>>mhm. What the special cube conversation here in Palo alto, I'm john Kerry host of the cube. We're here talking about kubernetes Cloud native and all things Cloud, cloud enterprise amir Sure VP of product and morgan Stanley is with me and we are great to have you on the cube. Thanks for coming on. I appreciate you taking the time, >>appreciate it, john good to be here. You >>know, cloud Native obviously super hot right now as the edges around the corner, you're seeing people looking at five G looking at amazon's wavelength outposts you've got as you got a lot of cloud companies really pushing distributed computing and I think one of the things that people really are getting into is okay, how do I take the cloud and re factor my business and then that's one business side then, the technical side. Okay, How do I do it? Like it's not that easy. Right. So it sounds, it sounds really easy to just go to move to the cloud. This is something that's been a big problem. So I know you guys in the center of all this uh and you've got, you know, microservices, kubernetes at the core of this, take a minute to introduce the company, what you guys do then I want to get into some specific questions. >>Mhm, of course. Well, bob Sani is a startup? Silicon Valley startup and what we do is automate system configuration that's typically worked at an engineer does and take lengthy and if done incorrectly at least to a lot of errors and cost overruns and the user experience problems. We completely automate that using an Ai and ml back end so that the engineering can focus on writing code and not worry about having to tune the little pieces working together. >>You know, I love the, I was talking to a V. C on our last uh startup showcase, cloud startup showcase and uh really prominent VC and he was talking about down stack up stack benefits and he says if you're going to be a down stack um, provider, you got to solve a problem. It has to be a big problem that people don't want to deal with. So, and you start getting into some of the systems configuration when you have automation at the center of this as a table stakes item problems are cropping up as new use cases are emerging. Can you talk about some of the problems that you guys see that you solve for developers and companies, >>of course. So they're basically, they're, the problem expresses itself in a number of domains. The first one is that he who pays the bills is separate from he who consumes the resources. It's the engineers that consume the resources and the incentives are to deliver code rapidly and deliver code that works well, but they don't really care about paying the bills. And then the CFO office sees the bills and there's a disparity between the two. The reason that creates a problem, a business problem is that the developers uh, will over provision stuff, uh to make sure that everything works and uh, they don't want to get caught in the middle of the night. You know, the bill comes due at the end of the month or into the quarter and then the CFO has smoke coming out of his ears because there's been clawed overruns. Then the reaction happens to all right, let's cut costs. And then, you know, there's an edict that comes down that says everything, reduce everything by 30%. So people go across and give a haircut to everything. So what happens next to systems out of balance? There's allocation resource misallocation and uh, systems start uh, suffering. So the customers become unhappy. And ironically, if you're not provisioned correctly, Not ironically, but maybe understandably, customers start suffering and that leads to a revenue problem down the line if you have too many problems unhappy. So you have to be very careful about how you cut costs and how you apportion resources. So both the revenue side is happy and it costs are happy because it all comes down to product experience and what the customers consume. You >>know, that's something that everyone who's done. Cloud development knows, you know, whose fault is it? You know, it's this fall. But now you can actually see the services you leave a switch open or, you know, I'm oversimplifying it. But, you know, you experiment services, you can the bills can just have massive, you know, overruns and then, and then you got to call the cloud company and you gotta call the engineers and say why did you do this? You got to get a refund or or the bad one. Bad apple could ruin it for everyone as you, as you highlighted over the bigger companies. So I have to ask you mean everyone lives this. How do companies have cost overruns? Is their patterns that you see that you guys wrote software 4-1, automate the obvious ones. Is there is there are certain things that you know always happen. Are there areas that have some indications? So why do, first of all, why do companies have cloud cost overruns? >>That's a great question. And let's start with a bit of history where we came from a pre cloud world, you built your own data centers, which means that you have an upfront Capex cost and you spend the money and you were forced to live within the needs that your data center provided. You really couldn't spend anymore. That provided kind of a predictable expenditure bottle it came in big chunks. But you know what, your budget was going to be four years from now, three years from now. And you built for that with the cloud computing, Your consumption is now on on demand basis and it's api enabled. So the developer can just ask for more resources. So without any kind of tools that tell the developer here is x amount of CPU or X amount of memory that you need for this particular service, that for it to deliver the right uh, performance that for the customer. The developers incentivized to basically give it a lot more than the application needs. Why? Because the developer doesn't want to pick up service tickets. He's incentivizing delivering functionality quickly and moving on to next project, not in optimizing costs. So that creates kind of uh an agency problem that the guy that actually controls how research are consumed is not incentivized to control the consumption of these resources. And we see that across the board in every company, engineers, engineering organization is a separate organization than the financial organization. So the control place is different. The consumption place and it breaks down the patterns are over provisions. And what we want to do is give engineers the tools to consume precisely the right amount of resources for the service level objectives that they have, given that you want a transaction rate of X and the literacy rate of Why here's how you configure your cloud infrastructure. So the application delivers according to the sls with the least possible resources consumed. >>So on this tool you guys have in the software you guys have, how how do you guys go to mark with that, you target the business buyer or the developer themselves and and how do you handle the developers say, I don't want anyone looking over my shoulder. I'm gonna go, I'm gonna have a blank check to do whatever it takes, um how do you guys roll that out because actually the business benefits are significant controlling the budget, I get that. Um how do you guys rolling this out? How do people engage with you? What's your strategy? >>Right. Are there, is the application owner, is the guy that owns the PML for the application? It tends to be a VP level or a senior director person that owns a SAAS platform and he or she is responsible for delivering good products to the market and delivering good financial results to the CFO So in that person of everything is rolled up, but that person will always favor the revenue site, which means consume more resources than you need in order to maximize customer happiness, therefore faster growth and uh they do that while sacrificing the cost side. So by giving the product owner the optimization tools autonomous of optimization tools that Sandy has, we allow him or her to deliver the right experience to the customer, with the right sufficient resources and address both the performance and the cost side of equation simultaneously, >>awesome. Can you talk about the impact c I C D s having in the cloud native computing on the optimization cycle? Um Obviously, you know, shifting left for security, we hear a lot of that, you're hearing a lot of more microservices being spun up, spun down automatically. Uh I'll see kubernetes clusters are going mainstream, you start to see a lot more dynamic uh activity if you if you in these new workflows, what is the impact of these new CSC D cloud? Native computing on the optimization cycle? >>C i c D is there to enable a fast delivery of software features basically. Uh So, you know, we have a combination of get get ups where you can just pull down repositories, libraries, open source projects from left and right. And using glue code, developers can deliver functionality really quick. In fact, microservices are there in service of that capability, deliver functionality quickly by being able to build functional blocks and then through a piece you put everything together. So ci cd is just accelerates the software delivery code. Between the time the boss says, give me an application until the application team plus the devops team plus SRE team puts it out in production. Now we can do this really quickly. The problem is though, nobody optimizes in the process. So when we deliver 1.0 in six months or less, we've done zero in terms of optimization and at one point, oh, becomes a way that we go through QA in many cases, unfortunately. And it also becomes a way that we go through the optimization. The customer screams that you eyes Laghi, you know, the throughput is really slow and we tinker and tinker and tinker and by the time it typically goes through a 12 month cycle of maturation, we get that system stability in the right performance with a I and machine learning that a person has enabled. We can deliver that, we can shrink that time out considerably. In fact, uh you know what we're going to announce in q khan is something that be called Kite storm is the ability to uh install our product and kubernetes environment in roughly 20 minutes and within two days you get the results. So before you have this optimization cycle that was going on for a very long time now that it's frank down and because of Ci Cd, you know, you don't have the luxury of waiting and the system itself can become part of the way of contributing system. The system being the uh ai ml service, that the presiding deliveries can be uh part and parcel of the Ci cd pipeline, that optimizes the code and gives you the right configuration and you get to go. So >>you guys are really getting down and injecting in some uh instrumentation for metadata around key areas. That right. Is that kind of how it's working? Are you getting in there with codes going to watch? Um how was it working under the hood? Can you just give me a quick example of, you know, how this would play out and what people might expect, how it would handle, >>of course. So what the way we optimize application performance is we have to have a metric against which we measure performance. That metric is an S L O service level, objective and in a kubernetes environment, we typically tap into Prometheus, which is the metrics gathering place metrics database for kubernetes workloads and we really focus on red metrics, the rate of transactions, the error rate and the for delay or latency. So we focus on these three metrics and what we have to do is inject a small container, it's an open source container into the application work space that we call that a container. Servo. Servo interacts with Prometheus to get the metrics and then it talks to our back end to tell the M L engine what's happening and then L engine and does this analysis and comes back with a new configuration which then servo implements in a canary instance. So the Canary instances where we run our experiments and we compare it against the main line, Which the application is doing after roughly 20 generations or so. The Bellingen Learns what part of the problem space to focus on in order to optimize to deliver optimal results. And then it very quickly comes to the right set of solutions to try and it tries those inside uh inside the canary instance and when it finds the optimal solution, it gives the recommendation back to the application team or alternatively, when you have enough trust in the tiny you can ought to promote it into mainline that >>gets the learning in there is a great example of some cloud native action. I want to get into some examples with your customer, but before we get there, I want to ask you, since I have you here, if you don't mind, what is cloud native mean these days, because you know, cloud native become kind of much cloud computing, um which essentially go move to the cloud, but as people start developing in the cloud where there's real new benefits, people talk about the word cloud native, could you take a quick minute to define? What is cloud Native, Does that even mean? What does cloud native mean? >>I'll try to give you my understanding government, we could get into a bit of philosophy. Uh Yeah, that's good. But basically cloud Native means it's, your application is built for the cloud and it takes advantages of the inherent benefits that a cloud environment can give you, which means that you can grow and shrink resources on the fly, if you built your application correctly, that you can scale up and scale down, you're a number of instances very quickly and uh, everything has taken advantage of a P I S so initially that was kind of done inside of the environment. Uh AWS Ec two is a perfect example of that. Kubernetes shifted cloud native to container its workload because it allows for rapid, more, rapid deployment and even enables or it takes advantage of a more rapid development cycle as we look forward. Cloud Native is more likely to be a surplus environment where you write functions and the backend systems of the cloud service provider, just give you that capability and you don't have to worry about maintaining and managing a fleet of any sort, whether it's VMS or containers, that's where it's gonna go. Currently we are to contain our space >>so as you start getting into the service molly good land, which we've been playing with, loves that as you get into that, that's going to accelerate more data. So I gotta ask you as you get into more of this this month, I will say monitoring or observe ability, how we want to look at it. You gotta get at the data. This becomes a critical part of solving a lot of problems and also making sure the machine learning is learning the right thing. How do you view that you guys over there? Because I think everyone is like getting that cloud native and it's not hard sell to say that's all good, but we can go back, you know, the expression ships created ships and then you have shipwrecks, you know, there's always a double edged sword here. So what's the downside? If you don't get the data right? >>Uh well, so the for us, the problem is not too much data, it's lack of data. So if you don't get data right is you don't have enough data. And the places where optimization cannot be automated is where the transaction rates are slow, where you don't have enough fruit. But coming into the application and it really becomes difficult to optimize that application with any kind of speed. You have to be able to profile the application long enough to know what moves its needle and in order for you to hit the S. L. O. Targets. So it's not too much data, it's not enough data. That seems to be the problem. And there are a lot of applications that are expensive to run but have a low throughput. And I would uh in all cases actually in every customer environment that have been in, where that's been the case if the application is just over provision, if you have a low throughput environment and it's costing too much, don't use ml to solve it. That's a wrong application of the technology. Just take a sledgehammer and back your resources by 50%, see what happens. And if that thing breaks back it again, until you find the baggage point. >>Exactly for you over prison, you bang it back down again. It's like the old school now with the cloud. Take me through some examples when you guys had some success, obviously you guys are in the right area right now, you're seeing a lot of people looking at this area to do that in some cases like changing the whole data center and respect of their business. But as you get it with customers with the app side, what some successes can you share some of the use cases, what you guys are being successful, your customers can get some examples. >>Yeah. So well known financial software for midsize businesses that that does accounting. It's uh there are customer during a large fleet and this product has been around for a while. It's not a container ice product. This product runs on VMS. Angela is a large component of that. So the problem for this particular vendor has been that they run on heterogeneous fleet that the application has been a along around for a very long time. And as new instance types on AWS have come in, developers have used those. So the fleet itself is quite heterogeneous and depending on the time of the day and what kind of reports are being run by organisations, they, the mix of resources that the applications need are different. So uh when we started analyzing the stack, we started we started looking at three different tiers, we looked at the database level, we looked at the job of mid tier and we looked at the web front end. And uh one of the things that became counterproductive is that m L. Discovered that using for the mid tier using larger instances but fear of a lot for better performance and lower cost and uh typically your gut feel is to go with smaller instances and more of a larger fleet if you would. But in this case, what the ML produced was completely counter intuitive And the net result for the customer was 78% cost reduction while agency went down by 10%. So think about it that you're, the response time is less, uh 10% less but your costs are down almost 80% 78% in this case. And the