Cloud at Google, according the Forbes. I wrote the story. Great to see you again. >> Thank you, great to be here with you. >> Thanks for coming on. >> CUBE alumni. Great to have you on. I want to get your prospective. One when you've seen a lot of action, certainly overseeing the group engineering team at Google and all the Kubernetes action. A lot of contribution, a lot of activity, that you guys are leading. >> Yes. >> And quite frankly enabling and contributing to the community. So, congratulations and thanks for that work. Kubernetes certainly looking good. People are pumped up. >> Very much. >> 8,000 people. A lot of activity. A lot of new things around that you guys are always kind of bringing into, the Geo, knative, a lot things. You gave a key note. What's your focus here this year? What's the message from Google? >> Yeah, well as you pointed out, this is the largest KubeCon ever. 8,000 people, 2,000 on the wait list. And people are telling me here that this is the... This is here to stay, right? It's in the early majority going to the mainstream very much like you kind of think about virtualization was 10 years ago. So that's the momentum that I'm seeing here, that I'm hearing here. My keynote was about the community. Thanking the community first of all. So I talked about how open-source really, success in contingent on contribution. And so, I started by showing the contribution over the last one year, the companies that are contributing. And 80% of contributions are by at least 10 entities. One of them is individual contributors. 40% percent I think was Google, which is still staggeringly high. And then the next highest was Red Hat. And so I think in many of the keynotes, we've been calling out the contributors because it's really important. 1.13, the 13th release of Kubernetes shipped last week. A lot of stability, a lot of GA features, and the uptake in the enterprise. The other thing I called out was just the amount of job opportunity in Kubernetes >> Yeah >> 230% growth in the last year. You see here so many customers that are here to talk about their experience. But also they're here to hire. >> Yeah. And there recruiters on the floor, so it's been I think a huge economic value add. And we feel very proud of that. >> Yeah, Aparna, great point. We've been talking about the end users. I always loved... There's a job board right outside the hall here and it's just covered. Big giant white board there. Bring us inside a little bit. I mean Google's always fascinating people. What's the hiring situation there? What's your team lookin' like? Is anybody smart enough to actually go work there? >> Google, I think we've been very, very fortunate in that we've had the original board team that started the Kubernetes project. And so we have a really, really deep bench because we've been running containers since the beginning. So now 15 years of experience with that, which many people tell me, I think that the reason that Kubernetes is so successful is because it's not new actually, right? >> Yeah >> It's been tried and true at scale. So, we have quite a bit of that, but we've been building this community and a lot of folks have been hired in through the community-- >> Yeah >> into Google. And really amazing, amazing people. So yeah. >> The thing about we had Brian Grant on yesterday and Tim Hockin -- Yes. >> Who was talking about some of those early board days. >> Yes. I want to ask you your point of about the hiring because I think this is a interesting dynamic. Open-source is key to your strategy. We've talked many times about how you guys are committed to open source, but what's interesting is not just net new jobs are available, we're seeing a revitalization around traditional roles like the network engineer under Kubernetes. Looking at the policy knobs that your folks pointed out that's... They think it's underutilized. And then on top of Kubernetes, new things are going on that's getting the app kind of server guy-- >> Yeah. >> Kind of energized. >> Yeah. >> It's kind of enabling a lot of thing, actions that's transforming existing jobs. >> That's right. >> And bringing new ones. >> Talk about that dynamic because you see it from both sides. >> Yes >> You've got SREs, site reliable engineers. >> Yes >> You've got developers. But, Now enterprises are now trying to adopt... >> That's right >> You guys are hitting that note. Talk about that dynamic. >> That's right, so I've been talking to a lot of customers here, it's been non-stop. I've not been able to attend any talks or keynotes. And I'm seeing two things. One there's the kind of operations now called platform teams. And they're under tremendous pressure. They're doing incredible work. Incredible. And they're energized. They're really... So one of the customers I was talking to was moving from VMs on EC2 to containers on GCE on Kubernetes. Google Cloud. And in the last one year, they looked... Honestly, they looked miserable because they have worked so hard in doing that transfomation. Turning their application from a VM-based application into containers. But you could also see that they were so happy and so successful because of the impact that it's had. And so and then I asked them so like, "What is driving that?" This is different customer. What is driving that? And it's really... As soon they get that environment up and running, and this is a large enterprise bank that I was talking to, this other one, their developers are just all over it. And they have, they have hundreds of services running within six months. And they're like, "Well we just got this platform up. "We still have to figure how we're going to upgrade it." But it's... So those are the two constituents. The developers are happy. >> The integration and delivery changes the makeup of how teams work. So that's one thing we're seeing here. And the other one is just scale. >> Yeah. >> So that seems to be the area. Now I got to ask you, as you guys look at... As you guys are doing the work on the enterprise side, you guys, I know you're working hard, I talk to Jennifer a lot, Jennifer Lynn, as well and we've talked before, are used to doing the work. But there's still a lot more work done. Where do you guys see the work that this community value opportunities for participants in the eco-system to fill white spaces? Where are the value lines starting to be drawn? Can you comment? >> Yeah, so I see two or three different areas. One of the areas is of course hardening. And that's why Janet Quill gave the keynote about "Kubernetes is boring and that's a good thing". And that's been something we've been working on for the last year at least. Adding a lot more security capabilities. Adding a lot more just moving everything to GA, right? Adding a lot more hooks in the enterprise storage and into enterprise networking. Building up the training and building up the partners that'll do the implementations. All of those things I think are very, very healthy. >> Yeah. >> Cause I see them. You probably talked to the CNCF. They're helping a lot with the certification and the training. So that's one piece of enterprise adoption. I think the other piece is the developer experience. And that's where a lot of the talks here, my key note as well, I demoed Istio and Knative on top of GKE. The developer experience is ultimately this whole thing. My perspective, this whole thing is about making your developers more productive. And developers have been driving this transition. Again going back to those customer examples. So that's getting a lot easier. >> Yeah, Aparna, I'd love you to talk a little about Knative. So, I know the excitement is there. Products only been around for five months. I remember at your show last summer it was announce and roll. Trying to understand exactly what it is. It's like, wait, wait is serverless going to kill Kubernetes? And how does this fit? How does this work with all the various services in the Cloud? Maybe just understand where we are. >> Right. >> What it is, what it isn't. >> Right. >> Again, so the heritage of serverless, I'm going to go back to Google, right? We have the first serverless offering in the world like 10 years ago. And so that's based on containers. Underneath it's based on containers. That's why we knew that with Kubernetes that's the right foundation for building serverless. And it actually, I think, we sort of held back for the longest time. And a couple of years ago there were one, two, and then 15, and then 17 serverless frameworks that just kind of all popped up around Kubernetes, on top of Kubernetes. I remember the first demo in the community. Here's this serverless piece. And at some point, a little bit over a year ago we decided that actually serverless is really important to our customers, to our users. The majority of Kubernetes tends to be on-prem, actually. And so it's important to them to have serverless capabilities on-prem. So then we need to make sure it's stable and it's something that's standard. >> I think it's a really important point... I talked to some people that are in the serverless ecosystem that is living on a AWS and they say, "You can't build serverless on-prem "because then you're racking "and stacking and dealing with it." And it's not... We know there's servers underneath of it and it's just system calls and how we consume that. But maybe explain the nuances to how this is important and we understand it. >> Yeah. >> There's not like a solution out there. >> Yeah. >> Server meshes, there's a lot of options out there right now. >> Yeah. >> So. >> A lot of things, because this is an open-source community, a lot of things come from the users. So when the user says, "You know what, actually need "the serverless capability on-prem. "Why? "Because I've got this developer group and I don't want "them to have to muck with the infrastructure. "I don't want them to have access to the infrastructure. "I want to just give them a simple interface "where they're going to write their applications "and the rest is taken care of for them." Right? And then I want to be able to bill them on a per-use basis. So, it's... Yeah there's someone managing the server. Someone building actually the severless capability and that's the platform team. That's the guys that I talked about that are working very hard these days happily. But, working very hard. >> And these are the new personas, by the way-- >> Yeah. >> In the enterprise. This is new kind of new re-architecting of how enterprises are creating value. These new platform teams. >> Right. >> This is the opportunity. Well I got to ask you, you know everyone that watches theCUBE knows I'm a big fan of scale. Love Amazon scale. I love Google scale. I love the enterprise market. And I want to get your thoughts... I want you to take a minute to explain the culture at Google Cloud. Because it's a separate building. Give you an opportunity to share. But you guys are working hard to go after the enterprise. It's not like a new thing. But the enterprise is interesting. It's not so much the best technology that wins. It's grit. It's almost like a street fight. You got to go out. You got to win those battles. Get all the work done. Hit those features. You can't just roll into town and say we've got great technology. We're Google. You guys recognize this. And I want you to share the culture you guys are building and how you guys are attacking the enterprise. What's the guiding principles? What are some of the core tenants? >> Yeah, yeah. So you know my entire life has been spent in enterprise software. >> Yeah. >> I do think that enterprises respect Google Cloud. I work very closely with them. And they respect certainly the engineering