other are the fact that happened in the job of mitt here is that we improve garbage collection significantly and because whenever garbage collection happens on a JV M it takes a pause and that from a customer perspective it reflects as downtime because the machines are not responding so by tuning garbage collection Andrzej VMS across this very large fleet we were able to recover over 5000 minutes and month across the entire fleet. So uh, these are some substantial savings and this is what the right application of machine learning on a large fleet can do for assess business. >>And so talk about this fleet dynamic, You mentioned several lists. How do you see the future evolving for you guys? Where are you skating to where the puck is? As the expression goes? Um obviously with server list is going to have essentially unlimited fleets potentially That's gonna put a lot of power in the hands of developers. Okay. And people building experiences, What's the next five years look like for you guys? >>So I'm looking at the product from a product perspective, the service market depends on the mercy of the cloud service provider and typically the algorithms that they use. Uh basically they keep very few instances warm for you until you're the rate of api calls goes up and they start they start uh start turning on VMS are containers for you and then the system becomes more responsive over time. One place that we can optimize the service environment is give predictability of what the cyclicality of load is. So we can pre provision those instances and warm up the engine before the loads come into the system always stays responsive. You may have noticed that some of your apps on your phone that when you start them up, they may have a start up like a minute or two. Especially if it's a it's a terror gap. What's happening in those cases that you're starting an api calls goes in containers being started up for you to start up that instance, not enough of our warm to give you that rapid response. And that can lead to customer churn. So by by analyzing what the load on the overall load of the system is and pre provision the system. We can prevent the downtime uh prevent the lag to start up black on the downside. Which when you know when the usage goes down, it doesn't make sense to keep that many instances up. So we can talk to the back in infrastructure and the commission of those VMS in order to make to prevent cost creeps basically. So that's one place that we're thinking about extending our technology. >>So it's like, it's like the classic example where people say, oh during black monday everyone searches to do e commerce. You guys are thinking about it on A level that's a user centric kind of use case where you look at the application and be smart about what the expectation is on any given situation and then flex the resources on that. Is that right? That by getting right? So if it's your example, the app is a good one. If I wanted to load fast, that's the expectation. It better load fast. >>Yes, that's exactly but more romantic. So I use valentine's day and flowers my example. But you know, it doesn't have to be annual cycles. It can be daily cycles or hourly cycles. And all those patterns are learning about by an Ml back in. >>Alright, so I gotta ask you love the, this, this this new concept because most people think auto scaling right? Because that's a server concept. Can auto scale or database. Okay. On a scale up, you're getting down to the point where, okay, we'll keep the engines warm, getting more detailed. How do you explain this versus a concept like auto scaling. Is it the same as a cousins? >>They're they're basically the way they're expressed, it's the same technology but their way there expressed is different. So uh in a cooper native environment, the H. B A is your auto scaler basically in response to the need, response more instances and you get more containers going on. What happens as services? Less environment is you're unaware of the underpinnings that do that scale up for you. But there is an auto Scaler in place that does that scale up for you. So the question becomes that we're in a stack from a customer's perspective, are you talking about if you imagine your instances we're dealing with the H. B. A. If you're managing at the functional level we have to have api calls on the service provider's infrastructure to pre warm up the engine before the load comes. >>I love I love this under the hood is kind of love new dynamics kind of the same wine, new bottle but still computer science, still coding, still cool and relevant to make these experiences great. Thanks for coming on this cube conversation. I really appreciate it. Take a minute to put a plug in for the company. What are you guys doing in terms of status funding scale employees, what are you looking for? And if someone's watching this and there should be a customer of you guys, what what's, what's, what's going on in their world? What tells them that they need to be calling you? >>Yeah, so we're serious. Dave we've had the privilege of uh, our we've been privileged by having a very good success with large enterprises. Uh, if you go to our website, you'll see the logos of who we have, we will be at Q khan and there were going to be actively targeting the mid market or smaller kubernetes instances, as I mentioned, it's gonna take about 20 minutes to get started and we'll show the results in two hours. And our goal is for our customers to deliver the best user experience in terms of performance, reliability. Uh, so that they, they delight their customers in return and they do so without breaking the bank. So deliver excellent products, do it at the most efficient way possible, deliver a good financial results for your stakeholders. This is what we do. So we encourage anybody who is running a SAS company to come and take a look at us because we think we can help them and we can accelerate there. The growth at the lower cost >>and the last thing people need is have someone coming breathing down their necks saying, hey, we're getting overcharged. Why are you guys screwing up when they're not? They're trying to make a great experience. And I think this is kind of where people really want to do push the envelope and not have to go back and revisit the cost overruns, which if it's actually a good sign if you get some cost overruns here and there because you're experimenting. But again, you don't want to get out of control. >>You don't want to be a visual like the U. S. Debt. >>Exactly. I'm here. Thank you for coming on. Great. We'll see a coupe con. The key will be there in person is a hybrid event. So uh, coupon is gonna be awesome and thanks for coming on the key. Appreciate it. >>John is a pleasure. Thank you for having me on. >>Okay. I'm john fryer with acute here in Palo alto California remote interview with upsetting hot startup series. I'm sure they're gonna do well in the right spot in the market. Really well poisoned cloud Native. Thanks for watching. Yeah.

>>what? Hello, I'm john free with the cube. I want to welcome Conrad Feldman, the founder and Ceo of Kwan cast here to kick off the quan cast industry summit on the demise of third party cookies. The events called the cookie conundrum, a recipe for success. The changing advertising landscape, super relevant conversation just now. More than ever. Conrad welcome to your own program kicking this off. Thanks for holding this event. It's a pleasure. Great to chat with you today. So a big fan been following your company since the founding of it. Been analytics is always the prize of any data driven company. Media. Anything's all data driven now. Um, talk about the open internet because now more than ever it's under siege. As I, as I mentioned in my open, um, we've been seeing the democratization, a new trend of decentralization. We're starting to see um, you know, everyone's present online now, Clay Shirky wrote a book called, here comes everyone in 2005. Well everyone's here. Right? So you know, we're here, it's gonna be more open. But yet people are looking at as close right now. You're seeing the big players, um, or in the data. What's your vision of this open internet? >>Well, an open internet exists for everyone. And if you think about the evolution of the internet, when the internet was created for the first time really in history, anyone that had access to the internet could publish the content, whatever they were interested in and could find an audience. And of course that's grown to where we are today, where five billion people around the world are able to engage in all sorts of content, whether that's entertainment or education, news, movies. What's perhaps not so widely understood is that most of that content is paid for by advertising and there's a lot of systems that support advertising on the open Internet and some of those are under siege today certainly. >>And what's the big pressure point? Is it just more control the data? Is it just that these walled gardens are wanting to, you know, suck the audience in there? Is that monetization driving it? What's where's the friction? >>Well, the challenges is sort of the accumulation of power into a really small number of now giant corporations who have actually reduced a lot of the friction that marketers have in spending their money effectively. And it means that those companies are capturing a disproportionate spend of the ad budgets that fund digital content. So the problem is if more of the money goes to them, less of its going to independent content creators. It's actually getting harder for independent voices to emerge and be heard. And so that's the real challenges. That has more power consolidates into just a limited number of tech giants. The funding path for the open Internet becomes constrained and there'll be less choice for consumers without having to pay for subscriptions. >>Everyone knows the more data you have the better and certainly, but the centralized power when the trend is going the other way, the consensus is everyone wants to be decentralized more truth, more trust all this is being talked about on the heels of the google's news around, you know, getting rid of third party cookies and others have followed suit. Um, what does this mean? I mean, this cookies have been the major vehicle for tracking and getting that kind of data. What is gonna be replaced with what is this all about? And can you share with us what the future will look like? >>Sure, Well, just as advertising funds the open Internet is advertising technology that supports that advertising spend. It supports sort of the business of advertising that funds the open Internet. And within all of that technology is the need for different systems to be able to align around um the identification of for example, a consumer, Have they been to this site before? Have they seen an ad before? So there's all of these different systems that might be used for advertising for measurement, for attribution, for creating personalization. And historically they've relied upon the third party cookie as the mechanism for synchronization. Well, the third party cookie has been in decline for some time. It's already mostly gone from actually apple safari browser, but google's chrome has so much control over how people access the internet. And so it was when Google announced that chrome was going to deprecate the third party cookie, that it really sort of focus the minds of the industry in terms of finding alternative ways to tailor content and ultimately to just simply measure the effectiveness of advertising. And so there's an enormous amount of um innovation taking place right now to find alternative solutions. >>You know, some are saying that the free open internet was pretty much killed when, you know, the big comes like facebook and google started bringing all this data and kind of pulls all sucks all the auction in the room, so to speak. What's this mean with cookies now getting, getting rid of um, by google has an impact publishers because is it helpful? I mean hurtful. I mean, where's the where is that, what the publisher impact? >>Well, I don't think anyone really knows right now. So first of all, cookies weren't necessarily a very good solution to the sort of the challenge of maintaining state and understanding those sorts of the delivery of advertising and so on. It's just the one that's commonly used, I think for different publishers it may mean different things. But many publishers need to be able to demonstrate the value and the effectiveness of the advertising solutions that they deliver. So they'll be innovating in terms of how they use their first party data. They'll be continuing to use contextual solutions that have long been used to create advertising relevant, relevant. I think the big question of course is how we're going to measure it that any of this is effective at all because everyone relies upon measuring advertising effectiveness to justify capturing those budgets in the first place. >>You know, you mentioned contextual come up a lot also in the other interviews we've done with the folks in the around the internet around this topic of machine learning is a big 12 What is the impact of this with the modernization of the solution? You mentioned cookies? Okay cookies, old technology. But the mechanisms in this ecosystem around it or not, it funds the open internet. What is that modern solution that goes that next level? Is it contextual metadata? Is that shared systems? What's the it's the modernization of that. >>It's all of those and and more. There's no there's no single solution to replace the third party cookie. There'll be a combination of solutions. Part of that will be alternative identity mechanisms. So you know, you will start to see more registration wars to access content so that you have what's called a deterministic identify there will be statistical models so called probabilistic models, contextual has always been important. It will become more important and it will be combined with we use contextual combining natural language processing with machine learning models to really understand the detailed context of different pages across the internet. You'll also see the use of first party data and there are discussions about shared data services as well. I think there's gonna be a whole set of different innovations that will need to inter operate and it's going to be an evolutionary process as people get used to using these different systems to satisfy the different stages of the media fulfillment cycle from research and planning to activation to measurement. >>You know, you put up walled gardens. I want to just touch on the on on this kind of concept of walled gardens and and and and compare and contrast that with the demand for community, open internet has always fostered a community vibe. You see network effects mostly in distinct user communities or subnets of sub networks. If you will kind of walled gardens became that kind of group get together but then became more of a media solution to make the user is the product, as they say, facebook's a great example, right? People talk about facebook and from that misinformation abuse walled garden is not the best thing happening right now in the world, but yet is there any other other choice? That's how they're going to make money? But yet everyone wants trust, truth community. Are they usually exclusive? How do you see this evolving, what's your take? >>Well, I think the open internet is a, is a forum where anyone can have their voice, uh, put their voice out there and have it discovered and it's in that regard, it's a it's a force for good look. I think there are there are challenges, obviously in terms of some of the some of the optimization that takes place with inside the walled gardens, which is, is sort of optimized to drive engagement can have some unintended consequences. Um obviously that's something that's, that's broadly being discussed today and the impact on society, but sort of more at a more pointed level, it's just the absorption of advertising dollars. There's a finite amount of money from advertisers. It's estimated to be $400 billion this year in digital advertising. So it's a huge amount of money in terms of funding the open Internet, which sounds great except for its increasingly concentrated in a tiny number of companies. And so, you know, our job at Quan cast as champions of the free and open Internet is to help direct money effectively to publishers across the open internet and give advertisers a reliable, repeatable way of accessing the audiences that they care about in the environment they care about and delivering advertising results. >>It's a publisher, we care a lot about what our audience wants and try to serve them and listen to them. If we could get the data, we want that data and then also broker in the monetization with advertisers, who might want to reach that audience in whatever way. So this brings up the question of, you know, automation and role of data. You know, this is a huge thing to having that data closed loop, if you will for for publishers. But yet most publishers are small, some niche. And even as they can become super large, they don't have all the data and more, the more data, the better the machine learning. So what's the answer to this as it goes forward? How do we get there? What's the dots that that we need to connect to get that future state? >>So I think it takes it takes companies working together effectively. I think a really important part of it is, is a more direct conversation with consumers. We've seen that change beginning to happen over the past few years with the introduction of regulations that require clear communication to consumers about the data that's captured. And y and I think that creates an opportunity to explain to your audience is the way in which content is funded. So I think that consumer that consumer conversation will be part of the collective solution. >>You know, I want to as we wind down this kickoff segment, get your thoughts and vision around um, the evolution of the internet and you guys have done some great work at quan Cast is well documented, but everyone used to talk about traffic by traffic, then it became cost of acquisitions. PPC search. This is either mechanisms that people have been using for a long, long time, then you know, your connections but audience is about traffic, audience traffic. If this if my family is online, doesn't it become about networks and the people. So I want to get your thoughts and your vision because if community is going to be more important than people agree that it is and things are gonna be decentralized, more openness, more voices to be heard. You need to dress ability. The formation of networks and groups become super important. What's your vision on that? >>So my vision is to create relevance and utility for consumers. I think that's one of the things that's often forgotten is that when we make advertising more relevant and useful for consumers, it automatically fulfils the objectives that publishers and marketers have, everyone wins when advertising is more relevant. And our vision is to make advertising relevant across the entire open internet so that that ad supported model can continue to flourish and that five billion and hopefully many more billions in the future, people around the world have access to high quality, diverse content. >>If someone asked you Conrad, what is quant cast doing to make the open internet viable now that cookies are going away? What's the answer? >>So well, the cookie pieces is a central piece of it in terms of finding solutions that will enable sort of planning activation and measurement post cookies and we have a lot of innovation going on. There were also working with a range of industry bodies and our and our partners to build solutions for this. What we're really trying to do is to make buying the open internet as straightforward for marketers as it is today and buying the walled gardens. The reason the walled gardens capture so much money is they made it really easy for marketers to get results, marketers would like to be able to spend their money across all of the diverse publishes the open internet. You know, our job at Comcast is to make it just as easy to effectively spend money in funding the content that they really care about in reaching the audiences that they want. >>Great stuff. Great Mission. Conrad, thanks for coming on. Conrad Feldmann founder and Ceo here at the cookie conundrum recipe for success event, Quant Cast Industry summit on the demise of third party cookies. Thank you. Conrad appreciate it. Thank you. Yeah, I'm john ferrier, stay with us for more on the industry event around the middle cookies. Mhm Yeah, yeah, thank you. Mhm. Welcome back to the Qantas industry summit on the demise of third party cookies, the cookie conundrum, a recipe for success. I'm john furrier host of the cube, the changing landscape of advertising is here and shit Gupta, founder of you of digital is joining us chief. Thanks for coming on this segment. Really appreciate, I know you're busy, you've got two young kids as well as providing education to the digital industry, you got some kids to take care of and train them to. So welcome to the cube conversation here as part of the program. >>Yeah, thanks for having me excited to be here. >>So the office of the changing landscape of advertising really centers around the open to walled garden mindset of the web and the big power players. We know the big 34 tech players dominate the marketplace so clearly in a major inflection point and we've seen this movie before Web mobile revolution which was basically a reply platform NG of capabilities. But now we're in an error of re factoring the industry, not re platt forming a complete changing over of the value proposition. So a lot at stake here as this open web, open internet, global internet evolves. What are your, what's your take on this, this industry proposals out there that are talking to this specific cookie issue? What does it mean? And what proposals are out there? >>Yeah, so, you know, I I really view the identity proposals and kind of to to kind of groups, two separate groups. So on one side you have what the walled gardens are doing and really that's being led by google. Right, so google um you know, introduce something called the privacy sandbox when they announced that they would be deprecating third party cookies uh as part of the privacy sandbox, they've had a number of proposals unfortunately, or you know, however you want to say they're all bird themed for some reason, I don't know why. Um but the one, the bird theme proposal that they've chosen to move forward with is called flock, which stands for Federated learning of cohorts. And essentially what it all boils down to is google is moving forward with cohort level learning and understanding of users in the future after third party cookies, unlike what we've been accustomed to in this space, which is a user level understanding of people and what they're doing online for targeting tracking purposes. And so that's on one side of the equation, it's what google is doing with flock and privacy sandbox now on the other side is, you know, things like unified I. D. Two point or the work that I. D five is doing around building new identity frameworks for the entire space that actually can still get down to the user level. Right? And so again, unified I. D. Two point oh comes to mind because it's the one that's probably got the most adoption in the space. It's an open source framework. So the idea is that it's free and pretty much publicly available to anybody that wants to use it and unified, I need to point out again is user level. So it's it's basically taking data that's authenticated data from users across various websites you know that are logging in and taking those authenticated users to create some kind of identity map. And so if you think about those two work streams right, you've got the walled gardens and or you know, google with flock on one side and then you've got unified I. D. Two point oh and other I. D. Frameworks for the open internet. On the other side, you've got these two very differing type of approaches to identity in the future. Again on the google side it's cohort level, it's going to be built into chrome. Um The idea is that you can pretty much do a lot of the things that we do with advertising today, but now you're just doing it at a group level so that you're protecting privacy, whereas on the other side of the open internet you're still getting down to the user level. Um And that's pretty powerful. But the the issue there is scale, right? We know that a lot of people are not logged in on lots of websites. I think the stat that I saw is under five of all website traffic is authenticated. So really if you if you simplify things you boil it all down, you have kind of these two very differing approaches. >>I guess the question it really comes down to what alternatives are out there for cookies and which ones do you think will be more successful? Because I think, you know, the consensus is at least from my reporting, in my view, is that the world agrees. Let's make it open, Which one is going to be better. >>Yeah, that's a great question, john So as I mentioned, right, we have we have to kind of work streams here, we've got the walled garden work streams, work stream being led by google and their work around flock, and then we've got the open internet, right? Let's say unified I. D to kind of represents that. I personally don't believe that there is a right answer or an endgame here. I don't think that one of them wins over the other, frankly, I think that, you know, first of all, you have those two frameworks, neither of them are perfect, they're both flawed in their own ways. There are pros and cons to both of them. And so what we're starting to see now is you have other companies kind of coming in and building on top of both of them as kind of a hybrid solution. Right? So they're saying, hey, we use, you know, an open I. D. Framework in this way to get down to the user level and use that authenticated data and that's important. But we don't have all the scale. So now we go to google and we go to flock to kind of fill the scale. Oh and hey, by the way, we have some of our own special sauce, right? We have some of our own data, we have some of our own partnerships, we're gonna bring that in and layer it on top. Right? And so really where I think things are headed is the right answer, frankly, is not one or the other. It's a little mishmash of both. With a little extra something on top. I think that's that's what we're starting to see out of a lot of companies in the space. And I think that's frankly where we're headed. >>What do you think the industry will evolve to, in your opinion? Because I think this is gonna, you can't ignore the big guys on this because these programmatic you mentioned also the data is there. But what do you think the market will evolve to with this, with this conundrum? >>So, so I think john where we're headed? You know, I think we're right now we're having this existential existential crisis, right? About identity in this industry, because our world is being turned upside down, all the mechanisms that we've used for years and years are being thrown out the window and we're being told they were gonna have new mechanisms, Right? So cookies are going away device ids are going away and now we got to come up with new things and so the world is being turned upside down and everything that you read about in the trades and you know, we're here talking about it, right? Like everyone's always talking about identity right now, where do I think this is going if I was to look into my crystal ball, you know, this is how I would kind of play this out. If you think about identity today. Right? Forget about all the changes. Just think about it now and maybe a few years before today, Identity for marketers in my opinion has been a little bit of a checkbox activity. Right? It's been hey, um, okay, uh, you know ad tech company or a media company, do you have an identity solution? Okay. Tell me a little bit more about it. Okay, Sounds good. That sounds good. Now can we move on and talk about my business and how are you going to drive meaningful outcomes or whatever for my business? And I believe the reason that is, is because identity is a little abstract, right? It's not something that you can actually get meaningful validation against. It's just something that, you know. Yes, You have it. Okay, great. Let's move on, type of thing. Right. And so that, that's, that's kind of where we've been now, all of a sudden The cookies are going away, the device ids are going away. And so the world is turning upside down in this crisis of how are we going to keep doing what we were doing for the last 10 years in the future. So everyone's talking about it and we're trying to re engineer right? The mechanisms now if I was to look into the crystal ball right 2 3 years from now where I think we're headed is not much is going to change. And what I mean by that john is um uh I think that marketers will still go to companies and say do you have an ID solution? Okay tell me more about it. Okay uh Let me understand a little bit better. Okay you do it this way. Sounds good. Now the ways in which companies are going to do it will be different right now. It's flock and unified I. D. And this and that right. The ways the mechanisms will be a little bit different but the end state right? Like the actual way in which we operate as an industry and kind of like the view of the landscape in my opinion will be very simple or very similar, right? Because marketers will still view it as a tell me you have an ID solution. Make me feel good about it. Help me check the box and let's move on and talk about my business and how you're going to solve for my needs. So I think that's where we're going. That is not by any means to discount this existential moment that we're in. This is a really important moment where we do have to talk about and figure out what we're going to do in the future. My just my viewpoint is that the future will actually not look all that different than the present. >>And I'll say the user base is the audience. Their their data behind it helps create new experiences, machine learning and Ai are going to create those and we have the data you have the sharing it or using it as we're finding shit Gupta great insight dropping some nice gems here. Founder of you of Digital and also the Adjunct professor of Programmatic advertising at Levi School of Business and santa Clara University professor. Thank you for coming dropping the gems here and insight. Thank you. >>Thanks a lot for having me john really appreciate >>it. Thanks for watching. The cooking 100 is the cube host Jon ferrier me. Thanks for watching. Mhm. Yeah. Mhm. Hello welcome back to the cookie conundrum recipe for success and industry conference and summit from Guanacaste on the demise of third party cookies. Got a great industry panel here to break it down chris Gunther Senior Vice president Global Head of programmatic at news corp chris thanks for coming on Zal in Managing Director Solutions at Z axis and Summer Simpson. Vice president Product at quan cast stellar panel. Looking forward to this conversation. Uh thanks for coming on and chatting about the cookie conundrum. Thank you for having us. So chris we'll start with you at news corp obviously a major publisher deprecation of third party cookies affects everyone. You guys have a ton of traffic, ton of audience across multiple formats. Um, tell us about the impact to you guys and the reliance he has had on them. And what are you gonna do to prepare for this next level change? >>Sure. I mean, I think like everyone in this industry there's uh a significant reliance and I think it's something that a lot of talk about audience targeting but obviously that reliance on third party cookies pervasive across the whole at tech ecosystem Martek stack. And so you know, we have to think about how that impact vendor vendors, we work with what it means in terms of use cases across marketing, across advertising, across site experience. So, you know, without a doubt, it it's it's significant, but you know, we look at it as listen, it's disruptive, uh, disruption and change is always a little scary. Um, but overall it's a, it's a long overdue reset. I mean, I think that, you know, our perspective is that the cookies, as we all know was it was a crutch, right sort of a technology being used in way it shouldn't. Um, and so as we look at what's going to happen presumably after Jan 2022 then it's, it's a good way to kind of fix on some bad practices practices that lead to data leakage, um, practice or devalue for our perspective, some of the, you know, we offered as as publishers and I think that this is a key thing is that we're not just looking to as we look at the post gender world, not just kind of recreating the prior world because the prior world was flawed or I guess you could say the current world since it hasn't changed yet. But the current world is flawed. Let's not just not, you know, let's not just replicate that. Let's make sure that, you know, third party cookie goes away. Other work around like fingerprinting and things like that. You know, also go away so philosophically, that's where our heads at. And so as we look at how we are preparing, you know, you look at what are the core building blocks of preparing for this world. Obviously one of the key ones is privacy compliance. Like how do we treat our users with consent? Yeah, obviously. Are we um aligned with the regulatory environments? Yeah. In some ways we're not looking just a Jan 2022, but Jan 23 where there's gonna be the majority of our audiences we covered by regulation. And so I think from regulation up to data gathering to data activation, all built around an internal identifier that we've developed that allows us to have a consistent look at our users whether they're logged in or obviously anonymous. So it's really looking across all those components across all our sites and in all in a privacy compliant way. So a lot of work to be done, a lot of work in progress. But we're >>excited about what's going on. I like how you framed at Old world or next gen kind of the current situation kind of flawed. And as you think about programmatic, the concept is mind blowing and what needs to be done. So we'll come back to that because I think that original content view is certainly relevant, a huge investment and you've got great content and audience consuming it from a major media standpoint. Get your perspective on the impact because you've got clients who want to get their their message out in front of the audience at the right time, at the right place and the right context. Right, So your privacy, you got consent, all these things kind of boiling up. How do you help clients prepare? Because now they can go direct to the consumer. Everyone, everyone has a megaphone, now, everyone's, everyone's here, everyone's connected. So how are you impacted by this new notion? >>You know, if if the cookie list future was a tic tac, dance will be dancing right now, and at least into the next year, um this has been top of mind for us and our clients for quite some time, but I think as each day passes, the picture becomes clearer and more in focus. Uh the end of the third party cookie does not mean the end of programmatic. Um so clients work with us in transforming their investments into real business outcomes based on our expertise and based on our tech. So we continue to be in a great position to lead to educate, to partner and to grow with them. Um, along this uh cookie list future, the impact will be all encompassing in changing the ways we do things now and also accelerating the things that we've already been building on. So we take it from the top planning will have a huge impact because it's gonna start becoming more strategic around real business outcomes. Uh where Omni channel, So clients want to drive outcomes, drew multiple touch points of a consumer's journey, whether it has programmatic, whether it has uh cookie free environment, like connected tv, digital home audio, gaming and so forth. So we're going to see more of these strategic holistic plans. Creative will have a lot of impact. It will start