prowess. Like, "Wow. I need that." >> Yeah. Right? Especially you see all these enterprises that are being transformed by technology. Their industry is being transformed by technology. Whether that's in transportation, or it's in retail, or it's in media. And they want the best. They want the latest. Right? And they also don't necessarily have the skills, like you said, right? So they're looking for a partner that'll both help them scale up but also provide them all of that guidance. And the one thing you asked about culture at Google. I think we are a revolutionary company. We are willing to do lots of things. Lots of things that you wouldn't expect. And that's why you saw GK on-prem from my team, right? The first, kind of, Kubernetes on-prem offering from a cloud provider. Managed by a cloud provider. And that's really... I mean we've seen tremendous, tremendous interest in that. Tremendous feedback from our users and new customers. People that hadn't thought about it. Hadn't thought about Google, necessarily before that have said, "Wow. If you are going to come and help me on-prem "with this, I'm ready. "Give it to me now. "Because I trust you and I know I want to go to the Cloud. "So it's the right step for me. "You have the right incentives." Right? "And you're the open cloud, which is important to me "because I may want to be multi cloud." So that's the piece that is... >> You got the enterprise chops. You've spent your whole career there. I know Jennifer as well. >> Yes. >> A lot of people you guys have hired. >> Right. >> The good news is you've got a market that's changing. So you don't have to come in and replicate the old IT. So that's an opportunity at Google. How are you guys attacking that, that beachhead? Because you have the check. What's the vibe? What's the grit? What's it like... How you guys attacking the enterprise? What do you see as opportunities knowing the enterprise of old-- >> Yeah >> As it shifts to new kind of method? >> Yeah. >> What's the core? >> I think about the problems the users are having. I think about what is the problem the customer is facing. And so... And then breaking that down and solving that for them. I mean that's what's important, right? And so some of the problems I see is one they need a developer platform. And the developer platform sometimes cannot be in the Cloud. When I talk to large financial institutions, there's so much compliance and regulation and things that have to be on-prem. That it has to be on-prem. And they try to move to the Cloud and some things will do it. But the majority, like 90% is on-prem. And so they need an agile development environment and there's no holding it back. Because, like I said, there's all this transformation. Their developers need that environment today. So you have to provide that. That's one use case. We provide an on-prem development and agile development environment. Best in class. Your developers are super happy. Your business is going to do well. The other thing I see, and I see this a lot in retail, but also in hospitality at some of these very kind of brick and mortar enterprises is the edge. They need a solution at their edge location. Thousands, these are thousands of branch locations. We've even got this use case with Chick-fil-A, right? And a lot of times this is... A lot of different use cases, but a lot of time the common thing is that they're collecting data. They're doing some processing at that site and then they're doing further processing in the Cloud. And so it's a connected, but an intimately, it's not always connected.... Intimately connected environment. So that's the second big use case. Edge retail or just edge. There's so many... For me, it's one of the most exciting. There's so many examples of that. >> Awesome. >> Aparna, first of all, just so many goodness I want to say thank you to Google because everything from I heard at the show Google wasn't giving out swag because it actually went to charitable givings instead of spending that money. One of the things we always look is open-source is, how much more value is being created for the eco-system not just the vendor that started it. And it is a really tough balance. We've seen it fail many times. Do you step too far back? And how much do you engage? How do you strike that bound? For the last five to 10 years, we've been saying, "Where is the independent place where we can have that "conversation about cloud?" We think found it at this show. I mean we've been here for three years now. Google Cloud, phenomenal event. Our teams loves to be there, but this feels like overnight has turned into oh wait, here's the show we were looking at to have that conversation. To have that commons where we can come together and there's so many diversity of people, diversity of projects in here. Many which have very disconnected from original Kubernetes and everything, so. It's been fascinating to watch and have to imagine your team is... When you watch that first piece go and everything that's built around it. It's got to be amazing. >> My team loves this event. We have literally I think 300 people here. And a lot of them are core maintainers. Everybody is a contributor, but they are core maintainers of the Kubernetes project. The Istio project. The Knative project. And I think the best thing here is just interacting with our users. Because this is a developer, this is a developer conference, primarily. There's a lot of businesses here. >> Yeah >> With their kind of director level executives. But primarily it's an action-oriented hands-on audience. And you just... These customer meetings that I have, we review their architecture and we're like... It's an engineer to engineer conversation. >> Yep. >> And so how can we make that better? And sometimes they're contributing back and it makes the whole project better. >> Yeah. The thing, too, is it's an engineering, it's a developer conference, true. But what's interesting about that evolution as it modernizes, those end users are developers. >> That's right. >> And so the end user aspect of this show. >> That's right. >> Is the developer piece. >> That's right. >> It never used to be like that. Used to be COMDEX or some big event. >> Yeah. >> And then people just selling their stuff. >> Yeah. >> Doing business. The end user participation... >> Yes. >> Is not a consumption conversation, it's a contribution. >> Right. And end users are all over the spectrum of sort of really, really hands-on. Very, very smart to just give me something that works and I respect all of that, right? And we were actually very far here in terms of GKE. Giving you something that you really don't need to get in, that's fully managed, right? But then on the other hand we had Uber on stage earlier today in their keynote talking about how they've built all of this advanced capability on GKE. And that's a power user. That's using all their capabilities. Like custom additions and an operator. And it's just really gratifying I think for us to work with them and for us to see the user base as well as the community. So the ecosystem. Google. I thinks it's very important for us to have and create economic opportunity for our partners. And you'll see that with GKE on-prem. We're partnering heavily on that one. And you'll see that also in our marketplace. Our Kubernetes marketplace. So many of the companies that have come out of this ecosystem are now part of selling through Google Cloud. >> Aparna, thank you for your time. I know you've had to move some things around to come here. Great to have you on. I love your leadership at Google, it's phenominal. You've got the enterprise chops building out heavily over there. Congratulations. And for more CUBE interviews check out theCUBE dot net. You can check out Aparna's other good news. Of course search her name on Forbes. I wrote a story about her featuring her. Talking about her background and her passion. Always great to have her on theCUBE and get some commentary from Google. Of course, theCUBE is breaking down live coverage. Been there from the beginning of KubeCon and now CloudNativeCon, the Linux Foundation. Bringing you all the analysis and insight. Be back with more coverage after this short break. [Techno Music]

I'm from Seattle Washington it's the cube covering Gube Khan and cloud native Khan North America 2018 brought to you by Red Hat the cloud native computing foundation and its ecosystem partners ok welcome back everyone we are here live with cube covers three days with wall-to-wall coverage here at coop con cloud native con 2018 in Seattle I'm John fer with the cubes to Minutemen here breaking it down we're at day two we've got a lot of action David Ronn chick who's the head of open source ml strategy at Azure at Microsoft Microsoft Azure formerly of Google now at Microsoft welcome back to the cube we had a great chat at Copenhagen good to see you great to see you too thank you so much for having me you've been there from day one it's still kind of day one in Korea is still growing you got a new gig here at Microsoft formerly at Google you had a great talk at Google next by the way which we watched and and caught on online you just you're still doing the same thing think of me to explain kind of what the new job is what your focus is absolutely so in many ways I'm doing a very similar job to the one I was doing at Google except now across all of Asher you know when you look at machine learning today the truth of the matter is is it is about open source it's about pulling in the best from academia and open source contributors developers across the spectrum and while I was at Google I was able to launch the cube flow project which solves the very specific but very important problem now that you look at Azure a company that is growing excuse me a division that is growing extremely quickly and looking to expand their overall open source offerings make investments work with partners and projects and make sure that that researchers and customers are able to get to machine learning solutions very quickly I'm coming in to help them think about how to make those investments and accelerate customers overall time to solutions so both on the commercial side Asscher which is got a business objective to make money but also open source how is it still open source for you is it all open sores or is it crossing a little bit of bulk just quickly clarify that yeah there's no question um you know obviously as you as a business they pay me a salary and and we're gonna have a great first party solution for all of these very things but the reality is much like kubernetes has both a commercial offering and an open-source offering I think that all the major cloud providers will have that kind of duality they'll work in open source and and you can measure you know how many contributions and what they're doing in the open source projects but then they'll also have hosted and other versions that make it easier for customers to migrate their data and adopt some of these new so you know one of the things that's interesting on that point is this a super important point is that open source community that's here with kubernetes around kubernetes it's all kind of upstream kind of concept but the downstream impacts our IT and your classic developer so you have your open source yeah and a thing going on that's the core of this community an event the IT investments are shifting in 2019 we are seeing the trend of somewhat radical but certainly a reimagining of the IT I mean certainly you guys have gone cloud at Azure has seen that that result absolutely good pick up by customers office 365 that's now a SAS that's now now you've got cloud you have cloud scale this is what machine learning is really shining so I the question to you is what do you think is gonna be the big impact of 2019 to IT investment strategies in terms of what they how they procure and consume technology how they build their apps with the new goodness coming in from kubernetes etc absolutely um you know I remember back in the day you know I was an IT admin myself and and I carried a pager for literally when you know a machine went down or a power supply went out or this Ram was bad or something like that today if you went to even the most sophisticated IT shop they would be like what are you crazy you you should never carry a pager for that you should have a system that understands it's ok if something that low-level goes out that's exactly what kubernetes provided it provided this abstraction layer on top of this so if you went down kubernetes knew had a reschedule a pod and move things back and forth taking that one step further now into machine learning unfortunately today people are carrying pagers for the equivalent of if a power supply goes out or something goes wrong it's still way too low-level we're asking data scientists ml engineers to think about how to provision pods how'd it work on drivers how to do all these very very low-level things with things like kubernetes with things like hume flow you're now able to give higher level abstraction so a data scientist can in and you know open up their Jupiter notebook work on the model see how it works and when they're done they hit a button and it will provision out all the machines necessary all the drivers all the everything spin it up run that training job and bring it back and shut everything down so they won't wonder if you can help expand on that a little bit more so you know what one of the things that that's great about kubernetes is it can live in a diverse amount of infrastructure one of the biggest challenges with machine learning is you know where's my data how do I get to the right place where do I do the training you know we've spending a lot a couple of years looking at you know edge and you know what's the connectivity and how we're gonna do this you help just kind of pan us picture the landscape and what do we have solved and what are we working at trying to get put together yeah you know I think that's a really excellent question today there's so much focus on well are you gonna choose pi torch or tensorflow CNT k MX net you know numpy scikit-learn there are a bunch of really great frameworks out there done in the open source and we're really excited but the reality is when you look at the overall landscape that's just 5% of the work that the average data scientist goes through exactly your point how do I get my data in how do I transform it how do I visualize it generate statistics on it make sure that it's not biased towards certain populations and then once I'm done training how do I roll it out to production and monitor it and log and all these things and that's really what we're talking about that's what we tried to get work on when it comes to cute flow is is to think about this in a much broader sense and so you take things like data the reality is you can't beat the speed of light if I have a petabyte of data here it's gonna take a long time to move it over there and so you're gonna be really thoughtful about those kind of things i I'm very hopeful that academic research and and industry will figure out ways to reduce the amount of data and make it much much more sane in overall addressing this problem and make it easier to train in various locations but the reality is is I think you're ultimately gonna have models and training and inference move to many many different locations and so you'll do inference at the edge on my phone or on a you know little Bluetooth device in the corner of my house saying whether or not it's too hot or too cold we're gonna need that kind of intelligence and we're gonna do that kind of training and data collection at the edge do you see a landscape evolving where you have specialty ml for instance like the big caution in IOT is move you know compute to the data yeah reads that latency you see machine learning models moving around at code so I can throw a machine learning at a problem and there's that and that is that what kubernetes fits and I'm trying to put together a mental model of how to think about how ml scales yeah what's your vision on that how do you see that evolving yeah absolutely I think that you know going back to what we talked about at the beginning we're really moving to much more of a solution driven architecture today ml you know is great and the academic research is phenomenal but it is academic research it didn't really start to take off until people invented things are you know creating things like image Nets and mobile net and things like that that did very important things like object detection but then people that you know commercial researchers were able to take that and move that into locations where people actually need it in I think you will continue to see that that migration I don't think you're gonna have single ml models that do a hundred different things you're gonna have a single ml model that does a vertical specific thing anomaly detection in whatever factories and you're gonna use that in a whole variety of locations rather than trying to you know develop 1 ml model to solve them all so it's application specific or vertical alright so that means the data is super important quality data clean data is clean results dirty date bad result absolutely right people have been in this kind of virtuous circle of cleaning data you know you guys know at Google certainly Microsoft as well you know datum data quality is critical but you got the horizontally scalable cloud but you need specialism around the data and for them ml how do you see that is that I mean obviously sounds like the right architecture this is where the finesse is and the nuance I don't see that so you know you you bring up a really interesting point today the the biggest problem is is how much data there is right it's not a matter of whether or not you're able to process it you are but but it's so easy to get lost caught and little anomalies you know if you have a petabyte of data and whatever a megabyte of it is the thing that's causing your model to go sideways that's really hard to detect I think what you're seeing right now is a lot of academic research which I'm very optimistic about that will ultimately reduce that that will both call out hey this particular data is smells kind of weird maybe take a closer look at this or you will see a smaller need for training you know where it was once a petabyte you're able to train on just 10 gigabytes I'm very optimistic that both of those things happen and as you start to get to that you get better signal-to-noise and you start saying oh in fact this is questionable data let's move that off to the side or spend more time on it rather than what happens today which is oh I got this model and it works pretty well I'm just going to throw everything at it and trying you know get some answer out and then we'll go from there and that's with a lot of false positives come in all absolutely all right so take the next level here at Kubb con cloud native con in this community where kubernetes is the center of all these sets of services and building blocks where's the ML action what if I Michelle wanna jump in this community I'm watching this with hey you know what I got Amazon Web Services reinvent just pumping up a lot of MLA I you know stage maker and a bunch of other things what's going on in this community where are the projects what are the notable things where can I jump in and engage what's the what's that what's that map look like I don't know yeah absolutely so obviously I'm pretty biased you know I helped start cube flow we're very very excited about that the cube flows one yeah absolutely but let me speak a little bit more broadly kubernetes gives you this wonderful platform highly scalable incredibly portable and and I can't overstate how valuable that portability is the reality is is that customers have we talked about data a bunch already they have data on Prem they've data in cloud hey cloud B it's everywhere they want to bring it together they want to bring the the training and the inference to where the data is kubernetes solves that for you it gives you portability and lets you abstract away the underlying stuff it gives you great scalability and reliability and it lets you compose these highly complex pipelines together that let you do real training anywhere rather than having to take all your data and move it through cloud and train on a single VM that you're not sure whether or not it's been updated or not this is the way to go versus the old way which was what cuz that's an easier way orchestrating and managing that what was the alternative the alternative was you built it yourself you you piece together a whole bunch of solutions you wired it together you made sure that this service over here had the right user account to access the data that that service over there was outputting it was just a crazy time now you use kubernetes constructs use first-class objects you extend the native kubernetes api and it works on your laptop and it works on Cloud a and B and on pram and wherever you need it that's the magic basically absolutely so multi cloud has come up a lot hybrid clouds the buzzword of the year I call that the 2000 18 maybe 19 buzzword but I think the real end game and all this is what from a customer standpoint that we are reporting a silk'n angle on the cube is choice yeah multi vendor is the new multi cloud is the multi clouds the modern version of the old multi vendor comes yes which basically is choice absolutely so how does kubernetes fit into the multi cloud why is that good for the industry and what's your take on that can you share your perspective absolutely so when you go and look at the recent right scale reports 81 percent of enterprises today are multi cloud . 