becoming more important with creative testing. Creative insights. You know, creative in itself is cookie list. So there will be more focused on how to drive uh brand dialogue to connect to consumers with less targeting. With less cookies, with the cohesiveness of holistic planning. Creative can align through multiple channels and lastly, the role of a. I will become increasingly important. You know, we've always looked to build our tech our products to complement new and existing technology as well as the client's own data and text back to deliver these outcomes for them. And ai in its core it's just taking input data uh and having an output of your desired outcome. So input data could be dSP data beyond cookies such as browser such as location, such as contextual or publisher taking clients first party data, first party crm data like store visitation, sales, site activity. Um and using that to optimize in real time regardless of what vendor or what channel we're on. Um So as we're learning more about this cookie list dance, we're helping our clients on the steps of it and also introducing our own moves. >>That's awesome. Data is going to be a key value proposition, connecting in with content real time. Great stuff. Somewhere with your background in journalism and you're the tech VP of product at quan cast. You have the keys to the kingdom over there. It's interesting Journalism is about truth and good content original content. But now you have a data challenge problem opportunity on both sides, brands and publishers coming together. It's a data problem in a way it's a it's a tech stack, not so much just getting the right as to show up at the right place the right time. It's really bigger than that now. What's your take on this? >>Um you know, >>so first >>I think that consumers already sort of like except that there is a reasonable value exchange for their data in order to access free content. Right? And that's that's a critical piece for us to all kind of like understand over the past. Hi guys, probably two years since even even before the G. D. P. R. We've been doing a ton of discovery with customers, both publishers and marketers. Um and so you know, we've kind of known this, this cookie going away thing has been coming. Um And you know, Google's announcement just kind of confirmed it and it's been, it's been really, really interesting since Google's announcement, how the conversations have changed with with our customers and other folks that we talked to. And I've almost gone from being like a product manager to a therapist because there's such an emotional response. Um you know, from the marketing perspective, there's real fear there. There's like, oh my God, how you know, it's not just about, you know, delivering ads, it's about how do I control frequency? How do I, how do I measure, you know, success? Because the technology has has grown so much over the years to really give marketers the ability to deliver personalized advertising, good content, right. The consumers um and be able to monitor it and control it so that it's not too too intrusive on the publisher perspective side, we see slightly different response. It's more of a yes, right. You know, we're taking back control and we're going to stop the data leakage, we're going to get the value back for our inventory. Um and that both things are a good thing, but if it's, if it's not managed, it's going to be like ships passing in the night, right? In terms of um of, you know, they're there, them coming together, right, and that's the critical pieces that they have to come together. They have to get closer, you got to cut out a lot of that loom escape in the middle so that they can talk to each other and understand what's the value exchange happening between marketers and publishers and how do we do that without cookies? >>It's a fascinating, I love love your insight there. I think it's so relevant and it's got broader implications because, you know, if you look at how data's impact, some of these big structural changes and re factoring of industries, look at cyber security, you know, no one wants to share their data, but now if they share they get more insight, more machine learning, benefit more ai benefit. So now we have the sharing notion, but that goes against counter the big guys that want to wall garden, they want to hoard all the data and and control that to provide their own personalization. So you have this confluence of, hey, I want to hoard the data and then now I want to share the data. So so christmas summer you're in the, in the wheelhouse, you got original content and there's other providers out there. So is there the sharing model coming with privacy and these kinds of services? Is the open, come back again? How do you guys see this uh confluence of open versus walled gardens, because you need the data to make machine learning good. >>So I'll start uh start off, I mean, listen, I think you have to give credit to the walled gardens have created, I think as we look as publishers, what are we offering to our clients, what are we offering to the buy side? We need to be compelling. We shouldn't just be uh yeah, actually as journalists, I think that there is a case of the importance of funding journalism. Um but ultimately we need to make sure we're meeting the KPI is and the business needs of the buy side. And I think around that it is the sort of three core pillars that its ease of access, its scope of of activation and targeting and finally measurable results. So as I think is us as an individual publishers, so we have, we have multiple publications. So we do have scale. But then in partnership with other publishers perhaps to organizations like pre bid, you know, I think we can, you know, we're trying to address that and I think we can offer something that's compelling um, and transparent in terms of what these results are. But obviously, you know, I want to make sure it's clear transparent terms of results, but obviously where there's privacy in terms of the data and I think the form, you know, I think we've all heard a lot like data clean rooms, a lot of them out there flogging those wears. I think there's something valuable but you know, I think it's the right who is sort of the right partner or partners um and ultimately who allows us to get as close as possible to the buy side. And so that we can share that data for targeting, share it for perhaps for measurement, but obviously all in a privacy compliant >>way summer, what's your take on this? Because you talk about the future of the open internet democratization, the network effect that we're seeing in Vire al Itty and across multiple on the on the channels. Is that pointed out what's happening? That's the distribution now. So um that's almost an open garden model. So it's like um yeah, >>yeah, it's it's um you know, back in the day, you know, um knight ridder who was who was the first group that I that I worked for, um you know, each of those individual properties, um we're not hugely valuable on their own from a digital perspective, but together as a unit, they became valuable, right, and got scale for advertisers. Now we're in a place where, you know, I kind of think that each of those big networks are going to have to come together and work together to compare in size to the, to the world gardens. Um, and yeah, this is something that we've talked about before and an open garden. Um, I think that's the, that's the definitely the right route to take. And I and I agree with chris it's, it's about publishers getting as close to the market. Is it possible working with the tech companies that enable them to do that and doing so in a very privacy centric >>way. So how do we bring the brands and agencies together to get ready for third party cookies? Because there is a therapist moment here of it's gonna be okay. The parachute will open. The future is not gonna be as as grim. Um, it's a real opportunity. But if managed properly, what's your take on this is just more first party data strategy and what's your assessment of this? >>So we collaborated right now with ball grants on how did this still very complex cookie list future. Um, you know what's going to happen in the future? 2, 6 steps that we can take right now and market should take. Um, The first step is to gather intel on what's working on your current campaign, analyzing the data sets across cookie free environment. So you can translate those tactics eventually when the cookies do go away. So we have to look at things like temperature or time analysis. We could look at log level data. We could look at site analytics data. We can look at brand measurement tools and how creative really impacts the campaign success. The second thing we can look at is geo targeting strategies. The geo target strategy has been uh underrated because the granularity and geo data could go down all the way to the local level, even beyond zip code. So for example the census black data and this is especially important for CPG brands. So we're working closely with the client teams to understand not only the online data but the offline data and how we can utilize that in the future. Uh We want to optimize investments around uh markets that are working so strong markets and then test and underperforming markets. The third thing we can look at is contextual. So contextual by itself is cookie free. Uh We could build on small scale usage to test and learn various keywords and content categories based sets. Working closely with partners to find ways to leverage their data to mimic audiences that you are trying to target right now with cookies. Um the 4th 1 is publisher data or publisher targeting. So working with your publishers that you have strong relationships with who can curate similar audiences using their own first party data and conducting RFs to understand the scale and reach against your audience and their future role maps. So work with your top publishers based on historical data to try to recreate your best strategies. The 15 and I think this is very important is first party data, you know, that's going to matter more than ever. In the calculus future brands will need to think about how to access and developed the first party data starting with the consumers seeing a value in exchange for the information. It's a gold mine and understanding of consumer, their intent, the journey um and you need a really great data science team to extract insights out of that data, which will be crucial. So partner with strategic onboarding vendors and vet their ability to accept first party data into a cleaner environment for targeting for modeling for insight. And lastly, the six thing that we can do is begin to inform prospect prospecting by dedicating test budget to start gaining learnings about cookie list 11 place that we can start and it is under invested right now is Safari and Firefox. They have been calculus for quite some time so you can start here and begin testing here. Uh work with your data scientist team to understand the right mix is to to target and start exploring other channels outside of um just programmatic cookies like CTV digital, out of home radio gaming and so forth. So those are the six steps that we're taking right now with our clients to uh prepare and plan for the cookie list future. >>So chris let's go back to you. What's the solution here? Is there one, is there multiple solutions? What's the future look like for a cookie was future? >>Uh I think the one certain answers, they're definitely not just one solution. Um as we all know right now there there seems to be endless solutions, a lot of ideas out there, proposals with the W three C uh work happening within other industry bodies uh you know private companies solutions being offered and you know, it's a little bit of it's enough to make everyone's head spin and to try to track it to understand and understand the impact. And as a publisher were obviously a lot of people are knocking on our door. Uh they're saying, hey our solution is one that is going to bring in lots of money, you know, the all the buy side is going to use it. This is the one like I ma call to spend um, and so expect here and so far is that none of these solutions are I think everyone is still testing and learning no one on the buy side from our, from our knowledge is really committed to one or a few. It's all about a testing stage. I think that, you know, putting aside all that noise, I think what matters the most to us as publisher is actually something summer mentioned before. It's about control. You know, if we're going to work with a again, outside of our sort of, you know, internal identifier work that we're doing is we're going to work with an outside party or outside approach doesn't give us control as a publisher to ensure that it is, we control the data from our users. There isn't that data leakage, it's probably compliant. What information gets shared out there. What is it, what's released within within the bid stream? Uh If it is something that's attached to a somewhat declared user registered user that if that then is not somehow amplified or leverage off on another site in a way that is leveraging bit stream data or fingerprinting and going against. I think that the spirit of what we're trying to do in a post third party cookie world so that those controls are critical and I think they have those controls, his publisher, we have collectively be disciplined in what solutions that we we test out and what we eventually adopt. But even when the adoption point arrives, uh definitely it will not be one. There will be multiple because it's just too many use cases to address >>great, great insight there from, from you guys, news corp summer. Let's get back to you. I want to get your thoughts. You've been in many waves of innovation ups and downs were on a new one. Now we talked about the open internet democratization. Journalism is under a lot of pressure now, but there's now a wave of quality people really leaning in towards fighting misinformation, understanding truth and community and date is at the heart of it. What do you see as the new future for journalists, reward journalism is our ways their path forward. >>So there's uh, there's what I hope is going to happen. Um, and then I'm just gonna ignore what could write. Um, you know, there's there's a trend in market right now, a number of fronts, right? So there are marketers who are leaning into wanting to spend their marketing dollars with quality journalists, focusing on bipac owned and operated, really leaning into into supporting those businesses that have been uh, those publishers that have been ignored for years. I really hope that this trend continues. Um We are leaning into into helping um, marketers curate that supply right? And really, uh, you know, speak with their dollars about the things that that they support. Um, and uh, and and value right in market. So I'm hoping that that trend continues and it's not just sort of like a marketing blip. Um, but we will do everything possible to kind of like encourage that behavior and and give people the information they need to find, you know, truly high quality journalism. >>That's awesome chris Summer. Thanks for coming on and sharing your insight on this panel on the cookie list future. Before we go, just quick summary each of you. If you don't mind just giving a quick sound bite or bumper sticker of what we can expect. If you had to throw a prediction For what's going to happen in the next 24 months Chris We'll start with you. >>Uh it's gonna be quite a ride. I think that's an understatement. Um I think that there, I wouldn't be surprised if if google delays the change to the chrome by a couple of months and and may give the industry some much needed time, but no one knows. I guess. I guess I'm not except for someone somewhere deep within chrome. So I think we all have to operate in a way that changes to happen, changes to happen quickly and it's gonna cover across all facets of the industry, all facets of from advertising, marketing. So just be >>prepared. >>Yeah, along the same lines, be prepared, nobody knows what's going to happen in the future. Uh You know, while dancing in this together. Uh I think um for us it's um planning and preparing and also building on what we've already been working on. Um So omni channel ai um creative and I think clients will uh lean more into those different channels, >>awesome. So we'll pick us home, last word. >>I think we're in the throwing spaghetti against the wall stage. Right, so this is a time of discovery of leaning in trying everything out, Learning and iterating as fast as we possibly >>can. Awesome. And I love the cat in the background over your shoulder. Can't stop staring at your wonderful cat. Thanks for coming on chris, Thanks for coming on. This awesome panel industry breakdown of the cookie conundrum. The recipe for success data ai open. Uh The future is here, it's coming, it's coming fast. I'm john fryer with the cube. Thanks for watching. Mhm. Yeah. Mhm. Mhm. Welcome back to the Quant Cast industry summit on the demise of third party cookies. The cookie conundrum, a recipe for success. We're here peter day. The cto of quad cast and crew T cop car, head of product marketing quad cast. Thanks for coming on talking about the changing advertising landscape. >>Thanks for having us. Thank you for having >>us. So we've been hearing this story out to the big players. Want to keep the data, make that centralized control, all the leverage and then you've got the other end. You got the open internet that still wants to be free and valuable for everyone. Uh what's what are you guys doing to solve this problem? Because cookies go away? What's going to happen there? How do people track things you guys are in this business first question? What is quan cast strategies to adapt to third party cookies going away? What's gonna be, what's gonna be the answer? >>Yeah. So uh very rightly said, john the mission, the Qantas mission is the champion of free and open internet. Uh And with that in mind, our approach to this world without third party cookies is really grounded in three fundamental things. Uh First as industry standards, we