81 percent and not just one cloud there they're on five different clouds that could be on pram could be multi zone could be Google or Amazon or a Salesforce you name how you define cloud they're spreading they're doing it because that kind of portability is right for their business kubernetes gives you the opportunity to operate in an abstraction layer that works across all of these clouds so whether or not you're on your laptop and you're using docker or mini cube you're on your private training rig whether that you go to Google cloud or as you're on Google clouds you can eat user you have a KS these you're able to build C I'd CD systems continuous delivery systems that that use common kubernetes constructs I want to roll this application out I want there to be seven pods I wanted to have an endpoint that looks like this and that works anywhere you have a kubernetes conformant cluster and when it gets to really complex apps like machine learning you're able to do that it even a higher level using constructs like cube flow and all the many many packages that go into coop load we have Nvidia contributing and we have you know Intel and I mean just countless Cisco I you know I hesitate to keep naming names because I'll be here all day but you know we have literally over Cisco's rays tailwind Francisco they're gonna have Network forever everybody wins at the the CI CD sides for developers one common construct the network guys get more programming because if you decompose an application absolutely the network ties it together yes everybody wins in the stack absolutely I think I breed is really interesting you know hybrid kind of gets a dirty word people like oh my god you know why would you ever deploy to multiple clouds why would you ever spread across multiple clouds and that I agree with a true hybrid deployment today isn't well I'm gonna take my app and I'm gonna spread it across six different locations in fact what you really want to do is have isolated deployments to each place that it enables you in a single button deploy to all three of these locations but to isolate them to have this particular application go and if you know AWS hasn't added GCP is there or if GCB does manage asher is there and you can do that very readily or you can bring it closed for geographic reasons or legal reasons or whatever it might be those kind of flexibility that ability to take a single construct of your application and deploy it to each one of these locations not spreading them but in fact just giving you that flexibility gives you pricing power gives you flexibility and lets you take advantage of the operating model if the if the if the ICD is common and that's the key value right there absolutely right David thanks so much coming on cue as usual great commentary great insight there there from the beginning just final question predictions for 2019 I think kubernetes what's gonna happen in 2019 with kubernetes what's your prediction well III think I think you've heard this message over and over again you're seeing kubernetes become boring and and that is incredibly powerful the the stability the flexibility people are building enormous businesses on top of it but not just that they're also continuing to build things like the the custom resource definition which lets you extend kubernetes in a safe and secure way and that's incredibly important that means you don't have to go and check in code into the main tree in order to make extension you're able to build on top of it and you're seeing more and more businesses build eight solutions customer focus solutions well next time we get together I want to do a drill down on the what the word stack means I heard me say kubernetes stack I'm like yeah I think that you love the stack words let a stack anymore sets the services David thanks so much come on I appreciate it here the queue coverage live here in Seattle for coop con cloud native found I'm John Fourier was too many men we back with more after this short break

(spirited orchestral music) >> Hello and I'm John Furrier, cohost of theCUBE, founder of SiliconANGLE Media. I'm here at Palo Alto studios for CUBE Conversation as a preview for upcoming, the CNCF-sponsored KubeCon event coming up in Shanghai and in Seattle. I'm here with Janet Kuo, who is a software engineer at Google and recently named the co-chair of KubeCon, the main event around Kubernetes, multi-cloud, all the things happening in cloud-native. Janet, thanks for joining me today. >> Thanks for having me. So you were recently named co-chair, Kelsey was previously the co-chair and he always had those good demos but the program has been changing a lot and you're the new co-chair, what's it like? What's happening? What's the focus this year? What's the content going to look like? Tell us what's happening >> So we get a lot of overwhelming number of submissions, much more than last year, and I see a lot of interesting case studies and also I see that because Kubernetes is actually help you extract the infrastructure away and it runs anywhere so I see a lot of people are actually deploying it everywhere, multi-cloud, hybrid, and even in Edge. For example, I see Chick-Fil-A, they are going to talk about how they deploy Kubernetes in their Edge restaurants and the store owners, they are not tech expert, as you can expect. >> Yeah, I mean that's the edge of the network, a Chick-Fil-A, and you know, great retail example. We run a lot of Chick-Fil-A certainly out here in California it's like In-N-Out Burger, they go hand in hand. But this is a good use case of Edge and this is real world, so Kubernetes has certainly grown up. We know from the growth of KubeCon, the event itself has gotten to be pretty massive, the number of people involved has been great, how has Kubernetes grown up? Because we're seeing the conversation move from we love containers, Kubernetes is great for orchestrating everything, but now people are starting to really start really cranking it up a notch, is that the trend that you're seeing as well, and is that some of the content you'll be focused on? >> So I see, I took a lot at the Google trend for search for Kubernetes and it's still going way up since the beginning and also I look at a recent CNCF survey and I realize that about 40% of people who'll respond to their survey and they work in a enterprise and they said they run Kubernetes in production so that's a huge number. >> That's awesome. Well, now that you're the new co-chair, tell us a little bit about yourself, how, what's your background, how did you get there? >> I started working at Google in 2015 and that's before Kubernetes 1.0 was released and before CNCF and before the first KubeCon and when I joined Google, it's Kubernetes is a way, very new concept and not like it's fixed and it's already adopted by everyone so we work very hard to get the ease of use and get more people adoption and we get a lot of feedback from people and then Kubernetes is getting more and more popular, so after that I decided that I want to submit my first ever conference talk to KubeCon and I got selected and then I start to feel like I enjoy this and I did, and other CNCF hosted events, for example, a panel in San Francisco and I think that might be how I was selected. >> What was your first talk about, that you talked about? >> So I talk about running workloads in Kubernetes and I did an overview of the workloads API because I am the developer of that workloads API. >> So that's also, you got hooked on Kubernetes like everybody else, it's like the Kubernetes drug. So how did you get involved in open source? Were you always developing with open source? How did you get involved in the open source community? >> So Kubernetes is actually my first open source project and before that, I had a phone call with Tim Hawkins, he's the principal engineer at Google and he sold me the idea of Kubernetes and we need to be open and let people choose the best technology for them and he sold me the idea and I think Kubernetes is the future and also I want to work on open source but I just didn't have the chance to work on it yet. >> So we had a good fun time in Copenhagen for the last KubeCon, and we, theCUBE, has been at all the KubeCons as you know. We love this community, we think it's really special, not only because we've been there from the beginning, but we've gotten to see the people involved and the people have been very close-knit but yet so open and inclusive, we're seeing a lot of input, and then at the same time, so that's always great, open source, inclusive, and fun, but then the companies are coming in in waves, a massive amount of waves of commercial vendors jumping in, and I think this foundation's done a great job of balancing being a good upstream and good project but that dynamic is very interesting. It's probably the fastest open source kind of commercial, yet good vibes, commercial open source, how does that change or affect you guys as you pick and look at the data, 'cause you get surveys, you see what people want, vendors, users, industry participants, developers, what is the data telling you? What's all this data coming from the different KubeCons and how is that changing the selections and what's the trend I guess, what's the trends coming from the community? >> So from selecting talks, because we want to focus on make Kubernetes, make KubeCon, still community-focused conference so when we pick talks, we pick the ones that not just doing vendor pitch or sales pitch but we pick the ones that we think the community is going to benefit from and especially when they are talking about a solution that others could adopt or is it open source or not, then that affect our choice and then we also see a lot of people start customizing Kubernetes for their own needs and a lot of people are starting using Kubernetes API to managing resources outside of Kubernetes and that's a very interesting trend because with that, you can have Kubernetes to manage everything your infrastructure, lot of things running on Kubernetes. >> So what are some of those examples that are outside Kubernetes? So for example, you can use, so Kubernetes has a concept called custom resource that you can register a custom API in Kubernetes and so you can use that, you can register an API and you can implement a controller to manage anything you want, for example, different cloud resources or VMs, I even saw people use Kubernetes API to manage robots. >> Wow, so this is real world, so you mentioned you were working workload API at Google, the big trend that we're seeing on theCUBE and that crosses all the different events, not just cloud-native, is workload management, managing workloads and workloads are changing and it's very dynamic, it's not a static world anymore. So managing workloads to the infrastructure is where we see this nice activity happening from containers, Kubernetes, to service meshes, so there's a lot of activity going on there and some of the stuff is straightforward, I won't say straightforward, but containers and Kubernetes is easy to work with but services meshes are difficult. Istio, for instance, Kubeflow or Hot Projects, there's a real focus of stateless has been there, but stateful is hard, is there going to be talks about stateful applications, are you guys looking at some of the Istio, is service mesh going to be a focus this year? >> Yeah, we still see a lot of submissions from service meshes and so you can use service mesh to manage your service easily and secure them easily and we also see a lot of talks for stateful workloads, for example, how you customize something that manage your stateful workloads or what that best practice is and there is a pattern that's popular in the community which is called operator and the concept is that you write a controller, use the custom API that I just mentioned, and you just embed the knowledge of a human operator into that controller and let the controller do the automation for you. >> So it's putting intelligence, like an operator, into the software and letting that ride? >> Yeah and it will do all the work for you and you only need to write it once. >> And automation's a big trend, so if you could stack or rank the top three trends that we expect to see at KubeCon this year, what would they be? >> In the top three, I would say customize and multi-cloud and then service mesh or serverless they're both pretty popular, yeah. >> Is storageless coming? So if we have serverless, will there be storageless (laughs) I made that up, I tweeted that the other day, if there's servers, there's no servers, there's going to be no storage. I mean, service and storage go together so again, this is where the fun action is, the infrastructure is being programmable. And I think one of the things I like about what KubeCon has done is they've really enabled developers to be more efficient with DevOps, the DevOps trend, which is the cloud-native trend. The question I want to ask you is specifically kind of a Google question because I think this is important and Google cloud, I really love the trend of how application developers are being modernized, that's so cool, I love that, but the SRE concept that Google pioneered is becoming more of a trend as more of an operator role, not