think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind, we've been participating >>with I. A. B. >>Tech lab, we've been part of their project Triarc. Uh same thing with pre bid, who's kind of trying to figure out the pipes of identity. Di di di di di pipes of uh of the future. Um And then also is W three C, which is the World Wide Web Consortium. Um And our engineers and our engineering team are participating in their weekly meetings trying to figure out what's happening with the browsers and keeping up with the progress they're on things such as google's block. Um The second uh sort of thing is interoperability, as you've mentioned, there are lots of different uh I. D. Solutions that are emerging. You have you I. D. Two point oh, you have live RAM, you have google's flock. Uh And there will be more, there are more and they will continue to be more. Uh We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. Uh The reason really is to meet our customers where they are at today. Our customers use multiple different data management platforms, the mps. Um and that's why we support multiple of those. Um This is not going to be much different than that. We have to meet our customers where we are, where they are at. And then finally, of course, which is at the very heart of who contrast is innovation. Uh As you can imagine being able to take all of these multiple signals in including the I. D. S. And the cohorts, but also others like contextual first party um consent is becoming more and more important. Um And then there are many other signals, like time, language geo location. So all of these signals can help us understand user behavior intent and interests um in absence of 3rd party cookies. However, uh there's there's something to note about this. They're very raw, their complex, they're messy all of these different signals. Um They are changing all the time, they're real time. Um And there's incomplete information isolation. Just one of these signals cannot help you build a true and complete picture. So what you really need is a technology like AI and machine learning to really bring all of these signals together, combine them statistically and get an understanding of user behavior intent and interests and then act on it, be it in terms of providing audience insights um or responding to bid requests and and so on and so forth. So those are sort of the three um fundamentals that our approach is grounded in which is industry standards, interoperability and and innovation. Uh and you know, you have peter here, who is who is the expert So you can dive much deeper into >>it. Is T. T. O. You've got to tell us how is this going to actually work? What are you guys doing from a technology standpoint to help with data driven advertising in a third party cookie list world? >>Well, we've been um This is not a shock, you know, I think anyone who's been close to his space has known that the 3rd Party Cookie has been um uh reducing inequality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really google chrome making a, making the changes that they're gonna be making. So we've been investing in the space for many years. Um and we've had to make a number of hugely diverse investment. So one of them is in how as a marketer, how do I tell if my marketing still working in the world without >>computers? The >>majority of marketers completely reliant on third party cookies today to tell them if they're if they're marketing is working or not. And so we've had to invest heavily and statistical techniques which are closer to kind of economic trick models that markets are used to things like out of home advertising, It's going to establishing whether they're advertising is working or not in a digital environment actually, >>just as >>often, you know, as is often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement has often mistaken precision for accuracy. And there's a real opportunity to kind of see the wood for the trees if you like. And start to come with better methods of measuring the affections of advertising without third party cookies. And in fact to make countless other investments in areas like contextual modeling and and targeting that third party cookies and and uh, connecting directly to publishers rather than going through this kind of bloom escape that's gonna tied together third party cookies. So if I was to enumerate all the investments we've made, I think we'll be here till midnight but we have to make a number of vestments over a number of years and that level investments only increasing at the moment. >>Peter on that contextual. Can you just double click on that and tell us more? >>Yeah, I mean contextual is unfortunately these things, this is really poorly defined. It can mean everything from a publisher saying, hey, trust us, this dissipated about CVS to what's possible now and has only really been possible the last couple of years, which is to build >>statistical >>models of the entire internet based on the content that people are actually consumed. And this type of technology requires massive data processing capabilities. It's able to take advantage of the latest innovations in there is like natural language processing and really gives um computers are kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize, organized the Internet in terms of the types of content of pages. So this type of technology has only been possible the last two years and we've been using contextual signals since our inception, it's always been massively predictive in terms of audience behaviours, in terms of where advertising is likely to work. And so we've been very fortunate to keep the investment going um and take advantage of many of these innovations that have happened in academia and in kind of uh in adjacent areas >>on the ai machine learning aspect, that seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and ai factoring into your platform? >>I think it's, it's how we've always operated right from our interception when we started as a measurement company, the way that we were giving our customers at the time, we were just publishers, just the publisher side of our business insights into who their audience was, were, was using machine learning techniques. And that's never really changed. The foundation of our platform has always been, has always been machine learning from from before. It was cool. A lot of our kind of, a lot of our core teams have backgrounds in machine learning phds in statistics and machine learning and and that really drives our our decision making. I mean, data is only useful if you can make sense of it and if you can organize it and if you can take action on it and to do that at this kind of scout scale, it's absolutely necessary to use machine learning technology. >>So you mentioned contextual also, you know, in advertising, everyone knows in that world that you've got the contextual behavioural dynamics, the behavior that's kind of generally everyone's believing is happening. The consensus is undeniable is that people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't wanna get walled into a walled garden, nobody wants to be in the world, are they want to be free to pop around and visit sites is more horizontal scalability than ever before. Yet, the bigger players are becoming walled garden, vertical platforms. So with future of ai the experience is going to come from this data. So the behavior is out there. How do you get that contextual relevance and provide the horizontal scale that users expect? >>Yeah, I think it's I think it's a really good point and we're definitely this kind of tipping point. We think, in the broader industry, I think, you know, every published right, we're really blessed to work with the biggest publishers in the world, all the way through to my mom's vlog, right? So we get to hear the perspectives of publishers at every scale. I think they consistently tell us the same thing, which is they want to more directly connected consumers, they don't wanna be tied into these walled gardens, which dictate how they must present their content and in some cases what content they're allowed to >>present. >>Um and so our job as a company is to really provide level >>the playing field a little bit, >>provide them the same capabilities they're only used to in the walled gardens, but let's give them more choice in terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively by making their audiences in their environments discoverable by marketers measurable by marketers and connect them as directly as possible to make that kind of ad funded economic model as effective in the open Internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet as it is in social media. It should be as effective for them to reach people in the environment is really high quality content as it is on facebook. And so we invest a lot of a lot of our R and D dollars in making that true. We're now live with the Comcast platform, which does exactly that. And as third party cookies go away, it only um only kind of exaggerated or kind of further emphasizes the need for direct connections between brands and publishers. And so we just wanna build the technology that helps make that true and gives the kind of technology to these marketers and publishers to connect and to deliver great experiences without relying on these kind of walled >>gardens. Yeah, the Director Director, Consumer Director audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for for that's happening in this new world? How do you ingest the content and just this consent uh signaling? >>Uh we were really fortunate to have an amazing, amazing R and D. Team and, you know, we've had to do all sorts to make this, you need to realize our vision. This has meant things like, you know, we have crawlers which scan the entire internet at this point, extract the content of the pages and kind of make sense of it and organize it uh, and organize it for publishers so they can understand how their audiences overlap with potential competitors or collaborators. But more importantly, organize it for marketers. So you can understand what kind of high impact opportunities are there for them there. So, you know, we've had to we've had to build a lot of technology. We've had to build analytics engines, which can get answers back in seconds so that marketers and publishers can kind of interact with their own data and make sense of it and present it in a way that's compelling and help them drive their strategy as well as their execution. We've had to invest in areas like consent management because we believe that a free and open internet is absolutely reliant on trust and therefore we spend a lot of our time thinking about how do we make it easy for end users to understand who has access to their data and easy for end users to be able to opt out. And uh and as a result of that, we've now got the world's most widely adopted adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. Were fortunate enough to have had a large enough R and D budget over the last four or five years, make a number investments, everything from consent and identity through context, your signals through the measurement technologies, which really bring advertisers >>and Publishers places together great insight. Last word for you is what's the what's the customer view here as you bring these new capabilities of the platform, uh what's what are you guys seeing as the highlight uh from a platform perspective? >>So the initial response that we've seen from our customers has been very encouraging, both on the publisher side as well as the marketer side. Um I think, you know, one of the things we hear quite a lot is uh you guys are at least putting forth a solution, an actual solution for us to test Peter mentioned measurement, that really is where we started because you cannot optimize what you cannot measure. Um so that that is where his team has started and we have some measurement very, very uh initial capabilities still in alpha, but they are available in the platform for marketers to test out today. Um so the initial response has been very encouraging. People want to engage with us um of course our, you know, our fundamental value proposition, which is that the Qantas platform was never built to be reliant on on third party data. These stale segments like we operate, we've always operated on real time live data. Um The second thing is, is our premium publisher relationships. We have had the privilege of working like Peter said with some of the um biggest publishers, but we also have a very wide footprint. We have first party tags across um over 100 million plus web and mobile destinations. Um and you know, as you must have heard like that sort of first party footprint is going to come in really handy in a world without third party cookies, we are encouraging all of our customers, publishers and marketers to grow their first party data. Um and so that that's something that's a strong point that customers love about us and and lean into it quite a bit. Um So yeah, the initial response has been great. Of course it doesn't hurt that we've made all these are in the investments. We can talk about consent. Um, and you know, I often say that consent, it sounds simple, but it isn't, there's a lot of technology involved, but there's lots of uh legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, very good response. Initially >>democratization. Everyone's a publisher. Everyone's a media company. They have to think about being a platform. You guys provide that. So I congratulate Peter. Thanks for dropping the gems there. Shruti, thanks for sharing the product highlights. Thanks for, for your time. Thank you. Okay, this is the quan cast industry summit on the demise of third party cookies. And what's next? The cookie conundrum. The recipe for success with Kwan Cast. I'm john free with the cube. Thanks for watching. Mm

>>from around the globe. It's the >>cube >>With digital coverage of IBM think 2021 brought to you by IBM. Hello and welcome back to the cubes coverage of IBM Think 2021 virtual. I'm john for a year host of the cube. We're virtual this year in real life. Soon, right around the corner as we come out of code, we've got a great guest cube alumni jerry, cuomo IBM fellow V P C T O for IBM automation jerry, Great to see you uh nonsense got almost since the early days of the cube. Good to see you, >>john thrilled to be back again. Thank you >>what I love about our conversations. One is your super technical, you've got patents under your belt during the cutting edge. You've been involved in web services and web technologies for a long, long time. You constantly riding the wave and also your creator of a great podcast called the art of automation, which is the subject of this discussion as automation becomes central in cloud operations and hybrid cloud, which is the main theme of this event this year and the industry so great to see you. Uh First team is a little background for the folks that may not know you about your history with IBM and who you are. >>Yeah, so thanks john, So I'm I'm jerry Carrillo, I've been with IBM for about three decades and I started my career at IBM research in Yorktown at the dawn of the internet and I've been incredibly fortunate, as you mentioned to be on the forefront of many technology trends over the last three decades. Internet software middleware, including being one of the founding fathers of web sphere software, uh I recently helped launch the IBM Blockchain initiative and now all about aI powered automation, which actually brings me back to my roots of studying AI and graduate school. So it's kind of come full circle for me, you know, really you know, enjoying the topic. >>You know, these funny, you mentioned aI in graduate school, I was really kind of into a I when I was an undergraduate and get a masters degree in computer science, I kind of went the NBA route. But if you think about what was going on in the eighties during those systems times, a lot of the concepts of systems programming and cloud operations kind of gel well together. So you've got this confluence of computer science and engineering A. K A. Now devops sec cops coming together. This is actually a really unique time to bring back the best of the best concepts, whether it's A I and systems and computer science and engineering into the automation. Could you share your view on this because you're in a unique position, you've been there, done that now. You're on the cutting edge with your thoughts. >>Yeah, absolutely, john And just when you think of automation and time, automation is not new, literally, if you go into Wikipedia and you look up automation, you see patents and references to like steam engine regulators at the dawn of the industrial era. Right? So automation has been around and and in the simplest form automation, whether it was back then, um whether it was in the 80s or today, it's about applying technology and that that performs, that uses like technology software to perform tasks that were once exclusively done by us humans. Right? So, but now what we're seeing is a I coming into the picture and and changing the landscape in an interesting way. But I think at its essence, you know, automation is this two step dance of both eliminating repetitive, mundane tasks. That helped reduce errors and free up our time. So we get back the gift of time but also helps. It's not about taking jobs away at that point, as I said, it's a two step dance, that's step one. But if you stop there, you're not getting the full value. Step two is to augment our skills right? And and to use automation to help augment our skills and we get speed, we get quality, we get lower costs, we get improved user experience. So whether it was back in the steam engine times or today with a I automation is evolving with technology >>and it's interesting to its you know, as a student of the history of the computer industry as you are and now a creator with your podcast which we'll get to in a second, you're starting to see the intersection of these concepts are not bespoke as much as they used to be. You got transformation. Digital, transformation and innovation are connected and scale. If you think about