in the sense of what we just talked about but like an SRE, businesses are starting to look at that kind of scale out infrastructure where there's a need for kind of like an SRE, does that come up at KubeCon at all or is that too operator-oriented? Is that on the agenda? Does that come up in the KubeCon selection criteria, the notion of having operators or SRE-like roles? >> So we have a track called operations, so some of the operator, human operator, talks are submitting through that, to that topic, but we didn't see... >> Might be too early. >> Yeah, too early. >> It might be a little bit too early, that's what I think, alright and then since I brought up some of the tracks, we're always interested in knowing about startups 'cause there seems to be a lot of startup activity, doing a lot of AI stuff or applications, AI ops, and some new things going on, is there a startup activity involved that you're seeing, is there features of startups at all, do you guys look at that, is there going to be an emphasis of emerging companies and startups involved or is it mostly coming from the community? >> We definitely see a lot of startups and something in talks and also you just mentioned mission learning, we also see several talks on and about mission learning and AI submitting to both the Shanghai event and Seattle event. So projects like Kubeflow and Spark, that's being used a lot and we still, we see a lot of submissions from those. >> So those are the popular ones? >> Yeah, the popular ones and those are from Shanghai, I saw some AI submissions and I'm excited about those. >> Okay, so now back to the popular question, everyone wants to know where the popular parties are, what's the popular projects if you had to, in terms of contributors, activity, do you guys have like a rating like here's the most popular project? Do you guys look at just number of contributors? How do you rank the popularity of the projects? >> Or how would you rank them? >> We didn't actually look at the popularity of the projects because are you talking about CNCF projects or any projects? >> CNCF and KubeCon, let me ask the question differently... If I go to Shanghai or Seattle, what's going on? What do I engage, what should I pay attention to, what can I expect if I'm a user and I come to the event, what's going to happen at Shanghai and Seattle? What's the format? >> We separate all the talks in tracks so you can look up the track that you are interested in, for example, do you want to know all the case studies, then you can go to case studies and if you're interested in observability then you go to the observability track and they'll be a lot of different projects, they are presenting their own solutions and you can go and figure out which one fits you the best. >> And so multi-cloud's high, I'll ask you a multi-cloud question 'cause one of the things that we're tracking is what is multi-cloud and how is that different from hybrid? How would you describe that 'cause there are people that talk about hybrid cloud all the time but multi-cloud seems to have different definitions. Is there a different definition to hybrid cloud versus multi-cloud? >> So I think hybrid includes things that's not cloud, for example, your on-prem versus you have your on-premise solutions and you also use some cloud solutions and that's hybrid... >> And multi-cloud is multiple clouds so workloads on different clouds or sharing workloads across clouds? >> Workloads on different clouds. >> Yeah, so Office 365, that's Azure, a TensorFlow on Google and something, okay. I always want to know, comparing running workloads between clouds, that would be the ideal scenario. Here's the tough question for you, put you on the spot here, what is your favorite open source project in the CNCF and favorite track at KubeCon? >> My favorite project is of course Kubernetes and my favorite track would be case studies because I care a lot about user experience and I love to hear user stories. So for Seattle we picked a lot of user stories that we think are interesting and we also pick some keynote speakers that are going to talk about their large-scale usage of Kubernetes and that's very exciting for me, I can't wait to hear their story. >> Yeah, we love the end user stories too, 'cause it really puts the real world scenario around it. Okay, final question for you Janet, I wanted to ask you about diversity at KubeCon, what's going on and what can you share around that program? >> Yeah, we care about diversity a lot. We look at that when we select talks to accept and also we have a diversity scholarship that allows people to apply for a scholarship, we're going to cover the ticket to conference and also the travel to conference and also we have a diversity luncheon on December 12 and that will be sponsored by both Google and Heptio. >> So December 12 in Seattle? And that was a great, by the way, you did a great job last year, the program with scholarship got I think a standing ovation, so that's awesome. Thanks for doing that. >> Thank you, thanks. For the folks watching that might not be really deep on Kubernetes, in your opinion, why is Kubernetes so important and why should IT leaders, developers, and people in mainstream tech who are now new to Kubernetes and seeing the trends, why should they pay attention to Kubernetes, what's the relevance, what's the impact, why should they pay attention to Kubernetes? >> Because Kubernetes allows you to easily adopt cloud, because it's extract every infrastructure the infrastructure level away and allows you to easily run your infrastructure anywhere and most importantly, because a lot of people on different cloud and different stack of development, for example, CICD service mesh, they put a lot energy to integrate with Kubernetes so if you have Kubernetes you have everything. >> You have Kubernetes, you have everything. We love the work you're doing, thanks for co-chairing the KubeCon event, we love going there, CNCF's been very successful, been a great relationship, we love working with them, obviously it's a content-rich environment and I think everyone who is interested in cloud-native should go to the CNCF, there's a lot of sponsors, and more and more logos come on every day, so you guys are doing a good job. Thanks for doing that, appreciate it. Maybe we'll do two cubes this year. Janet Kuo, who is a software engineer at Google is joining me here at theCUBE. She's also the co-chair for KubeCon, the event put on by the CNCF and the industry around cloud-native and all things Kubernetes, multi-cloud, and really applications' workloads for a cloud environment. I'm John Furrier here in theCUBE studios in Palo Alto, thanks for watching. (spirited orchestral music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Hello everyone and welcome back to theCube's live coverage of ServiceNow Knowledge 18 here in Las Vegas. I'm your host Rebacca Knight along with my co-host Dave Vellante, and we are theCube. We are the leader in live tech coverage. We're joined by Sean Caron. He is the principal architect of Linium, at Linium. Thanks so much for coming on theCube again, you're welcome back. >> My second time, and thank you very much for the opportunity. I've really been looking forward to it all week. >> Awesome, Good to have you back. >> We love to hear that. So tell us about Linium and what you do as principal architect. >> Sure, so we are a gold services and sales partner of ServiceNow. Been in the ServiceNow space for about nine years total. And we specialize in helping organizations do digital transformations. So they want to take the platform and really get maximum value from that and that's both a technology discussion, but it's also a organizational change discussion, and you know can be a process discussion. All those kind of things are things that we help our customers with. >> We've been talking a lot about the technology but the organizational change is really what fascinates me. Can you tell, can you just talk about a lot of the organizational change challenges that customers are facing, and they come to you. >> You've got it right. So we've been in this business for 18 years. We started out as a Peregrine partner and also HP, when HP acquired Peregrine, and we noticed that we would get specs from customers and we would nail it. It would be a perfect technical delivery and then six months later when you talk to the customer, they weren't using the product. They didn't get any value from the investment that they made. So we started to engineer a process and we do that around, you know we look at the structure. Where is this project going to land? What's the structure around it? Who supports it? What's your culture? Do you have a culture of dedication to accuracy or customer service? If you don't have those kind of things, we can help build those in your organization. And of course that also gets to helping you find talent, right. So if you need the right people, we can help with that process. Helping you define business best practice process for your organization. Those are all things we work with customers every day and frankly we don't do technology projects. We only do a project where we know when we deliver the technology that that structure will be there to catch it and get value from it. >> So you were recently acquired by Ness Digital Engineering, >> Correct >> Which is really an interesting name for a company. Tell us more about the motivation for that acquisition and how things have changed, and what the future looks like. >> So for the first 17 years of our business we were a privately held company and we grew organically, and we did a great job at that. I mean we became several hundred employees across the U.S. and a couple in AMIA, and a couple in Canada. But to really take the next step right, we saw, we had a vision of what we wanted to do, to take that next step was going to require an equity investment of some type. So we started probably about this time last year, talking to organizations. Ness was one of the first ones that we met and it became immediately apparent that they were a great fit for us. So they have about, well with us about 4,000 people across the world. They're not a billion dollar company right. So their culture is very similar to our culture. They do digital engineering projects, industrial scale, you know hard core grade digital engineering projects, and they tend to focus on platforms that are front of the business, so customer touching. They own the platform under Standard & Poor's right, so they built that. So Standard Poor's ratings, all that information flows in, they do the ratings based on that. That's something they built. PayPal, they do a lot of work in the payments industry. But they didn't really do much on the backend right. The operations that keep all the lights on and obviously that's a great fit for Linium, where we would come in with the ServiceNow platform and help them with that process. So that really worked out well. It was a great fit for us. >> So how do you guys compete? What's your difference relative to, you've been here a while in this ecosystem. It's started to get crowded. How do you, what's your secret sauce? How do you guys compete? >> So our goal is always to try and stay 12 months ahead of where ServiceNow is going. In the past couple of years, that really has been around user experience. Really designing experiences with the platform that are intuitive, that don't require a lot of training, that allow people to approach the platform and get value from it very quickly. Whether that's end users, or our customer's customers. Those kind of things, really, and that's in our DNA. That's a big