those three concepts they don't stand alone anymore. They can stand alone but they work better together transformation. And is the innovation innovation provides cloud scale. So if you think about automation, automation is powering this dynamic of taking all that undifferentiated heavy lifting and moving the creativity and the skill set into higher integrated areas. Can you share >>your john Yeah no right on there when you talk about transformation, jeez look around us, the pandemic has made transformation and specifically digital transformation the default so everything is digital. You know whether it's ordering a pizza, you know visiting a doctor through telemedicine or or this zoom webex based workplace that we live in. But picture of telemedicine environment right? Talking about transformation and going digital With 10 x more users. They can't hire 10 x more support staff and think about it I forgot my password. Um Does does this work on my version of the Apple iphone or all of that kind of stuff? So their support desks or lit up? Right. So uh as they scale digitally automation is the relief that that comes into play which is which is just in time. Right? So the digital transformation needs automation and john I think about it like this um businesses like cars are have become computers right? So they are programmable. So automation software just like in the cars it makes you know the car self driving? I think about the Tesla model three which I recently test drove. Um so with this digital acceleration digital opens the door for automation And now we can use about a self driving business. We can use about uh maybe that's step one, right? That's the um remove repetitive work, but maybe we can actually augment business to have an autopilot so it doesn't eat us there all the time to drive. And that's the scale that you talked about. That's the scale we need. So automation is really like the peanut butter and chocolate Digital is the peanut butter, automation is the chocolate. They go well together and they produce amazing tastes. >>You know, that's a really, that's a really interesting insight and I will just put an exclamation point on that because you mentioned self driving business, you're implying, you said the computer, the business is a computer. So if you just just think about that mind blowing concept for a second, if it's a computer, what's the operating system and what's the suite of applications that are on top of it? So, Okay, let's go in the old days at a Windows machine and you had office, which is a system software, applications, software construct. Okay, If you map that to the entire company, you're talking about Red hat and IBM kind of come working together. Kind of connects the dots a little bit on what Red Hackett because they're not bring system company. So if hybrid cloud is the system mm hybrid, then you got the applications suite is all software for the That's >>right. That's right. And if you, you know, if you listen to anything these days about what IBM stands words, hybrid cloud and and think red hat as as, you know, kind of the core element of that with open shift in a I right. And both of those really matter in terms of automation and maybe I'll come back to the hybrid cloud and red hat thing in a second. Let's just talk about you know Watson and Ai, you know, which is the application and you mentioned scale, which I'm so glad you did. You know a I could help scale automation. And the trick is is that ai automation sometimes gets stuck right? It gets stuck when it's working with data that is noisy or unstructured. Right? So there's a lot of structured data in your organization and it it with that we can breeze through automation. But if there is more ambiguous data unstructured noisy, you need a human in the loop. And when you get a human in the loop, it slows things down. So what a I can start to do a I. And its subordinates, machine learning, natural language processing, computer vision. We can start to make sense of both unstructured and structured data together and we can make a big deal going forward. Right? So that's that's the way I part you mentioned Red hat and and hybrid cloud part. We'll think about it this way. When you shop, how many stores do you don't just shop in one store? Right. You you go to specialty stores to pick up that special uh ketchup, I don't know or must store and maybe do shopping another store, customers using clouds john aren't very different. You know, they have their specialty places to go. Maybe they're going to be running workloads and google involving search and a I related to search, right? And they're going to be using other clouds for more specialty things. Right? So from that perspective, that's a view of hybrid, you know, customers today, you know, take that shopping analogy, they're going to be using sales force or service Now, IBM cloud, they have a private cloud, right? So, when you think about automating that world, All right. It's the real world. It's how we shop, whether it's for groceries or for cloud, right? So the hybrid cloud is a reality. Um and how do you make sense of a high of that? Right, Because when when an average customer has five clouds, How do you deal with five things? Right. How do you make it easy normalize? And that's what red hat really >>does. It's interesting. I just just share with you the and I interviewed Arvin um who is now the ceo of IBM when he was at Red Hat some in 2019 in SAn Francisco before he made the acquisition here that I was, I was peppered with questions like you know, you need to get this cloud and he loves cloud, you know, he loves clouds. So so he was smiling, he just wanted to say it, I wanted to just say it and I think Red Hat brings that operating kind of mindset where the clouds are just subsystems in the Os >>yes of the middle >>where which is now software which is software to find business. And this kind of is the talk of your, your your views. Now you have a podcast called Art of automation. Want to get that in there for the folks watching uh search for the podcast, Art of automation. This is the stories that you tell. Tell us some stories from this phenomenon. What's the impact of automation for the holistic picture? >>Well, it starts with a lot of, I guess it starts with customers. The stories start with the customers. So we're hearing from customers that Ai and automation is where they're investing in 2021. Um for all the reasons we briefly mentioned and and IBM has a lot to offer there. So we've made a I powered automation of priority but john in the pursuit of making it a priority. I've started talking with many of our subject matter experts and was floored by their knowledge, their energy, their passion and their stories. And I said we can't keep this to ourselves, we can't keep this locked away, we have to share it, we have to let it out. So, so basically this is what started the podcast around that. And since then we've had many industry luminaries from IBM and outside, starting with customers, we had claus Jensen who is the ceo of memorial clones Kettering hospital to talk about automation and health care. And he shared great stories. You need to listen to them about. Automation is not going to take the place of doctors, but automation will help better read um x rays and look at those shades of gray on the X ray and interpret it much better than we can and be able to ingest all of the up to date medical research to provide pointers and make connections that the human may not be able to do in that moment. Right. So the two working together or better than any individual carol Poulsen recently joined me to talk and she's the C. I. O. For cooperators to talk about automation and insurance. And she had some great stories to uh so john with that a bunch of IBM great IBM fellows like Rama Agra jew, who is one of Forbes top 20 women in AI research, talking about Ai ops and also Russia near pori talking and Russia has been working on Watson since jeopardy to tell stories about ultimately now how we're teaching ai to code and all the modern programming languages and really automating application modernization and the like uh, 14 episodes in we have those under our belt, About 6000 downloads so far. So it's it's coming along pretty well. Thanks. >>Thanks for being done. Yeah. The key is your your content creator now as well as a fellow and this is the democratization, as we say, direct to audience, share those stories also here. And thank you released an e book. Tell us a little quickly about that. We've got one minute left, give a quick plug. >>The book echoes the podcast chapters relate to the, to the episodes of the book. We're dropping the first five chapters plus forward for free on the IBM website. Other chapters will become available um, and drop as they become available. The book makes the content searchable on the internet. We go into more detail with advice on how to get started. You get to hear the topics and the voice of those subject matter experts and uh I really, you know, suggest you go out and check it out. >>Alright, jerry, cuomo IBM fellow VPC T IBM automation um also a content creator podcast, art of automation, jerry. We're gonna lift it listed on our silicon angle and our cube sites. Get you some extra love on that. Love the podcast. Love the focus on sharing from experts in the field. Thanks for coming on. >>Thank you so much for having me again, john >>Okay. I'm John Fryer with the Cube here for IBM think 2021. Thanks for watching.

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone here live in San Francisco at Moscone West of cubes exclusive coverage of Red Hat summit 2018 I'm John four with mykos John Troy a founder of tech reckoning advisory and on community services firm our next guest is Jason O'Connell openshift platform owner of mark mcquarrie group welcome to the cubes let's get it right that's right well the retail bank of Macquarie so thank you and financial services thanks for coming on so bossy begging is pretty hot big time early adopter of all things tech yes and you doing a lot of work at kubernetes tell us about what you're doing take a minute to explain your job what your focus is some of the some of the environment DevOps things you're doing it's a basically I'm head of the container platform team at Macquarie Bank so basically my team manages open shifts on AWS we do the architecture on there but we also focus a lot on the value add on top so we don't just give our our customers for my team are the developers and the development teams we don't just give them a blank platform we do a lot of automation a lot of work on top of that basically because we want to make sure that the idea of a platform as a service is that we do as much as possible to make developers lives easy talk about the journey when did you start on this effort Asli Amazon's great cloud we use it as well other clouds are coming on you had Google and Microsoft and others but when did the open shift conversations start happening where were you what year was it how long have you been using it it's gone through some great changes I want to get your experience on that open shifter journey I mean somewhat of an early adopter I mean we started looking at this two years ago so that was openshift 3.1 a lot of the basic features weren't even there and it took us a year to both build it out as well as migrate about 40 applications to production so it was only a year ago that we've been in production so it's evolved like so rapidly during that time so 40 applications migrating right that enough in and of itself in a year is is a pretty heavy lift can you talk a little bit about are you just re platforming the applications obviously probably not rewriting at this point the open shift has been a good home for the applications that you started out with it sounds like I mean one of the reasons to choose open shift was docker and it was about that migration path I mean part of the migration was ensuring that developers could get everything running locally get these legacy systems we did a lot of micro services running locally on docker containers on their laptop then the migration was was easy from there but we deliberately didn't want to do like a lift and shift we wanted to rethink how we delivered software as part of this project okay what's the biggest challenges you had in doing this I mean as you can open ships got some great movement Houston Cooper native good bet and kubernetes is looking like a really awesome way to move workloads around and manage containers and clusters so you know what's what are some of the things we've learned what are some of the complexities that you overcame can you share a little bit about some of the specifics I think I think the newness is is probably the biggest challenge I mean going back to two years ago there was some very basic components that weren't there at the time and we knew were coming and even now there are pieces of work which we just don't tackle and we do a very quick fix because we know it's coming later I mean it's just moving and evolving so quickly you know we're waiting a lot for sto which is coming in the future so we're holding back on investing in certain areas because of that so it's always a constant challenge yeah I still looking good and the service mesh is hot as well how has OpenShift helped you but what's the list if you had to kind of boil it down what's the bin the the impact to you guys where's the where's that coming from I mean before we even selected OpenShift we had we're looking at our objectives from a business perspective not a technology perspective I'm the biggest objective we had was speed to delivery you know how could you get a business idea a product idea into production as fast as possible or even if you look at a minor fix to something something that should be easier develop it takes a data ride why does it take a month to release the production so speed of delivery was one of the key objectives and I can tell you more about how we we delivered that in detail but just going back to the objectives we also looked at developer experience you know sometimes the developers are not spending enough time coding and doing it they want they get bogged down in a lot of other pieces of work that I I'm really delivering business value yeah so again we wanted the platform to handle that for them they could focus more on their work this is the promise of DevOps and the whole idea of DevOps is to automate away the hassles and I mean my partner Dave a lot that calls a rock fetches no one likes to do all that work it's like can someone else just handle it and then when you got now automation that frees it up but this brings up the thing that I would love to get your reaction to because one things we've been covering and talking a lot about in the cube is this isn't happening around us it's not just what we're doing but this new modern way to deploy software you'll get like some of the big things that are happening in with cloud native and you mission is do is to do this awesome dynamic things on the fly that are automated away so it changes the how software is being built how are you guys embracing that what's the thought obviously you've got a team that's got the mindset of dev yeah I'll see embracing this vision and if everything else is probably substandard she'll you look at you know waterfall or any kind of non agile what is the your view of this modern era of writing code and building applications what I mean for people who don't aren't getting it how are you how do you explain it you know I think it's I mean it's an unbelievable time that we're in at the moment I mean the amount of automation that we're doing is huge and part of our openshift is that it's an automated bull platform so I've got a few junior guys in my team they're like two graduates and in turn they do a lot of the automation yeah it's that easy if you look at interestingly in like security and risk teams and governance teams where we're finding look they can improve security risk and all this by automating you know they're the one set and now we've got SEC offs movements and things like that so speed of production is is does not prohibit better security and in fact with Sec ups the amount of automation we do you got a far greater amount of security because we now know everything that's deployed we can continually scanning for vulnerabilities yeah so Jason you talked about it being new we've talked a little bit about culture how much of this has been a training exercise how much is that it's been a cultural shift within your organization as one of the leaders of it how are you approaching I mean we're lucky there within Macquarie Bank there was a large scale culture shift towards agile where the whole bank runs in that gel manner so that's helped us then fill in our technology and automation it complements that way of delivering so we've got some very unique ways where we've done automation and delivery which completely rethinks how we used to deliver before so right example yeah for instance now if you think why were people scared of delivering something into production why was a small change scary change and a big part of it is the blast radius if something went wrong you know connecting through to our API is we've got our own channels mobile apps a website you've got a lot of partners there are the companies connecting through as well and so even if you did a small change if it costs an issue everyone's affected at once so a big piece of what we did to deliver faster is allowed targeted releases you know I could target a release and a change just to you we could target it to a percentage of customers monitor rolled out quickly if there's a problem dial it up if it's looking good good target to any channel it seems like there's a business benefit to that too right that's massive here because you also can promise stability on certain channels if you want you can have faster channels that are moving quickly and in an API driven world we've got external companies connecting through to these api's you want to be able to say that we've given you a stable offering and you can upgrade when you want and then our channels we cannot move more fast so we've got a minister no-brainer I mean really the old way is completely dead because of that because I think what the blast radius you're pointing about blast radius the risk is massive so everyone's kind of on edge all these tests have to go in redundancies as if the planning is ridiculous all for the risk all that energy you're optimizing for a potential non-event or event here with micro services and you an out can go down to the granular level the granularity is really amazing so when you go forward first of all it's a recruiting opportunity to get better engineers wait this is a way we work I'm going forward I want you to comment on your opinion as an industry participant and can clarify this because a lot of people get confused here Automation they think jobs are going away administration is getting automated system admin type roles where junior people can now do more operating things but the operating roles not going away so talk about that that ops side because now the ops are more efficient the right things are audited maybe but talk about that dynamic between the right things being automated and the right things that are gonna roll to operational service messages or whatnot yeah I mean basically it's about getting people to do these higher-order functions so the people who are doing things manually and operating things manually you look at our Ops teams now morphing into like the classic SRE team you know the side reliability engineering teams where they're spending a significant amount of that time automating things you know looking at alerting and monitoring and then Auto healing I mean it's actually more work to automate everything but with a far greater amount of quality and reliability and what we get and the benefits are long it's worth it basically you do the work upfront and you reap the benefits and then variety away it's like writing rolling out software managing workloads talk about multi class here on Amazon multi cloud is a big focus to your hybrid cloud multi-cloud obviously we're seeing that trend how do you look at multi cloud as a practitioner what are some of the things that check our check boxes for you in terms of okay as we start looking to the next level there might be a multiple cloud scenario how do you think about that and how do you put that into perspective that's worth noting even two years ago and we selected openshift it was with the idea that we could go multi cloud you know that for the users for the developers they're not going to know the difference where we run it on so we're not locked into any provider final question for you if you can boil down openshift into kind of like a soundbite for you what does it mean to you guys what's been the benefit what's been it it's been that what's been the role what's the benefit of OpenShift as you pour the cloud journey you know I could say speed I could say automation I mean that's huge but but really open shift and read how to pick the winner which is docker and kubernetes and a colleague of mine is in coop con in Copenhagen last week he's constantly messaging me saying there's new tooling you guys can use this you can use that and it means that rather than us doing the work we're just getting tooling from the community so it's the de facto standards so that's that's probably the biggest benefit all the goodness is just coming right to your front door luckily and I got to do my homework every night playing around with this technology so yeah gates success story and again the great community open-source projects out there you guys can bring that in and productize it for the retail bank congratulations love open-source stories like this tier one citizen and again continues to power the world open source softens the cube do our part bring and use all the data from Red Hat summit 2018 I'm John fryer with John Tory we'll be back with more after this short break

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone here live in San Francisco at Moscone West of cubes exclusive coverage of Red Hat summit 2018 I'm John four with mykos John Shroyer founder of tech reckoning advisory and on community services firm our next guest is Jason O'Connell openshift platform owner of mark McQuarrie group welcome to the Cuse let's get it right that's right well the retail bank of Macquarie so thank you and financial services thanks for coming on so bas lead banking is pretty hot big-time early adopter of all things tech yes and you doing a lot of work at kubernetes tell us about what you're doing take a minute to explain your job what your focus is some of the some of the environment DevOps things you're doing that's the basic I'm head of the container platforms team at Macquarie Bank so basically my team manages open shifts on AWS we do the architecture on there but we also focus a lot on the value add on top so we don't just give our our customers for my team are the developers and the development teams we don't just give them a blank platform we do a lot of automation a lot of work on top of that basically because we want to make sure that the idea of a platform as a service is that we do as much as possible to make developers lives easy tell about the journey when did you start on this effort Asli Amazon's great cloud we use it as well other clouds are coming on you got Google and Microsoft and others but when did the open shift conversations start happening where were you what year was it how long have you been using it it's gone through some great changes I want to get your experience on that opened she have to journey I mean somewhat of an early adopter I mean we started looking at this two years ago so that was openshift 3.1 a lot of the basic features weren't even there but it took us a year to both build it out as well as migrate about 40 applications to production so there's only a year ago that we've been in production so it's evolved like so rapidly during that time so 40 applications migrating right that enough in and of itself in a year is is a pretty heavy lift can you talk a little bit about are you just replied forming the applications obviously probably not rewriting at this point the open shift has been a good home for the applications that you started out with it sounds like I mean one of the reasons to choose openshift was docker and it was about that migration path I mean part of the migration was ensuring that developers could get everything running locally get these legacy systems we did a lot of micro services running locally on docker containers on their laptop then the migration was was easy from there but we deliberately didn't want to do like a lift and shift we wanted to rethink how we delivered software as part of this project okay what's the biggest challenges you had in doing this I mean as you go but she has got some great movements you could burn aces a good bet and kubernetes is looking like a really awesome way to move workloads around and manage containers and clusters so you know what's what are some of the things we've learned what are some of the complexities that you overcame can you share a little bit about some of the specifics I think I think the newness is is probably the biggest challenge I mean going back to two years ago there were some very basic components that weren't there at the time when we knew were coming and even now there are pieces of work which we just don't tackle and we do a very quick fix because we know it's coming later I mean it's just moving and evolving so quickly you know we're waiting a lot for sto which is coming in the future so we're holding back on investing in certain areas because of that so it's always a constant challenge yeah I still looking good and the service mesh is hot as well how has OpenShift helped you but what's the what's the if you had to kind of boil it down what's the been the the impact to you guys where's the where's that coming from I mean before we even selected OpenShift we had we're looking at our objectives from a business perspective not a technology perspective I'm the biggest objective we had with speed to delivery you know how could you get a business idea a product idea into production as fast as possible or even if you look at a minor fix to something something that should be easier develop it takes a data ride why does it take a month to release the production so speed of delivery was one of the key objectives and I can tell you more about how we we delivered that in detail but just going back to the objectives we also looked at developer experience you know sometimes the developers are not spending enough time coding and doing if they want they get bogged down in a lot of other pieces of work dinner I'm really delivering business value yeah so again we wanted the platform to handle that for them they could focus more on their work and this is the promise of DevOps and the whole idea of DevOps is to automate away the hassles and I mean my part to Dave a lot that calls a rock fetches no one likes to do all that work it's like can someone else just handle it and then when you got now automation that frees it up but this brings up the thing I would love to get your reaction to because one things we've been covering and talking a lot about in the cube is this is been happening around us it's not just what we're doing but this new modern way to deploy software you look at like some of the big things that are happening in with cloud native and you mention SEO is to do this awesome dynamic things on the fly that are automated away so it changes the how software is being built how are you guys embracing that what's the thought oh so you've got a team that's got the mindset of DevOps yeah I'll see embracing this vision and if everything else is probably substandard she'll you look at you know waterfall or any kind of non agile what is the your view of this modern era of writing code and building applications what I mean for people who don't aren't getting it how are you how do you explain it you know I think it's I mean it's an unbelievable time that we're in at the moment I mean the amount of automation that we're doing is huge and part of our openshift is that it's an automated bull platform so I've got a few junior guys in my team they're like two graduates and in turn they do a lot of the automation yeah it's that easy now everything's got API so we can connect everything so I do find when we interface with some of the older school teams in different parts of the bank that aren't doing this level of automation they used to manual processes and manual ways of doing things and now we look at everything where everything can be automated that's thing you really truly feel now opened up that you could automate absolutely everything I mean the developer productivity one is key you know state of mind is another I mean the mood is better okay people are in a better mood more productive yeah and I think if you look at interestingly in like security and risk teams and governments teams where we're finding look they can improve security risk and all this by automating you know they're the one set and now we've got SEC offs movements and things like that so speed of production is is does not prohibit better security and in fact with Sec ups the amount of automation we do you got a far greater amount of security because we now know everything that's deployed we can continually scanning for vulnerabilities yeah what so Jason you talked about it being new we've talked a little bit about culture how much of this has been a training exercise how much is that it's a cultural shift within your organization as one of the leaders of it how are you approaching I mean we're lucky there within Macquarie Bank there was a large scale culture shift towards agile where the whole thing runs in that gel manner so that's helped us then feel in our technology and automation it complements that way of delivering so we've got some very unique ways where we've done automation and delivery which completely rethinks how we used to deliver before so example yeah for instance now if you think why were people scared of delivering something into production why was a small change scary change and a big part of it is the blast radius if something went wrong you know connecting through to our API is we've got our own channels we've got mobile apps got a website you've got a lot of partners there are the companies connecting through as well and so even if you did a small change if it costs an issue everyone's affected at once so a big piece of what we did to deliver faster is allowed targeted releases you know I could target a release and a change just to you we could target it to a percentage of customers monitor rolled out quickly if there's a problem dial it up if it's looking good good target to any channel it seems like there's a business benefit to that too oh it's massive here because you also can promise stability on certain channels if you want you can have faster channels that are moving quickly and in an API driven world we've got external companies connecting through to these api's you want to be able to say that we've given you a stable offering and you can upgrade when you want and then our channels we cannot move more fast so we've got mr. no-brainer I mean really the old way is completely dead because of that because you think about the blast radius you're pointing about blast radius the risk is massive so everyone's kind of on edge all these tests have to go in redundancies as if the planning is ridiculous all for the risk well that energy you're optimizing for a potential non-event or event here with micro-services and you and app can go down to the granular level the granularity is really amazing so when you go forward first of all it's a recruiting opportunity to get better engineers wait this is a way we work I'm going forward I want you to comment on your opinion as an industry participant and can clarify this because a lot of you'll get confused here automation they think jobs are going away administration is getting automated system admin type roles where junior people can now do more operating things but the operating roles not going away so talk about that that ops side because now the ops are more efficient the right things are audited me you but talk about that dynamic between the right things being automated and the right things that are gonna roll to operational service meshes or whatnot yeah I mean basically it's about getting people to do these higher-order functions so the people who are doing things manually and operating things manually you look at our Ops teams now morphing into like the classic SRE team you know the side reliability engineering teams where they're spending a significant amount of that time automating things you know looking at alerting and monitoring then Auto healing I mean it's actually more work to automate everything but with a far greater amount of quality and reliability when we go and the benefits are long it's worth it basically you do the work upfront and you reap the benefits and then variety of ways like writing rolling out software managing workloads talk about multi class here on Amazon multi cloud is a big focus to your hybrid cloud multi-cloud obviously we're seeing that trend how do you look at multi cloud as a practitioner what are some of the things that check our check boxes for you in terms of ok as we start looking for the next level there might be a multiple cloud scenario how do you think about that and how do you put that into perspective that's worth noting even two years ago and we selected open shifty it was with the idea that we could go multi-cloud you know that for the users for the developers they're not going to know the difference where we run it on so we're not locked into any provider I mean at the moment we're kind of just exploring Google cloud and we're looking at what it would look like so even we don't know yet some people have spoken about stretching your cluster across to clouds that means one cluster across two seems very difficult to me that a lot of latency issues potentially there's also cloud arbitrage you know can we get certain workloads on a card that's cheaper can we use spot instances can we spin things up and down we're on Google it's cheaper and then it also raises questions around okay do we need Federation and we know Federation has been talked about a lot with kubernetes how do we manage so many clusters and even on AWS now we have three production clusters you had multi clouds how am I gonna manage that what about the services layer of clouds right obviously the Red Hat platform gives you a services layer that could run anywhere but underneath that right AWS has its own services layer Google you know a lot of AI ml you know it could you be able to are you thinking about taking advantage or how are you thinking about those different offerings on different different places I mean this is the challenge I face and what we're exploring is that do some teams have the differentiating services the unique services that they want on Google especially for managing data machine learning we know those services are key for them some teams will have that but yet then can we call them over from AWS even oh do we have to deploy in in Google and have that in one data center can we go across with services so it's really like not just cloud AWS cloud Google but it's actually criss-crossing that's another thing we're exploring Jason thanks for coming on the cube really appreciate your commentary I've seen multiple red hats you guys have won awards you've been here before great job final question for you if you could boil down OpenShift into kind of like a sound byte for you what does it mean to you guys what's been the benefit what's been it it's been that what's been the role what's the benefit of openshift as you explore the cloud journey you know I could say speed I could say automation I mean that's huge but but really OpenShift and read how to pick the winner which is docker and kubernetes and a colleague of mine is in pucon in copenhagen last week he's constantly messaging me saying there's new tooling you guys can use this you can use that and a means that rather than us doing the work we're just getting tooling from the community so it's the de facto standards so that's that's probably the biggest benefit all the goodness is just coming right to your front door likely and I got to do my homework every night playing around with this technology so yeah great success story and again the great community open-source projects out there you guys can bring that in and productize it for the retail bank congratulations love open-source stories like this tier one citizen and again continues to power the world open-source softens the cube doing our part bring and use all the data from Red Hat summit 2018 I'm John fryer with John Tory we'll be back with more after this short break