part of what we do is design these experiences and do them in a way that really help our customers get value. I would say, you know looking forward, so the buzzword that we've heard around here this week is DevOps right, and we see, and one of the things that Ness does very well is DevOps engineering. I think next year will be the knowledge of DevOps. It will be what everybody's talkin' about. ServiceNow will have a lot more throw-weight in that space. So really that's where we're going. We're helping people get that continuous integration, continuous deployment process using ServiceNow as a foundation. >> CJ Desai laid out the roadmap in more detail than I had seen publicly anyway, and we were talking to him and he said, "Look the motivation really came from the ecosystem." You know obviously the customers as well, but the ecosystem as well, wanted better visibility on what was coming, because you guys have to plan for that. You're tryin' to fill white space. You're tryin' to fill a vacuum. So I wondered if you could talk about that. It's a two-edged coin though right? I mean, but having that visibility has to be a godsend. >> Right and we found that when we are some number of months ahead of ServiceNow, we work very well with them. We, you know obviously, like any large ServiceNow partner, we're very plugged in to where they're going. Their roadmap sets our direction and the kind of things that we can do. But it enables conversations, especially DevOps, and user experience too, enabled conversations at new levels within the organization and that's a big differentiator for us. >> But so, what I'm trying to understand is you guys have to make a call on where to put your investments and your resources, and you don't want to, you've said a couple of times, you're ahead of ServiceNow by, let's say N months, six months, 12 months, 9 months, whatever it is. You don't want to develop something and put too much into something that they're just going to replace in a few months. >> Right. >> Dave: So how do you keep that innovation engine going on your end? >> That right, so it takes a lot of research. We have a person whose dedicated job at our organization is Chief Innovation Officer. She spends her entire day talking to customers, hearing what buzzwords are in the industry, looking and talking to ServiceNow, looking at where they're going. So how can we be positioned when ServiceNow gets there 'cause to deliver services, that's not an instant on right. If the technology shows up tomorrow in the next release, to be able to deliver services for that, you have to start well in advance to actually be able to do that, to understand the process, and the structure, and what's required. >> I see, okay so by being ahead of ServiceNow, what you mean is you're going to develop capabilities that plug in to their release when it hits. >> So that we can deliver to what they have, >> Not things that are duplicative, but things that are, add value when it hits. >> Yeah, I mean ServiceNow comes out with, let's say automated testing. That's something they want to really, they want to get into the automated testing market. That's a discipline. You can't be instant on with that and if you want to have credibility with customers, you have to have trained people. You've got to be six months ahead to be able to step into that world and get value from the platform. >> So take the DevOps example that we heard Pat Casey talk about yesterday. So you guys are preparing for that now obviously. >> Yes. >> And how will you go about it? How will that change your customers world? If can take us through an example. >> So obviously DevOps is, you know it's the big accelerator. It's the idea of we're going to do what we've always done and we're going to do it in timeframes that are minutes or hours, as opposed to weeks, or months, or even years right, so it's a big ramp up. So understanding how to put that in play is a big deal. If you're a startup, alright so one of the themes of DevOps is the two pizza team right. You should never have teams bigger than you can feed with a couple of pizzas. If you're a startup and you already got a two pizza team it's easy to do DevOps. You build it into your culture and away you go. But our customers, you know many of our customers, one we were talkin' about here, talking to here at the show, 130 year old firm and they want to do DevOps. So what's that on-ramp? How do you figure that out? One of our new colleagues from Ness, who has been in the DevOps world for a while says, "You know, it's all about unlearning stuff." Because in order to move into this world, you got to unlearn that old world. >> Well right, it is a mindset. >> It is, it's a culture. >> So how, and one that will be very tricky for a 130 year old firm that maybe doesn't order pizzas that often (chuckling) for it's team. So how do you do that? I mean that's a challenge. >> We're working diligently on having a roadmap to onboard DevOps into existing organizations. The secret really tends to be, start with a NET new project and introduce DevOps into those kind of projects. Build one, build two, build three now you've got a culture of DevOps and you can start then to do some of the unlearning and the retrofitting right. But it's very difficult. You can't really take an existing projects and transform how they do their work. Which is what DevOps is all about. >> No, but in a lot of the companies that I've talked to that have, you know hundred plus year old companies that want to do DevOps right. A lot of times, and I wonder if this has been your experience, it's the Ops guys learning Dev, as opposed to the Dev guys learning Ops. I mean the Dev guys like, "Yeah, yeah we can do infrastructure as code, that's fine", but then you've got all these Ops guys runnin' around. So it's a urgency to retrain the Ops guys, who are eager to learn, most of 'em. The ones that aren't probably in trouble. >> Will do something else. >> So I often joke about OpsDev versus DevOps. What's your experience? >> So I think the big difference is Ops guys are trained from the day they take that job to, you know shun failure right. Failure of a system is a big problem. In DevOps it's going to happen. Not only is it going to happen but the best DevOps practitioners create failure. >> Break stuff (laughing) >> Yeah, you know Netflix kind of has this famous program called Chaos Monkey, when it runs running, turn stuff off right, and how do you respond to that. And that's a big leap culturally and structurally for the Ops guys to get over that. You know the idea is we break stuff, but we learn from that, and not only do I learn from that, but I spread that knowledge across the organization. And that's where ServiceNow steps in right, because they know when things are broken, 'cause they're tied to monitoring, and they got this great knowledge capability to hook up the information we learn from how that broke. So what better testing could we have done so that we could have avoided that break? Or if it's a enforced break, what could we have learned about how to respond to that more quickly? You know the classic example is when AWS lost their east availability center and Netflix kept tickin' because they had lost their east availability center through Chaos Monkey a half a dozen times. >> Right >> It was old hat, and everybody else kind of went dark right. So that idea, and enabling that with the ServiceNow platform is a great opportunity. We really see ServiceNow as the context, the engine with all the knowledge about when things happen, how to fix them, and how to record the knowledge that you learn. >> Give us an example of a company, I mean you're talking about simple, streamlined, intuitive tech, no-training required, so give us some examples of some of the most creative uses. >> I'll give you a great example. So, we have a center in Atlanta. We have some folks in Atlanta. And of course if your in Atlanta, you love Chick-fil-a, and maybe if you're anywhere else you love Chick-fil-a. And they had an issue, which was they have franchisees, and their franchises are different from McDonald's, where you might have one franchisee at McDonald's that owns 200 restaurants. They have a lot of power, market power, and they don't share information with any other franchisee, 'cause that's differentiating for them. Chick-fil-a doesn't do that. The maximum number of restaurants you can own as a Chick-fil-a franchisee I believe is three. It's a number like that. So their franchisees are incented to talk to each other and share information. "Hey I found a better way to clean the ice cream machine", or something like that or to fix a problem. So they were looking to build a portal that they could use to both answer questions from the organization to the franchisees, but allow the franchisees to talk to each other. That kind of a thing has to be zero training right, because the people who are on that might be store managers, but it could be, you know the teenager who runs the point of sale terminal and is havin' a problem with that, so it's really got to be intuitive. So we spent a lot of time with them. We actually, it was we brought one of our designers, so we have UI, UX designers, experience designers, and we were in the sales meeting, and we're having a discussion about what they need, and he's kind of heads down typin' on his computer. And they're kind of lookin' at him like, what's up with this guy right, he's not payin' attention. >> He's designing the interface. >> These guys pay attention to everything. He's lookin' at the logo as we're walkin' in, the colors that are on the wall, the way they talk about themselves. So about an hour into the meeting we got a pause and he just kind of picks his head up and goes, "You mean like this?" And turned his computer around and he had a prototype that he built in the meeting of this really easy to use process. >> Very cool. >> Sean: So that was our intro to Chick-fil-a. >> Your sales guy must'a hated that. (hosts laughing) >> No, no, it was, I'll tell you what, so it was competitive, we have multiple competitors, who were going for that business, when he turned that computer around, the sale was done. >> Dave: Boom. >> We were done, right. They looked at that and said, This is, you know it's not perfect clearly, but this is what we need. >> This is the kind of company we want to work with. >> Exactly, well and that, you know part of that is there are partners in the ecosystem who come in and say, "We can do anything. "Tell us what you want." We are much more consultative and we'll come in and be prescriptive and say this is what you should do, and it's a differentiator for us. It's something we do differently. >> Well Sean that's a great note to end on. Thanks so much for coming on theCUBE again. >> It's been great, I really enjoyed my time. >> We'll look forward to having you back at Knowledge 19. >> Terrific, I will certainly be here. >> Great, I'm Rebecca Knight for Dave Vellante. We will have more of theCUBE's live coverage of ServiceNow Knowledge 18 in just a little bit. (electronic music)

okay we're back here live at IBM information on demand this is the cube our flagship program would go out to the advanced extracted signal from the noise this is SiliconANGLE and booking bonds production exclusive coverage of information on demand we have a crowd chatting on right now go to crouch at net / IBM iod this is a chat web app mobile version coming so I saw the complaints earlier be part of the conversation to log in and share your opinion with us ask questions a lot of folks on there right now great engagements with all that all the comments go to the public timeline of LinkedIn or Twitter wherever you sign in on to the hashtag IBM iod we'll be watching that I'm John Furyk gentleman my coach Dave vellante and we have Marsha Connor on who's the principle of sense of I grew she's also an author and she writes about the topic welcome to the queue thank you glad to be here so what is social business I mean you know we love we love talking about social business but it's kind of like you had this term web 2.0 which is everyone argued about you had big data which everyone kind of argued about which actually Israel 30 it's a real market social business which is kind of an elusive term what the hell does it mean is that Twitter or Facebook is it social media consultants is the real value there since this is the kind of question that everyone's talking about and we're talking about so what's your take on that >> my take is very simple for way too many years decades when people go to work they have to leave their personality their heart their cares their relationships in the car or in the subway or however they got to work that day and social business is really the first opportunity we have to be human beings at work we're allowed to actually talk about the things we care about to be able to bring our interests and our passions into the conversation to be real trustworthy people and what happens as a result of that is that for the first time ever there is an acceleration in the workplace because people can actually be their full selves it seems so simple only because the the backlash or the way that we have worked for so long has been so strong and so overpowering that we almost equates not being human with what business is so the idea of social and business being together it seems a little off we assume that business is human is inhuman but the idea of bringing them together is a huge step in the right direction and it opens up the possibility of actually doing great things >> there should be some anti social >> Jeff chick just say we maybe software in commenting about it's almost too social right now people need to kind of bring that personality to work so it's very interesting day what's your take on this I mean you're an analyst you look at the market is social business really mean what's your take on that yeah I think it slowly rabbids to me it's just it's second nature right i mean i remember the conversations not that long ago it's probably 2006-2007 what's the ROI on social media and do we really want to apply it to business and then so what happened was people just did it right and when they did it they said this surely works and we're getting productivity gains and people are happier and it's just a sort of a natural progression of what we're doing in our everyday lives so I just think to me the real opportunity is now okay what's the future what can you do with all this data were collecting and how can you actually affect you know changes within organizations and feedback to people and power them in different ways so that's kind of you know what I think about it I mean does that make sense to you >> it does actually I take the almost opposite view though it's not that they're in fighting with one another but the idea is that we need to figure out what we need to remove not add so it's not that we have all this new data and we can actually be doing more stuff but the question becomes for me and their organizations that I work with this what can we remove what are the policies that the nonsense that happens in work every single day that shouldn't be there is only there because we don't have a better way a more trustworthy more human way of actually working together so it's incredibly liberating or incredibly open from our perspective simply because it's it's less >> processes you haven't evolved to adopt >> so you're saying the business ooh the permeation of social networking within organizations that's not true for >> all organizations right i mean when >> they're starting with a green field the >> business processes are very social right >> about 70 people though and all of a sudden somebody says we need an HR department we need that the number was 50 >> 70 actually well especially for organizations that have aspirations of growing very very large and they get to this point where they believe that they have to put these things in place because there's this expectation that business means heavy process organized codified and I'm not saying that there aren't some benefits of actually having some order amid the chaos there's absolutely benefit there but we need to be thinking about what is needed at human scale versus what is the building or the organization itself need to be maintained to keep going >> saying if they take a small startup that >> so you're very social they've got social tools in place as they grow your day they muck it up just that what you see >> that is what I'm saying one of my clients a number of years ago I pulled me well actually I overheard this and then I had a conversation with him off line he pulled me aside who said you know what you really do is you make work not suck and he said it so candidly and it's a leader in a very large corporation I thought to myself wait a minute I had never really thought about it that way but for the large part that's people in the organization's feel like the amount of time that each of us spend on actually just maintaining the organization it's time that we could be using for far better things and so if we can start moving away from that maintaining of the organizational rigor we can actually start using that in those ingenious skills back to what we're doing >> example i was using about the use of the >> so the startup of the green sheet of paper the better example is the big company that you're sort of overlaying these social processes on top of how are you helping them sort of break the old habits maybe >> talk about what they should be doing >> yeah well the most specific thing I do is I very rigorously scalpel like actually organizations tell me of going in and identify one of the things keeping people from being able to do work that they were hired to do when's the last time you hired an idiot when I >> asked that question >> question we were just talking about I >> I won't answer that >> I ask that question actually very often is sometimes actually just speaking to a very large group and somebody always gonna raise their hand there's time the story and that's a little uncomfortable at times but the reality is we hire the best and brightest people that we know we try to find great people but something happens about two and a half weeks in all of a sudden they just get stupid right all of a sudden they can't do whatever it is >> very social they don't blame yourselves someone else I didn't I didn't improve that guy but let's not over though but some finish the story here because you're basically saying we inject stupidity into the system it's generally >> Yes we inject the stupidity in but we put them in cages in large part we ask people to say leave a large part of who they are what they're capable of doing somewhere else and so what happens is the longer you work for an organization the more likely you are to be incredibly invested in your community you either work at the Boy Scouts or or you you know you lead a program inside of your community to do better food services a well we have we find consistently is the more you feel like you've been stuffed into a desk drawer the more likely you are to still bring those capabilities to some other part of your life that's just ridiculous don't get me wrong I'm a big fan of people doing great things in our communities but it's really sad to me to understand that we can't bring those same capabilities that same ingenuity into the workplace where people were hired to actually share those gifts >> okay so so but so you go with the scalpel okay oh let me tell you a policy manual how do you not cut to the bone sami do you absolutely there are you not cut into muscle well such an example yeah that would help us I'd say most organizations have no idea where that muscle on that bone is it i mean that's actually a great question so so it at a more abstract level let me just say that there's i have been handed paper-based read notebooks from some of the world's largest organizations where you are going page by page by page of the policies the procedures and sometimes those are handed out in the new employee orientation other times that they're just assumed where people have to actually to start learning from you know social learning from the people around them as to what's the appropriate thing or what's an inappropriate thing to be doing and if you start actually looking at those you discover time and again that those policies those guidelines this what is establishing the culture are largely based on one person doing something really stupid and that person probably especially given a social business world probably wouldn't have done it a second time in this new environment but in this particular case they did that and all of a sudden we had to actually like in a community after a wreck now a stop sign are you had to you know put up a light because you hate had the lawyers be involved in this there's an incredibly yeah covering your ass you're overreacting simply because we haven't had better processes in the past one of the things we know for example of social tools is that when somebody says something stupid their co-workers almost always rise up and say that's not right anymore that's incorrect or here's a better way to do it the only thing worse than people saying dumb things work is people believing dumb things work and with these tools we all of a sudden have the opportunity to correct those things where people do smart things again so from a scalpel like perspective it's looking at what are the underpinnings of our work what are the things that are controlling how we work not only just the processes but the behaviors that are there and to actually look through them systematically and to remove everything that's there then the next step is really talking with people and being able to prove to them that when they work in different sorts of ways that they will be treated in different sorts of ways and frankly that becomes a harder exercise the larger the corporation >> chat from grant case how does an >> so question from our crowd organization start that journey especially in a firm like financial services where that might already be part of the culture >> is always part of the culture you advances in financial services I work with a very large business the business ensure for example and what we found is that when they start introducing social tools into the workplace they weren't so worried that people are going to say dumb things they were more worried that their employees were like cats under the stairs that nobody would say anything because they were so terrified of what would happen as a result of them saying that and so we had to do is are introducing into the culture of that organization processes that would say we care about what you think we had a woman for example say that when we went to her and we've been told that she would not participate in something like this when we went to her she said you know I've been putting in my desk drawers literally for over 20 years all the cool things I've wanted to do in this organization and you're telling me i can now blog about those things or i can actually put them in a micro and and we said yes and says well i really don't believe you so it wasn't even mad saying we can do it but well I get in trouble you know I get in trouble and I not even