>>Welcome back everyone. This is our final wrap-up of the Amazon web services. Reinvent conferences is SiliconANGLE and Wiki bonds. The cube is our flagship program. We go out to the events, extract the signal from the noise. I'm John furry or the founders to look an angle. And of course I'm joining my cohost partner in crime. Dave Volante, co-founder with you bond.org. Um, really exciting event, Dave, I got to say, this is our wrap up. Let's put a bow on this show. Let's put the bumper sticker on the car and let's see what, uh, what was this document? What happened day one enterprise day to infrastructure day three ties it all together with Kinesis. Amazon is doing two things. That's very, very rare in tech history, and that is a disrupting and innovating at the same time. The magic it's the magic formula. And to me, it's really two tactical executions, one ball moving the ball yard by yard first and 10, do it again to use the football analogy, moving the chains, moving the ball down the field, kind of a running game, ground game, whatever a call it. >>And then the big yardage passing play with Kinesis, I think really brings their success of an integrated stack. And I believe they're going to be the iPhone like model for the cloud they're they're light years ahead of everybody else on public cloud. Uh, they're winning the developers. And again, we just heard from Dr. Matt would kind of reiterating what we were saying in our previous segment about the diversity of the successes. It's not a one trick pony. They got diversity from startups to large enterprises to NASA. So Dave, I mean, I mean, who is going to take on Amazon, who is going to challenge Amazon? That's the question that we want to know right now. It's not looking good right now. They're got a commanding lead in the cloud space and it'd be really interesting to watch how the Kinesis, the enterprise movement, uh, with VDI announcement and workspaces and all the enhancements in the, in the performance is going to shift the sand in the industry. And you're already seeing Cisco down 12% VMware stocks down. I mean, game-changing, the sands are shifting. What's your >>Well, I think we're seeing history in the making here, John. I mean, I think last year at reinvent com leading up to we reinvent, we realized that this event was going to be big and not just the event. The event is a metaphor for the shift that's occurring in the industry. We're talking about a trillion plus dollar marketplace that Amazon is disrupting and believe it or not, they're tiny, even though there are three or 4 billion, they're tiny, it's a trillion dollar Tam that is absolutely getting flipped on its head. And what do we mean by that? Every premise about the it business is changing. We talk about a lot. Amazon has ch has turned the data center into an API. It's a very powerful concept. I think you're right on. It's the, it's the iPhone of the enterprise. Yes. That's. They're not like hall monitors checking about every application in the app store. >>That's not the point. The point is it's a consistent environment that is controlled by Amazon, very tightly controlled and it works. You know what you're getting, and it's innovating at a, at a breakneck speed. It's antithetical to everything we know about it. So, you know, you've been asking people all week what the bumper sticker is on the show. I can't wait to go back and see some of those, but I mean, this is the trend and the trend is your friend, or it might be your enemy. So when you say who's going to be able to compete with Amazon, I think Martin of eucalyptus set a set of best historically in economics. There's always people that will rent and there's always people that will buy. And the, the old guard is Amazon calls them is not going to take this lying down, but the old guard has to replicate an Amazon's model. How does it do that? It's got to create an open entry into its system. That's equivalent in terms of simplicity and power to the Amazon API. Number one, number two is it's got to be able to demonstrate to the developer community that you can inter-operate across those platforms in a way that you can get critical mass, the same way that you can with Amazon. And that's going to be the, the massive battle that's going to take place in the cloud Wars. >>I mean, I think one of the things that's interesting is that the word lock-in was something that we were talking on day one, especially in the enterprise, that's a word that gets kicked around. And you know, my feeling has always been lock-in is not necessarily a bad thing if it's, if you can, if you can have switching costs that aren't super high locking means, switching costs are so high that you can switch. I can switch from my iPhone to Android anytime I want. But the problem is that iPhone is a better product. It's integrated with the apps and I can buy all the same apps. So that's a very key thing. And I think the switching costs here are a lot higher and I, there are Amazon >>On the record. Amazon is the mother of all lock-ins. I mean, this is a beautiful business model and here's, what's so great about it is the customers. You heard them this week say if you took AWS away from me, I would burst out into tears. So Amazon's, I think brilliant challenge here is to how do they keep innovating? They're doing that, but how do they keep lowering prices? So people don't want to leave. So that that's, that's what I see as the disruptive piece. It, >>Well, being in this business all these years were, you know, a little bit older than some of the young guns were on the cube to me lock-in is moving right? You see, um, in the old days, huge capital outlays for, uh, for equipment, you had maintenance, all this stuff was locking. Now the lock-in shifting to OPEX and agility. So what's happening is Amazon is basically commoditizing the old way of how people would spend and shifting the lock-in to the op X side of the equation. I call it the heroin addiction where, Hey, it's so low cost and the agility is the lock-in. So the functionality of agility guarantees the lock. And I think that's what Amazon's betting the ranch on is that when can go to time to market, to value quicker, that is inherently a lock-in, that's a quote, user experience to use my iPhone example. >>If I'm going to have a good experience making money as an enterprise, that's good. That's good. Lock-in right. So it's all a relative term in that the lock-in has been around. I mean, they call it differentiation, but at the end of the day, I think Amazon's got a good, good play there. But like I said, I don't think Amazon has cracked the it nut yet. I think they're going to have some it penetration. And this is top of the first ending, as we were saying, the enterprise, it nut enterprise, it is not, has not. The nut has not been cracked. What >>Do you need to see to be convinced? Well, >>I just think the stack is going to be the, the same paradigm of having an integrated staff. I just want to see different levels of services because the table stakes for the enterprise are different. There's certain compliance issues and you know, they're checking the boxes right now. This is the ground game I was referring to earlier. Amazon is going to start checking the boxes. Oh, VDI, we got workspaces, I got this. I'm going to check the boxes. Ultimately the list is just too long to win everyone. Right? So I think, you know, so it's going to be an opportunity. I think OpenStack has a great hope. I think VMware and IBM and HP are big players. And I think OpenStack needs to step up its game and have a big player, pop down a billion dollars with like IBM David Linux and saying, look at OpenStack, we're behind it. And rally the troops. And that's all >>Sorry, go back to the lock-in comments because this is critical because to me, the definition of lock-in is it's, it's, it's less economically attractive to leave than it is to stay. And that's what Amazon is doing. They're making it, making it more economically attractive to stay than they are to leave. Here's why that's so important. The more people that they pull, and this is why Carlisle and back said, you know, we can't lose to the bookseller. And you said that because they know the old guard knows that if people go to Amazon, they're not going to leave. Cause it's going to be less attractive for them to leave than it is to stay. So there's a huge battle over that trillion dollar Tam. So the key is John that OpenStack and IBM and VMware and Oracle and all the others have to make it economically attractive to not go into Amazon. And that is the battle. >>One of the things that's very clear, Dave, that's coming out of the show for me. My bumper sticker is dev ops wins. And I think what that mean by that is, is that, and we refer to the cloud being in the top of the first inning, meaning really everything else was spring training. He used the baseball metaphor in the sense that this is all that this is all activation of a paradigm shift. That is so game-changing the dev ops concept of software developers. Writing code that trickles into a fully integrated stack is really amazing, right? This really replaces the pain of provisioning hardware cost of it, cost of the infrastructure. That stuff is that that is the real value of the crowd. So if you take the dev ops concepts, which to me is already a winner and put that into the enterprise market, that's going to be cloud ops. >>So to me, I think the opportunity right now for anyone who wants to with Amazon in my opinion, is to go out there and say, look it, you got to win the software developers, look at what a Mongo DB has done. We had Elliot the co-founder on, they made it good goodness for the developer. Whoever can do that for the enterprise will win. And I don't think that there's a direct one-to-one mapping of what dev ops is. It is in the Amazon world. And what dev ops is in the enterprise. I think that's more cloud ops because the guys that are provisioning EMC drives dealing with IBM and red hat a little bit slower, I would say in terms of deployment, they used to the big slow cycles. Dev ops guys are pushing code a little bit more, you know, nimble startup, clean sheet of paper, you know, Uber, Airbnb, those younger generations, but this is a generational shift and it's happening and it's all on the software. So to me, I think dev ops speaks to, >>I wanna, I wanna, uh, keep this thread going. So, so what's the playbook to, for the old guard to compete, you're saying you gotta, uh, attract developers, but that's not enough. You need a cloud platform, right? So take, for example, VMware, VMware announces, you know, hybrid cloud infrastructure as a service it's early days, they need a cloud platform. So what else do you need to compete? You need developers. You need, >>You gotta have, you gotta have trust and security, right? So here's the thing. Developers care about success of creativity for the solutions. And what Amazon's demonstrate is the time to value is the key thing. You hear people, whether they're startups or big company get to some value, double down on success, figure out how to be agile succeed. Fast, move on with the problem right now is that developers are like deer in the headlights. They go where the action is, right? And it's always been that way. I think OpenStack to me is an opportunity or whatever platform that is. Someone's got to get a big anchor tenant in that platform needs to step up and be the galvanizing force and create some solidarity around that approach for it. That is an opportunity for VMware. I think Pat Gelsinger is probably best positioned to do that. Pivotal is a, is a genius, but I think ultimately they might be biting off more than they can chew. So I worry about, you know, their car not being fast enough right now in, in the game. So, you know, worry about pivotal there. But I think VMware probably is a better position there. So they need, they need, they need infrastructure. They need this middleware, which is database queuing notifications. A lot of that, a lot of the stuff you see Amazon doing at the top of the stack managed services. So that's streaming data and all the goodness on them, >>Developers, you got to have a cloud platform at scale, you gotta have trust and security. I would add to that. You got to do things that Amazon's not going to do. So for instance, we heard all week, Amazon doesn't want to do one-offs. They don't like to do customization, whatever they do. They want everybody to benefit from that enterprise enterprises want customization. We've talked about this, John. That's why, for instance, you, you find that some of the customers won't go into Amazon, not because the security is bad, it's just different. And Amazon's not going to change the security profile. They're not going to change the policy. So enterprise, uh, players, the old guard, so to speak must continue to do custom stuff. One-off that Amazon won't do, but here's the bet that Amazon's making Amazon's that its ecosystem will over time be able to do those one-offs for the customer and put a buffer in between the Amazon platform and the customer. So that's, that's really interesting. >>Yeah. I would also add to that, that the main differentiation where Amazon and other potential people to compete with Amazon is scale, scale matters. Scale gives leverage. Amazon has proven that, and they're trying to use that leverage now to catapult into other markets for market expansion. So that's one thing. So, so, so the, so for the enterprise in particular, one area we watch heavily, I see two major trends. I see a cloud service that's similar to Amazon. It smells like an integrated stack, but it just has different feature sets tailored for the enterprise. That's more of that's the hybrid cloud clearly hybrid cloud is a winner. Amazon is not using that term hybrid cloud. And he's a hybrid ID, which is basically a head fake. It really means hybrid cloud. So that's hybrid cloud. The second thing is I think you're going to see data centers be Amazon in a box. >>So that's why I like io.com because io.com has essentially built pods and containers and essentially is cloud in a box. And I think shipping data centers is the future. And I think what I like about IO and here's why I'm interested in double clicking on that company is that they're basically shipping data centers. You've got Goldman Sachs, big companies. So IO IO has got, got that going on. And then you've got hybrid cloud. And then the third thing that's really relevant is that you started to see the vertical integration Dave of, of services. Look at CSC, CSC bought service mesh. We had, uh, this guy Jeff on earlier with, uh, that company is doing all the user experience they're offering full end-to-end full-stack developers for essentially web apps. Okay. That is a shift to what I call the dev ops world. Those two things. You're going to see these industries where it's ISV and integrators are kind of vertically integrated. They're going to actually build their own stuff. And that's going to be the, I think the innovation on the channel side. So the channel is up for grabs. Everything's being disrupted >>Battlefield. We've got developers, we've got cloud scale, we've got trust and security. We've got customization. And I'm going to add another one, which is the ecosystem, which is essentially your, you know, in part in your channel, but got to have a strong ecosystem, want to pick up this discussion with you and getting the hook. >>So the Dave wants to of what's the bumper sticker for the show. Give me the Dave Volante bumper sticker. You. We heard everyone said a story here. Um, >>What AWS, the, the trend is your friend, >>My bumper sticker. I'm going to throw a hashtag in there. The hashtag next generation computer revolution to me, this is the next generation computer revolution, total transformative hashtag next generation computer revolution. I think Amazon's leading the charge and I think they're going to shift the sands and everyone else is going to have to adjust. And that's good for everyone, Dave and the market wins a ruin murky on Hortonworks tweeted. Hey, we'd love it. Market expansion, rising tide floats all boats. And I think that's all >>Ultimately ultimately billion dollar Tam Gianna. I'm thrilled to a >>Part of covering that with the cube. I want to thank everyone for watching. Thanks. This is the day three wrap up this acute exclusive coverage from Amazon web services. Want to thank the crew here? All the guys back at the ranch. Kristen, Nicole art Lindsay, Mark Hopkins. Andrew, we got mic. We got Alex. Good job, Jeff Fricks do, uh, everyone. Jeff Kelly. We have the analysts. Come on. We've got this show covered, Dave. I think we fished this pond out. So look for us next to HP. Discover will be there. And, uh, December the week of the 10th or 11th and 12th, we'll be doing the OpenStack summit as well. Look for that. When that gets announced, um, my maybe doing the node node summit in December, we got also the spark summit and MIT event in January. The security event would be at Berkeley. We're going to all these great events tubes out of control. We've got storage, big data now cloud, we look for a lot of research. You can see a lot of cloud coverage coming out on the research. So I looked for that over the next few months, I will get bon.org. Thank you for watching. Well, that's a wrap day three exclusive coverage. This is the cube. I'm John fryer with Dave Volante here in Las Vegas until next time take care.