get troubled by the big police but just well I get you know looks from my peers and so we actually started giving her examples of some of her peers and some of her colleagues who were doing different sorts of things in her being able to build trust that this was a workable system >> does crowdsourcing just Twitter does a success of Facebook and LinkedIn the social networks nicely the rise of the hashtag which has become a great waited for people to dial into folksonomies of groups or active conversations does that change and give people more of a it removed some dissidents if you will about okay it's okay to be public does that change the game a little bit on social software is it validated or just a scare people further into the into their caves we see on crowd chatter there's more anonymous viewers that happy boo actually sign in it has become kind of like an arena we mentioned sometimes it's like gladiator the thought leaders battling it out for you know we seen this on forums right higher see chat rooms you know so people just want to watch yeah >> so what you're what you've done though is reduce this down to one personality type and the reality is that we have have extroverts and introverts in our workplace we have people who are comfortable talking in public and those who aren't and so the simple introduction of online tools brings to our workplaces a way for people who are uncomfortable sharing to do that with a little bit more anonymity and to have a lot more comfort and being able to do that they may not want actually look people in the eye when they say these things but it doesn't mean they don't have valuable things to say I was asked by a journalist a number of years ago if I believe that the introduction of social tools would all of a sudden mean the end of meetings in the workplace and I said absolutely not but what you're now going to hear is the voice of people who never spoke up at meetings and to actually have a well-rounded workforce you need to have the voice of all those brilliant people you hired >> wait a moment yes I think I said all the forecast for cars was limited because they didn't people think enough chauffeurs to drive them you know nobody will buy them still is gonna bite it's a big barrier small market it's not enough show first is a wreck yeah >> but if we can actually provide a venue for everybody to be able to contribute at work one that's either in person or online we're just opening up the possibility of who could >> okay so what's the craziest thing you've seen both on two spectrums with social business successful crazy and crazy good meaning kind of like Anna Steve Jobs craziness way to a crazy fail you have to name names he just can talk about the use cases I mean by that or you can talk about the names if you want to the appoint people out crazy good wow they really levered all the aspects of the data they they were innovative just or lucky or two they put a lot of money into it and it could failed miserably yeah okay I think I can come up with two I'm not so sure and the crazy like in woohoo were in Vegas kind of crazy example though give me a few minutes wrapping up with that one okay though I will say that in a large financial services organization that the Vice President of Human Resources i actually have photos of her going around to every single cube on her floor and taking person and taking photos of each employee for their personal profiles because people are so terrified of actually even doing taking that step that she walked around the floor of her building and took pictures of every single person and that may not see a saying some crazy in Las Vegas sense but it was pretty radical for her to be doing that but it showed her commitment to be able to do this so let me give you a different example electronics firm we're going through I'm so a large global not going to name names but you can probably actually make some guesses we're going through some horrible financial problems and it was just a right around the time they introduced social business tools into their workforce and when they did that the the pretty much the person who is supporting that initiative would send out emails to move people toward working in a social way at he would send out emails that would be fairly scandalous actually and they would say things like it's about to get on the press that we were about to lose dot dot dot at all his email would say and then there was a link that they had to actually go into the social system to be able to learn the rest of the things he not only had a blast actually eliminating the whole lot of link faded the entire over a hundred thousand personal work for that's good pageviews assassin twitter / ma been going on to in a matter of days they had pretty much converted the entire organization to be using these tools and as a result of that they believe that they actually didn't have all the problems they would have had had they not done this because for the first time ever people weren't just sitting behind their desks and being terrified for their lives going back to your crowdsource point they were there together and they actually could talk about what's going on they created what we call rumor central which is a practice that I bring into many organizations they actually had a group within the organization that anybody could ask anything they could actually ask the question what is the rumor you know they could say here's the rumor I've heard how accurate is it and then somebody in the organization would actually be there to answer that and be able to correct that and be able to fix that and it was a beautiful example of how that works >> from the crowd chat along the line of >> we had a question coming question we just had to run the people extroverts and introverts so the question is what is the value of a lurker in social business is there one well if it's a person kind of hanging around question was that that's a great question oh yeah >> I thought you're muttering under your breath like a lurker okay the problem with workers he said she's yelling in the cheap seats what we know about lurkers is that traditionally they are people who wouldn't raise their voice in a meeting that they are also somebody who is just going to you know sit and listen but what happens is it that person then goes to the restroom or goes to the cafeteria or actually even on the bus that night or in their community and they talk about what they've learned so the idea of measuring people as lurkers or participants is a very shallow way of looking at it because it only means that the value is in the conversation of their having at that time or that they didn't comment or they didn't contribute that that is what provides value it's a skewed perspective on engagement it's a cute perspective of what brings value to the organization if they can be listening which is a truly an untapped skill and most of our workforces that they can be listening and then they can actually be thinking also a crazy idea and actually then be able to figure out what they are doing and then be able to do that all the value there but I'm I actually am a little bit weary sometimes when I see the people who are commenting all the time >> it's like lurker so in social context if you can see the participation if someone's just just online with an online button you don't even know if they're listening right so I think that's I think that's the key point if they're listening and they're active that's an interesting data point so like one things that Dave and I look at and lurkers is are they in context to the conversation and are they active so getting that active data is interesting in context to what's being measured so if we look at a cluster of a crowd like a crowdsource crouched at hey if someone's actively talking they're in in the in context >> I still think that's an extroverted way of looking at it I still think it's a way of saying that that engagement is only by hearing or seeing their voice so let me give you the example so I work with a large an organization the intelligence community I'll leave it at that and one of the things that they track is where people actually look online and as a result of that they're actually able to follow the thread from the first thing that they looked at what do they look at next and they have and are able to establish breadcrumbs as to what someone looked at first and then what they looked at next and then what they did after that and what happened is along that whole continuum somebody eventually at some point in time will do sort of the equivalent of a like or they'll add a comment somewhere along that path but then if you go in and you were looking at that first document and you then get to see sort of like amazon recommends other books you can then say other people who looked at this document looked at these things next now that first person may have not commented for a very long time if ever but the value to the other people in that organization by understanding the other amazing and wonderful and helpful or not helpful things they saw afterwards brought incredible value to the organization and that was a a passive way of actually sharing and helping and narrowing down and helping people make better decisions but it was by no means the level of active engagements that so often we are looking at as the only measure of value in the organization Marcia we got cut on time here our next guest but amazing conversation folks go see her blog guys awesome thanks for the comment we'd go another hour okay but they'll give you the final word what is just share with the folks out there your view of the future next couple years what's going to come around the corner connect the dots what do you see happening is going to be an implosion the kind of Biggs is going to be more growth what's going to happen what do you think is going to how is this industry industry how is social business going to shape up >> well I'm if we're talking about the next few years I think that we are all in for a big wake-up call not only are we starting to see the structures and the systems around us failing from my government and economy all sorts of different ways a perspective but if we look at epochs of history this happens consistently and we're about the end of this particular epoch and I say that not as a doom and gloom er at all but to say that I believe for the first time we have the tools and technologies to be able to do something significant to be actually be able to rewrite how organizations work what work means how human beings get to interact to be able to make change in the world that has been cordoned off for way too long and so as these systems the systems that aren't workings are falling away we have the opportunity to actually be able to lean in to be able to live in and to be able to say I want to be a human being 24 hours a day I don't want to be a number or a chess pawn any longer and i am going to actually make a difference in the work i do and i'm going to do that throughout my day every day so i'm i'm incredibly excited about the prospect of what we can do it requires us all to actually look inside figure out who we are figure out what we want to do and actually be able to go do that social destruction of old with new new >> humanization of the crowd and waves of innovations we always say tave you don't get out in front of you become driftwood and there will be some destruction in business models we love it this is social business this is the cube exclusive coverage from information on demand ibm's conference here in Las Vegas is the cube we write back with our next guest right thank you the cube